{ "openapi": "3.0.0", "info": { "title": "Microsoft Foundry", "version": "v1" }, "tags": [ { "name": "MLflow Experiments" }, { "name": "MLflow Runs" }, { "name": "MLflow Metrics" }, { "name": "MLflow Artifacts" }, { "name": "MLflow Registered Models" }, { "name": "MLflow Model Versions" }, { "name": "Agents" }, { "name": "Connections" }, { "name": "Datasets" }, { "name": "Deployments" }, { "name": "Evaluation Taxonomies" }, { "name": "Evaluation Rules" }, { "name": "Evaluators" }, { "name": "Indexes" }, { "name": "Insights" }, { "name": "Memory Stores" }, { "name": "Models" }, { "name": "Conversations" }, { "name": "Evals" }, { "name": "Fine-Tuning" }, { "name": "Responses" }, { "name": "Redteams" }, { "name": "Schedules" }, { "name": "Skills" }, { "name": "Toolsets" }, { "name": "TrainingJobs" } ], "paths": { "/agents": { "post": { "operationId": "Agents_createAgent", "description": "Creates the agent.", "parameters": [ { "name": "Foundry-Features", "in": "header", "required": false, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "anyOf": [ { "$ref": "#/components/schemas/AgentDefinitionOptInKeys" }, { "type": "string", "enum": [ "AgentEndpoints=V1Preview" ] } ] } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/AgentObject" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Agents" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/CreateAgentRequest" } } } }, "x-ms-foundry-meta": { "conditional_previews": [ "HostedAgents=V1Preview", "ContainerAgents=V1Preview", "WorkflowAgents=V1Preview" ] } }, "get": { "operationId": "Agents_listAgents", "description": "Returns the list of all agents.", "parameters": [ { "name": "kind", "in": "query", "required": false, "description": "Filter agents by kind. If not provided, all agents are returned.", "schema": { "$ref": "#/components/schemas/AgentKind" }, "explode": false }, { "name": "limit", "in": "query", "required": false, "description": "A limit on the number of objects to be returned. Limit can range between 1 and 100, and the\ndefault is 20.", "schema": { "type": "integer", "format": "int32", "default": 20 }, "explode": false }, { "name": "order", "in": "query", "required": false, "description": "Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and`desc`\nfor descending order.", "schema": { "$ref": "#/components/schemas/PageOrder" }, "explode": false }, { "name": "after", "in": "query", "required": false, "description": "A cursor for use in pagination. `after` is an object ID that defines your place in the list.\nFor instance, if you make a list request and receive 100 objects, ending with obj_foo, your\nsubsequent call can include after=obj_foo in order to fetch the next page of the list.", "schema": { "type": "string" }, "explode": false }, { "name": "before", "in": "query", "required": false, "description": "A cursor for use in pagination. `before` is an object ID that defines your place in the list.\nFor instance, if you make a list request and receive 100 objects, ending with obj_foo, your\nsubsequent call can include before=obj_foo in order to fetch the previous page of the list.", "schema": { "type": "string" }, "explode": false }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "type": "object", "required": [ "data", "has_more" ], "properties": { "data": { "type": "array", "items": { "$ref": "#/components/schemas/AgentObject" }, "description": "The requested list of items." }, "first_id": { "type": "string", "description": "The first ID represented in this list." }, "last_id": { "type": "string", "description": "The last ID represented in this list." }, "has_more": { "type": "boolean", "description": "A value indicating whether there are additional values available not captured in this list." } }, "description": "The response data for a requested list of items." } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Agents" ] } }, "/agents/{agent_name}": { "get": { "operationId": "Agents_getAgent", "description": "Retrieves the agent.", "parameters": [ { "name": "agent_name", "in": "path", "required": true, "description": "The name of the agent to retrieve.", "schema": { "type": "string" } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/AgentObject" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Agents" ] }, "post": { "operationId": "Agents_updateAgent", "description": "Updates the agent by adding a new version if there are any changes to the agent definition.\nIf no changes, returns the existing agent version.", "parameters": [ { "name": "Foundry-Features", "in": "header", "required": false, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "$ref": "#/components/schemas/AgentDefinitionOptInKeys" } }, { "name": "agent_name", "in": "path", "required": true, "description": "The name of the agent to retrieve.", "schema": { "type": "string" } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/AgentObject" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Agents" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/UpdateAgentRequest" } } } } }, "delete": { "operationId": "Agents_deleteAgent", "description": "Deletes an agent.", "parameters": [ { "name": "agent_name", "in": "path", "required": true, "description": "The name of the agent to delete.", "schema": { "type": "string" } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/DeleteAgentResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Agents" ] } }, "/agents/{agent_name}/import": { "post": { "operationId": "Agents_updateAgentFromManifest", "description": "Updates the agent from a manifest by adding a new version if there are any changes to the agent definition.\nIf no changes, returns the existing agent version.", "parameters": [ { "name": "agent_name", "in": "path", "required": true, "description": "The name of the agent to update.", "schema": { "type": "string" } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/AgentObject" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Agents" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/UpdateAgentFromManifestRequest" } } } } } }, "/agents/{agent_name}/versions": { "post": { "operationId": "Agents_createAgentVersion", "description": "Create a new agent version.", "parameters": [ { "name": "Foundry-Features", "in": "header", "required": false, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "anyOf": [ { "$ref": "#/components/schemas/AgentDefinitionOptInKeys" }, { "type": "string", "enum": [ "AgentEndpoints=V1Preview" ] } ] } }, { "name": "agent_name", "in": "path", "required": true, "description": "The unique name that identifies the agent. Name can be used to retrieve/update/delete the agent.\n- Must start and end with alphanumeric characters,\n- Can contain hyphens in the middle\n- Must not exceed 63 characters.", "schema": { "type": "string", "maxLength": 63 } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/AgentVersionObject" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Agents" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/CreateAgentVersionRequest" } } } }, "x-ms-foundry-meta": { "conditional_previews": [ "HostedAgents=V1Preview", "ContainerAgents=V1Preview", "WorkflowAgents=V1Preview" ] } }, "get": { "operationId": "Agents_listAgentVersions", "description": "Returns the list of versions of an agent.", "parameters": [ { "name": "agent_name", "in": "path", "required": true, "description": "The name of the agent to retrieve versions for.", "schema": { "type": "string" } }, { "name": "limit", "in": "query", "required": false, "description": "A limit on the number of objects to be returned. Limit can range between 1 and 100, and the\ndefault is 20.", "schema": { "type": "integer", "format": "int32", "default": 20 }, "explode": false }, { "name": "order", "in": "query", "required": false, "description": "Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and`desc`\nfor descending order.", "schema": { "$ref": "#/components/schemas/PageOrder" }, "explode": false }, { "name": "after", "in": "query", "required": false, "description": "A cursor for use in pagination. `after` is an object ID that defines your place in the list.\nFor instance, if you make a list request and receive 100 objects, ending with obj_foo, your\nsubsequent call can include after=obj_foo in order to fetch the next page of the list.", "schema": { "type": "string" }, "explode": false }, { "name": "before", "in": "query", "required": false, "description": "A cursor for use in pagination. `before` is an object ID that defines your place in the list.\nFor instance, if you make a list request and receive 100 objects, ending with obj_foo, your\nsubsequent call can include before=obj_foo in order to fetch the previous page of the list.", "schema": { "type": "string" }, "explode": false }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "type": "object", "required": [ "data", "has_more" ], "properties": { "data": { "type": "array", "items": { "$ref": "#/components/schemas/AgentVersionObject" }, "description": "The requested list of items." }, "first_id": { "type": "string", "description": "The first ID represented in this list." }, "last_id": { "type": "string", "description": "The last ID represented in this list." }, "has_more": { "type": "boolean", "description": "A value indicating whether there are additional values available not captured in this list." } }, "description": "The response data for a requested list of items." } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Agents" ] } }, "/agents/{agent_name}/versions/{agent_version}": { "get": { "operationId": "Agents_getAgentVersion", "description": "Retrieves a specific version of an agent.", "parameters": [ { "name": "agent_name", "in": "path", "required": true, "description": "The name of the agent to retrieve.", "schema": { "type": "string" } }, { "name": "agent_version", "in": "path", "required": true, "description": "The version of the agent to retrieve.", "schema": { "type": "string" } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/AgentVersionObject" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Agents" ] }, "delete": { "operationId": "Agents_deleteAgentVersion", "description": "Deletes a specific version of an agent.", "parameters": [ { "name": "agent_name", "in": "path", "required": true, "description": "The name of the agent to delete.", "schema": { "type": "string" } }, { "name": "agent_version", "in": "path", "required": true, "description": "The version of the agent to delete", "schema": { "type": "string" } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/DeleteAgentVersionResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Agents" ] } }, "/agents/{agent_name}/versions:import": { "post": { "operationId": "Agents_createAgentVersionFromManifest", "description": "Create a new agent version from a manifest.", "parameters": [ { "name": "agent_name", "in": "path", "required": true, "description": "The unique name that identifies the agent. Name can be used to retrieve/update/delete the agent.\n- Must start and end with alphanumeric characters,\n- Can contain hyphens in the middle\n- Must not exceed 63 characters.", "schema": { "type": "string", "maxLength": 63 } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/AgentVersionObject" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Agents" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/CreateAgentVersionFromManifestRequest" } } } } } }, "/agents:import": { "post": { "operationId": "Agents_createAgentFromManifest", "description": "Creates an agent from a manifest.", "parameters": [ { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/AgentObject" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Agents" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/CreateAgentFromManifestRequest" } } } } } }, "/connections": { "get": { "operationId": "Connections_list", "description": "List all connections in the project, without populating connection credentials", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "connectionType", "in": "query", "required": false, "description": "List connections of this specific type", "schema": { "$ref": "#/components/schemas/ConnectionType" }, "explode": false }, { "name": "defaultConnection", "in": "query", "required": false, "description": "List connections that are default connections", "schema": { "type": "boolean" }, "explode": false }, { "$ref": "#/components/parameters/Azure.Core.ClientRequestIdHeader" } ], "responses": { "200": { "description": "The request has succeeded.", "headers": { "x-ms-client-request-id": { "required": false, "description": "An opaque, globally-unique, client-generated string identifier for the request.", "schema": { "$ref": "#/components/schemas/Azure.Core.uuid" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/PagedConnection" } } } }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Connections" ] } }, "/connections/{name}": { "get": { "operationId": "Connections_get", "description": "Get a connection by name, without populating connection credentials", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "name", "in": "path", "required": true, "description": "The friendly name of the connection, provided by the user.", "schema": { "type": "string" } }, { "$ref": "#/components/parameters/Azure.Core.ClientRequestIdHeader" } ], "responses": { "200": { "description": "The request has succeeded.", "headers": { "x-ms-client-request-id": { "required": false, "description": "An opaque, globally-unique, client-generated string identifier for the request.", "schema": { "$ref": "#/components/schemas/Azure.Core.uuid" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Connection" } } } }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Connections" ] } }, "/connections/{name}/getConnectionWithCredentials": { "post": { "operationId": "Connections_getWithCredentials", "description": "Get a connection by name, with its connection credentials", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "name", "in": "path", "required": true, "description": "The friendly name of the connection, provided by the user.", "schema": { "type": "string" } }, { "$ref": "#/components/parameters/Azure.Core.ClientRequestIdHeader" } ], "responses": { "200": { "description": "The request has succeeded.", "headers": { "x-ms-client-request-id": { "required": false, "description": "An opaque, globally-unique, client-generated string identifier for the request.", "schema": { "$ref": "#/components/schemas/Azure.Core.uuid" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Connection" } } } }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Connections" ] } }, "/datasets": { "get": { "operationId": "Datasets_listLatest", "description": "List the latest version of each DatasetVersion", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/PagedDatasetVersion" } } } }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Datasets" ] } }, "/datasets/{name}/versions": { "get": { "operationId": "Datasets_listVersions", "description": "List all versions of the given DatasetVersion", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "name", "in": "path", "required": true, "description": "The name of the resource", "schema": { "type": "string" } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/PagedDatasetVersion" } } } }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Datasets" ] } }, "/datasets/{name}/versions/{version}": { "get": { "operationId": "Datasets_getVersion", "description": "Get the specific version of the DatasetVersion. The service returns 404 Not Found error if the DatasetVersion does not exist.", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "name", "in": "path", "required": true, "description": "The name of the resource", "schema": { "type": "string" } }, { "name": "version", "in": "path", "required": true, "description": "The specific version id of the DatasetVersion to retrieve.", "schema": { "type": "string" } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/DatasetVersion" } } } }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Datasets" ] }, "delete": { "operationId": "Datasets_deleteVersion", "description": "Delete the specific version of the DatasetVersion. The service returns 204 No Content if the DatasetVersion was deleted successfully or if the DatasetVersion does not exist.", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "name", "in": "path", "required": true, "description": "The name of the resource", "schema": { "type": "string" } }, { "name": "version", "in": "path", "required": true, "description": "The version of the DatasetVersion to delete.", "schema": { "type": "string" } } ], "responses": { "204": { "description": "There is no content to send for this request, but the headers may be useful." }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Datasets" ] }, "patch": { "operationId": "Datasets_createOrUpdateVersion", "description": "Create a new or update an existing DatasetVersion with the given version id", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "name", "in": "path", "required": true, "description": "The name of the resource", "schema": { "type": "string" } }, { "name": "version", "in": "path", "required": true, "description": "The specific version id of the DatasetVersion to create or update.", "schema": { "type": "string" } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/DatasetVersion" } } } }, "201": { "description": "The request has succeeded and a new resource has been created as a result.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/DatasetVersion" } } } }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Datasets" ], "requestBody": { "required": true, "content": { "application/merge-patch+json": { "schema": { "$ref": "#/components/schemas/DatasetVersionUpdate" } } }, "description": "The DatasetVersion to create or update." } } }, "/datasets/{name}/versions/{version}/credentials": { "post": { "operationId": "Datasets_getCredentials", "description": "Get the SAS credential to access the storage account associated with a Dataset version.", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "name", "in": "path", "required": true, "description": "The name of the resource", "schema": { "type": "string" } }, { "name": "version", "in": "path", "required": true, "description": "The specific version id of the DatasetVersion to operate on.", "schema": { "type": "string" } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/AssetCredentialResponse" } } } }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Datasets" ] } }, "/datasets/{name}/versions/{version}/startPendingUpload": { "post": { "operationId": "Datasets_startPendingUploadVersion", "description": "Start a new or get an existing pending upload of a dataset for a specific version.", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "name", "in": "path", "required": true, "description": "The name of the resource", "schema": { "type": "string" } }, { "name": "version", "in": "path", "required": true, "description": "The specific version id of the DatasetVersion to operate on.", "schema": { "type": "string" } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/PendingUploadResponse" } } } }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Datasets" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/PendingUploadRequest" } } }, "description": "The pending upload request parameters" } } }, "/deployments": { "get": { "operationId": "Deployments_list", "description": "List all deployed models in the project", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "modelPublisher", "in": "query", "required": false, "description": "Model publisher to filter models by", "schema": { "type": "string" }, "explode": false }, { "name": "modelName", "in": "query", "required": false, "description": "Model name (the publisher specific name) to filter models by", "schema": { "type": "string" }, "explode": false }, { "name": "deploymentType", "in": "query", "required": false, "description": "Type of deployment to filter list by", "schema": { "$ref": "#/components/schemas/DeploymentType" }, "explode": false }, { "$ref": "#/components/parameters/Azure.Core.ClientRequestIdHeader" } ], "responses": { "200": { "description": "The request has succeeded.", "headers": { "x-ms-client-request-id": { "required": false, "description": "An opaque, globally-unique, client-generated string identifier for the request.", "schema": { "$ref": "#/components/schemas/Azure.Core.uuid" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/PagedDeployment" } } } }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Deployments" ] } }, "/deployments/{name}": { "get": { "operationId": "Deployments_get", "description": "Get a deployed model.", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "name", "in": "path", "required": true, "description": "Name of the deployment", "schema": { "type": "string" } }, { "$ref": "#/components/parameters/Azure.Core.ClientRequestIdHeader" } ], "responses": { "200": { "description": "The request has succeeded.", "headers": { "x-ms-client-request-id": { "required": false, "description": "An opaque, globally-unique, client-generated string identifier for the request.", "schema": { "$ref": "#/components/schemas/Azure.Core.uuid" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Deployment" } } } }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Deployments" ] } }, "/evaluationrules": { "get": { "operationId": "EvaluationRules_list", "description": "List all evaluation rules.", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "actionType", "in": "query", "required": false, "description": "Filter by the type of evaluation rule.", "schema": { "$ref": "#/components/schemas/EvaluationRuleActionType" }, "explode": false }, { "name": "agentName", "in": "query", "required": false, "description": "Filter by the agent name.", "schema": { "type": "string" }, "explode": false }, { "name": "enabled", "in": "query", "required": false, "description": "Filter by the enabled status.", "schema": { "type": "boolean" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/PagedEvaluationRule" } } } }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Evaluation Rules" ] } }, "/evaluationrules/{id}": { "get": { "operationId": "EvaluationRules_get", "description": "Get an evaluation rule.", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "id", "in": "path", "required": true, "description": "Unique identifier for the evaluation rule.", "schema": { "type": "string" } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/EvaluationRule" } } } }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Evaluation Rules" ] }, "delete": { "operationId": "EvaluationRules_delete", "description": "Delete an evaluation rule.", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "id", "in": "path", "required": true, "description": "Unique identifier for the evaluation rule.", "schema": { "type": "string" } } ], "responses": { "204": { "description": "There is no content to send for this request, but the headers may be useful." }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Evaluation Rules" ] }, "put": { "operationId": "EvaluationRules_createOrUpdate", "description": "Create or update an evaluation rule.", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "id", "in": "path", "required": true, "description": "Unique identifier for the evaluation rule.", "schema": { "type": "string" } }, { "name": "Foundry-Features", "in": "header", "required": false, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "Evaluations=V1Preview" ] } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/EvaluationRule" } } } }, "201": { "description": "The request has succeeded and a new resource has been created as a result.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/EvaluationRule" } } } }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Evaluation Rules" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/EvaluationRule" } } }, "description": "Evaluation rule resource" } } }, "/evaluationtaxonomies": { "get": { "operationId": "EvaluationTaxonomies_list", "description": "List evaluation taxonomies", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "inputName", "in": "query", "required": false, "description": "Filter by the evaluation input name.", "schema": { "type": "string" }, "explode": false }, { "name": "inputType", "in": "query", "required": false, "description": "Filter by taxonomy input type.", "schema": { "type": "string" }, "explode": false }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "Evaluations=V1Preview" ] } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/PagedEvaluationTaxonomy" } } } }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Evaluation Taxonomies" ] } }, "/evaluationtaxonomies/{name}": { "get": { "operationId": "EvaluationTaxonomies_get", "description": "Get an evaluation run by name.", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "name", "in": "path", "required": true, "description": "The name of the resource", "schema": { "type": "string" } }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "Evaluations=V1Preview" ] } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/EvaluationTaxonomy" } } } }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Evaluation Taxonomies" ] }, "delete": { "operationId": "EvaluationTaxonomies_delete", "description": "Delete an evaluation taxonomy by name.", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "name", "in": "path", "required": true, "description": "The name of the resource", "schema": { "type": "string" } }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "Evaluations=V1Preview" ] } } ], "responses": { "204": { "description": "There is no content to send for this request, but the headers may be useful." }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Evaluation Taxonomies" ] }, "put": { "operationId": "EvaluationTaxonomies_create", "description": "Create an evaluation taxonomy.", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "Evaluations=V1Preview" ] } }, { "name": "name", "in": "path", "required": true, "description": "The name of the evaluation taxonomy.", "schema": { "type": "string" } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/EvaluationTaxonomy" } } } }, "201": { "description": "The request has succeeded and a new resource has been created as a result.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/EvaluationTaxonomy" } } } }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Evaluation Taxonomies" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/EvaluationTaxonomyCreateOrUpdate" } } }, "description": "The evaluation taxonomy." } }, "patch": { "operationId": "EvaluationTaxonomies_update", "description": "Update an evaluation taxonomy.", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "Evaluations=V1Preview" ] } }, { "name": "name", "in": "path", "required": true, "description": "The name of the evaluation taxonomy.", "schema": { "type": "string" } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/EvaluationTaxonomy" } } } }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Evaluation Taxonomies" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/EvaluationTaxonomyUpdate" } } }, "description": "The evaluation taxonomy." } } }, "/evaluators": { "get": { "operationId": "Evaluators_listLatestVersions", "description": "List the latest version of each evaluator", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "type", "in": "query", "required": false, "description": "Filter evaluators by type. Possible values: 'all', 'custom', 'builtin'.", "schema": { "anyOf": [ { "$ref": "#/components/schemas/EvaluatorType" }, { "type": "string", "enum": [ "all" ] } ] }, "explode": false }, { "name": "limit", "in": "query", "required": false, "description": "A limit on the number of objects to be returned. Limit can range between 1 and 100, and the default is 20.", "schema": { "type": "integer", "format": "int32", "default": 20 }, "explode": false }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "Evaluations=V1Preview" ] } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/PagedEvaluatorVersion" } } } }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Evaluators" ] } }, "/evaluators/{name}/versions": { "get": { "operationId": "Evaluators_listVersions", "description": "List all versions of the given evaluator", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "name", "in": "path", "required": true, "description": "The name of the resource", "schema": { "type": "string" } }, { "name": "type", "in": "query", "required": false, "description": "Filter evaluators by type. Possible values: 'all', 'custom', 'builtin'.", "schema": { "anyOf": [ { "$ref": "#/components/schemas/EvaluatorType" }, { "type": "string", "enum": [ "all" ] } ] }, "explode": false }, { "name": "limit", "in": "query", "required": false, "description": "A limit on the number of objects to be returned. Limit can range between 1 and 100, and the default is 20.", "schema": { "type": "integer", "format": "int32", "default": 20 }, "explode": false }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "Evaluations=V1Preview" ] } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/PagedEvaluatorVersion" } } } }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Evaluators" ] }, "post": { "operationId": "Evaluators_createVersion", "description": "Create a new EvaluatorVersion with auto incremented version id", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "name", "in": "path", "required": true, "description": "The name of the resource", "schema": { "type": "string" } }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "Evaluations=V1Preview" ] } } ], "responses": { "201": { "description": "The request has succeeded and a new resource has been created as a result.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/EvaluatorVersion" } } } }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Evaluators" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/EvaluatorVersionCreate" } } } } } }, "/evaluators/{name}/versions/{version}": { "get": { "operationId": "Evaluators_getVersion", "description": "Get the specific version of the EvaluatorVersion. The service returns 404 Not Found error if the EvaluatorVersion does not exist.", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "name", "in": "path", "required": true, "description": "The name of the resource", "schema": { "type": "string" } }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "Evaluations=V1Preview" ] } }, { "name": "version", "in": "path", "required": true, "description": "The specific version id of the EvaluatorVersion to retrieve.", "schema": { "type": "string" } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/EvaluatorVersion" } } } }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Evaluators" ] }, "delete": { "operationId": "Evaluators_deleteVersion", "description": "Delete the specific version of the EvaluatorVersion. The service returns 204 No Content if the EvaluatorVersion was deleted successfully or if the EvaluatorVersion does not exist.", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "name", "in": "path", "required": true, "description": "The name of the resource", "schema": { "type": "string" } }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "Evaluations=V1Preview" ] } }, { "name": "version", "in": "path", "required": true, "description": "The version of the EvaluatorVersion to delete.", "schema": { "type": "string" } } ], "responses": { "204": { "description": "There is no content to send for this request, but the headers may be useful." }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Evaluators" ] }, "patch": { "operationId": "Evaluators_updateVersion", "description": "Update an existing EvaluatorVersion with the given version id", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "name", "in": "path", "required": true, "description": "The name of the resource", "schema": { "type": "string" } }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "Evaluations=V1Preview" ] } }, { "name": "version", "in": "path", "required": true, "description": "The version of the EvaluatorVersion to update.", "schema": { "type": "string" } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/EvaluatorVersion" } } } }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Evaluators" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/EvaluatorVersionUpdate" } } }, "description": "Evaluator resource" } } }, "/evaluators/{name}/versions/{version}/credentials": { "post": { "operationId": "Evaluators_getCredentials", "description": "Get the SAS credential to access the storage account associated with an Evaluator version.", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "name", "in": "path", "required": true, "description": "The name of the resource", "schema": { "type": "string" } }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "Evaluations=V1Preview" ] } }, { "name": "version", "in": "path", "required": true, "description": "The specific version id of the EvaluatorVersion to operate on.", "schema": { "type": "string" } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/AssetCredentialResponse" } } } }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Evaluators" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/EvaluatorCredentialRequest" } } }, "description": "The credential request parameters" } } }, "/evaluators/{name}/versions/{version}/startPendingUpload": { "post": { "operationId": "Evaluators_startPendingUpload", "description": "Start a new or get an existing pending upload of an evaluator for a specific version.", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "name", "in": "path", "required": true, "description": "The name of the resource", "schema": { "type": "string" } }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "Evaluations=V1Preview" ] } }, { "name": "version", "in": "path", "required": true, "description": "The specific version id of the EvaluatorVersion to operate on.", "schema": { "type": "string" } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/PendingUploadResponse" } } } }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Evaluators" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/PendingUploadRequest" } } }, "description": "The pending upload request parameters" } } }, "/indexes": { "get": { "operationId": "Indexes_listLatest", "description": "List the latest version of each Index", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/PagedIndex" } } } }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Indexes" ] } }, "/indexes/{name}/versions": { "get": { "operationId": "Indexes_listVersions", "description": "List all versions of the given Index", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "name", "in": "path", "required": true, "description": "The name of the resource", "schema": { "type": "string" } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/PagedIndex" } } } }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Indexes" ] } }, "/indexes/{name}/versions/{version}": { "get": { "operationId": "Indexes_getVersion", "description": "Get the specific version of the Index. The service returns 404 Not Found error if the Index does not exist.", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "name", "in": "path", "required": true, "description": "The name of the resource", "schema": { "type": "string" } }, { "name": "version", "in": "path", "required": true, "description": "The specific version id of the Index to retrieve.", "schema": { "type": "string" } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Index" } } } }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Indexes" ] }, "delete": { "operationId": "Indexes_deleteVersion", "description": "Delete the specific version of the Index. The service returns 204 No Content if the Index was deleted successfully or if the Index does not exist.", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "name", "in": "path", "required": true, "description": "The name of the resource", "schema": { "type": "string" } }, { "name": "version", "in": "path", "required": true, "description": "The version of the Index to delete.", "schema": { "type": "string" } } ], "responses": { "204": { "description": "There is no content to send for this request, but the headers may be useful." }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Indexes" ] }, "patch": { "operationId": "Indexes_createOrUpdateVersion", "description": "Create a new or update an existing Index with the given version id", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "name", "in": "path", "required": true, "description": "The name of the resource", "schema": { "type": "string" } }, { "name": "version", "in": "path", "required": true, "description": "The specific version id of the Index to create or update.", "schema": { "type": "string" } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Index" } } } }, "201": { "description": "The request has succeeded and a new resource has been created as a result.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Index" } } } }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Indexes" ], "requestBody": { "required": true, "content": { "application/merge-patch+json": { "schema": { "$ref": "#/components/schemas/IndexUpdate" } } }, "description": "The Index to create or update." } } }, "/insights": { "post": { "operationId": "Insights_generate", "description": "Generate Insights", "parameters": [ { "name": "Foundry-Features", "in": "header", "required": false, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "Insights=V1Preview" ] } }, { "name": "Repeatability-Request-ID", "in": "header", "required": false, "description": "Unique, client-generated identifier for ensuring request idempotency. Use the same ID for retries to prevent duplicate evaluations.", "schema": { "type": "string" } }, { "name": "Repeatability-First-Sent", "in": "header", "required": false, "description": "Timestamp indicating when this request was first initiated. Used in conjunction with repeatability-request-id for idempotency control.", "schema": { "type": "string", "format": "http-date" } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "201": { "description": "The request has succeeded and a new resource has been created as a result.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Insight" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Insights" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Insight" } } }, "description": "Complete evaluation configuration including data source, evaluators, and result settings" } }, "get": { "operationId": "Insights_list", "description": "List all insights in reverse chronological order (newest first).", "parameters": [ { "name": "Foundry-Features", "in": "header", "required": false, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "Insights=V1Preview" ] } }, { "name": "type", "in": "query", "required": false, "description": "Filter by the type of analysis.", "schema": { "$ref": "#/components/schemas/InsightType" }, "explode": false }, { "name": "evalId", "in": "query", "required": false, "description": "Filter by the evaluation ID.", "schema": { "type": "string" }, "explode": false }, { "name": "runId", "in": "query", "required": false, "description": "Filter by the evaluation run ID.", "schema": { "type": "string" }, "explode": false }, { "name": "agentName", "in": "query", "required": false, "description": "Filter by the agent name.", "schema": { "type": "string" }, "explode": false }, { "name": "includeCoordinates", "in": "query", "required": false, "description": "Whether to include coordinates for visualization in the response. Defaults to false.", "schema": { "type": "boolean" }, "explode": false }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/PagedInsight" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Insights" ] } }, "/insights/{id}": { "get": { "operationId": "Insights_get", "description": "Get a specific insight by Id.", "parameters": [ { "name": "Foundry-Features", "in": "header", "required": false, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "Insights=V1Preview" ] } }, { "name": "includeCoordinates", "in": "query", "required": false, "description": "Whether to include coordinates for visualization in the response. Defaults to false.", "schema": { "type": "boolean" }, "explode": false }, { "name": "id", "in": "path", "required": true, "description": "The unique identifier for the insights report.", "schema": { "type": "string" } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Insight" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Insights" ] } }, "/memory_stores": { "post": { "operationId": "createMemoryStore", "description": "Create a memory store.", "parameters": [ { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "MemoryStores=V1Preview" ] } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/MemoryStoreObject" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Memory Stores" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "type": "object", "properties": { "name": { "type": "string", "maxLength": 256, "description": "The name of the memory store." }, "description": { "type": "string", "maxLength": 512, "description": "A human-readable description of the memory store." }, "metadata": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Arbitrary key-value metadata to associate with the memory store." }, "definition": { "allOf": [ { "$ref": "#/components/schemas/MemoryStoreDefinition" } ], "description": "The memory store definition." } }, "required": [ "name", "definition" ] } } } }, "x-ms-foundry-meta": { "conditional_previews": [ "MemoryStores=V1Preview" ] } }, "get": { "operationId": "listMemoryStores", "description": "List all memory stores.", "parameters": [ { "name": "limit", "in": "query", "required": false, "description": "A limit on the number of objects to be returned. Limit can range between 1 and 100, and the\ndefault is 20.", "schema": { "type": "integer", "format": "int32", "default": 20 }, "explode": false }, { "name": "order", "in": "query", "required": false, "description": "Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and`desc`\nfor descending order.", "schema": { "$ref": "#/components/schemas/PageOrder" }, "explode": false }, { "name": "after", "in": "query", "required": false, "description": "A cursor for use in pagination. `after` is an object ID that defines your place in the list.\nFor instance, if you make a list request and receive 100 objects, ending with obj_foo, your\nsubsequent call can include after=obj_foo in order to fetch the next page of the list.", "schema": { "type": "string" }, "explode": false }, { "name": "before", "in": "query", "required": false, "description": "A cursor for use in pagination. `before` is an object ID that defines your place in the list.\nFor instance, if you make a list request and receive 100 objects, ending with obj_foo, your\nsubsequent call can include before=obj_foo in order to fetch the previous page of the list.", "schema": { "type": "string" }, "explode": false }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "MemoryStores=V1Preview" ] } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "type": "object", "required": [ "data", "has_more" ], "properties": { "data": { "type": "array", "items": { "$ref": "#/components/schemas/MemoryStoreObject" }, "description": "The requested list of items." }, "first_id": { "type": "string", "description": "The first ID represented in this list." }, "last_id": { "type": "string", "description": "The last ID represented in this list." }, "has_more": { "type": "boolean", "description": "A value indicating whether there are additional values available not captured in this list." } }, "description": "The response data for a requested list of items." } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Memory Stores" ], "x-ms-foundry-meta": { "conditional_previews": [ "MemoryStores=V1Preview" ] } } }, "/memory_stores/{name}": { "post": { "operationId": "updateMemoryStore", "description": "Update a memory store.", "parameters": [ { "name": "name", "in": "path", "required": true, "description": "The name of the memory store to update.", "schema": { "type": "string" } }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "MemoryStores=V1Preview" ] } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/MemoryStoreObject" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Memory Stores" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "type": "object", "properties": { "description": { "type": "string", "maxLength": 512, "description": "A human-readable description of the memory store." }, "metadata": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Arbitrary key-value metadata to associate with the memory store." } } } } } }, "x-ms-foundry-meta": { "conditional_previews": [ "MemoryStores=V1Preview" ] } }, "get": { "operationId": "getMemoryStore", "description": "Retrieve a memory store.", "parameters": [ { "name": "name", "in": "path", "required": true, "description": "The name of the memory store to retrieve.", "schema": { "type": "string" } }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "MemoryStores=V1Preview" ] } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/MemoryStoreObject" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Memory Stores" ], "x-ms-foundry-meta": { "conditional_previews": [ "MemoryStores=V1Preview" ] } }, "delete": { "operationId": "deleteMemoryStore", "description": "Delete a memory store.", "parameters": [ { "name": "name", "in": "path", "required": true, "description": "The name of the memory store to delete.", "schema": { "type": "string" } }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "MemoryStores=V1Preview" ] } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/DeleteMemoryStoreResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Memory Stores" ], "x-ms-foundry-meta": { "conditional_previews": [ "MemoryStores=V1Preview" ] } } }, "/memory_stores/{name}/updates/{update_id}": { "get": { "operationId": "getUpdateResult", "description": "Get memory store update result.", "parameters": [ { "name": "name", "in": "path", "required": true, "description": "The name of the memory store.", "schema": { "type": "string" } }, { "name": "update_id", "in": "path", "required": true, "description": "The ID of the memory update operation.", "schema": { "type": "string" } }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "MemoryStores=V1Preview" ] } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/MemoryStoreUpdateResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Memory Stores" ], "x-ms-foundry-meta": { "conditional_previews": [ "MemoryStores=V1Preview" ] } } }, "/memory_stores/{name}:delete_scope": { "post": { "operationId": "deleteScopeMemories", "description": "Delete all memories associated with a specific scope from a memory store.", "parameters": [ { "name": "name", "in": "path", "required": true, "description": "The name of the memory store.", "schema": { "type": "string" } }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "MemoryStores=V1Preview" ] } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/MemoryStoreDeleteScopeResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Memory Stores" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "type": "object", "properties": { "scope": { "type": "string", "description": "The namespace that logically groups and isolates memories to delete, such as a user ID." } }, "required": [ "scope" ] } } } }, "x-ms-foundry-meta": { "conditional_previews": [ "MemoryStores=V1Preview" ] } } }, "/memory_stores/{name}:search_memories": { "post": { "operationId": "searchMemories", "description": "Search for relevant memories from a memory store based on conversation context.", "parameters": [ { "name": "name", "in": "path", "required": true, "description": "The name of the memory store to search.", "schema": { "type": "string" } }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "MemoryStores=V1Preview" ] } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/MemoryStoreSearchResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Memory Stores" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "type": "object", "properties": { "scope": { "type": "string", "description": "The namespace that logically groups and isolates memories, such as a user ID." }, "items": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.InputItem" }, "description": "Items for which to search for relevant memories." }, "previous_search_id": { "type": "string", "description": "The unique ID of the previous search request, enabling incremental memory search from where the last operation left off." }, "options": { "allOf": [ { "$ref": "#/components/schemas/MemorySearchOptions" } ], "description": "Memory search options." } }, "required": [ "scope" ] } } } }, "x-ms-foundry-meta": { "conditional_previews": [ "MemoryStores=V1Preview" ] } } }, "/memory_stores/{name}:update_memories": { "post": { "operationId": "updateMemories", "description": "Update memory store with conversation memories.", "parameters": [ { "name": "name", "in": "path", "required": true, "description": "The name of the memory store to update.", "schema": { "type": "string" } }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "MemoryStores=V1Preview" ] } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "202": { "description": "The request has been accepted for processing, but processing has not yet completed.", "headers": { "Operation-Location": { "required": true, "description": "The location for monitoring the operation state.", "schema": { "type": "string", "format": "uri" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/MemoryStoreUpdateResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Memory Stores" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "type": "object", "properties": { "scope": { "type": "string", "description": "The namespace that logically groups and isolates memories, such as a user ID." }, "items": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.InputItem" }, "description": "Conversation items to be stored in memory." }, "previous_update_id": { "type": "string", "description": "The unique ID of the previous update request, enabling incremental memory updates from where the last operation left off." }, "update_delay": { "type": "integer", "format": "int32", "description": "Timeout period before processing the memory update in seconds.\nIf a new update request is received during this period, it will cancel the current request and reset the timeout.\nSet to 0 to immediately trigger the update without delay.\nDefaults to 300 (5 minutes).", "default": 300 } }, "required": [ "scope" ] } } } }, "x-ms-foundry-meta": { "conditional_previews": [ "MemoryStores=V1Preview" ] } } }, "/mlflow/api/2.0/mlflow/artifacts/list": { "get": { "operationId": "Artifacts_list", "description": "List MLflow artifacts.", "parameters": [ { "name": "run_id", "in": "query", "required": false, "description": "MLflow run identifier.", "schema": { "type": "string" }, "explode": false }, { "name": "run_uuid", "in": "query", "required": false, "description": "MLflow run UUID.", "schema": { "type": "string" }, "explode": false }, { "name": "path", "in": "query", "required": false, "description": "Artifact path to list.", "schema": { "type": "string" }, "explode": false }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Artifacts" ] } }, "/mlflow/api/2.0/mlflow/experiments/create": { "post": { "operationId": "Experiments_create", "description": "Create an MLflow experiment.", "parameters": [ { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Experiments" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowPayload" } } } } } }, "/mlflow/api/2.0/mlflow/experiments/delete": { "post": { "operationId": "Experiments_delete", "description": "Delete an MLflow experiment.", "parameters": [ { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Experiments" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowPayload" } } } } } }, "/mlflow/api/2.0/mlflow/experiments/get": { "get": { "operationId": "Experiments_get", "description": "Get an MLflow experiment by ID.", "parameters": [ { "name": "experiment_id", "in": "query", "required": false, "description": "MLflow experiment identifier.", "schema": { "type": "string" }, "explode": false }, { "name": "experiment_name", "in": "query", "required": false, "description": "MLflow experiment name.", "schema": { "type": "string" }, "explode": false }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Experiments" ] } }, "/mlflow/api/2.0/mlflow/experiments/get-by-name": { "get": { "operationId": "Experiments_getByName", "description": "Get an MLflow experiment by name.", "parameters": [ { "name": "experiment_id", "in": "query", "required": false, "description": "MLflow experiment identifier.", "schema": { "type": "string" }, "explode": false }, { "name": "experiment_name", "in": "query", "required": false, "description": "MLflow experiment name.", "schema": { "type": "string" }, "explode": false }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Experiments" ] } }, "/mlflow/api/2.0/mlflow/experiments/list": { "get": { "operationId": "Experiments_list", "description": "List MLflow experiments.", "parameters": [ { "name": "max_results", "in": "query", "required": false, "description": "Maximum number of items to return.", "schema": { "type": "integer", "format": "int32" }, "explode": false }, { "name": "page_token", "in": "query", "required": false, "description": "Token used to retrieve the next page of results.", "schema": { "type": "string" }, "explode": false }, { "name": "view_type", "in": "query", "required": false, "description": "Experiment lifecycle stage filter.", "schema": { "type": "string" }, "explode": false }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Experiments" ] } }, "/mlflow/api/2.0/mlflow/experiments/restore": { "post": { "operationId": "Experiments_restore", "description": "Restore a deleted MLflow experiment.", "parameters": [ { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Experiments" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowPayload" } } } } } }, "/mlflow/api/2.0/mlflow/experiments/search": { "post": { "operationId": "Experiments_search", "description": "Search MLflow experiments.", "parameters": [ { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Experiments" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowPayload" } } } } } }, "/mlflow/api/2.0/mlflow/experiments/set-experiment-tag": { "post": { "operationId": "Experiments_setTag", "description": "Set an MLflow experiment tag.", "parameters": [ { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Experiments" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowPayload" } } } } } }, "/mlflow/api/2.0/mlflow/experiments/update": { "post": { "operationId": "Experiments_update", "description": "Update MLflow experiment metadata.", "parameters": [ { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Experiments" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowPayload" } } } } } }, "/mlflow/api/2.0/mlflow/metrics/get-history": { "get": { "operationId": "Metrics_getHistory", "description": "Get MLflow metric history.", "parameters": [ { "name": "run_id", "in": "query", "required": false, "description": "MLflow run identifier.", "schema": { "type": "string" }, "explode": false }, { "name": "run_uuid", "in": "query", "required": false, "description": "MLflow run UUID.", "schema": { "type": "string" }, "explode": false }, { "name": "metric_key", "in": "query", "required": false, "description": "Metric key.", "schema": { "type": "string" }, "explode": false }, { "name": "max_results", "in": "query", "required": false, "description": "Maximum number of metric points to return.", "schema": { "type": "integer", "format": "int32" }, "explode": false }, { "name": "page_token", "in": "query", "required": false, "description": "Token used to retrieve the next page of metric points.", "schema": { "type": "string" }, "explode": false }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Metrics" ] } }, "/mlflow/api/2.0/mlflow/model-versions/create": { "post": { "operationId": "ModelVersions_create", "description": "Create an MLflow model version.", "parameters": [ { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Model Versions" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowPayload" } } } } } }, "/mlflow/api/2.0/mlflow/model-versions/delete": { "delete": { "operationId": "ModelVersions_delete", "description": "Delete an MLflow model version.", "parameters": [ { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Model Versions" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowPayload" } } } } } }, "/mlflow/api/2.0/mlflow/model-versions/delete-tag": { "delete": { "operationId": "ModelVersions_deleteTag", "description": "Delete an MLflow model-version tag.", "parameters": [ { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Model Versions" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowPayload" } } } } } }, "/mlflow/api/2.0/mlflow/model-versions/get": { "get": { "operationId": "ModelVersions_get", "description": "Get an MLflow model version.", "parameters": [ { "name": "name", "in": "query", "required": false, "description": "Registered model name.", "schema": { "type": "string" }, "explode": false }, { "name": "version", "in": "query", "required": false, "description": "Model version.", "schema": { "type": "string" }, "explode": false }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Model Versions" ] } }, "/mlflow/api/2.0/mlflow/model-versions/get-download-uri": { "get": { "operationId": "ModelVersions_getDownloadUri", "description": "Get an MLflow model version download URI.", "parameters": [ { "name": "name", "in": "query", "required": false, "description": "Registered model name.", "schema": { "type": "string" }, "explode": false }, { "name": "version", "in": "query", "required": false, "description": "Model version.", "schema": { "type": "string" }, "explode": false }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Model Versions" ] } }, "/mlflow/api/2.0/mlflow/model-versions/get-storage-location-uri": { "get": { "operationId": "ModelVersions_getStorageLocationUri", "description": "Get an MLflow model version storage location URI.", "parameters": [ { "name": "name", "in": "query", "required": false, "description": "Registered model name.", "schema": { "type": "string" }, "explode": false }, { "name": "version", "in": "query", "required": false, "description": "Model version.", "schema": { "type": "string" }, "explode": false }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Model Versions" ] } }, "/mlflow/api/2.0/mlflow/model-versions/search": { "get": { "operationId": "ModelVersions_search", "description": "Search MLflow model versions.", "parameters": [ { "name": "max_results", "in": "query", "required": false, "description": "Maximum number of items to return.", "schema": { "type": "integer", "format": "int32" }, "explode": false }, { "name": "page_token", "in": "query", "required": false, "description": "Token used to retrieve the next page of results.", "schema": { "type": "string" }, "explode": false }, { "name": "filter", "in": "query", "required": false, "description": "Model version search filter.", "schema": { "type": "string" }, "explode": false }, { "name": "order_by", "in": "query", "required": false, "description": "Model version ordering expression.", "schema": { "type": "string" }, "explode": false }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Model Versions" ] }, "post": { "operationId": "ModelVersions_searchWithFilter", "description": "Search MLflow model versions with search options in the request body.", "parameters": [ { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Model Versions" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowPayload" } } } } } }, "/mlflow/api/2.0/mlflow/model-versions/set-tag": { "post": { "operationId": "ModelVersions_setTag", "description": "Set an MLflow model-version tag.", "parameters": [ { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Model Versions" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowPayload" } } } } } }, "/mlflow/api/2.0/mlflow/model-versions/transition-stage": { "post": { "operationId": "ModelVersions_transitionStage", "description": "Transition an MLflow model version stage.", "parameters": [ { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Model Versions" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowPayload" } } } } } }, "/mlflow/api/2.0/mlflow/model-versions/update": { "patch": { "operationId": "ModelVersions_update", "description": "Update an MLflow model version.", "parameters": [ { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Model Versions" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowPayload" } } } } } }, "/mlflow/api/2.0/mlflow/registered-models/create": { "post": { "operationId": "RegisteredModels_create", "description": "Create an MLflow registered model.", "parameters": [ { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Registered Models" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowPayload" } } } } } }, "/mlflow/api/2.0/mlflow/registered-models/delete": { "delete": { "operationId": "RegisteredModels_delete", "description": "Delete an MLflow registered model.", "parameters": [ { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Registered Models" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowPayload" } } } } } }, "/mlflow/api/2.0/mlflow/registered-models/delete-tag": { "delete": { "operationId": "RegisteredModels_deleteTag", "description": "Delete an MLflow registered-model tag.", "parameters": [ { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Registered Models" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowPayload" } } } } } }, "/mlflow/api/2.0/mlflow/registered-models/get": { "get": { "operationId": "RegisteredModels_get", "description": "Get an MLflow registered model.", "parameters": [ { "name": "name", "in": "query", "required": false, "description": "Registered model name.", "schema": { "type": "string" }, "explode": false }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Registered Models" ] } }, "/mlflow/api/2.0/mlflow/registered-models/get-latest-versions": { "get": { "operationId": "RegisteredModels_getLatestVersions", "description": "Get latest versions for an MLflow registered model.", "parameters": [ { "name": "name", "in": "query", "required": false, "description": "Registered model name.", "schema": { "type": "string" }, "explode": false }, { "name": "stages", "in": "query", "required": false, "description": "Model version stages to include.", "schema": { "type": "array", "items": { "type": "string" } }, "explode": false }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Registered Models" ] }, "post": { "operationId": "RegisteredModels_getLatestVersionsNameInBody", "description": "Get latest versions for an MLflow registered model with the model name in the request body.", "parameters": [ { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Registered Models" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowPayload" } } } } } }, "/mlflow/api/2.0/mlflow/registered-models/list": { "get": { "operationId": "RegisteredModels_list", "description": "List MLflow registered models.", "parameters": [ { "name": "max_results", "in": "query", "required": false, "description": "Maximum number of items to return.", "schema": { "type": "integer", "format": "int32" }, "explode": false }, { "name": "page_token", "in": "query", "required": false, "description": "Token used to retrieve the next page of results.", "schema": { "type": "string" }, "explode": false }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Registered Models" ] } }, "/mlflow/api/2.0/mlflow/registered-models/rename": { "post": { "operationId": "RegisteredModels_rename", "description": "Rename an MLflow registered model.", "parameters": [ { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Registered Models" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowPayload" } } } } } }, "/mlflow/api/2.0/mlflow/registered-models/search": { "get": { "operationId": "RegisteredModels_search", "description": "Search MLflow registered models.", "parameters": [ { "name": "max_results", "in": "query", "required": false, "description": "Maximum number of items to return.", "schema": { "type": "integer", "format": "int32" }, "explode": false }, { "name": "page_token", "in": "query", "required": false, "description": "Token used to retrieve the next page of results.", "schema": { "type": "string" }, "explode": false }, { "name": "filter", "in": "query", "required": false, "description": "Registered model search filter.", "schema": { "type": "string" }, "explode": false }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Registered Models" ] } }, "/mlflow/api/2.0/mlflow/registered-models/set-tag": { "post": { "operationId": "RegisteredModels_setTag", "description": "Set an MLflow registered-model tag.", "parameters": [ { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Registered Models" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowPayload" } } } } } }, "/mlflow/api/2.0/mlflow/registered-models/update": { "patch": { "operationId": "RegisteredModels_update", "description": "Update an MLflow registered model.", "parameters": [ { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Registered Models" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowPayload" } } } } } }, "/mlflow/api/2.0/mlflow/runs/create": { "post": { "operationId": "Runs_create", "description": "Create an MLflow run.", "parameters": [ { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Runs" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowPayload" } } } } } }, "/mlflow/api/2.0/mlflow/runs/delete": { "post": { "operationId": "Runs_delete", "description": "Delete an MLflow run.", "parameters": [ { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Runs" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowPayload" } } } } } }, "/mlflow/api/2.0/mlflow/runs/delete-tag": { "post": { "operationId": "Runs_deleteTag", "description": "Delete an MLflow run tag.", "parameters": [ { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Runs" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowPayload" } } } } } }, "/mlflow/api/2.0/mlflow/runs/get": { "get": { "operationId": "Runs_get", "description": "Get an MLflow run.", "parameters": [ { "name": "run_id", "in": "query", "required": false, "description": "MLflow run identifier.", "schema": { "type": "string" }, "explode": false }, { "name": "run_uuid", "in": "query", "required": false, "description": "MLflow run UUID.", "schema": { "type": "string" }, "explode": false }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Runs" ] } }, "/mlflow/api/2.0/mlflow/runs/log-batch": { "post": { "operationId": "Runs_logBatch", "description": "Log a batch of metrics, parameters, and tags to an MLflow run.", "parameters": [ { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Runs" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowPayload" } } } } } }, "/mlflow/api/2.0/mlflow/runs/log-inputs": { "post": { "operationId": "Runs_logInputs", "description": "Log MLflow run input relationships.", "parameters": [ { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Runs" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowPayload" } } } } } }, "/mlflow/api/2.0/mlflow/runs/log-metric": { "post": { "operationId": "Runs_logMetric", "description": "Log one metric to an MLflow run.", "parameters": [ { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Runs" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowPayload" } } } } } }, "/mlflow/api/2.0/mlflow/runs/log-model": { "post": { "operationId": "Runs_logModel", "description": "Log MLflow model metadata.", "parameters": [ { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Runs" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowPayload" } } } } } }, "/mlflow/api/2.0/mlflow/runs/log-parameter": { "post": { "operationId": "Runs_logParameter", "description": "Log one parameter to an MLflow run.", "parameters": [ { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Runs" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowPayload" } } } } } }, "/mlflow/api/2.0/mlflow/runs/restore": { "post": { "operationId": "Runs_restore", "description": "Restore a deleted MLflow run.", "parameters": [ { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Runs" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowPayload" } } } } } }, "/mlflow/api/2.0/mlflow/runs/search": { "post": { "operationId": "Runs_search", "description": "Search MLflow runs.", "parameters": [ { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Runs" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowPayload" } } } } } }, "/mlflow/api/2.0/mlflow/runs/set-tag": { "post": { "operationId": "Runs_setTag", "description": "Set an MLflow run tag.", "parameters": [ { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Runs" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowPayload" } } } } } }, "/mlflow/api/2.0/mlflow/runs/update": { "post": { "operationId": "Runs_update", "description": "Update MLflow run metadata or status.", "parameters": [ { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "MLflow Runs" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Mlflow.MlflowPayload" } } } } } }, "/models/operations/{operation_id}/result": { "get": { "operationId": "Models_getTrainingOperationResult", "description": "Poll the result of a managed model training operation.", "parameters": [ { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "TrainingJobs=V1Preview" ] } }, { "name": "operation_id", "in": "path", "required": true, "description": "The managed model training operation identifier.", "schema": { "type": "string" } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ModelTrainingOperation" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Models" ] } }, "/models:create_training_job": { "post": { "operationId": "Models_createTrainingJob", "description": "Create a model by running managed model training.", "parameters": [ { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "TrainingJobs=V1Preview" ] } }, { "name": "Operation-Id", "in": "header", "required": false, "description": "Idempotency key used to safely retry managed model training.", "schema": { "type": "string" } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "202": { "description": "The request has been accepted for processing, but processing has not yet completed.", "headers": { "Operation-Location": { "required": true, "description": "The location for monitoring the operation state.", "schema": { "type": "string", "format": "uri" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ModelTrainingOperation" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Models" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ModelTrainingJobCreate" } } }, "description": "The managed model training job to create." } } }, "/openai/v1/conversations": { "post": { "operationId": "createConversation", "description": "Create a conversation.", "parameters": [], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/OpenAI.ConversationResource" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Conversations" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/OpenAI.CreateConversationBody" } } } } }, "get": { "operationId": "listConversations", "description": "Returns the list of all conversations.", "parameters": [ { "name": "limit", "in": "query", "required": false, "description": "A limit on the number of objects to be returned. Limit can range between 1 and 100, and the\ndefault is 20.", "schema": { "type": "integer", "format": "int32", "default": 20 }, "explode": false }, { "name": "order", "in": "query", "required": false, "description": "Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and`desc`\nfor descending order.", "schema": { "$ref": "#/components/schemas/PageOrder" }, "explode": false }, { "name": "after", "in": "query", "required": false, "description": "A cursor for use in pagination. `after` is an object ID that defines your place in the list.\nFor instance, if you make a list request and receive 100 objects, ending with obj_foo, your\nsubsequent call can include after=obj_foo in order to fetch the next page of the list.", "schema": { "type": "string" }, "explode": false }, { "name": "before", "in": "query", "required": false, "description": "A cursor for use in pagination. `before` is an object ID that defines your place in the list.\nFor instance, if you make a list request and receive 100 objects, ending with obj_foo, your\nsubsequent call can include before=obj_foo in order to fetch the previous page of the list.", "schema": { "type": "string" }, "explode": false }, { "name": "agent_name", "in": "query", "required": false, "description": "Filter by agent name. If provided, only items associated with the specified agent will be returned.", "schema": { "type": "string" }, "explode": false }, { "name": "agent_id", "in": "query", "required": false, "description": "Filter by agent ID in the format `name:version`. If provided, only items associated with the specified agent ID will be returned.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "type": "object", "required": [ "data", "has_more" ], "properties": { "data": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.ConversationResource" }, "description": "The requested list of items." }, "first_id": { "type": "string", "description": "The first ID represented in this list." }, "last_id": { "type": "string", "description": "The last ID represented in this list." }, "has_more": { "type": "boolean", "description": "A value indicating whether there are additional values available not captured in this list." } }, "description": "The response data for a requested list of items." } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Conversations" ] } }, "/openai/v1/conversations/{conversation_id}": { "post": { "operationId": "updateConversation", "description": "Update a conversation.", "parameters": [ { "name": "conversation_id", "in": "path", "required": true, "description": "The id of the conversation to update.", "schema": { "type": "string" } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/OpenAI.ConversationResource" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Conversations" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/OpenAI.UpdateConversationBody" } } } } }, "get": { "operationId": "getConversation", "description": "Retrieves a conversation.", "parameters": [ { "name": "conversation_id", "in": "path", "required": true, "description": "The id of the conversation to retrieve.", "schema": { "type": "string" } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/OpenAI.ConversationResource" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Conversations" ] }, "delete": { "operationId": "deleteConversation", "description": "Deletes a conversation.", "parameters": [ { "name": "conversation_id", "in": "path", "required": true, "description": "The id of the conversation to delete.", "schema": { "type": "string" } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/OpenAI.DeletedConversationResource" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Conversations" ] } }, "/openai/v1/conversations/{conversation_id}/items": { "post": { "operationId": "createConversationItems", "description": "Create items in a conversation with the given ID.", "parameters": [ { "name": "conversation_id", "in": "path", "required": true, "description": "The id of the conversation on which the item needs to be created.", "schema": { "type": "string" } }, { "name": "include", "in": "query", "required": false, "description": "Additional fields to include in the response.\nSee the `include` parameter for listing Conversation items for more information.", "schema": { "type": "array", "items": { "type": "string" } }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/OpenAI.ConversationItemList" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Conversations" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "type": "object", "properties": { "items": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.Item" }, "maxItems": 20, "description": "The items to add to the conversation. You may add up to 20 items at a time." } }, "required": [ "items" ] } } } } }, "get": { "operationId": "listConversationItems", "description": "List all items for a conversation with the given ID.", "parameters": [ { "name": "conversation_id", "in": "path", "required": true, "description": "The id of the conversation on which the items needs to be listed.", "schema": { "type": "string" } }, { "name": "limit", "in": "query", "required": false, "description": "A limit on the number of objects to be returned. Limit can range between 1 and 100, and the\ndefault is 20.", "schema": { "type": "integer", "format": "int32", "default": 20 }, "explode": false }, { "name": "order", "in": "query", "required": false, "description": "Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and`desc`\nfor descending order.", "schema": { "$ref": "#/components/schemas/PageOrder" }, "explode": false }, { "name": "after", "in": "query", "required": false, "description": "A cursor for use in pagination. `after` is an object ID that defines your place in the list.\nFor instance, if you make a list request and receive 100 objects, ending with obj_foo, your\nsubsequent call can include after=obj_foo in order to fetch the next page of the list.", "schema": { "type": "string" }, "explode": false }, { "name": "before", "in": "query", "required": false, "description": "A cursor for use in pagination. `before` is an object ID that defines your place in the list.\nFor instance, if you make a list request and receive 100 objects, ending with obj_foo, your\nsubsequent call can include before=obj_foo in order to fetch the previous page of the list.", "schema": { "type": "string" }, "explode": false }, { "name": "item_type", "in": "query", "required": false, "description": "Filter by item type. If provided, only items of the specified type will be returned.", "schema": { "$ref": "#/components/schemas/OpenAI.ItemType" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "type": "object", "required": [ "data", "has_more" ], "properties": { "data": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.OutputItem" }, "description": "The requested list of items." }, "first_id": { "type": "string", "description": "The first ID represented in this list." }, "last_id": { "type": "string", "description": "The last ID represented in this list." }, "has_more": { "type": "boolean", "description": "A value indicating whether there are additional values available not captured in this list." } }, "description": "The response data for a requested list of items." } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Conversations" ] } }, "/openai/v1/conversations/{conversation_id}/items/{item_id}": { "get": { "operationId": "getConversationItem", "description": "Get a single item from a conversation with the given IDs.", "parameters": [ { "name": "conversation_id", "in": "path", "required": true, "description": "The ID of the conversation that contains the item.", "schema": { "type": "string" } }, { "name": "item_id", "in": "path", "required": true, "description": "The id of the conversation item to retrieve.", "schema": { "type": "string" } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/OpenAI.OutputItem" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Conversations" ] }, "delete": { "operationId": "deleteConversationItem", "description": "Delete an item from a conversation with the given IDs.", "parameters": [ { "name": "conversation_id", "in": "path", "required": true, "description": "The id of the conversation on which the item needs to be deleted from.", "schema": { "type": "string" } }, { "name": "item_id", "in": "path", "required": true, "description": "The id of the conversation item to delete.", "schema": { "type": "string" } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/OpenAI.ConversationResource" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Conversations" ] } }, "/openai/v1/evals": { "get": { "operationId": "Evals_listEvals", "summary": "List all evaluations", "description": "List evaluations for a project.", "parameters": [ { "name": "after", "in": "query", "required": false, "description": "Identifier for the last run from the previous pagination request.", "schema": { "type": "string" }, "explode": false }, { "name": "limit", "in": "query", "required": false, "description": "Number of runs to retrieve.", "schema": { "allOf": [ { "$ref": "#/components/schemas/integer" } ], "default": 20 }, "explode": false }, { "name": "order", "in": "query", "required": false, "description": "Sort order for runs by timestamp. Use `asc` for ascending order or `desc` for descending order. Defaults to `asc`.", "schema": { "type": "string", "enum": [ "asc", "desc" ], "default": "asc" }, "explode": false }, { "name": "order_by", "in": "query", "required": false, "description": "Evals can be ordered by creation time or last updated time.\nUse `created_at` for creation time or `updated_at` for last updated time.", "schema": { "type": "string", "enum": [ "created_at", "updated_at" ], "default": "created_at" } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "type": "object", "required": [ "data", "has_more" ], "properties": { "data": { "type": "array", "items": { "$ref": "#/components/schemas/Eval" }, "description": "The requested list of items." }, "first_id": { "type": "string", "description": "The first ID represented in this list." }, "last_id": { "type": "string", "description": "The last ID represented in this list." }, "has_more": { "type": "boolean", "description": "A value indicating whether there are additional values available not captured in this list." } }, "description": "The response data for a requested list of items." } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Evals" ] }, "post": { "operationId": "Evals_createEval", "summary": "Create evaluation", "description": "Create the structure of an evaluation that can be used to test a model's performance.\nAn evaluation is a set of testing criteria and the config for a data source, which dictates the schema of the data used in the evaluation. After creating an evaluation, you can run it on different models and model parameters. We support several types of graders and datasources.\nFor more information, see the [Evals guide](https://platform.openai.com/docs/guides/evals).", "parameters": [], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Eval" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Evals" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/CreateEvalRequest" } } } } } }, "/openai/v1/evals/{eval_id}": { "delete": { "operationId": "Evals_deleteEval", "summary": "Delete an evaluation", "description": "Delete an evaluation.", "parameters": [ { "name": "eval_id", "in": "path", "required": true, "description": "The ID of the evaluation to delete.", "schema": { "type": "string" } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/DeleteEvalResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Evals" ] }, "get": { "operationId": "Evals_getEval", "summary": "Get an evaluation", "description": "Get an evaluation by ID.", "parameters": [ { "name": "eval_id", "in": "path", "required": true, "description": "The ID of the evaluation to retrieve.", "schema": { "type": "string" } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Eval" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Evals" ] }, "post": { "operationId": "Evals_updateEval", "summary": "Update an evaluation", "description": "Update certain properties of an evaluation.", "parameters": [ { "name": "eval_id", "in": "path", "required": true, "description": "The ID of the evaluation to update.", "schema": { "type": "string" } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Eval" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Evals" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/UpdateEvalParametersBody" } } } } } }, "/openai/v1/evals/{eval_id}/runs": { "get": { "operationId": "Evals_listRuns", "summary": "Get a list of runs for an evaluation", "description": "Get a list of runs for an evaluation.", "parameters": [ { "name": "eval_id", "in": "path", "required": true, "description": "The ID of the evaluation to retrieve runs for.", "schema": { "type": "string" } }, { "name": "after", "in": "query", "required": false, "description": "Identifier for the last run from the previous pagination request.", "schema": { "type": "string" }, "explode": false }, { "name": "limit", "in": "query", "required": false, "description": "Number of runs to retrieve.", "schema": { "allOf": [ { "$ref": "#/components/schemas/integer" } ], "default": 20 }, "explode": false }, { "name": "order", "in": "query", "required": false, "description": "Sort order for runs by timestamp. Use `asc` for ascending order or `desc` for descending order. Defaults to `asc`.", "schema": { "type": "string", "enum": [ "asc", "desc" ], "default": "asc" }, "explode": false }, { "name": "status", "in": "query", "required": false, "description": "Filter runs by status. One of `queued` | `in_progress` | `failed` | `completed` | `canceled`.", "schema": { "type": "string", "enum": [ "queued", "in_progress", "completed", "canceled", "failed" ] }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "type": "object", "required": [ "data", "has_more" ], "properties": { "data": { "type": "array", "items": { "$ref": "#/components/schemas/EvalRun" }, "description": "The requested list of items." }, "first_id": { "type": "string", "description": "The first ID represented in this list." }, "last_id": { "type": "string", "description": "The last ID represented in this list." }, "has_more": { "type": "boolean", "description": "A value indicating whether there are additional values available not captured in this list." } }, "description": "The response data for a requested list of items." } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Evals" ] }, "post": { "operationId": "Evals_createEvalRun", "summary": "Create evaluation run", "parameters": [ { "name": "eval_id", "in": "path", "required": true, "description": "The ID of the evaluation to create a run for.", "schema": { "type": "string" } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/EvalRun" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Evals" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/CreateEvalRunRequest" } } } } } }, "/openai/v1/evals/{eval_id}/runs/{run_id}": { "delete": { "operationId": "Evals_deleteEvalRun", "summary": "Delete evaluation run", "description": "Delete an eval run.", "parameters": [ { "name": "eval_id", "in": "path", "required": true, "description": "The ID of the evaluation to delete the run from.", "schema": { "type": "string" } }, { "name": "run_id", "in": "path", "required": true, "description": "The ID of the run to delete.", "schema": { "type": "string" } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/DeleteEvalRunResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Evals" ] }, "get": { "operationId": "Evals_getEvalRun", "summary": "Get an evaluation run", "description": "Get an evaluation run by ID.", "parameters": [ { "name": "eval_id", "in": "path", "required": true, "description": "The ID of the evaluation to retrieve runs for.", "schema": { "type": "string" } }, { "name": "run_id", "in": "path", "required": true, "description": "The ID of the run to retrieve.", "schema": { "type": "string" } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/EvalRun" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Evals" ] }, "post": { "operationId": "Evals_cancelEvalRun", "summary": "Cancel evaluation run", "description": "Cancel an ongoing evaluation run.", "parameters": [ { "name": "eval_id", "in": "path", "required": true, "description": "The ID of the evaluation whose run you want to cancel.", "schema": { "type": "string" } }, { "name": "run_id", "in": "path", "required": true, "description": "The ID of the run to cancel.", "schema": { "type": "string" } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/EvalRun" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Evals" ] } }, "/openai/v1/evals/{eval_id}/runs/{run_id}/output_items": { "get": { "operationId": "Evals_getEvalRunOutputItems", "summary": "Get evaluation run output items", "description": "Get a list of output items for an evaluation run.", "parameters": [ { "name": "eval_id", "in": "path", "required": true, "schema": { "type": "string" } }, { "name": "run_id", "in": "path", "required": true, "description": "The ID of the run to retrieve output items for.", "schema": { "type": "string" } }, { "name": "after", "in": "query", "required": false, "description": "Identifier for the last run from the previous pagination request.", "schema": { "type": "string" }, "explode": false }, { "name": "limit", "in": "query", "required": false, "description": "Number of runs to retrieve.", "schema": { "allOf": [ { "$ref": "#/components/schemas/integer" } ], "default": 20 }, "explode": false }, { "name": "order", "in": "query", "required": false, "description": "Sort order for runs by timestamp. Use `asc` for ascending order or `desc` for descending order. Defaults to `asc`.", "schema": { "type": "string", "enum": [ "asc", "desc" ], "default": "asc" }, "explode": false }, { "name": "status", "in": "query", "required": false, "description": "Filter output items by status. Use `failed` to filter by failed output\nitems or `pass` to filter by passed output items.", "schema": { "type": "string", "enum": [ "fail", "pass" ] } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "type": "object", "required": [ "data", "has_more" ], "properties": { "data": { "type": "array", "items": { "$ref": "#/components/schemas/EvalRunOutputItem" }, "description": "The requested list of items." }, "first_id": { "type": "string", "description": "The first ID represented in this list." }, "last_id": { "type": "string", "description": "The last ID represented in this list." }, "has_more": { "type": "boolean", "description": "A value indicating whether there are additional values available not captured in this list." } }, "description": "The response data for a requested list of items." } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Evals" ] } }, "/openai/v1/evals/{eval_id}/runs/{run_id}/output_items/{output_item_id}": { "get": { "operationId": "Evals_getEvalRunOutputItem", "summary": "Get an output item of an evaluation run", "description": "Get an evaluation run output item by ID.", "parameters": [ { "name": "eval_id", "in": "path", "required": true, "description": "The ID of the evaluation to retrieve runs for.", "schema": { "type": "string" } }, { "name": "run_id", "in": "path", "required": true, "description": "The ID of the run to retrieve.", "schema": { "type": "string" } }, { "name": "output_item_id", "in": "path", "required": true, "description": "The ID of the output item to retrieve.", "schema": { "type": "string" } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/EvalRunOutputItem" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Evals" ] } }, "/openai/v1/fine_tuning/jobs": { "post": { "operationId": "createFineTuningJob", "description": "Creates a fine-tuning job which begins the process of creating a new model from a given dataset.\n\nResponse includes details of the enqueued job including job status and the name of the fine-tuned models once complete.\n\n[Learn more about fine-tuning](https://platform.openai.com/docs/guides/fine-tuning)", "parameters": [ { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/OpenAI.FineTuningJob" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Fine-Tuning" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/OpenAI.CreateFineTuningJobRequest" } } } } }, "get": { "operationId": "listPaginatedFineTuningJobs", "description": "List your organization's fine-tuning jobs", "parameters": [ { "name": "after", "in": "query", "required": false, "description": "Identifier for the last job from the previous pagination request.", "schema": { "type": "string" }, "explode": false }, { "name": "limit", "in": "query", "required": false, "description": "Number of fine-tuning jobs to retrieve.", "schema": { "type": "integer", "format": "int32", "default": 20 }, "explode": false }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/OpenAI.ListPaginatedFineTuningJobsResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Fine-Tuning" ] } }, "/openai/v1/fine_tuning/jobs/{fine_tuning_job_id}": { "get": { "operationId": "retrieveFineTuningJob", "description": "Get info about a fine-tuning job.\n\n[Learn more about fine-tuning](https://platform.openai.com/docs/guides/fine-tuning)", "parameters": [ { "name": "fine_tuning_job_id", "in": "path", "required": true, "description": "The ID of the fine-tuning job.", "schema": { "type": "string" } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/OpenAI.FineTuningJob" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Fine-Tuning" ] } }, "/openai/v1/fine_tuning/jobs/{fine_tuning_job_id}/cancel": { "post": { "operationId": "cancelFineTuningJob", "description": "Immediately cancel a fine-tune job.", "parameters": [ { "name": "fine_tuning_job_id", "in": "path", "required": true, "description": "The ID of the fine-tuning job to cancel.", "schema": { "type": "string" } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/OpenAI.FineTuningJob" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Fine-Tuning" ] } }, "/openai/v1/fine_tuning/jobs/{fine_tuning_job_id}/checkpoints": { "get": { "operationId": "listFineTuningJobCheckpoints", "description": "List checkpoints for a fine-tuning job.", "parameters": [ { "name": "fine_tuning_job_id", "in": "path", "required": true, "description": "The ID of the fine-tuning job to get checkpoints for.", "schema": { "type": "string" } }, { "name": "after", "in": "query", "required": false, "description": "Identifier for the last checkpoint ID from the previous pagination request.", "schema": { "type": "string" }, "explode": false }, { "name": "limit", "in": "query", "required": false, "description": "Number of checkpoints to retrieve.", "schema": { "type": "integer", "format": "int32", "default": 10 }, "explode": false }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/OpenAI.ListFineTuningJobCheckpointsResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Fine-Tuning" ] } }, "/openai/v1/fine_tuning/jobs/{fine_tuning_job_id}/events": { "get": { "operationId": "listFineTuningJobEvents", "description": "Get fine-grained status updates for a fine-tuning job.", "parameters": [ { "name": "fine_tuning_job_id", "in": "path", "required": true, "description": "The ID of the fine-tuning job to get events for.", "schema": { "type": "string" } }, { "name": "after", "in": "query", "required": false, "description": "Identifier for the last event from the previous pagination request.", "schema": { "type": "string" }, "explode": false }, { "name": "limit", "in": "query", "required": false, "description": "Number of events to retrieve.", "schema": { "type": "integer", "format": "int32", "default": 20 }, "explode": false }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/OpenAI.ListFineTuningJobEventsResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Fine-Tuning" ] } }, "/openai/v1/fine_tuning/jobs/{fine_tuning_job_id}/pause": { "post": { "operationId": "pauseFineTuningJob", "description": "Pause a running fine-tune job.", "parameters": [ { "name": "fine_tuning_job_id", "in": "path", "required": true, "description": "The ID of the fine-tuning job to pause.", "schema": { "type": "string" } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/OpenAI.FineTuningJob" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Fine-Tuning" ] } }, "/openai/v1/fine_tuning/jobs/{fine_tuning_job_id}/resume": { "post": { "operationId": "resumeFineTuningJob", "description": "Resume a paused fine-tune job.", "parameters": [ { "name": "fine_tuning_job_id", "in": "path", "required": true, "description": "The ID of the fine-tuning job to resume.", "schema": { "type": "string" } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/OpenAI.FineTuningJob" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Fine-Tuning" ] } }, "/openai/v1/responses": { "post": { "operationId": "createResponse_createResponseStream", "parameters": [], "description": "Creates a model response. Creates a model response (streaming response).", "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/OpenAI.Response" } }, "text/event-stream": { "schema": { "$ref": "#/components/schemas/OpenAI.CreateResponseStreamingResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Responses" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "anyOf": [ { "type": "object", "properties": { "metadata": { "type": "object", "allOf": [ { "$ref": "#/components/schemas/OpenAI.Metadata" } ], "nullable": true }, "top_logprobs": { "type": "integer", "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "nullable": true }, "temperature": { "type": "number", "allOf": [ { "$ref": "#/components/schemas/OpenAI.numeric" } ], "nullable": true, "default": 1 }, "top_p": { "type": "number", "allOf": [ { "$ref": "#/components/schemas/OpenAI.numeric" } ], "nullable": true, "default": 1 }, "user": { "type": "string", "description": "This field is being replaced by `safety_identifier` and `prompt_cache_key`. Use `prompt_cache_key` instead to maintain caching optimizations.\n A stable identifier for your end-users.\n Used to boost cache hit rates by better bucketing similar requests and to help OpenAI detect and prevent abuse. [Learn more](/docs/guides/safety-best-practices#safety-identifiers).", "deprecated": true }, "safety_identifier": { "type": "string", "description": "A stable identifier used to help detect users of your application that may be violating OpenAI's usage policies.\n The IDs should be a string that uniquely identifies each user. We recommend hashing their username or email address, in order to avoid sending us any identifying information. [Learn more](/docs/guides/safety-best-practices#safety-identifiers)." }, "prompt_cache_key": { "type": "string", "description": "Used by OpenAI to cache responses for similar requests to optimize your cache hit rates. Replaces the `user` field. [Learn more](/docs/guides/prompt-caching)." }, "service_tier": { "$ref": "#/components/schemas/OpenAI.ServiceTier" }, "prompt_cache_retention": { "type": "string", "enum": [ "in-memory", "24h" ], "nullable": true }, "previous_response_id": { "type": "string", "nullable": true }, "model": { "type": "string", "description": "The model deployment to use for the creation of this response." }, "reasoning": { "type": "object", "allOf": [ { "$ref": "#/components/schemas/OpenAI.Reasoning" } ], "nullable": true }, "background": { "type": "boolean", "nullable": true }, "max_output_tokens": { "type": "integer", "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "nullable": true }, "max_tool_calls": { "type": "integer", "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "nullable": true }, "text": { "$ref": "#/components/schemas/OpenAI.ResponseTextParam" }, "tools": { "$ref": "#/components/schemas/OpenAI.ToolsArray" }, "tool_choice": { "oneOf": [ { "$ref": "#/components/schemas/OpenAI.ToolChoiceOptions" }, { "$ref": "#/components/schemas/OpenAI.ToolChoiceParam" } ] }, "prompt": { "$ref": "#/components/schemas/OpenAI.Prompt" }, "truncation": { "type": "string", "enum": [ "auto", "disabled" ], "nullable": true, "default": "disabled" }, "input": { "$ref": "#/components/schemas/OpenAI.InputParam" }, "include": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.IncludeEnum" }, "nullable": true }, "parallel_tool_calls": { "type": "boolean", "nullable": true, "default": true }, "store": { "type": "boolean", "nullable": true, "default": true }, "instructions": { "type": "string", "nullable": true }, "stream": { "type": "boolean", "nullable": true }, "stream_options": { "type": "object", "allOf": [ { "$ref": "#/components/schemas/OpenAI.ResponseStreamOptions" } ], "nullable": true }, "conversation": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ConversationParam" } ], "nullable": true }, "context_management": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.ContextManagementParam" }, "nullable": true, "description": "Context management configuration for this request." }, "agent_reference": { "allOf": [ { "$ref": "#/components/schemas/AgentReference" } ], "description": "The agent to use for generating the response." }, "structured_inputs": { "type": "object", "additionalProperties": {}, "description": "The structured inputs to the response that can participate in prompt template substitution or tool argument bindings." } } }, { "type": "object", "properties": { "metadata": { "type": "object", "allOf": [ { "$ref": "#/components/schemas/OpenAI.Metadata" } ], "nullable": true }, "top_logprobs": { "type": "integer", "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "nullable": true }, "temperature": { "type": "number", "allOf": [ { "$ref": "#/components/schemas/OpenAI.numeric" } ], "nullable": true, "default": 1 }, "top_p": { "type": "number", "allOf": [ { "$ref": "#/components/schemas/OpenAI.numeric" } ], "nullable": true, "default": 1 }, "user": { "type": "string", "description": "This field is being replaced by `safety_identifier` and `prompt_cache_key`. Use `prompt_cache_key` instead to maintain caching optimizations.\n A stable identifier for your end-users.\n Used to boost cache hit rates by better bucketing similar requests and to help OpenAI detect and prevent abuse. [Learn more](/docs/guides/safety-best-practices#safety-identifiers).", "deprecated": true }, "safety_identifier": { "type": "string", "description": "A stable identifier used to help detect users of your application that may be violating OpenAI's usage policies.\n The IDs should be a string that uniquely identifies each user. We recommend hashing their username or email address, in order to avoid sending us any identifying information. [Learn more](/docs/guides/safety-best-practices#safety-identifiers)." }, "prompt_cache_key": { "type": "string", "description": "Used by OpenAI to cache responses for similar requests to optimize your cache hit rates. Replaces the `user` field. [Learn more](/docs/guides/prompt-caching)." }, "service_tier": { "$ref": "#/components/schemas/OpenAI.ServiceTier" }, "prompt_cache_retention": { "type": "string", "enum": [ "in-memory", "24h" ], "nullable": true }, "previous_response_id": { "type": "string", "nullable": true }, "model": { "type": "string", "description": "The model deployment to use for the creation of this response." }, "reasoning": { "type": "object", "allOf": [ { "$ref": "#/components/schemas/OpenAI.Reasoning" } ], "nullable": true }, "background": { "type": "boolean", "nullable": true }, "max_output_tokens": { "type": "integer", "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "nullable": true }, "max_tool_calls": { "type": "integer", "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "nullable": true }, "text": { "$ref": "#/components/schemas/OpenAI.ResponseTextParam" }, "tools": { "$ref": "#/components/schemas/OpenAI.ToolsArray" }, "tool_choice": { "oneOf": [ { "$ref": "#/components/schemas/OpenAI.ToolChoiceOptions" }, { "$ref": "#/components/schemas/OpenAI.ToolChoiceParam" } ] }, "prompt": { "$ref": "#/components/schemas/OpenAI.Prompt" }, "truncation": { "type": "string", "enum": [ "auto", "disabled" ], "nullable": true, "default": "disabled" }, "input": { "$ref": "#/components/schemas/OpenAI.InputParam" }, "include": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.IncludeEnum" }, "nullable": true }, "parallel_tool_calls": { "type": "boolean", "nullable": true, "default": true }, "store": { "type": "boolean", "nullable": true, "default": true }, "instructions": { "type": "string", "nullable": true }, "stream": { "type": "boolean", "nullable": true }, "stream_options": { "type": "object", "allOf": [ { "$ref": "#/components/schemas/OpenAI.ResponseStreamOptions" } ], "nullable": true }, "conversation": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ConversationParam" } ], "nullable": true }, "context_management": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.ContextManagementParam" }, "nullable": true, "description": "Context management configuration for this request." }, "agent_reference": { "allOf": [ { "$ref": "#/components/schemas/AgentReference" } ], "description": "The agent to use for generating the response." }, "structured_inputs": { "type": "object", "additionalProperties": {}, "description": "The structured inputs to the response that can participate in prompt template substitution or tool argument bindings." } } } ] } } } } }, "get": { "operationId": "listResponses", "description": "Returns the list of all responses.", "parameters": [ { "name": "limit", "in": "query", "required": false, "description": "A limit on the number of objects to be returned. Limit can range between 1 and 100, and the\ndefault is 20.", "schema": { "type": "integer", "format": "int32", "default": 20 }, "explode": false }, { "name": "order", "in": "query", "required": false, "description": "Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and`desc`\nfor descending order.", "schema": { "$ref": "#/components/schemas/PageOrder" }, "explode": false }, { "name": "after", "in": "query", "required": false, "description": "A cursor for use in pagination. `after` is an object ID that defines your place in the list.\nFor instance, if you make a list request and receive 100 objects, ending with obj_foo, your\nsubsequent call can include after=obj_foo in order to fetch the next page of the list.", "schema": { "type": "string" }, "explode": false }, { "name": "before", "in": "query", "required": false, "description": "A cursor for use in pagination. `before` is an object ID that defines your place in the list.\nFor instance, if you make a list request and receive 100 objects, ending with obj_foo, your\nsubsequent call can include before=obj_foo in order to fetch the previous page of the list.", "schema": { "type": "string" }, "explode": false }, { "name": "agent_name", "in": "query", "required": false, "description": "Filter by agent name. If provided, only items associated with the specified agent will be returned.", "schema": { "type": "string" }, "explode": false }, { "name": "agent_id", "in": "query", "required": false, "description": "Filter by agent ID in the format `name:version`. If provided, only items associated with the specified agent ID will be returned.", "schema": { "type": "string" }, "explode": false }, { "name": "conversation_id", "in": "query", "required": false, "description": "Filter by conversation ID. If provided, only responses associated with the specified conversation will be returned.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "type": "object", "required": [ "data", "has_more" ], "properties": { "data": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.Response" }, "description": "The requested list of items." }, "first_id": { "type": "string", "description": "The first ID represented in this list." }, "last_id": { "type": "string", "description": "The last ID represented in this list." }, "has_more": { "type": "boolean", "description": "A value indicating whether there are additional values available not captured in this list." } }, "description": "The response data for a requested list of items." } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Responses" ] } }, "/openai/v1/responses/compact": { "post": { "operationId": "compactResponseConversation", "description": "Produces a compaction of a responses conversation.", "parameters": [], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/OpenAI.CompactResource" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Responses" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/OpenAI.CompactResponseMethodPublicBody" } } } } } }, "/openai/v1/responses/{response_id}": { "get": { "operationId": "getResponse_getResponseStream", "parameters": [ { "name": "response_id", "in": "path", "required": true, "schema": { "type": "string" } }, { "name": "include[]", "in": "query", "required": false, "schema": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.IncludeEnum" }, "default": [] } }, { "name": "stream", "in": "query", "required": false, "schema": { "type": "boolean", "default": false }, "explode": false }, { "name": "starting_after", "in": "query", "required": false, "schema": { "type": "integer", "format": "int32" }, "explode": false }, { "name": "accept", "in": "header", "required": false, "schema": { "type": "string", "enum": [ "text/event-stream" ] } } ], "description": "Retrieves a model response with the given ID. Retrieves a model response with the given ID (streaming response).", "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/OpenAI.Response" } }, "text/event-stream": { "schema": { "$ref": "#/components/schemas/OpenAI.CreateResponseStreamingResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Responses" ] }, "delete": { "operationId": "deleteResponse", "description": "Deletes a model response.", "parameters": [ { "name": "response_id", "in": "path", "required": true, "description": "The ID of the response to delete.", "schema": { "type": "string" } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/DeleteResponseResult" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Responses" ] } }, "/openai/v1/responses/{response_id}/cancel": { "post": { "operationId": "cancelResponse", "description": "Cancels a model response.", "parameters": [ { "name": "response_id", "in": "path", "required": true, "description": "The ID of the response to cancel.", "schema": { "type": "string" } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/OpenAI.Response" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Responses" ] } }, "/openai/v1/responses/{response_id}/input_items": { "get": { "operationId": "listInputItems", "description": "Returns a list of input items for a given response.", "parameters": [ { "name": "response_id", "in": "path", "required": true, "schema": { "type": "string" } }, { "name": "limit", "in": "query", "required": false, "description": "A limit on the number of objects to be returned. Limit can range between 1 and 100, and the\ndefault is 20.", "schema": { "type": "integer", "format": "int32", "default": 20 }, "explode": false }, { "name": "order", "in": "query", "required": false, "description": "Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and`desc`\nfor descending order.", "schema": { "$ref": "#/components/schemas/PageOrder" }, "explode": false }, { "name": "after", "in": "query", "required": false, "description": "A cursor for use in pagination. `after` is an object ID that defines your place in the list.\nFor instance, if you make a list request and receive 100 objects, ending with obj_foo, your\nsubsequent call can include after=obj_foo in order to fetch the next page of the list.", "schema": { "type": "string" }, "explode": false }, { "name": "before", "in": "query", "required": false, "description": "A cursor for use in pagination. `before` is an object ID that defines your place in the list.\nFor instance, if you make a list request and receive 100 objects, ending with obj_foo, your\nsubsequent call can include before=obj_foo in order to fetch the previous page of the list.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "type": "object", "required": [ "data", "has_more" ], "properties": { "data": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.ItemResource" }, "description": "The requested list of items." }, "first_id": { "type": "string", "description": "The first ID represented in this list." }, "last_id": { "type": "string", "description": "The last ID represented in this list." }, "has_more": { "type": "boolean", "description": "A value indicating whether there are additional values available not captured in this list." } }, "description": "The response data for a requested list of items." } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Responses" ] } }, "/redTeams/runs": { "get": { "operationId": "RedTeams_list", "description": "List a redteam by name.", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "RedTeams=V1Preview" ] } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/PagedRedTeam" } } } }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Redteams" ] } }, "/redTeams/runs/{name}": { "get": { "operationId": "RedTeams_get", "description": "Get a redteam by name.", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "name", "in": "path", "required": true, "description": "Identifier of the red team run.", "schema": { "type": "string" } }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "RedTeams=V1Preview" ] } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/RedTeam" } } } }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Redteams" ] } }, "/redTeams/runs:run": { "post": { "operationId": "RedTeams_create", "description": "Creates a redteam run.", "parameters": [ { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "RedTeams=V1Preview" ] } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "201": { "description": "The request has succeeded and a new resource has been created as a result.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/RedTeam" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Redteams" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/RedTeam" } } }, "description": "Redteam to be run" } } }, "/schedules": { "get": { "operationId": "Schedules_list", "description": "List all schedules.", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "type", "in": "query", "required": false, "description": "Filter by the type of schedule.", "schema": { "$ref": "#/components/schemas/ScheduleTaskType" }, "explode": false }, { "name": "enabled", "in": "query", "required": false, "description": "Filter by the enabled status.", "schema": { "type": "boolean" }, "explode": false }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "Schedules=V1Preview" ] } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/PagedSchedule" } } } }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Schedules" ] } }, "/schedules/{id}": { "delete": { "operationId": "Schedules_delete", "description": "Delete a schedule.", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "id", "in": "path", "required": true, "description": "Identifier of the schedule.", "schema": { "type": "string" } }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "Schedules=V1Preview" ] } } ], "responses": { "204": { "description": "There is no content to send for this request, but the headers may be useful." }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Schedules" ] }, "get": { "operationId": "Schedules_get", "description": "Get a schedule by id.", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "id", "in": "path", "required": true, "description": "Identifier of the schedule.", "schema": { "type": "string" } }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "Schedules=V1Preview" ] } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Schedule" } } } }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Schedules" ] }, "put": { "operationId": "Schedules_createOrUpdate", "description": "Create or update operation template.", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "id", "in": "path", "required": true, "description": "Identifier of the schedule.", "schema": { "type": "string" } }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "Schedules=V1Preview" ] } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Schedule" } } } }, "201": { "description": "The request has succeeded and a new resource has been created as a result.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Schedule" } } } }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Schedules" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Schedule" } } }, "description": "The resource instance." } } }, "/schedules/{id}/runs": { "get": { "operationId": "Schedules_listRuns", "description": "List all schedule runs.", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "id", "in": "path", "required": true, "description": "Identifier of the schedule.", "schema": { "type": "string" } }, { "name": "type", "in": "query", "required": false, "description": "Filter by the type of schedule.", "schema": { "$ref": "#/components/schemas/ScheduleTaskType" }, "explode": false }, { "name": "enabled", "in": "query", "required": false, "description": "Filter by the enabled status.", "schema": { "type": "boolean" }, "explode": false }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "Schedules=V1Preview" ] } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/PagedScheduleRun" } } } }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "Schedules" ] } }, "/schedules/{schedule_id}/runs/{run_id}": { "get": { "operationId": "Schedules_getRun", "description": "Get a schedule run by id.", "parameters": [ { "name": "schedule_id", "in": "path", "required": true, "description": "The unique identifier of the schedule.", "schema": { "type": "string" } }, { "name": "run_id", "in": "path", "required": true, "description": "The unique identifier of the schedule run.", "schema": { "type": "string" } }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "Schedules=V1Preview" ] } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ScheduleRun" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Schedules" ] } }, "/skills": { "post": { "operationId": "Skills_createSkill", "description": "Creates a skill.", "parameters": [ { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "Skills=V1Preview" ] } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/SkillObject" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Skills" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "type": "object", "properties": { "name": { "type": "string", "maxLength": 63, "description": "The unique name of the skill." }, "description": { "type": "string", "maxLength": 1024, "description": "A human-readable description of the skill." }, "instructions": { "type": "string", "maxLength": 102400, "description": "Instructions that define the behavior of the skill." }, "metadata": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Set of key-value pairs associated with the skill." } }, "required": [ "name" ] } } } }, "x-ms-foundry-meta": { "conditional_previews": [ "Skills=V1Preview" ] } }, "get": { "operationId": "Skills_listSkills", "description": "Returns the list of all skills.", "parameters": [ { "name": "limit", "in": "query", "required": false, "description": "A limit on the number of objects to be returned. Limit can range between 1 and 100, and the\ndefault is 20.", "schema": { "type": "integer", "format": "int32", "default": 20 }, "explode": false }, { "name": "order", "in": "query", "required": false, "description": "Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and`desc`\nfor descending order.", "schema": { "$ref": "#/components/schemas/PageOrder" }, "explode": false }, { "name": "after", "in": "query", "required": false, "description": "A cursor for use in pagination. `after` is an object ID that defines your place in the list.\nFor instance, if you make a list request and receive 100 objects, ending with obj_foo, your\nsubsequent call can include after=obj_foo in order to fetch the next page of the list.", "schema": { "type": "string" }, "explode": false }, { "name": "before", "in": "query", "required": false, "description": "A cursor for use in pagination. `before` is an object ID that defines your place in the list.\nFor instance, if you make a list request and receive 100 objects, ending with obj_foo, your\nsubsequent call can include before=obj_foo in order to fetch the previous page of the list.", "schema": { "type": "string" }, "explode": false }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "Skills=V1Preview" ] } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "type": "object", "required": [ "data", "has_more" ], "properties": { "data": { "type": "array", "items": { "$ref": "#/components/schemas/SkillObject" }, "description": "The requested list of items." }, "first_id": { "type": "string", "description": "The first ID represented in this list." }, "last_id": { "type": "string", "description": "The last ID represented in this list." }, "has_more": { "type": "boolean", "description": "A value indicating whether there are additional values available not captured in this list." } }, "description": "The response data for a requested list of items." } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Skills" ], "x-ms-foundry-meta": { "conditional_previews": [ "Skills=V1Preview" ] } } }, "/skills/{skill_name}": { "get": { "operationId": "Skills_getSkill", "description": "Retrieves a skill.", "parameters": [ { "name": "skill_name", "in": "path", "required": true, "description": "The unique name of the skill.", "schema": { "type": "string" } }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "Skills=V1Preview" ] } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/SkillObject" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Skills" ], "x-ms-foundry-meta": { "conditional_previews": [ "Skills=V1Preview" ] } }, "post": { "operationId": "Skills_updateSkill", "description": "Updates an existing skill.", "parameters": [ { "name": "skill_name", "in": "path", "required": true, "description": "The unique name of the skill.", "schema": { "type": "string" } }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "Skills=V1Preview" ] } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/SkillObject" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Skills" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "type": "object", "properties": { "description": { "type": "string", "maxLength": 1024, "description": "A human-readable description of the skill." }, "instructions": { "type": "string", "maxLength": 102400, "description": "Instructions that define the behavior of the skill." }, "metadata": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Set of key-value pairs associated with the skill." } } } } } }, "x-ms-foundry-meta": { "conditional_previews": [ "Skills=V1Preview" ] } }, "delete": { "operationId": "Skills_deleteSkill", "description": "Deletes a skill.", "parameters": [ { "name": "skill_name", "in": "path", "required": true, "description": "The unique name of the skill.", "schema": { "type": "string" } }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "Skills=V1Preview" ] } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/DeleteSkillResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Skills" ], "x-ms-foundry-meta": { "conditional_previews": [ "Skills=V1Preview" ] } } }, "/skills/{skill_name}:download": { "get": { "operationId": "Skills_downloadSkill", "description": "Downloads a skill package.", "parameters": [ { "name": "skill_name", "in": "path", "required": true, "description": "The unique name of the skill.", "schema": { "type": "string" } }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "Skills=V1Preview" ] } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The response body for downloading a skill package.", "content": { "application/gzip": { "schema": { "type": "string", "format": "binary" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Skills" ], "x-ms-foundry-meta": { "conditional_previews": [ "Skills=V1Preview" ] } } }, "/skills:import": { "post": { "operationId": "Skills_createSkillFromPackage", "description": "Creates a skill from a GZip package.", "parameters": [ { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "Skills=V1Preview" ] } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/SkillObject" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Skills" ], "requestBody": { "required": true, "content": { "application/gzip": { "schema": { "type": "string", "format": "binary" } } }, "description": "The GZip package used to create the skill." }, "x-ms-foundry-meta": { "conditional_previews": [ "Skills=V1Preview" ] } } }, "/toolsets": { "post": { "operationId": "createToolset", "description": "Create a toolset.", "parameters": [ { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "Toolsets=V1Preview" ] } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ToolsetObject" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Toolsets" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "type": "object", "properties": { "name": { "type": "string", "maxLength": 256, "description": "The name of the toolset." }, "description": { "type": "string", "maxLength": 512, "description": "A human-readable description of the toolset." }, "metadata": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Arbitrary key-value metadata to associate with the toolset." }, "tools": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.Tool" }, "description": "The list of tools to include in the toolset." } }, "required": [ "name", "tools" ] } } } }, "x-ms-foundry-meta": { "conditional_previews": [ "Toolsets=V1Preview" ] } }, "get": { "operationId": "listToolsets", "description": "List all toolsets.", "parameters": [ { "name": "limit", "in": "query", "required": false, "description": "A limit on the number of objects to be returned. Limit can range between 1 and 100, and the\ndefault is 20.", "schema": { "type": "integer", "format": "int32", "default": 20 }, "explode": false }, { "name": "order", "in": "query", "required": false, "description": "Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and`desc`\nfor descending order.", "schema": { "$ref": "#/components/schemas/PageOrder" }, "explode": false }, { "name": "after", "in": "query", "required": false, "description": "A cursor for use in pagination. `after` is an object ID that defines your place in the list.\nFor instance, if you make a list request and receive 100 objects, ending with obj_foo, your\nsubsequent call can include after=obj_foo in order to fetch the next page of the list.", "schema": { "type": "string" }, "explode": false }, { "name": "before", "in": "query", "required": false, "description": "A cursor for use in pagination. `before` is an object ID that defines your place in the list.\nFor instance, if you make a list request and receive 100 objects, ending with obj_foo, your\nsubsequent call can include before=obj_foo in order to fetch the previous page of the list.", "schema": { "type": "string" }, "explode": false }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "Toolsets=V1Preview" ] } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "type": "object", "required": [ "data", "has_more" ], "properties": { "data": { "type": "array", "items": { "$ref": "#/components/schemas/ToolsetObject" }, "description": "The requested list of items." }, "first_id": { "type": "string", "description": "The first ID represented in this list." }, "last_id": { "type": "string", "description": "The last ID represented in this list." }, "has_more": { "type": "boolean", "description": "A value indicating whether there are additional values available not captured in this list." } }, "description": "The response data for a requested list of items." } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Toolsets" ], "x-ms-foundry-meta": { "conditional_previews": [ "Toolsets=V1Preview" ] } } }, "/toolsets/{tool_set_name}": { "post": { "operationId": "updateToolset", "description": "Update a toolset.", "parameters": [ { "name": "tool_set_name", "in": "path", "required": true, "description": "The name of the toolset to update.", "schema": { "type": "string" } }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "Toolsets=V1Preview" ] } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ToolsetObject" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Toolsets" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "type": "object", "properties": { "description": { "type": "string", "maxLength": 512, "description": "A human-readable description of the toolset." }, "metadata": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Arbitrary key-value metadata to associate with the toolset." }, "tools": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.Tool" }, "description": "The list of tools to include in the toolset." } }, "required": [ "tools" ] } } } }, "x-ms-foundry-meta": { "conditional_previews": [ "Toolsets=V1Preview" ] } }, "get": { "operationId": "getToolset", "description": "Retrieve a toolset.", "parameters": [ { "name": "tool_set_name", "in": "path", "required": true, "description": "The name of the toolset to retrieve.", "schema": { "type": "string" } }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "Toolsets=V1Preview" ] } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ToolsetObject" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Toolsets" ], "x-ms-foundry-meta": { "conditional_previews": [ "Toolsets=V1Preview" ] } }, "delete": { "operationId": "deleteToolset", "description": "Delete a toolset.", "parameters": [ { "name": "tool_set_name", "in": "path", "required": true, "description": "The name of the toolset to delete.", "schema": { "type": "string" } }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "Toolsets=V1Preview" ] } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/DeleteToolsetResponse" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "Toolsets" ], "x-ms-foundry-meta": { "conditional_previews": [ "Toolsets=V1Preview" ] } } }, "/training_jobs": { "get": { "operationId": "TrainingJobs_list", "description": "List training jobs.", "parameters": [ { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "TrainingJobs=V1Preview" ] } }, { "name": "job_type", "in": "query", "required": false, "description": "Filter by job type (e.g. 'Command').", "schema": { "$ref": "#/components/schemas/JobType" }, "explode": false }, { "name": "tag", "in": "query", "required": false, "description": "Filter jobs by tag in the format 'key=value' (e.g., 'framework=pytorch').", "schema": { "type": "string" }, "explode": false }, { "name": "list_view_type", "in": "query", "required": false, "description": "Specifies which view type to apply when listing jobs.", "schema": { "$ref": "#/components/schemas/ListViewType" }, "explode": false }, { "name": "properties", "in": "query", "required": false, "description": "Comma-separated user property names and optionally values. Example: prop1,prop2=value2.", "schema": { "type": "string" }, "explode": false }, { "name": "limit", "in": "query", "required": false, "description": "A limit on the number of objects to be returned. Limit can range between 1 and 100, and the\ndefault is 20.", "schema": { "type": "integer", "format": "int32", "default": 20 }, "explode": false }, { "name": "order", "in": "query", "required": false, "description": "Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and`desc`\nfor descending order.", "schema": { "$ref": "#/components/schemas/PageOrder" }, "explode": false }, { "name": "after", "in": "query", "required": false, "description": "A cursor for use in pagination. `after` is an object ID that defines your place in the list.\nFor instance, if you make a list request and receive 100 objects, ending with obj_foo, your\nsubsequent call can include after=obj_foo in order to fetch the next page of the list.", "schema": { "type": "string" }, "explode": false }, { "name": "before", "in": "query", "required": false, "description": "A cursor for use in pagination. `before` is an object ID that defines your place in the list.\nFor instance, if you make a list request and receive 100 objects, ending with obj_foo, your\nsubsequent call can include before=obj_foo in order to fetch the previous page of the list.", "schema": { "type": "string" }, "explode": false }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "type": "object", "required": [ "data", "has_more" ], "properties": { "data": { "type": "array", "items": { "$ref": "#/components/schemas/Job" }, "description": "The requested list of items." }, "first_id": { "type": "string", "description": "The first ID represented in this list." }, "last_id": { "type": "string", "description": "The last ID represented in this list." }, "has_more": { "type": "boolean", "description": "A value indicating whether there are additional values available not captured in this list." } }, "description": "The response data for a requested list of items." } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "TrainingJobs" ] }, "post": { "operationId": "TrainingJobs_create", "description": "Create and execute a model training job.", "parameters": [ { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "TrainingJobs=V1Preview" ] } }, { "name": "Operation-Id", "in": "header", "required": false, "description": "Idempotency key used to safely retry job creation.", "schema": { "type": "string" } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "201": { "description": "The request has succeeded and a new resource has been created as a result.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Job" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "TrainingJobs" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/JobCreate" } } }, "description": "The training job to create." } } }, "/training_jobs/operations/{operation_id}/result": { "get": { "operationId": "TrainingJobOperations_getOperationResult", "description": "Poll the result of an asynchronous training job operation.", "parameters": [ { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "TrainingJobs=V1Preview" ] } }, { "name": "operation_id", "in": "path", "required": true, "description": "The operation identifier returned by a training job create, cancel, or delete request.", "schema": { "type": "string" } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/JobOperationResource" } } } }, "202": { "description": "Response returned when a training job operation is still in progress.", "headers": { "Location": { "required": false, "description": "URL to poll for the operation result.", "schema": { "type": "string" } }, "Operation-Location": { "required": false, "description": "URL to poll for the operation status.", "schema": { "type": "string" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "TrainingJobs" ] } }, "/training_jobs/operations/{operation_id}/status": { "get": { "operationId": "TrainingJobOperations_getOperationStatus", "description": "Poll the status of an asynchronous training job operation.", "parameters": [ { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "TrainingJobs=V1Preview" ] } }, { "name": "operation_id", "in": "path", "required": true, "description": "The operation identifier returned by a training job create, cancel, or delete request.", "schema": { "type": "string" } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/JobOperationResource" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "TrainingJobs" ] } }, "/training_jobs/{job_name}/attempts": { "get": { "operationId": "TrainingJobAttempts_listAttempts", "description": "List attempts for a training job.", "parameters": [ { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "TrainingJobs=V1Preview" ] } }, { "name": "job_name", "in": "path", "required": true, "description": "The training job name.", "schema": { "type": "string" } }, { "name": "limit", "in": "query", "required": false, "description": "A limit on the number of objects to be returned. Limit can range between 1 and 100, and the\ndefault is 20.", "schema": { "type": "integer", "format": "int32", "default": 20 }, "explode": false }, { "name": "order", "in": "query", "required": false, "description": "Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and`desc`\nfor descending order.", "schema": { "$ref": "#/components/schemas/PageOrder" }, "explode": false }, { "name": "after", "in": "query", "required": false, "description": "A cursor for use in pagination. `after` is an object ID that defines your place in the list.\nFor instance, if you make a list request and receive 100 objects, ending with obj_foo, your\nsubsequent call can include after=obj_foo in order to fetch the next page of the list.", "schema": { "type": "string" }, "explode": false }, { "name": "before", "in": "query", "required": false, "description": "A cursor for use in pagination. `before` is an object ID that defines your place in the list.\nFor instance, if you make a list request and receive 100 objects, ending with obj_foo, your\nsubsequent call can include before=obj_foo in order to fetch the previous page of the list.", "schema": { "type": "string" }, "explode": false }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "type": "object", "required": [ "data", "has_more" ], "properties": { "data": { "type": "array", "items": { "$ref": "#/components/schemas/JobAttempt" }, "description": "The requested list of items." }, "first_id": { "type": "string", "description": "The first ID represented in this list." }, "last_id": { "type": "string", "description": "The last ID represented in this list." }, "has_more": { "type": "boolean", "description": "A value indicating whether there are additional values available not captured in this list." } }, "description": "The response data for a requested list of items." } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "TrainingJobs" ] } }, "/training_jobs/{job_name}/attempts/{attempt_id}": { "get": { "operationId": "TrainingJobAttempts_getAttempt", "description": "Get one attempt for a training job.", "parameters": [ { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "TrainingJobs=V1Preview" ] } }, { "name": "job_name", "in": "path", "required": true, "description": "The training job name.", "schema": { "type": "string" } }, { "name": "attempt_id", "in": "path", "required": true, "description": "The attempt identifier.", "schema": { "type": "string" } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/JobAttempt" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "TrainingJobs" ] } }, "/training_jobs/{job_name}/attempts/{attempt_id}/artifacts": { "get": { "operationId": "TrainingJobAttemptArtifacts_listAttemptArtifacts", "description": "List artifacts for a training job attempt. Use 'latest' for the latest attempt.", "parameters": [ { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "TrainingJobs=V1Preview" ] } }, { "name": "job_name", "in": "path", "required": true, "description": "The training job name.", "schema": { "type": "string" } }, { "name": "attempt_id", "in": "path", "required": true, "description": "The attempt identifier, or 'latest' for the latest attempt.", "schema": { "$ref": "#/components/schemas/JobAttemptIdentifier" } }, { "name": "limit", "in": "query", "required": false, "description": "A limit on the number of objects to be returned. Limit can range between 1 and 100, and the\ndefault is 20.", "schema": { "type": "integer", "format": "int32", "default": 20 }, "explode": false }, { "name": "order", "in": "query", "required": false, "description": "Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and`desc`\nfor descending order.", "schema": { "$ref": "#/components/schemas/PageOrder" }, "explode": false }, { "name": "after", "in": "query", "required": false, "description": "A cursor for use in pagination. `after` is an object ID that defines your place in the list.\nFor instance, if you make a list request and receive 100 objects, ending with obj_foo, your\nsubsequent call can include after=obj_foo in order to fetch the next page of the list.", "schema": { "type": "string" }, "explode": false }, { "name": "before", "in": "query", "required": false, "description": "A cursor for use in pagination. `before` is an object ID that defines your place in the list.\nFor instance, if you make a list request and receive 100 objects, ending with obj_foo, your\nsubsequent call can include before=obj_foo in order to fetch the previous page of the list.", "schema": { "type": "string" }, "explode": false }, { "name": "path_prefix", "in": "query", "required": false, "description": "Artifact path prefix to list.", "schema": { "type": "string" }, "explode": false }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "type": "object", "required": [ "data", "has_more" ], "properties": { "data": { "type": "array", "items": { "$ref": "#/components/schemas/JobArtifact" }, "description": "The requested list of items." }, "first_id": { "type": "string", "description": "The first ID represented in this list." }, "last_id": { "type": "string", "description": "The last ID represented in this list." }, "has_more": { "type": "boolean", "description": "A value indicating whether there are additional values available not captured in this list." } }, "description": "The response data for a requested list of items." } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "TrainingJobs" ] } }, "/training_jobs/{job_name}/attempts/{attempt_id}/artifacts/content": { "get": { "operationId": "TrainingJobAttemptArtifacts_downloadAttemptArtifact", "description": "Download artifact content from a training job attempt. Use 'latest' for the latest attempt.", "parameters": [ { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "TrainingJobs=V1Preview" ] } }, { "name": "job_name", "in": "path", "required": true, "description": "The training job name.", "schema": { "type": "string" } }, { "name": "attempt_id", "in": "path", "required": true, "description": "The attempt identifier, or 'latest' for the latest attempt.", "schema": { "$ref": "#/components/schemas/JobAttemptIdentifier" } }, { "name": "path", "in": "query", "required": true, "description": "The artifact path.", "schema": { "type": "string" }, "explode": false }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/octet-stream": { "schema": { "type": "string", "format": "binary" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "TrainingJobs" ] } }, "/training_jobs/{job_name}/attempts/{attempt_id}/artifacts/content_info": { "get": { "operationId": "TrainingJobAttemptArtifacts_getAttemptArtifactContentInfo", "description": "Get download information for an artifact from a training job attempt. Use 'latest' for the latest attempt.", "parameters": [ { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "TrainingJobs=V1Preview" ] } }, { "name": "job_name", "in": "path", "required": true, "description": "The training job name.", "schema": { "type": "string" } }, { "name": "attempt_id", "in": "path", "required": true, "description": "The attempt identifier, or 'latest' for the latest attempt.", "schema": { "$ref": "#/components/schemas/JobAttemptIdentifier" } }, { "name": "path", "in": "query", "required": true, "description": "The artifact path.", "schema": { "type": "string" }, "explode": false }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/JobArtifactContentInfo" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "TrainingJobs" ] } }, "/training_jobs/{job_name}/attempts/{attempt_id}/artifacts/content_info_by_prefix": { "get": { "operationId": "TrainingJobAttemptArtifacts_getAttemptArtifactContentInfoByPrefix", "description": "List download information for artifacts under a path prefix from a training job attempt. Use 'latest' for the latest attempt.", "parameters": [ { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "TrainingJobs=V1Preview" ] } }, { "name": "job_name", "in": "path", "required": true, "description": "The training job name.", "schema": { "type": "string" } }, { "name": "attempt_id", "in": "path", "required": true, "description": "The attempt identifier, or 'latest' for the latest attempt.", "schema": { "$ref": "#/components/schemas/JobAttemptIdentifier" } }, { "name": "path_prefix", "in": "query", "required": false, "description": "Artifact path prefix to list download information for. If omitted, download information is returned for the artifact root.", "schema": { "type": "string" }, "explode": false }, { "name": "limit", "in": "query", "required": false, "description": "A limit on the number of objects to be returned. Limit can range between 1 and 100, and the\ndefault is 20.", "schema": { "type": "integer", "format": "int32", "default": 20 }, "explode": false }, { "name": "order", "in": "query", "required": false, "description": "Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and`desc`\nfor descending order.", "schema": { "$ref": "#/components/schemas/PageOrder" }, "explode": false }, { "name": "after", "in": "query", "required": false, "description": "A cursor for use in pagination. `after` is an object ID that defines your place in the list.\nFor instance, if you make a list request and receive 100 objects, ending with obj_foo, your\nsubsequent call can include after=obj_foo in order to fetch the next page of the list.", "schema": { "type": "string" }, "explode": false }, { "name": "before", "in": "query", "required": false, "description": "A cursor for use in pagination. `before` is an object ID that defines your place in the list.\nFor instance, if you make a list request and receive 100 objects, ending with obj_foo, your\nsubsequent call can include before=obj_foo in order to fetch the previous page of the list.", "schema": { "type": "string" }, "explode": false }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "type": "object", "required": [ "data", "has_more" ], "properties": { "data": { "type": "array", "items": { "$ref": "#/components/schemas/JobArtifactContentInfo" }, "description": "The requested list of items." }, "first_id": { "type": "string", "description": "The first ID represented in this list." }, "last_id": { "type": "string", "description": "The last ID represented in this list." }, "has_more": { "type": "boolean", "description": "A value indicating whether there are additional values available not captured in this list." } }, "description": "The response data for a requested list of items." } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "TrainingJobs" ] } }, "/training_jobs/{job_name}/attempts/{attempt_id}/artifacts/metadata": { "get": { "operationId": "TrainingJobAttemptArtifacts_getAttemptArtifactMetadata", "description": "Get metadata for an artifact from a training job attempt. Use 'latest' for the latest attempt.", "parameters": [ { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "TrainingJobs=V1Preview" ] } }, { "name": "job_name", "in": "path", "required": true, "description": "The training job name.", "schema": { "type": "string" } }, { "name": "attempt_id", "in": "path", "required": true, "description": "The attempt identifier, or 'latest' for the latest attempt.", "schema": { "$ref": "#/components/schemas/JobAttemptIdentifier" } }, { "name": "path", "in": "query", "required": true, "description": "The artifact path.", "schema": { "type": "string" }, "explode": false }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/JobArtifact" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "TrainingJobs" ] } }, "/training_jobs/{job_name}/attempts/{attempt_id}/metrics": { "get": { "operationId": "TrainingJobAttemptMetrics_listAttemptMetrics", "description": "List metrics emitted by a training job attempt. Use 'latest' for the latest attempt.", "parameters": [ { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "TrainingJobs=V1Preview" ] } }, { "name": "job_name", "in": "path", "required": true, "description": "The training job name.", "schema": { "type": "string" } }, { "name": "attempt_id", "in": "path", "required": true, "description": "The attempt identifier, or 'latest' for the latest attempt.", "schema": { "$ref": "#/components/schemas/JobAttemptIdentifier" } }, { "name": "limit", "in": "query", "required": false, "description": "A limit on the number of objects to be returned. Limit can range between 1 and 100, and the\ndefault is 20.", "schema": { "type": "integer", "format": "int32", "default": 20 }, "explode": false }, { "name": "order", "in": "query", "required": false, "description": "Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and`desc`\nfor descending order.", "schema": { "$ref": "#/components/schemas/PageOrder" }, "explode": false }, { "name": "after", "in": "query", "required": false, "description": "A cursor for use in pagination. `after` is an object ID that defines your place in the list.\nFor instance, if you make a list request and receive 100 objects, ending with obj_foo, your\nsubsequent call can include after=obj_foo in order to fetch the next page of the list.", "schema": { "type": "string" }, "explode": false }, { "name": "before", "in": "query", "required": false, "description": "A cursor for use in pagination. `before` is an object ID that defines your place in the list.\nFor instance, if you make a list request and receive 100 objects, ending with obj_foo, your\nsubsequent call can include before=obj_foo in order to fetch the previous page of the list.", "schema": { "type": "string" }, "explode": false }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "type": "object", "required": [ "data", "has_more" ], "properties": { "data": { "type": "array", "items": { "$ref": "#/components/schemas/JobMetric" }, "description": "The requested list of items." }, "first_id": { "type": "string", "description": "The first ID represented in this list." }, "last_id": { "type": "string", "description": "The last ID represented in this list." }, "has_more": { "type": "boolean", "description": "A value indicating whether there are additional values available not captured in this list." } }, "description": "The response data for a requested list of items." } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "TrainingJobs" ] } }, "/training_jobs/{job_name}/attempts/{attempt_id}/metrics/last_values": { "get": { "operationId": "TrainingJobAttemptMetrics_getAttemptMetricLastValues", "description": "Get latest metric values for a training job attempt. Use 'latest' for the latest attempt.", "parameters": [ { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "TrainingJobs=V1Preview" ] } }, { "name": "job_name", "in": "path", "required": true, "description": "The training job name.", "schema": { "type": "string" } }, { "name": "attempt_id", "in": "path", "required": true, "description": "The attempt identifier, or 'latest' for the latest attempt.", "schema": { "$ref": "#/components/schemas/JobAttemptIdentifier" } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "type": "object", "required": [ "data", "has_more" ], "properties": { "data": { "type": "array", "items": { "$ref": "#/components/schemas/JobMetricLastValue" }, "description": "The requested list of items." }, "first_id": { "type": "string", "description": "The first ID represented in this list." }, "last_id": { "type": "string", "description": "The last ID represented in this list." }, "has_more": { "type": "boolean", "description": "A value indicating whether there are additional values available not captured in this list." } }, "description": "The response data for a requested list of items." } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "TrainingJobs" ] } }, "/training_jobs/{job_name}/attempts/{attempt_id}/metrics/{metric_name}": { "get": { "operationId": "TrainingJobAttemptMetrics_getAttemptMetric", "description": "Get the full history for a metric from a training job attempt. Use 'latest' for the latest attempt.", "parameters": [ { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "TrainingJobs=V1Preview" ] } }, { "name": "job_name", "in": "path", "required": true, "description": "The training job name.", "schema": { "type": "string" } }, { "name": "attempt_id", "in": "path", "required": true, "description": "The attempt identifier, or 'latest' for the latest attempt.", "schema": { "$ref": "#/components/schemas/JobAttemptIdentifier" } }, { "name": "metric_name", "in": "path", "required": true, "description": "The metric name.", "schema": { "type": "string" } }, { "name": "started_at", "in": "query", "required": false, "description": "Start of the metric time range.", "schema": { "$ref": "#/components/schemas/FoundryTimestamp" }, "explode": false }, { "name": "ended_at", "in": "query", "required": false, "description": "End of the metric time range.", "schema": { "$ref": "#/components/schemas/FoundryTimestamp" }, "explode": false }, { "name": "min_step", "in": "query", "required": false, "description": "Minimum metric step to include.", "schema": { "type": "integer", "format": "int64" }, "explode": false }, { "name": "max_step", "in": "query", "required": false, "description": "Maximum metric step to include.", "schema": { "type": "integer", "format": "int64" }, "explode": false }, { "name": "limit", "in": "query", "required": false, "description": "Maximum number of metric points to return.", "schema": { "type": "integer", "format": "int32" }, "explode": false }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "type": "object", "required": [ "data", "has_more" ], "properties": { "data": { "type": "array", "items": { "$ref": "#/components/schemas/JobMetricPoint" }, "description": "The requested list of items." }, "first_id": { "type": "string", "description": "The first ID represented in this list." }, "last_id": { "type": "string", "description": "The last ID represented in this list." }, "has_more": { "type": "boolean", "description": "A value indicating whether there are additional values available not captured in this list." } }, "description": "The response data for a requested list of items." } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "TrainingJobs" ] } }, "/training_jobs/{job_name}/attempts/{attempt_id}/metrics/{metric_name}/aggregates": { "get": { "operationId": "TrainingJobAttemptMetrics_getAttemptMetricAggregates", "description": "Get aggregate metric values from a training job attempt. Use 'latest' for the latest attempt.", "parameters": [ { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "TrainingJobs=V1Preview" ] } }, { "name": "job_name", "in": "path", "required": true, "description": "The training job name.", "schema": { "type": "string" } }, { "name": "attempt_id", "in": "path", "required": true, "description": "The attempt identifier, or 'latest' for the latest attempt.", "schema": { "$ref": "#/components/schemas/JobAttemptIdentifier" } }, { "name": "metric_name", "in": "path", "required": true, "description": "The metric name.", "schema": { "type": "string" } }, { "name": "started_at", "in": "query", "required": false, "description": "Start of the metric time range.", "schema": { "$ref": "#/components/schemas/FoundryTimestamp" }, "explode": false }, { "name": "ended_at", "in": "query", "required": false, "description": "End of the metric time range.", "schema": { "$ref": "#/components/schemas/FoundryTimestamp" }, "explode": false }, { "name": "min_step", "in": "query", "required": false, "description": "Minimum metric step to include.", "schema": { "type": "integer", "format": "int64" }, "explode": false }, { "name": "max_step", "in": "query", "required": false, "description": "Maximum metric step to include.", "schema": { "type": "integer", "format": "int64" }, "explode": false }, { "name": "limit", "in": "query", "required": false, "description": "Maximum number of metric points to return.", "schema": { "type": "integer", "format": "int32" }, "explode": false }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "type": "object", "required": [ "data", "has_more" ], "properties": { "data": { "type": "array", "items": { "$ref": "#/components/schemas/JobMetricAggregate" }, "description": "The requested list of items." }, "first_id": { "type": "string", "description": "The first ID represented in this list." }, "last_id": { "type": "string", "description": "The last ID represented in this list." }, "has_more": { "type": "boolean", "description": "A value indicating whether there are additional values available not captured in this list." } }, "description": "The response data for a requested list of items." } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "TrainingJobs" ] } }, "/training_jobs/{job_name}/attempts/{attempt_id}/metrics/{metric_name}/sample": { "get": { "operationId": "TrainingJobAttemptMetrics_getAttemptMetricSample", "description": "Get one sampled value or window from a training job attempt. Use 'latest' for the latest attempt.", "parameters": [ { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "TrainingJobs=V1Preview" ] } }, { "name": "job_name", "in": "path", "required": true, "description": "The training job name.", "schema": { "type": "string" } }, { "name": "attempt_id", "in": "path", "required": true, "description": "The attempt identifier, or 'latest' for the latest attempt.", "schema": { "$ref": "#/components/schemas/JobAttemptIdentifier" } }, { "name": "metric_name", "in": "path", "required": true, "description": "The metric name.", "schema": { "type": "string" } }, { "name": "started_at", "in": "query", "required": false, "description": "Start of the metric time range.", "schema": { "$ref": "#/components/schemas/FoundryTimestamp" }, "explode": false }, { "name": "ended_at", "in": "query", "required": false, "description": "End of the metric time range.", "schema": { "$ref": "#/components/schemas/FoundryTimestamp" }, "explode": false }, { "name": "min_step", "in": "query", "required": false, "description": "Minimum metric step to include.", "schema": { "type": "integer", "format": "int64" }, "explode": false }, { "name": "max_step", "in": "query", "required": false, "description": "Maximum metric step to include.", "schema": { "type": "integer", "format": "int64" }, "explode": false }, { "name": "limit", "in": "query", "required": false, "description": "Maximum number of metric points to return.", "schema": { "type": "integer", "format": "int32" }, "explode": false }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/JobMetricSample" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "TrainingJobs" ] } }, "/training_jobs/{job_name}/attempts/{attempt_id}/metrics/{metric_name}/samples": { "get": { "operationId": "TrainingJobAttemptMetrics_getAttemptMetricSamples", "description": "Get sampled metric values from a training job attempt. Use 'latest' for the latest attempt.", "parameters": [ { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "TrainingJobs=V1Preview" ] } }, { "name": "job_name", "in": "path", "required": true, "description": "The training job name.", "schema": { "type": "string" } }, { "name": "attempt_id", "in": "path", "required": true, "description": "The attempt identifier, or 'latest' for the latest attempt.", "schema": { "$ref": "#/components/schemas/JobAttemptIdentifier" } }, { "name": "metric_name", "in": "path", "required": true, "description": "The metric name.", "schema": { "type": "string" } }, { "name": "started_at", "in": "query", "required": false, "description": "Start of the metric time range.", "schema": { "$ref": "#/components/schemas/FoundryTimestamp" }, "explode": false }, { "name": "ended_at", "in": "query", "required": false, "description": "End of the metric time range.", "schema": { "$ref": "#/components/schemas/FoundryTimestamp" }, "explode": false }, { "name": "min_step", "in": "query", "required": false, "description": "Minimum metric step to include.", "schema": { "type": "integer", "format": "int64" }, "explode": false }, { "name": "max_step", "in": "query", "required": false, "description": "Maximum metric step to include.", "schema": { "type": "integer", "format": "int64" }, "explode": false }, { "name": "limit", "in": "query", "required": false, "description": "Maximum number of metric points to return.", "schema": { "type": "integer", "format": "int32" }, "explode": false }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/JobMetricSample" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "TrainingJobs" ] } }, "/training_jobs/{job_name}/attempts/{attempt_id}/outputs": { "get": { "operationId": "TrainingJobAttemptOutputs_listAttemptOutputs", "description": "List outputs produced by a specific training job attempt.", "parameters": [ { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "TrainingJobs=V1Preview" ] } }, { "name": "job_name", "in": "path", "required": true, "description": "The training job name.", "schema": { "type": "string" } }, { "name": "attempt_id", "in": "path", "required": true, "description": "The attempt identifier.", "schema": { "type": "string" } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "type": "object", "required": [ "data", "has_more" ], "properties": { "data": { "type": "array", "items": { "$ref": "#/components/schemas/JobOutputReference" }, "description": "The requested list of items." }, "first_id": { "type": "string", "description": "The first ID represented in this list." }, "last_id": { "type": "string", "description": "The last ID represented in this list." }, "has_more": { "type": "boolean", "description": "A value indicating whether there are additional values available not captured in this list." } }, "description": "The response data for a requested list of items." } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "TrainingJobs" ] } }, "/training_jobs/{job_name}/attempts/{attempt_id}/outputs/{output_name}": { "get": { "operationId": "TrainingJobAttemptOutputs_getAttemptOutput", "description": "Get one output produced by a specific training job attempt.", "parameters": [ { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "TrainingJobs=V1Preview" ] } }, { "name": "job_name", "in": "path", "required": true, "description": "The training job name.", "schema": { "type": "string" } }, { "name": "attempt_id", "in": "path", "required": true, "description": "The attempt identifier.", "schema": { "type": "string" } }, { "name": "output_name", "in": "path", "required": true, "description": "The output name.", "schema": { "type": "string" } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/JobOutputReference" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "TrainingJobs" ] } }, "/training_jobs/{job_name}/outputs": { "get": { "operationId": "TrainingJobOutputs_listOutputs", "description": "List outputs produced by a training job.", "parameters": [ { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "TrainingJobs=V1Preview" ] } }, { "name": "job_name", "in": "path", "required": true, "description": "The training job name.", "schema": { "type": "string" } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "type": "object", "required": [ "data", "has_more" ], "properties": { "data": { "type": "array", "items": { "$ref": "#/components/schemas/JobOutputReference" }, "description": "The requested list of items." }, "first_id": { "type": "string", "description": "The first ID represented in this list." }, "last_id": { "type": "string", "description": "The last ID represented in this list." }, "has_more": { "type": "boolean", "description": "A value indicating whether there are additional values available not captured in this list." } }, "description": "The response data for a requested list of items." } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "TrainingJobs" ] } }, "/training_jobs/{job_name}/outputs/{output_name}": { "get": { "operationId": "TrainingJobOutputs_getOutput", "description": "Get one output produced by a training job.", "parameters": [ { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "TrainingJobs=V1Preview" ] } }, { "name": "job_name", "in": "path", "required": true, "description": "The training job name.", "schema": { "type": "string" } }, { "name": "output_name", "in": "path", "required": true, "description": "The output name.", "schema": { "type": "string" } }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/JobOutputReference" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "TrainingJobs" ] } }, "/training_jobs/{job_name}/services": { "get": { "operationId": "TrainingJobs_showServices", "description": "List service endpoints for the current view of a training job.", "parameters": [ { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "TrainingJobs=V1Preview" ] } }, { "name": "job_name", "in": "path", "required": true, "description": "The training job name.", "schema": { "type": "string" } }, { "name": "node_id", "in": "query", "required": false, "description": "Node identifier whose service endpoints should be returned. If omitted, leader-node services are returned.", "schema": { "type": "integer", "format": "int32" }, "explode": false }, { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string" }, "explode": false } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/TrainingJobServiceCollection" } } } }, "default": { "description": "An unexpected error response.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ApiErrorResponse" } } } } }, "tags": [ "TrainingJobs" ] } }, "/training_jobs/{name}": { "get": { "operationId": "TrainingJobs_get", "description": "Get a training job by name.", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "name", "in": "path", "required": true, "description": "The name of the training job. This is case-sensitive.", "schema": { "type": "string" } }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "TrainingJobs=V1Preview" ] } } ], "responses": { "200": { "description": "The request has succeeded.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Job" } } } }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "TrainingJobs" ] }, "delete": { "operationId": "TrainingJobs_beginDelete", "description": "Delete a training job by name. Returns 202 Accepted with Location and Operation-Location headers to poll for completion, or 204 if the job does not exist.", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "name", "in": "path", "required": true, "description": "The name of the training job. This is case-sensitive.", "schema": { "type": "string" } }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "TrainingJobs=V1Preview" ] } } ], "responses": { "202": { "description": "Response returned when a job delete operation is accepted asynchronously.", "headers": { "Location": { "required": true, "description": "URL to poll for the final result of the delete operation.", "schema": { "type": "string" } }, "Operation-Location": { "required": false, "description": "URL to poll for the status of the delete operation.", "schema": { "type": "string" } }, "Retry-After": { "required": false, "description": "Suggested delay in seconds before polling.", "schema": { "type": "integer", "format": "int32" } } } }, "204": { "description": "There is no content to send for this request, but the headers may be useful." }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "TrainingJobs" ] } }, "/training_jobs/{name}:cancel": { "post": { "operationId": "TrainingJobs_beginCancel", "description": "Cancel a training job by name. Returns 200 if cancelled immediately, or 202 Accepted with Location and Operation-Location headers to poll for completion.", "parameters": [ { "$ref": "#/components/parameters/Azure.Core.Foundations.ApiVersionParameter" }, { "name": "name", "in": "path", "required": true, "description": "The name of the training job. This is case-sensitive.", "schema": { "type": "string" } }, { "name": "Foundry-Features", "in": "header", "required": true, "description": "A feature flag opt-in required when using preview operations or modifying persisted preview resources.", "schema": { "type": "string", "enum": [ "TrainingJobs=V1Preview" ] } } ], "responses": { "200": { "description": "The request has succeeded." }, "202": { "description": "Response returned when a job cancel operation is accepted asynchronously.", "headers": { "Location": { "required": true, "description": "URL to poll for the final result of the cancel operation.", "schema": { "type": "string" } }, "Operation-Location": { "required": false, "description": "URL to poll for the status of the cancel operation.", "schema": { "type": "string" } }, "Retry-After": { "required": false, "description": "Suggested delay in seconds before polling.", "schema": { "type": "integer", "format": "int32" } } } }, "default": { "description": "An unexpected error response.", "headers": { "x-ms-error-code": { "required": false, "description": "String error code indicating what went wrong.", "schema": { "type": "string" } } }, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Azure.Core.Foundations.ErrorResponse" } } } } }, "tags": [ "TrainingJobs" ] } } }, "security": [ { "ApiKeyAuth": [] }, { "OAuth2Auth": [ "https://ai.azure.com/.default" ] } ], "components": { "parameters": { "Azure.Core.ClientRequestIdHeader": { "name": "x-ms-client-request-id", "in": "header", "required": false, "description": "An opaque, globally-unique, client-generated string identifier for the request.", "schema": { "$ref": "#/components/schemas/Azure.Core.uuid" } }, "Azure.Core.Foundations.ApiVersionParameter": { "name": "api-version", "in": "query", "required": true, "description": "The API version to use for this operation.", "schema": { "type": "string", "minLength": 1 }, "explode": false } }, "schemas": { "A2APreviewTool": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "a2a_preview" ], "description": "The type of the tool. Always `\"a2a_preview`." }, "name": { "type": "string", "description": "Optional user-defined name for this tool or configuration." }, "description": { "type": "string", "description": "Optional user-defined description for this tool or configuration." }, "base_url": { "type": "string", "format": "uri", "description": "Base URL of the agent." }, "agent_card_path": { "type": "string", "description": "The path to the agent card relative to the `base_url`.\nIf not provided, defaults to `/.well-known/agent-card.json`" }, "project_connection_id": { "type": "string", "description": "The connection ID in the project for the A2A server.\nThe connection stores authentication and other connection details needed to connect to the A2A server." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Tool" } ], "description": "An agent implementing the A2A protocol." }, "A2AToolCall": { "type": "object", "required": [ "type", "call_id", "name", "arguments", "status" ], "properties": { "type": { "type": "string", "enum": [ "a2a_preview_call" ] }, "call_id": { "type": "string", "description": "The unique ID of the tool call generated by the model." }, "name": { "type": "string", "description": "The name of the A2A agent card being called." }, "arguments": { "type": "string", "description": "A JSON string of the arguments to pass to the tool." }, "status": { "allOf": [ { "$ref": "#/components/schemas/ToolCallStatus" } ], "description": "The status of the tool call." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ], "description": "An A2A (Agent-to-Agent) tool call." }, "A2AToolCallOutput": { "type": "object", "required": [ "type", "call_id", "name", "status" ], "properties": { "type": { "type": "string", "enum": [ "a2a_preview_call_output" ] }, "call_id": { "type": "string", "description": "The unique ID of the tool call generated by the model." }, "name": { "type": "string", "description": "The name of the A2A agent card that was called." }, "output": { "allOf": [ { "$ref": "#/components/schemas/ToolCallOutputContent" } ], "description": "The output from the A2A tool call." }, "status": { "allOf": [ { "$ref": "#/components/schemas/ToolCallStatus" } ], "description": "The status of the tool call." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ], "description": "The output of an A2A (Agent-to-Agent) tool call." }, "AISearchIndexResource": { "type": "object", "properties": { "project_connection_id": { "type": "string", "description": "An index connection ID in an IndexResource attached to this agent." }, "index_name": { "type": "string", "description": "The name of an index in an IndexResource attached to this agent." }, "name": { "type": "string", "description": "Optional user-defined name for this tool or configuration." }, "description": { "type": "string", "description": "Optional user-defined description for this tool or configuration." }, "query_type": { "allOf": [ { "$ref": "#/components/schemas/AzureAISearchQueryType" } ], "description": "Type of query in an AIIndexResource attached to this agent." }, "top_k": { "type": "integer", "format": "int32", "description": "Number of documents to retrieve from search and present to the model." }, "filter": { "type": "string", "description": "filter string for search resource. [Learn more here](https://learn.microsoft.com/azure/search/search-filters)." }, "index_asset_id": { "type": "string", "description": "Index asset id for search resource." } }, "description": "A AI Search Index resource." }, "AgentClusterInsightRequest": { "type": "object", "required": [ "type", "agentName" ], "properties": { "type": { "type": "string", "enum": [ "AgentClusterInsight" ], "description": "The type of request." }, "agentName": { "type": "string", "description": "Identifier for the agent." }, "modelConfiguration": { "allOf": [ { "$ref": "#/components/schemas/InsightModelConfiguration" } ], "description": "Configuration of the model used in the insight generation." } }, "allOf": [ { "$ref": "#/components/schemas/InsightRequest" } ], "description": "Insights on set of Agent Evaluation Results" }, "AgentClusterInsightResult": { "type": "object", "required": [ "type", "clusterInsight" ], "properties": { "type": { "type": "string", "enum": [ "AgentClusterInsight" ], "description": "The type of insights result." }, "clusterInsight": { "$ref": "#/components/schemas/ClusterInsightResult" } }, "allOf": [ { "$ref": "#/components/schemas/InsightResult" } ], "description": "Insights from the agent cluster analysis." }, "AgentDefinition": { "type": "object", "required": [ "kind" ], "properties": { "kind": { "$ref": "#/components/schemas/AgentKind" }, "rai_config": { "allOf": [ { "$ref": "#/components/schemas/RaiConfig" } ], "description": "Configuration for Responsible AI (RAI) content filtering and safety features." } }, "discriminator": { "propertyName": "kind", "mapping": { "prompt": "#/components/schemas/PromptAgentDefinition", "workflow": "#/components/schemas/WorkflowAgentDefinition", "hosted": "#/components/schemas/HostedAgentDefinition" } }, "x-ms-foundry-meta": { "conditional_previews": [ "HostedAgents=V1Preview", "ContainerAgents=V1Preview", "WorkflowAgents=V1Preview" ] } }, "AgentDefinitionOptInKeys": { "type": "string", "enum": [ "HostedAgents=V1Preview", "WorkflowAgents=V1Preview" ], "description": "Opt-in keys for defining preview Hosted or Workflow Agents." }, "AgentKind": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "prompt", "hosted", "workflow" ] } ] }, "AgentObject": { "type": "object", "required": [ "object", "id", "name", "versions" ], "properties": { "object": { "type": "string", "enum": [ "agent" ], "description": "The object type, which is always 'agent'." }, "id": { "type": "string", "description": "The unique identifier of the agent." }, "name": { "type": "string", "maxLength": 63, "description": "The name of the agent." }, "versions": { "type": "object", "properties": { "latest": { "$ref": "#/components/schemas/AgentVersionObject" } }, "required": [ "latest" ], "description": "The latest version of the agent." } } }, "AgentProtocol": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "activity_protocol", "responses" ] } ] }, "AgentReference": { "type": "object", "required": [ "type", "name" ], "properties": { "type": { "type": "string", "enum": [ "agent_reference" ] }, "name": { "type": "string", "maxLength": 256, "description": "The name of the agent." }, "version": { "type": "string", "description": "The version identifier of the agent." } } }, "AgentTaxonomyInput": { "type": "object", "required": [ "type", "target", "riskCategories" ], "properties": { "type": { "type": "string", "enum": [ "agent" ], "description": "Input type of the evaluation taxonomy." }, "target": { "allOf": [ { "$ref": "#/components/schemas/Target" } ], "description": "Target configuration for the agent." }, "riskCategories": { "type": "array", "items": { "$ref": "#/components/schemas/RiskCategory" }, "description": "List of risk categories to evaluate against." } }, "allOf": [ { "$ref": "#/components/schemas/EvaluationTaxonomyInput" } ], "description": "Input configuration for the evaluation taxonomy when the input type is agent." }, "AgentTaxonomyInputUpdate": { "type": "object", "properties": { "type": { "type": "string", "enum": [ "agent" ], "description": "Input type of the evaluation taxonomy." }, "target": { "allOf": [ { "$ref": "#/components/schemas/TargetUpdate" } ], "description": "Target configuration for the agent." }, "riskCategories": { "type": "array", "items": { "$ref": "#/components/schemas/RiskCategory" }, "description": "List of risk categories to evaluate against." } }, "allOf": [ { "$ref": "#/components/schemas/EvaluationTaxonomyInputUpdate" } ], "description": "Input configuration for the evaluation taxonomy when the input type is agent." }, "AgentVersionObject": { "type": "object", "required": [ "metadata", "object", "id", "name", "version", "created_at", "definition" ], "properties": { "metadata": { "type": "object", "additionalProperties": { "type": "string" }, "nullable": true, "description": "Set of 16 key-value pairs that can be attached to an object. This can be\nuseful for storing additional information about the object in a structured\nformat, and querying for objects via API or the dashboard.\n\nKeys are strings with a maximum length of 64 characters. Values are strings\nwith a maximum length of 512 characters.", "x-oaiTypeLabel": "map" }, "object": { "type": "string", "enum": [ "agent.version" ], "description": "The object type, which is always 'agent.version'." }, "id": { "type": "string", "description": "The unique identifier of the agent version." }, "name": { "type": "string", "maxLength": 256, "description": "The name of the agent. Name can be used to retrieve/update/delete the agent." }, "version": { "type": "string", "description": "The version identifier of the agent. Agents are immutable and every update creates a new version while keeping the name same." }, "description": { "type": "string", "maxLength": 512, "description": "A human-readable description of the agent." }, "created_at": { "type": "integer", "format": "unixtime", "description": "The Unix timestamp (seconds) when the agent was created." }, "definition": { "$ref": "#/components/schemas/AgentDefinition" } } }, "AgenticIdentityPreviewCredentials": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "AgenticIdentityToken_Preview" ], "description": "The credential type", "readOnly": true } }, "allOf": [ { "$ref": "#/components/schemas/BaseCredentials" } ], "description": "Agentic identity credential definition" }, "ApiErrorResponse": { "type": "object", "required": [ "error" ], "properties": { "error": { "$ref": "#/components/schemas/OpenAI.Error" } }, "description": "Error response for API failures." }, "ApiKeyCredentials": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "ApiKey" ], "description": "The credential type", "readOnly": true }, "key": { "type": "string", "description": "API Key", "readOnly": true } }, "allOf": [ { "$ref": "#/components/schemas/BaseCredentials" } ], "description": "API Key Credential definition" }, "AssetCredentialResponse": { "type": "object", "required": [ "blobReference" ], "properties": { "blobReference": { "allOf": [ { "$ref": "#/components/schemas/BlobReference" } ], "description": "Credential info to access the storage account." } }, "description": "Represents a reference to a blob for consumption" }, "AssetId": { "type": "string", "description": "Identifier of a saved asset." }, "AssetTypes": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "uri_file", "uri_folder", "safetensors_model", "literal" ] } ], "description": "Type of job input/output asset." }, "AttackStrategy": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "easy", "moderate", "difficult", "ascii_art", "ascii_smuggler", "atbash", "base64", "binary", "caesar", "character_space", "jailbreak", "ansi_attack", "character_swap", "suffix_append", "string_join", "unicode_confusable", "unicode_substitution", "diacritic", "flip", "leetspeak", "rot13", "morse", "url", "baseline", "indirect_jailbreak", "tense", "multi_turn", "crescendo" ] } ], "description": "Strategies for attacks." }, "Azure.Core.Foundations.Error": { "type": "object", "required": [ "code", "message" ], "properties": { "code": { "type": "string", "description": "One of a server-defined set of error codes." }, "message": { "type": "string", "description": "A human-readable representation of the error." }, "target": { "type": "string", "description": "The target of the error." }, "details": { "type": "array", "items": { "$ref": "#/components/schemas/Azure.Core.Foundations.Error" }, "description": "An array of details about specific errors that led to this reported error." }, "innererror": { "allOf": [ { "$ref": "#/components/schemas/Azure.Core.Foundations.InnerError" } ], "description": "An object containing more specific information than the current object about the error." } }, "description": "The error object." }, "Azure.Core.Foundations.ErrorResponse": { "type": "object", "required": [ "error" ], "properties": { "error": { "allOf": [ { "$ref": "#/components/schemas/Azure.Core.Foundations.Error" } ], "description": "The error object." } }, "description": "A response containing error details." }, "Azure.Core.Foundations.InnerError": { "type": "object", "properties": { "code": { "type": "string", "description": "One of a server-defined set of error codes." }, "innererror": { "allOf": [ { "$ref": "#/components/schemas/Azure.Core.Foundations.InnerError" } ], "description": "Inner error." } }, "description": "An object containing more specific information about the error. As per Azure REST API guidelines - https://aka.ms/AzureRestApiGuidelines#handling-errors." }, "Azure.Core.Foundations.OperationState": { "anyOf": [ { "type": "string", "enum": [ "NotStarted", "Running", "Succeeded", "Failed", "Canceled" ] }, { "type": "string" } ], "description": "Enum describing allowed operation states." }, "Azure.Core.uuid": { "type": "string", "format": "uuid", "description": "Universally Unique Identifier" }, "AzureAIAgentTarget": { "type": "object", "required": [ "type", "name" ], "properties": { "type": { "type": "string", "enum": [ "azure_ai_agent" ], "description": "The type of target, always `azure_ai_agent`." }, "name": { "type": "string", "description": "The unique identifier of the Azure AI agent." }, "version": { "type": "string", "description": "The version of the Azure AI agent." }, "tool_descriptions": { "type": "array", "items": { "$ref": "#/components/schemas/ToolDescription" }, "description": "The parameters used to control the sampling behavior of the agent during text generation." } }, "allOf": [ { "$ref": "#/components/schemas/Target" } ], "description": "Represents a target specifying an Azure AI agent." }, "AzureAIAgentTargetUpdate": { "type": "object", "properties": { "type": { "type": "string", "enum": [ "azure_ai_agent" ], "description": "The type of target, always `azure_ai_agent`." }, "name": { "type": "string", "description": "The unique identifier of the Azure AI agent." }, "version": { "type": "string", "description": "The version of the Azure AI agent." }, "tool_descriptions": { "type": "array", "items": { "$ref": "#/components/schemas/ToolDescription" }, "description": "The parameters used to control the sampling behavior of the agent during text generation." } }, "allOf": [ { "$ref": "#/components/schemas/TargetUpdate" } ], "description": "Represents a target specifying an Azure AI agent." }, "AzureAIBenchmarkDataSourceConfig": { "type": "object", "required": [ "scenario", "benchmark_name" ], "properties": { "scenario": { "type": "string", "enum": [ "benchmark_preview" ], "description": "Data schema scenario, always `benchmark` for benchmark evaluations." }, "benchmark_name": { "allOf": [ { "$ref": "#/components/schemas/BenchmarkName" } ], "description": "The name of the benchmark specification." }, "benchmark_version": { "type": "string", "description": "The version of the benchmark specification (e.g., '0.1'). Latest version if not specified." }, "grader_model": { "type": "string", "description": "Optional grader model for benchmarks that use model graders, Required when the benchmark's testing_criteria uses a model grader type." } }, "allOf": [ { "$ref": "#/components/schemas/AzureAIDataSourceConfig" } ], "description": "Data source configuration for benchmark evaluations." }, "AzureAIBenchmarkPreviewEvalRunDataSource": { "type": "object", "required": [ "type", "target" ], "properties": { "type": { "type": "string", "enum": [ "azure_ai_benchmark_preview" ], "description": "The type of data source, always `azure_ai_benchmark_preview`." }, "input_messages": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.CreateEvalCompletionsRunDataSourceInputMessagesItemReference" } ], "description": "Input messages configuration." }, "target": { "anyOf": [ { "$ref": "#/components/schemas/AzureAIModelTarget" }, { "$ref": "#/components/schemas/AzureAIAgentTarget" } ], "description": "The target model or agent to evaluate against the benchmark.\nWhen using `azure_ai_model` target, `sampling_params` must not be provided;\ninference parameters are auto-filled from the benchmark specification stored in eval group properties." } }, "allOf": [ { "$ref": "#/components/schemas/EvalRunDataSource" } ], "description": "Represents a data source for benchmark evaluation runs." }, "AzureAIDataSourceConfig": { "type": "object", "required": [ "type", "scenario" ], "properties": { "type": { "type": "string", "enum": [ "azure_ai_source" ], "description": "The object type, which is always `azure_ai_source`." }, "scenario": { "type": "string", "enum": [ "red_team", "responses", "traces_preview", "synthetic_data_gen_preview", "benchmark_preview" ], "description": "Data schema scenario." } }, "discriminator": { "propertyName": "scenario", "mapping": { "benchmark_preview": "#/components/schemas/AzureAIBenchmarkDataSourceConfig" } }, "allOf": [ { "$ref": "#/components/schemas/DataSourceConfig" } ] }, "AzureAIModelTarget": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "azure_ai_model" ], "description": "The type of target, always `azure_ai_model`." }, "model": { "type": "string", "description": "The unique identifier of the Azure AI model." }, "sampling_params": { "allOf": [ { "$ref": "#/components/schemas/ModelSamplingParams" } ], "description": "The parameters used to control the sampling behavior of the model during text generation." } }, "allOf": [ { "$ref": "#/components/schemas/Target" } ], "description": "Represents a target specifying an Azure AI model for operations requiring model selection." }, "AzureAIModelTargetUpdate": { "type": "object", "properties": { "type": { "type": "string", "enum": [ "azure_ai_model" ], "description": "The type of target, always `azure_ai_model`." }, "model": { "type": "string", "description": "The unique identifier of the Azure AI model." }, "sampling_params": { "allOf": [ { "$ref": "#/components/schemas/ModelSamplingParamsUpdate" } ], "description": "The parameters used to control the sampling behavior of the model during text generation." } }, "allOf": [ { "$ref": "#/components/schemas/TargetUpdate" } ], "description": "Represents a target specifying an Azure AI model for operations requiring model selection." }, "AzureAIResponsesEvalRunDataSource": { "type": "object", "required": [ "type", "item_generation_params", "max_runs_hourly", "event_configuration_id" ], "properties": { "type": { "type": "string", "enum": [ "azure_ai_responses" ], "description": "The type of data source, always `azure_ai_responses`." }, "item_generation_params": { "allOf": [ { "$ref": "#/components/schemas/ResponseRetrievalItemGenerationParams" } ], "description": "The parameters for item generation." }, "max_runs_hourly": { "type": "integer", "format": "int32", "description": "Maximum number of evaluation runs allowed per hour." }, "event_configuration_id": { "type": "string", "description": "The event configuration name associated with this evaluation run." } }, "allOf": [ { "$ref": "#/components/schemas/EvalRunDataSource" } ], "description": "Represents a data source for evaluation runs that are specific to Continuous Evaluation scenarios." }, "AzureAISearchIndex": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "AzureSearch" ], "description": "Type of index" } }, "allOf": [ { "$ref": "#/components/schemas/Index" } ], "description": "Azure AI Search Index Definition" }, "AzureAISearchIndexUpdate": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "AzureSearch" ], "description": "Type of index" } }, "allOf": [ { "$ref": "#/components/schemas/IndexUpdate" } ], "description": "Azure AI Search Index Definition" }, "AzureAISearchQueryType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "simple", "semantic", "vector", "vector_simple_hybrid", "vector_semantic_hybrid" ] } ], "description": "Available query types for Azure AI Search tool." }, "AzureAISearchTool": { "type": "object", "required": [ "type", "azure_ai_search" ], "properties": { "type": { "type": "string", "enum": [ "azure_ai_search" ], "description": "The object type, which is always 'azure_ai_search'." }, "name": { "type": "string", "description": "Optional user-defined name for this tool or configuration." }, "description": { "type": "string", "description": "Optional user-defined description for this tool or configuration." }, "azure_ai_search": { "allOf": [ { "$ref": "#/components/schemas/AzureAISearchToolResource" } ], "description": "The azure ai search index resource." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Tool" } ], "description": "The input definition information for an Azure AI search tool as used to configure an agent." }, "AzureAISearchToolCall": { "type": "object", "required": [ "type", "call_id", "arguments", "status" ], "properties": { "type": { "type": "string", "enum": [ "azure_ai_search_call" ] }, "call_id": { "type": "string", "description": "The unique ID of the tool call generated by the model." }, "arguments": { "type": "string", "description": "A JSON string of the arguments to pass to the tool." }, "status": { "allOf": [ { "$ref": "#/components/schemas/ToolCallStatus" } ], "description": "The status of the tool call." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ], "description": "An Azure AI Search tool call." }, "AzureAISearchToolCallOutput": { "type": "object", "required": [ "type", "call_id", "status" ], "properties": { "type": { "type": "string", "enum": [ "azure_ai_search_call_output" ] }, "call_id": { "type": "string", "description": "The unique ID of the tool call generated by the model." }, "output": { "allOf": [ { "$ref": "#/components/schemas/ToolCallOutputContent" } ], "description": "The output from the Azure AI Search tool call." }, "status": { "allOf": [ { "$ref": "#/components/schemas/ToolCallStatus" } ], "description": "The status of the tool call." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ], "description": "The output of an Azure AI Search tool call." }, "AzureAISearchToolResource": { "type": "object", "required": [ "indexes" ], "properties": { "name": { "type": "string", "description": "Optional user-defined name for this tool or configuration." }, "description": { "type": "string", "description": "Optional user-defined description for this tool or configuration." }, "indexes": { "type": "array", "items": { "$ref": "#/components/schemas/AISearchIndexResource" }, "maxItems": 1, "description": "The indices attached to this agent. There can be a maximum of 1 index\nresource attached to the agent." } }, "description": "A set of index resources used by the `azure_ai_search` tool." }, "AzureContentFilterBlocklistIdResult": { "type": "object", "required": [ "id", "filtered" ], "properties": { "id": { "type": "string", "description": "The ID of the custom blocklist." }, "filtered": { "type": "boolean", "description": "Whether the blocklist resulted in filtering." } }, "description": "A content filter blocklist ID result." }, "AzureContentFilterBlocklistResult": { "type": "object", "required": [ "filtered" ], "properties": { "filtered": { "type": "boolean", "description": "Whether any blocklist resulted in filtering." }, "details": { "type": "array", "items": { "$ref": "#/components/schemas/AzureContentFilterBlocklistIdResult" }, "description": "The pairs of individual blocklist IDs and their filtering results." } }, "description": "A collection of filtering results for configured custom blocklists." }, "AzureContentFilterCitation": { "type": "object", "properties": { "license": { "type": "string", "description": "The license associated with the detection." }, "url": { "type": "string", "format": "uri", "description": "The URL associated with the license." } }, "description": "Citation details for protected material detection." }, "AzureContentFilterCompletionTextSpan": { "type": "object", "required": [ "completion_start_offset", "completion_end_offset" ], "properties": { "completion_start_offset": { "type": "integer", "format": "int32", "description": "Offset of the UTF32 code point which begins the span." }, "completion_end_offset": { "type": "integer", "format": "int32", "description": "Offset of the first UTF32 code point which is excluded from the span." } }, "description": "A representation of a span of completion text as used by Azure OpenAI content filter results." }, "AzureContentFilterCompletionTextSpanDetectionResult": { "type": "object", "required": [ "filtered", "detected", "details" ], "properties": { "filtered": { "type": "boolean", "description": "Whether the content was filtered." }, "detected": { "type": "boolean", "description": "Whether the content category was detected." }, "details": { "type": "array", "items": { "$ref": "#/components/schemas/AzureContentFilterCompletionTextSpan" }, "description": "Detailed information about the detected completion text spans." } }, "description": "A content filter detection result with completion text span details." }, "AzureContentFilterDetectionResult": { "type": "object", "required": [ "filtered", "detected" ], "properties": { "filtered": { "type": "boolean", "description": "Whether the content was filtered." }, "detected": { "type": "boolean", "description": "Whether the content category was detected." } }, "description": "A content filter result indicating whether the content was detected and filtered." }, "AzureContentFilterDetectionWithCitationResult": { "type": "object", "required": [ "filtered", "detected" ], "properties": { "filtered": { "type": "boolean", "description": "Whether the content was filtered." }, "detected": { "type": "boolean", "description": "Whether the content category was detected." }, "citation": { "allOf": [ { "$ref": "#/components/schemas/AzureContentFilterCitation" } ], "description": "Citation details describing the associated license and its location." } }, "description": "A content filter detection result that includes citation information for protected material." }, "AzureContentFilterDetectionWithReasonResult": { "type": "object", "required": [ "filtered", "detected" ], "properties": { "filtered": { "type": "boolean", "description": "Whether the content was filtered." }, "detected": { "type": "boolean", "description": "Whether the content category was detected." }, "reason": { "type": "string", "description": "A human-readable explanation of why the detection result was produced." } }, "description": "A content filter detection result that includes a reason description." }, "AzureContentFilterError": { "type": "object", "required": [ "code", "message" ], "properties": { "code": { "type": "integer", "format": "int32", "description": "A machine-readable error code." }, "message": { "type": "string", "description": "A human-readable error message." } }, "description": "Error details from the content filtering system." }, "AzureContentFilterPersonallyIdentifiableInformationResult": { "type": "object", "required": [ "filtered", "detected" ], "properties": { "filtered": { "type": "boolean", "description": "Whether the content was filtered." }, "detected": { "type": "boolean", "description": "Whether PII was detected in the content." }, "sub_categories": { "type": "array", "items": { "$ref": "#/components/schemas/AzureContentFilterPiiSubCategoryResult" }, "description": "Detailed results for individual PII subcategories." } }, "description": "A content filter detection result for Personally Identifiable Information." }, "AzureContentFilterPiiSubCategoryResult": { "type": "object", "required": [ "sub_category", "filtered", "detected" ], "properties": { "sub_category": { "type": "string", "description": "The PII subcategory that was evaluated." }, "filtered": { "type": "boolean", "description": "Whether the content was filtered for this subcategory." }, "detected": { "type": "boolean", "description": "Whether the subcategory was detected in the content." } }, "description": "Result details for an individual PII subcategory." }, "AzureContentFilterResultsForResponses": { "type": "object", "properties": { "sexual": { "allOf": [ { "$ref": "#/components/schemas/AzureContentFilterSeverityResult" } ], "description": "Severity result for sexual content." }, "hate": { "allOf": [ { "$ref": "#/components/schemas/AzureContentFilterSeverityResult" } ], "description": "Severity result for hate content." }, "violence": { "allOf": [ { "$ref": "#/components/schemas/AzureContentFilterSeverityResult" } ], "description": "Severity result for violence content." }, "self_harm": { "allOf": [ { "$ref": "#/components/schemas/AzureContentFilterSeverityResult" } ], "description": "Severity result for self-harm content." }, "profanity": { "allOf": [ { "$ref": "#/components/schemas/AzureContentFilterDetectionResult" } ], "description": "Detection result for profanity." }, "custom_blocklists": { "allOf": [ { "$ref": "#/components/schemas/AzureContentFilterBlocklistResult" } ], "description": "Results for configured custom blocklists." }, "jailbreak": { "allOf": [ { "$ref": "#/components/schemas/AzureContentFilterDetectionResult" } ], "description": "Detection result for jailbreak attempts." }, "task_adherence": { "allOf": [ { "$ref": "#/components/schemas/AzureContentFilterDetectionWithReasonResult" } ], "description": "Detection result for task adherence evaluation." }, "protected_material_text": { "allOf": [ { "$ref": "#/components/schemas/AzureContentFilterDetectionResult" } ], "description": "Detection result for protected material text." }, "protected_material_code": { "allOf": [ { "$ref": "#/components/schemas/AzureContentFilterDetectionWithCitationResult" } ], "description": "Detection result for protected material code with citation." }, "ungrounded_material": { "allOf": [ { "$ref": "#/components/schemas/AzureContentFilterCompletionTextSpanDetectionResult" } ], "description": "Detection result for ungrounded material with completion text span details." }, "personally_identifiable_information": { "allOf": [ { "$ref": "#/components/schemas/AzureContentFilterPersonallyIdentifiableInformationResult" } ], "description": "Detection result for Personally Identifiable Information." }, "indirect_attack": { "allOf": [ { "$ref": "#/components/schemas/AzureContentFilterDetectionResult" } ], "description": "Detection result for indirect attacks." }, "error": { "allOf": [ { "$ref": "#/components/schemas/AzureContentFilterError" } ], "description": "Error details if content filtering evaluation failed." } }, "description": "Content filter results for the Responses API." }, "AzureContentFilterSeverity": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "safe", "low", "medium", "high" ] } ], "description": "Ratings for the intensity and risk level of harmful content." }, "AzureContentFilterSeverityResult": { "type": "object", "required": [ "filtered", "severity" ], "properties": { "filtered": { "type": "boolean", "description": "Whether the content was filtered." }, "severity": { "allOf": [ { "$ref": "#/components/schemas/AzureContentFilterSeverity" } ], "description": "The severity level of the content." } }, "description": "A content filter result indicating severity level and whether content was filtered." }, "AzureFunctionBinding": { "type": "object", "required": [ "type", "storage_queue" ], "properties": { "type": { "type": "string", "enum": [ "storage_queue" ], "description": "The type of binding, which is always 'storage_queue'." }, "storage_queue": { "allOf": [ { "$ref": "#/components/schemas/AzureFunctionStorageQueue" } ], "description": "Storage queue." } }, "description": "The structure for keeping storage queue name and URI." }, "AzureFunctionDefinition": { "type": "object", "required": [ "function", "input_binding", "output_binding" ], "properties": { "function": { "type": "object", "properties": { "name": { "type": "string", "description": "The name of the function to be called." }, "description": { "type": "string", "description": "A description of what the function does, used by the model to choose when and how to call the function." }, "parameters": { "type": "object", "additionalProperties": {}, "description": "The parameters the functions accepts, described as a JSON Schema object." } }, "required": [ "name", "parameters" ], "description": "The definition of azure function and its parameters." }, "input_binding": { "allOf": [ { "$ref": "#/components/schemas/AzureFunctionBinding" } ], "description": "Input storage queue. The queue storage trigger runs a function as messages are added to it." }, "output_binding": { "allOf": [ { "$ref": "#/components/schemas/AzureFunctionBinding" } ], "description": "Output storage queue. The function writes output to this queue when the input items are processed." } }, "description": "The definition of Azure function." }, "AzureFunctionStorageQueue": { "type": "object", "required": [ "queue_service_endpoint", "queue_name" ], "properties": { "queue_service_endpoint": { "type": "string", "description": "URI to the Azure Storage Queue service allowing you to manipulate a queue." }, "queue_name": { "type": "string", "description": "The name of an Azure function storage queue." } }, "description": "The structure for keeping storage queue name and URI." }, "AzureFunctionTool": { "type": "object", "required": [ "type", "azure_function" ], "properties": { "type": { "type": "string", "enum": [ "azure_function" ], "description": "The object type, which is always 'browser_automation'." }, "azure_function": { "allOf": [ { "$ref": "#/components/schemas/AzureFunctionDefinition" } ], "description": "The Azure Function Tool definition." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Tool" } ], "description": "The input definition information for an Azure Function Tool, as used to configure an Agent." }, "AzureFunctionToolCall": { "type": "object", "required": [ "type", "call_id", "name", "arguments", "status" ], "properties": { "type": { "type": "string", "enum": [ "azure_function_call" ] }, "call_id": { "type": "string", "description": "The unique ID of the tool call generated by the model." }, "name": { "type": "string", "description": "The name of the Azure Function being called." }, "arguments": { "type": "string", "description": "A JSON string of the arguments to pass to the tool." }, "status": { "allOf": [ { "$ref": "#/components/schemas/ToolCallStatus" } ], "description": "The status of the tool call." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ], "description": "An Azure Function tool call." }, "AzureFunctionToolCallOutput": { "type": "object", "required": [ "type", "call_id", "name", "status" ], "properties": { "type": { "type": "string", "enum": [ "azure_function_call_output" ] }, "call_id": { "type": "string", "description": "The unique ID of the tool call generated by the model." }, "name": { "type": "string", "description": "The name of the Azure Function that was called." }, "output": { "allOf": [ { "$ref": "#/components/schemas/ToolCallOutputContent" } ], "description": "The output from the Azure Function tool call." }, "status": { "allOf": [ { "$ref": "#/components/schemas/ToolCallStatus" } ], "description": "The status of the tool call." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ], "description": "The output of an Azure Function tool call." }, "AzureOpenAIModelConfiguration": { "type": "object", "required": [ "type", "modelDeploymentName" ], "properties": { "type": { "type": "string", "enum": [ "AzureOpenAIModel" ] }, "modelDeploymentName": { "type": "string", "description": "Deployment name for AOAI model. Example: gpt-4o if in AIServices or connection based `connection_name/deployment_name` (e.g. `my-aoai-connection/gpt-4o`)." } }, "allOf": [ { "$ref": "#/components/schemas/TargetConfig" } ], "description": "Azure OpenAI model configuration. The API version would be selected by the service for querying the model." }, "BaseCredentials": { "type": "object", "required": [ "type" ], "properties": { "type": { "allOf": [ { "$ref": "#/components/schemas/CredentialType" } ], "description": "The type of credential used by the connection", "readOnly": true } }, "discriminator": { "propertyName": "type", "mapping": { "ApiKey": "#/components/schemas/ApiKeyCredentials", "AAD": "#/components/schemas/EntraIDCredentials", "CustomKeys": "#/components/schemas/CustomCredential", "SAS": "#/components/schemas/SASCredentials", "None": "#/components/schemas/NoAuthenticationCredentials", "AgenticIdentityToken_Preview": "#/components/schemas/AgenticIdentityPreviewCredentials" } }, "description": "A base class for connection credentials" }, "BaseModelReferenceConfiguration": { "type": "object", "required": [ "kind" ], "properties": { "kind": { "type": "string", "enum": [ "base_model" ], "description": "Reference policy kind, always 'base_model'." } }, "allOf": [ { "$ref": "#/components/schemas/ModelTrainingReferenceConfiguration" } ], "description": "Use the submitted base model as the reference policy." }, "BenchmarkName": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "builtin.gpqa_diamond", "builtin.bbeh", "builtin.bigbenchhard", "builtin.frontierscience", "builtin.musr", "builtin.truthful_qa", "builtin.inspect_ai.gpqa_diamond", "builtin.inspect_ai.chembench", "builtin.inspect_ai.aime_2025", "builtin.inspect_ai.musr" ] } ], "description": "The set of available benchmark specifications." }, "BingCustomSearchConfiguration": { "type": "object", "required": [ "project_connection_id", "instance_name" ], "properties": { "name": { "type": "string", "description": "Optional user-defined name for this tool or configuration." }, "description": { "type": "string", "description": "Optional user-defined description for this tool or configuration." }, "project_connection_id": { "type": "string", "description": "Project connection id for grounding with bing search" }, "instance_name": { "type": "string", "description": "Name of the custom configuration instance given to config." }, "market": { "type": "string", "description": "The market where the results come from." }, "set_lang": { "type": "string", "description": "The language to use for user interface strings when calling Bing API." }, "count": { "type": "integer", "format": "int64", "description": "The number of search results to return in the bing api response" }, "freshness": { "type": "string", "description": "Filter search results by a specific time range. See [accepted values here](https://learn.microsoft.com/bing/search-apis/bing-web-search/reference/query-parameters)." } }, "description": "A bing custom search configuration." }, "BingCustomSearchPreviewTool": { "type": "object", "required": [ "type", "bing_custom_search_preview" ], "properties": { "type": { "type": "string", "enum": [ "bing_custom_search_preview" ], "description": "The object type, which is always 'bing_custom_search_preview'." }, "name": { "type": "string", "description": "Optional user-defined name for this tool or configuration." }, "description": { "type": "string", "description": "Optional user-defined description for this tool or configuration." }, "bing_custom_search_preview": { "allOf": [ { "$ref": "#/components/schemas/BingCustomSearchToolParameters" } ], "description": "The bing custom search tool parameters." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Tool" } ], "description": "The input definition information for a Bing custom search tool as used to configure an agent." }, "BingCustomSearchToolCall": { "type": "object", "required": [ "type", "call_id", "arguments", "status" ], "properties": { "type": { "type": "string", "enum": [ "bing_custom_search_preview_call" ] }, "call_id": { "type": "string", "description": "The unique ID of the tool call generated by the model." }, "arguments": { "type": "string", "description": "A JSON string of the arguments to pass to the tool." }, "status": { "allOf": [ { "$ref": "#/components/schemas/ToolCallStatus" } ], "description": "The status of the tool call." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ], "description": "A Bing custom search tool call." }, "BingCustomSearchToolCallOutput": { "type": "object", "required": [ "type", "call_id", "status" ], "properties": { "type": { "type": "string", "enum": [ "bing_custom_search_preview_call_output" ] }, "call_id": { "type": "string", "description": "The unique ID of the tool call generated by the model." }, "output": { "allOf": [ { "$ref": "#/components/schemas/ToolCallOutputContent" } ], "description": "The output from the Bing custom search tool call." }, "status": { "allOf": [ { "$ref": "#/components/schemas/ToolCallStatus" } ], "description": "The status of the tool call." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ], "description": "The output of a Bing custom search tool call." }, "BingCustomSearchToolParameters": { "type": "object", "required": [ "search_configurations" ], "properties": { "name": { "type": "string", "description": "Optional user-defined name for this tool or configuration." }, "description": { "type": "string", "description": "Optional user-defined description for this tool or configuration." }, "search_configurations": { "type": "array", "items": { "$ref": "#/components/schemas/BingCustomSearchConfiguration" }, "maxItems": 1, "description": "The project connections attached to this tool. There can be a maximum of 1 connection\nresource attached to the tool." } }, "description": "The bing custom search tool parameters." }, "BingGroundingSearchConfiguration": { "type": "object", "required": [ "project_connection_id" ], "properties": { "name": { "type": "string", "description": "Optional user-defined name for this tool or configuration." }, "description": { "type": "string", "description": "Optional user-defined description for this tool or configuration." }, "project_connection_id": { "type": "string", "description": "Project connection id for grounding with bing search" }, "market": { "type": "string", "description": "The market where the results come from." }, "set_lang": { "type": "string", "description": "The language to use for user interface strings when calling Bing API." }, "count": { "type": "integer", "format": "int64", "description": "The number of search results to return in the bing api response" }, "freshness": { "type": "string", "description": "Filter search results by a specific time range. See [accepted values here](https://learn.microsoft.com/bing/search-apis/bing-web-search/reference/query-parameters)." } }, "description": "Search configuration for Bing Grounding" }, "BingGroundingSearchToolParameters": { "type": "object", "required": [ "search_configurations" ], "properties": { "name": { "type": "string", "description": "Optional user-defined name for this tool or configuration." }, "description": { "type": "string", "description": "Optional user-defined description for this tool or configuration." }, "search_configurations": { "type": "array", "items": { "$ref": "#/components/schemas/BingGroundingSearchConfiguration" }, "maxItems": 1, "description": "The search configurations attached to this tool. There can be a maximum of 1\nsearch configuration resource attached to the tool." } }, "description": "The bing grounding search tool parameters." }, "BingGroundingTool": { "type": "object", "required": [ "type", "bing_grounding" ], "properties": { "type": { "type": "string", "enum": [ "bing_grounding" ], "description": "The object type, which is always 'bing_grounding'." }, "name": { "type": "string", "description": "Optional user-defined name for this tool or configuration." }, "description": { "type": "string", "description": "Optional user-defined description for this tool or configuration." }, "bing_grounding": { "allOf": [ { "$ref": "#/components/schemas/BingGroundingSearchToolParameters" } ], "description": "The bing grounding search tool parameters." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Tool" } ], "description": "The input definition information for a bing grounding search tool as used to configure an agent." }, "BingGroundingToolCall": { "type": "object", "required": [ "type", "call_id", "arguments", "status" ], "properties": { "type": { "type": "string", "enum": [ "bing_grounding_call" ] }, "call_id": { "type": "string", "description": "The unique ID of the tool call generated by the model." }, "arguments": { "type": "string", "description": "A JSON string of the arguments to pass to the tool." }, "status": { "allOf": [ { "$ref": "#/components/schemas/ToolCallStatus" } ], "description": "The status of the tool call." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ], "description": "A Bing grounding tool call." }, "BingGroundingToolCallOutput": { "type": "object", "required": [ "type", "call_id", "status" ], "properties": { "type": { "type": "string", "enum": [ "bing_grounding_call_output" ] }, "call_id": { "type": "string", "description": "The unique ID of the tool call generated by the model." }, "output": { "allOf": [ { "$ref": "#/components/schemas/ToolCallOutputContent" } ], "description": "The output from the Bing grounding tool call." }, "status": { "allOf": [ { "$ref": "#/components/schemas/ToolCallStatus" } ], "description": "The status of the tool call." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ], "description": "The output of a Bing grounding tool call." }, "BlobReference": { "type": "object", "required": [ "blobUri", "storageAccountArmId", "credential" ], "properties": { "blobUri": { "type": "string", "format": "uri", "description": "Blob URI path for client to upload data. Example: `https://blob.windows.core.net/Container/Path`" }, "storageAccountArmId": { "type": "string", "description": "ARM ID of the storage account to use." }, "credential": { "allOf": [ { "$ref": "#/components/schemas/SasCredential" } ], "description": "Credential info to access the storage account." } }, "description": "Blob reference details." }, "BrowserAutomationPreviewTool": { "type": "object", "required": [ "type", "browser_automation_preview" ], "properties": { "type": { "type": "string", "enum": [ "browser_automation_preview" ], "description": "The object type, which is always 'browser_automation_preview'." }, "name": { "type": "string", "description": "Optional user-defined name for this tool or configuration." }, "description": { "type": "string", "description": "Optional user-defined description for this tool or configuration." }, "browser_automation_preview": { "allOf": [ { "$ref": "#/components/schemas/BrowserAutomationToolParameters" } ], "description": "The Browser Automation Tool parameters." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Tool" } ], "description": "The input definition information for a Browser Automation Tool, as used to configure an Agent." }, "BrowserAutomationToolCall": { "type": "object", "required": [ "type", "call_id", "arguments", "status" ], "properties": { "type": { "type": "string", "enum": [ "browser_automation_preview_call" ] }, "call_id": { "type": "string", "description": "The unique ID of the tool call generated by the model." }, "arguments": { "type": "string", "description": "A JSON string of the arguments to pass to the tool." }, "status": { "allOf": [ { "$ref": "#/components/schemas/ToolCallStatus" } ], "description": "The status of the tool call." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ], "description": "A browser automation tool call." }, "BrowserAutomationToolCallOutput": { "type": "object", "required": [ "type", "call_id", "status" ], "properties": { "type": { "type": "string", "enum": [ "browser_automation_preview_call_output" ] }, "call_id": { "type": "string", "description": "The unique ID of the tool call generated by the model." }, "output": { "allOf": [ { "$ref": "#/components/schemas/ToolCallOutputContent" } ], "description": "The output from the browser automation tool call." }, "status": { "allOf": [ { "$ref": "#/components/schemas/ToolCallStatus" } ], "description": "The status of the tool call." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ], "description": "The output of a browser automation tool call." }, "BrowserAutomationToolConnectionParameters": { "type": "object", "required": [ "project_connection_id" ], "properties": { "name": { "type": "string", "description": "Optional user-defined name for this tool or configuration." }, "description": { "type": "string", "description": "Optional user-defined description for this tool or configuration." }, "project_connection_id": { "type": "string", "description": "The ID of the project connection to your Azure Playwright resource." } }, "description": "Definition of input parameters for the connection used by the Browser Automation Tool." }, "BrowserAutomationToolParameters": { "type": "object", "required": [ "connection" ], "properties": { "name": { "type": "string", "description": "Optional user-defined name for this tool or configuration." }, "description": { "type": "string", "description": "Optional user-defined description for this tool or configuration." }, "connection": { "allOf": [ { "$ref": "#/components/schemas/BrowserAutomationToolConnectionParameters" } ], "description": "The project connection parameters associated with the Browser Automation Tool." } }, "description": "Definition of input parameters for the Browser Automation Tool." }, "CaptureStructuredOutputsTool": { "type": "object", "required": [ "type", "outputs" ], "properties": { "type": { "type": "string", "enum": [ "capture_structured_outputs" ], "description": "The type of the tool. Always `capture_structured_outputs`." }, "outputs": { "allOf": [ { "$ref": "#/components/schemas/StructuredOutputDefinition" } ], "description": "The structured outputs to capture from the model." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Tool" } ], "description": "A tool for capturing structured outputs" }, "ChartCoordinate": { "type": "object", "required": [ "x", "y", "size" ], "properties": { "x": { "type": "integer", "format": "int32", "description": "X-axis coordinate." }, "y": { "type": "integer", "format": "int32", "description": "Y-axis coordinate." }, "size": { "type": "integer", "format": "int32", "description": "Size of the chart element." } }, "description": "Coordinates for the analysis chart." }, "ChatSummaryMemoryItem": { "type": "object", "required": [ "kind" ], "properties": { "kind": { "type": "string", "enum": [ "chat_summary" ], "description": "The kind of the memory item." } }, "allOf": [ { "$ref": "#/components/schemas/MemoryItem" } ], "description": "A memory item containing a summary extracted from conversations.", "x-ms-foundry-meta": { "conditional_previews": [ "MemoryStores=V1Preview" ] } }, "ChatTemplate": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "chatml", "llama_3", "zephyr", "gemma", "phi_3" ] } ], "description": "Chat template used to format conversational training data." }, "ClusterInsightResult": { "type": "object", "required": [ "summary", "clusters" ], "properties": { "summary": { "allOf": [ { "$ref": "#/components/schemas/InsightSummary" } ], "description": "Summary of the insights report." }, "clusters": { "type": "array", "items": { "$ref": "#/components/schemas/InsightCluster" }, "description": "List of clusters identified in the insights." }, "coordinates": { "type": "object", "additionalProperties": { "$ref": "#/components/schemas/ChartCoordinate" }, "description": " Optional mapping of IDs to 2D coordinates used by the UX for visualization.\n\n The map keys are string identifiers (for example, a cluster id or a sample id)\n and the values are the coordinates and visual size for rendering on a 2D chart.\n\n This property is omitted unless the client requests coordinates (for example,\n by passing `includeCoordinates=true` as a query parameter).\n\n Example:\n ```\n {\n \"cluster-1\": { \"x\": 12, \"y\": 34, \"size\": 8 },\n \"sample-123\": { \"x\": 18, \"y\": 22, \"size\": 4 }\n }\n ```\n\n Coordinates are intended only for client-side visualization and do not\n modify the canonical insights results." } }, "description": "Insights from the cluster analysis." }, "ClusterTokenUsage": { "type": "object", "required": [ "inputTokenUsage", "outputTokenUsage", "totalTokenUsage" ], "properties": { "inputTokenUsage": { "type": "integer", "format": "int32", "description": "input token usage" }, "outputTokenUsage": { "type": "integer", "format": "int32", "description": "output token usage" }, "totalTokenUsage": { "type": "integer", "format": "int32", "description": "total token usage" } }, "description": "Token usage for cluster analysis" }, "CodeBasedEvaluatorDefinition": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "code" ] }, "code_text": { "type": "string", "description": "Inline code text for the evaluator" }, "entry_point": { "type": "string", "description": "The entry point Python file name for the uploaded evaluator code (e.g. 'answer_length_evaluator.py')" }, "image_tag": { "type": "string", "description": "The container image tag to use for evaluator code execution" }, "blob_uri": { "type": "string", "description": "The blob URI for the evaluator storage" } }, "allOf": [ { "$ref": "#/components/schemas/EvaluatorDefinition" } ], "description": "Code-based evaluator definition using python code" }, "CommandJob": { "type": "object", "required": [ "job_type", "compute_id" ], "properties": { "job_type": { "type": "string", "enum": [ "command" ], "description": "Job type." }, "command": { "type": "string", "description": "The command to execute on startup of the job. Required when training is not specified, and must be omitted when training is specified." }, "environment_image_reference": { "type": "string", "description": "ACR path or Azure ML environment reference. Required when training is not specified." }, "training": { "allOf": [ { "$ref": "#/components/schemas/TrainingConfiguration" } ], "description": "Declarative training recipe. When specified, the service compiles the recipe into the command and environment used for execution." }, "display_name": { "type": "string", "description": "Display name of job." }, "description": { "type": "string", "description": "The asset description text." }, "tags": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Tag dictionary. Tags can be added, removed, and updated." }, "properties": { "type": "object", "additionalProperties": { "type": "string" }, "description": "The asset property dictionary." }, "code_id": { "type": "string", "description": "Code asset reference." }, "compute_id": { "type": "string", "description": "Compute resource ID." }, "inputs": { "type": "object", "additionalProperties": { "$ref": "#/components/schemas/Input" }, "description": "Mapping of input data bindings used in the job." }, "outputs": { "type": "object", "additionalProperties": { "$ref": "#/components/schemas/Output" }, "description": "Mapping of output data bindings used in the job." }, "environment_variables": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Environment variables included in the job." }, "resources": { "allOf": [ { "$ref": "#/components/schemas/JobResourceConfiguration" } ], "description": "Compute Resource configuration for the job." }, "gpu_count": { "type": "integer", "format": "int32", "description": "Number of GPUs requested by the training job." }, "distribution": { "allOf": [ { "$ref": "#/components/schemas/DistributionConfiguration" } ], "description": "Distribution configuration of the job. If set, this should be one of Mpi, Tensorflow, PyTorch, or null." }, "limits": { "allOf": [ { "$ref": "#/components/schemas/CommandJobLimits" } ], "description": "Command Job limit." }, "queue_settings": { "allOf": [ { "$ref": "#/components/schemas/QueueSettings" } ], "description": "Queue settings for the job." }, "user_assigned_identity_id": { "type": "string", "description": "user-assigned managed identity" }, "status": { "type": "string", "description": "Status of the job.", "readOnly": true } }, "allOf": [ { "$ref": "#/components/schemas/JobProperties" } ], "description": "Properties of a Command Job." }, "CommandJobLimits": { "type": "object", "required": [ "job_limits_type" ], "properties": { "job_limits_type": { "type": "string", "enum": [ "command" ], "description": "JobLimit type." }, "timeout": { "type": "string", "format": "duration", "description": "The max run duration in ISO 8601 format, after which the job will be cancelled. Only supports duration with precision as low as Seconds." } }, "description": "Command Job limit class." }, "CompletionMessageToolCallChunk": { "type": "object", "required": [ "id", "type" ], "properties": { "id": { "type": "string", "description": "The Id for the tool call." }, "type": { "type": "string", "enum": [ "function" ], "description": "The type of tool call, which is always \"function\"." }, "function": { "allOf": [ { "$ref": "#/components/schemas/FunctionToolCall" } ], "description": "Details of the function tool call, if applicable." } }, "description": "Tool call details within a message." }, "Connection": { "type": "object", "required": [ "name", "id", "type", "target", "isDefault", "credentials", "metadata" ], "properties": { "name": { "type": "string", "description": "The friendly name of the connection, provided by the user.", "readOnly": true }, "id": { "type": "string", "description": "A unique identifier for the connection, generated by the service", "readOnly": true }, "type": { "allOf": [ { "$ref": "#/components/schemas/ConnectionType" } ], "description": "Category of the connection", "readOnly": true }, "target": { "type": "string", "description": "The connection URL to be used for this service", "readOnly": true }, "isDefault": { "type": "boolean", "description": "Whether the connection is tagged as the default connection of its type", "readOnly": true }, "credentials": { "allOf": [ { "$ref": "#/components/schemas/BaseCredentials" } ], "description": "The credentials used by the connection", "readOnly": true }, "metadata": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Metadata of the connection", "readOnly": true } }, "description": "Response from the list and get connections operations" }, "ConnectionType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "AzureOpenAI", "AzureBlob", "AzureStorageAccount", "CognitiveSearch", "CosmosDB", "ApiKey", "AppConfig", "AppInsights", "CustomKeys", "RemoteTool_Preview" ] } ], "description": "The Type (or category) of the connection" }, "ContentFilterResult": { "type": "object", "required": [ "blocked", "source_type", "content_filter_results" ], "properties": { "blocked": { "type": "boolean", "description": "Whether the content was blocked by the content filter." }, "source_type": { "type": "string", "description": "The source type of the content filter evaluation (e.g., 'prompt', 'response', 'pre_tool_call', 'post_tool_call')." }, "content_filter_results": { "allOf": [ { "$ref": "#/components/schemas/AzureContentFilterResultsForResponses" } ], "description": "The content filter results for this evaluation." }, "tool_call_id": { "type": "string", "description": "The ID of the tool call associated with this content filter result, if applicable." } }, "description": "A content filter evaluation result for a specific source in the response." }, "ContinuousEvaluationRuleAction": { "type": "object", "required": [ "type", "evalId" ], "properties": { "type": { "type": "string", "enum": [ "continuousEvaluation" ] }, "evalId": { "type": "string", "description": "Eval Id to add continuous evaluation runs to." }, "maxHourlyRuns": { "type": "integer", "format": "int32", "description": "Maximum number of evaluation runs allowed per hour." } }, "allOf": [ { "$ref": "#/components/schemas/EvaluationRuleAction" } ], "description": "Evaluation rule action for continuous evaluation." }, "CosmosDBIndex": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "CosmosDBNoSqlVectorStore" ], "description": "Type of index" } }, "allOf": [ { "$ref": "#/components/schemas/Index" } ], "description": "CosmosDB Vector Store Index Definition" }, "CosmosDBIndexUpdate": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "CosmosDBNoSqlVectorStore" ], "description": "Type of index" } }, "allOf": [ { "$ref": "#/components/schemas/IndexUpdate" } ], "description": "CosmosDB Vector Store Index Definition" }, "CpoTrainingConfiguration": { "type": "object", "required": [ "algorithm" ], "properties": { "algorithm": { "type": "string", "enum": [ "cpo" ], "description": "Training algorithm, always 'cpo'." }, "lora": { "allOf": [ { "$ref": "#/components/schemas/TrainingLoraConfiguration" } ], "description": "LoRA adapter configuration." }, "eval": { "allOf": [ { "$ref": "#/components/schemas/TrainingEvalConfiguration" } ], "description": "Evaluation configuration." } }, "allOf": [ { "$ref": "#/components/schemas/TrainingConfiguration" } ], "description": "Contrastive preference optimization training recipe." }, "CreateAgentFromManifestRequest": { "type": "object", "required": [ "name", "manifest_id", "parameter_values" ], "properties": { "name": { "type": "string", "maxLength": 63, "description": "The unique name that identifies the agent. Name can be used to retrieve/update/delete the agent.\n- Must start and end with alphanumeric characters,\n- Can contain hyphens in the middle\n- Must not exceed 63 characters." }, "metadata": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Set of 16 key-value pairs that can be attached to an object. This can be\nuseful for storing additional information about the object in a structured\nformat, and querying for objects via API or the dashboard.\n\nKeys are strings with a maximum length of 64 characters. Values are strings\nwith a maximum length of 512 characters.", "x-oaiTypeLabel": "map" }, "description": { "type": "string", "maxLength": 512, "description": "A human-readable description of the agent." }, "manifest_id": { "type": "string", "description": "The manifest ID to import the agent version from." }, "parameter_values": { "type": "object", "additionalProperties": {}, "description": "The inputs to the manifest that will result in a fully materialized Agent." } } }, "CreateAgentRequest": { "type": "object", "required": [ "name", "definition" ], "properties": { "name": { "type": "string", "maxLength": 63, "description": "The unique name that identifies the agent. Name can be used to retrieve/update/delete the agent.\n- Must start and end with alphanumeric characters,\n- Can contain hyphens in the middle\n- Must not exceed 63 characters." }, "metadata": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Set of 16 key-value pairs that can be attached to an object. This can be\nuseful for storing additional information about the object in a structured\nformat, and querying for objects via API or the dashboard.\n\nKeys are strings with a maximum length of 64 characters. Values are strings\nwith a maximum length of 512 characters.", "x-oaiTypeLabel": "map" }, "description": { "type": "string", "maxLength": 512, "description": "A human-readable description of the agent." }, "definition": { "allOf": [ { "$ref": "#/components/schemas/AgentDefinition" } ], "description": "The agent definition. This can be a workflow, hosted agent, or a simple agent definition.", "x-ms-foundry-meta": { "conditional_previews": [ "HostedAgents=V1Preview", "ContainerAgents=V1Preview", "WorkflowAgents=V1Preview" ] } } }, "x-ms-foundry-meta": { "conditional_previews": [ "HostedAgents=V1Preview", "ContainerAgents=V1Preview", "WorkflowAgents=V1Preview" ] } }, "CreateAgentVersionFromManifestRequest": { "type": "object", "required": [ "manifest_id", "parameter_values" ], "properties": { "metadata": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Set of 16 key-value pairs that can be attached to an object. This can be\nuseful for storing additional information about the object in a structured\nformat, and querying for objects via API or the dashboard.\n\nKeys are strings with a maximum length of 64 characters. Values are strings\nwith a maximum length of 512 characters.", "x-oaiTypeLabel": "map" }, "description": { "type": "string", "maxLength": 512, "description": "A human-readable description of the agent." }, "manifest_id": { "type": "string", "description": "The manifest ID to import the agent version from." }, "parameter_values": { "type": "object", "additionalProperties": {}, "description": "The inputs to the manifest that will result in a fully materialized Agent." } } }, "CreateAgentVersionRequest": { "type": "object", "required": [ "definition" ], "properties": { "metadata": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Set of 16 key-value pairs that can be attached to an object. This can be\nuseful for storing additional information about the object in a structured\nformat, and querying for objects via API or the dashboard.\n\nKeys are strings with a maximum length of 64 characters. Values are strings\nwith a maximum length of 512 characters.", "x-oaiTypeLabel": "map" }, "description": { "type": "string", "maxLength": 512, "description": "A human-readable description of the agent." }, "definition": { "allOf": [ { "$ref": "#/components/schemas/AgentDefinition" } ], "description": "The agent definition. This can be a workflow, hosted agent, or a simple agent definition.", "x-ms-foundry-meta": { "conditional_previews": [ "HostedAgents=V1Preview", "ContainerAgents=V1Preview", "WorkflowAgents=V1Preview" ] } } }, "x-ms-foundry-meta": { "conditional_previews": [ "HostedAgents=V1Preview", "ContainerAgents=V1Preview", "WorkflowAgents=V1Preview" ] } }, "CreateEvalRequest": { "type": "object", "required": [ "data_source_config", "testing_criteria" ], "properties": { "name": { "type": "string", "description": "The name of the evaluation." }, "metadata": { "type": "object", "allOf": [ { "$ref": "#/components/schemas/OpenAI.Metadata" } ], "nullable": true }, "data_source_config": { "oneOf": [ { "$ref": "#/components/schemas/OpenAI.CreateEvalCustomDataSourceConfig" }, { "$ref": "#/components/schemas/OpenAI.CreateEvalLogsDataSourceConfig" }, { "$ref": "#/components/schemas/OpenAI.CreateEvalStoredCompletionsDataSourceConfig" }, { "$ref": "#/components/schemas/AzureAIDataSourceConfig" }, { "$ref": "#/components/schemas/AzureAIBenchmarkDataSourceConfig" } ], "description": "The configuration for the data source used for the evaluation runs. Dictates the schema of the data used in the evaluation." }, "testing_criteria": { "type": "array", "items": { "anyOf": [ { "$ref": "#/components/schemas/OpenAI.EvalGraderLabelModel" }, { "$ref": "#/components/schemas/OpenAI.EvalGraderStringCheck" }, { "$ref": "#/components/schemas/OpenAI.EvalGraderTextSimilarity" }, { "$ref": "#/components/schemas/OpenAI.EvalGraderPython" }, { "$ref": "#/components/schemas/OpenAI.EvalGraderScoreModel" }, { "$ref": "#/components/schemas/EvalGraderAzureAIEvaluator" }, { "$ref": "#/components/schemas/EvalGraderInspectAI" } ] }, "description": "A list of graders for all eval runs in this group. Graders can reference variables in the data source using double curly braces notation, like `{{item.variable_name}}`. To reference the model's output, use the `sample` namespace (ie, `{{sample.output_text}}`)." }, "properties": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Set of immutable 16 key-value pairs that can be attached to an object for storing additional information.\n Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters." } }, "title": "CreateEvalRequest" }, "CreateEvalRunRequest": { "type": "object", "required": [ "data_source" ], "properties": { "name": { "type": "string", "description": "The name of the run." }, "metadata": { "type": "object", "allOf": [ { "$ref": "#/components/schemas/OpenAI.Metadata" } ], "nullable": true }, "data_source": { "oneOf": [ { "$ref": "#/components/schemas/OpenAI.CreateEvalJsonlRunDataSource" }, { "$ref": "#/components/schemas/OpenAI.CreateEvalCompletionsRunDataSource" }, { "$ref": "#/components/schemas/OpenAI.CreateEvalResponsesRunDataSource" }, { "$ref": "#/components/schemas/EvalRunDataSource" } ], "description": "Details about the run's data source." }, "properties": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Set of immutable 16 key-value pairs that can be attached to an object for storing additional information.\n Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters." } }, "title": "CreateEvalRunRequest" }, "CredentialType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "ApiKey", "AAD", "SAS", "CustomKeys", "None", "AgenticIdentityToken_Preview" ] } ], "description": "The credential type used by the connection" }, "CronTrigger": { "type": "object", "required": [ "type", "expression" ], "properties": { "type": { "type": "string", "enum": [ "Cron" ] }, "expression": { "type": "string", "description": "Cron expression that defines the schedule frequency." }, "timeZone": { "type": "string", "description": "Time zone for the cron schedule.", "default": "UTC" }, "startTime": { "type": "string", "description": "Start time for the cron schedule in ISO 8601 format." }, "endTime": { "type": "string", "description": "End time for the cron schedule in ISO 8601 format." } }, "allOf": [ { "$ref": "#/components/schemas/Trigger" } ], "description": "Cron based trigger." }, "CustomCredential": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "CustomKeys" ], "description": "The credential type", "readOnly": true } }, "additionalProperties": { "type": "string" }, "allOf": [ { "$ref": "#/components/schemas/BaseCredentials" } ], "description": "Custom credential definition" }, "DailyRecurrenceSchedule": { "type": "object", "required": [ "type", "hours" ], "properties": { "type": { "type": "string", "enum": [ "Daily" ], "description": "Daily recurrence type." }, "hours": { "type": "array", "items": { "type": "integer", "format": "int32" }, "description": "Hours for the recurrence schedule." } }, "allOf": [ { "$ref": "#/components/schemas/RecurrenceSchedule" } ], "description": "Daily recurrence schedule." }, "DataSourceConfig": { "type": "object", "required": [ "type", "schema" ], "properties": { "type": { "type": "string", "description": "The data source type discriminator." }, "schema": { "type": "object", "additionalProperties": {}, "description": "The overall object JSON schema for the run data source items." } }, "discriminator": { "propertyName": "type", "mapping": {} }, "description": "Base class for run data sources with discriminator support." }, "DatasetType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "uri_file", "uri_folder" ] } ], "description": "Enum to determine the type of data." }, "DatasetVersion": { "type": "object", "required": [ "dataUri", "type", "name", "version" ], "properties": { "dataUri": { "type": "string", "minLength": 1, "pattern": "[a-zA-Z0-9_]", "description": "URI of the data ([example](https://go.microsoft.com/fwlink/?linkid=2202330))" }, "type": { "allOf": [ { "$ref": "#/components/schemas/DatasetType" } ], "description": "Dataset type" }, "isReference": { "type": "boolean", "description": "Indicates if the dataset holds a reference to the storage, or the dataset manages storage itself. If true, the underlying data will not be deleted when the dataset version is deleted", "readOnly": true }, "connectionName": { "type": "string", "description": "The Azure Storage Account connection name. Required if startPendingUploadVersion was not called before creating the Dataset" }, "id": { "type": "string", "description": "Asset ID, a unique identifier for the asset", "readOnly": true }, "name": { "type": "string", "description": "The name of the resource", "readOnly": true }, "version": { "type": "string", "description": "The version of the resource", "readOnly": true } }, "discriminator": { "propertyName": "type", "mapping": { "uri_file": "#/components/schemas/FileDatasetVersion", "uri_folder": "#/components/schemas/FolderDatasetVersion" } }, "description": "DatasetVersion Definition" }, "DatasetVersionUpdate": { "type": "object", "required": [ "type" ], "properties": { "type": { "allOf": [ { "$ref": "#/components/schemas/DatasetType" } ], "description": "Dataset type" }, "description": { "type": "string", "description": "The asset description text." }, "tags": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Tag dictionary. Tags can be added, removed, and updated." } }, "discriminator": { "propertyName": "type", "mapping": { "uri_file": "#/components/schemas/FileDatasetVersionUpdate", "uri_folder": "#/components/schemas/FolderDatasetVersionUpdate" } }, "description": "DatasetVersion Definition" }, "DayOfWeek": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "Sunday", "Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday" ] } ], "description": "Days of the week for recurrence schedule." }, "DeleteAgentResponse": { "type": "object", "required": [ "object", "name", "deleted" ], "properties": { "object": { "type": "string", "enum": [ "agent.deleted" ], "description": "The object type. Always 'agent.deleted'." }, "name": { "type": "string", "description": "The name of the agent." }, "deleted": { "type": "boolean", "description": "Whether the agent was successfully deleted." } }, "description": "A deleted agent Object" }, "DeleteAgentVersionResponse": { "type": "object", "required": [ "object", "name", "version", "deleted" ], "properties": { "object": { "type": "string", "enum": [ "agent.version.deleted" ], "description": "The object type. Always 'agent.version.deleted'." }, "name": { "type": "string", "description": "The name of the agent." }, "version": { "type": "string", "description": "The version identifier of the agent." }, "deleted": { "type": "boolean", "description": "Whether the agent was successfully deleted." } }, "description": "A deleted agent version Object" }, "DeleteEvalResponse": { "type": "object", "required": [ "object", "eval_id", "deleted" ], "properties": { "object": { "type": "string", "enum": [ "eval.deleted" ], "description": "The object type. Always 'eval.deleted'." }, "eval_id": { "type": "string", "description": "id of the eval." }, "deleted": { "type": "boolean", "description": "Whether the eval was successfully deleted." } }, "description": "A deleted evaluation Object" }, "DeleteEvalRunResponse": { "type": "object", "properties": { "object": { "type": "string", "enum": [ "eval.deleted" ], "description": "The object type. Always 'eval.deleted'." }, "run_id": { "type": "string", "description": "id of the eval." }, "deleted": { "type": "boolean", "description": "Whether the eval was successfully deleted." } }, "description": "A deleted evaluation run Object." }, "DeleteMemoryStoreResponse": { "type": "object", "required": [ "object", "name", "deleted" ], "properties": { "object": { "type": "string", "enum": [ "memory_store.deleted" ], "description": "The object type. Always 'memory_store.deleted'." }, "name": { "type": "string", "description": "The name of the memory store." }, "deleted": { "type": "boolean", "description": "Whether the memory store was successfully deleted." } }, "x-ms-foundry-meta": { "conditional_previews": [ "MemoryStores=V1Preview" ] } }, "DeleteResponseResult": { "type": "object", "required": [ "id", "object", "deleted" ], "properties": { "id": { "type": "string", "description": "The operation ID." }, "object": { "type": "string", "enum": [ "response" ], "description": "Always return 'response'." }, "deleted": { "type": "boolean", "enum": [ true ], "description": "Always return true" } }, "description": "The result of a delete response operation." }, "DeleteSkillResponse": { "type": "object", "required": [ "object", "name", "deleted" ], "properties": { "object": { "allOf": [ { "$ref": "#/components/schemas/SkillObjectType" } ], "description": "The object type. Always 'skill.deleted'.", "default": "skill.deleted" }, "name": { "type": "string", "description": "The unique name of the skill." }, "deleted": { "type": "boolean", "description": "Whether the skill was successfully deleted." } }, "description": "A deleted skill Object" }, "DeleteToolsetResponse": { "type": "object", "required": [ "object", "name", "deleted" ], "properties": { "object": { "type": "string", "enum": [ "toolset.deleted" ], "description": "The object type. Always 'toolset.deleted'." }, "name": { "type": "string", "description": "The name of the toolset." }, "deleted": { "type": "boolean", "description": "Whether the toolset was successfully deleted." } }, "description": "Response returned when a toolset is deleted." }, "Deployment": { "type": "object", "required": [ "type", "name" ], "properties": { "type": { "allOf": [ { "$ref": "#/components/schemas/DeploymentType" } ], "description": "The type of the deployment" }, "name": { "type": "string", "description": "Name of the deployment", "readOnly": true } }, "discriminator": { "propertyName": "type", "mapping": { "ModelDeployment": "#/components/schemas/ModelDeployment" } }, "description": "Model Deployment Definition" }, "DeploymentType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "ModelDeployment" ] } ] }, "DistributionConfiguration": { "type": "object", "required": [ "distribution_type" ], "properties": { "distribution_type": { "type": "string", "description": "Specifies the type of distribution framework." } }, "discriminator": { "propertyName": "distribution_type", "mapping": { "pytorch": "#/components/schemas/PyTorchDistribution", "mpi": "#/components/schemas/MpiDistribution", "tensorflow": "#/components/schemas/TensorFlowDistribution", "ray": "#/components/schemas/RayDistribution" } }, "description": "Distribution configuration of the job. If set, this should be one of Mpi, Tensorflow, PyTorch, Ray, or null." }, "DpoTrainingConfiguration": { "type": "object", "required": [ "algorithm" ], "properties": { "algorithm": { "type": "string", "enum": [ "dpo" ], "description": "Training algorithm, always 'dpo'." }, "lora": { "allOf": [ { "$ref": "#/components/schemas/TrainingLoraConfiguration" } ], "description": "LoRA adapter configuration." }, "eval": { "allOf": [ { "$ref": "#/components/schemas/TrainingEvalConfiguration" } ], "description": "Evaluation configuration." } }, "allOf": [ { "$ref": "#/components/schemas/TrainingConfiguration" } ], "description": "Direct preference optimization training recipe." }, "EntraIDCredentials": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "AAD" ], "description": "The credential type", "readOnly": true } }, "allOf": [ { "$ref": "#/components/schemas/BaseCredentials" } ], "description": "Entra ID credential definition" }, "Eval": { "type": "object", "required": [ "object", "id", "name", "data_source_config", "testing_criteria", "created_at", "metadata" ], "properties": { "object": { "type": "string", "enum": [ "eval" ], "description": "The object type.", "x-stainless-const": true, "default": "eval" }, "id": { "type": "string", "description": "Unique identifier for the evaluation." }, "name": { "type": "string", "description": "The name of the evaluation." }, "data_source_config": { "oneOf": [ { "$ref": "#/components/schemas/OpenAI.CreateEvalCustomDataSourceConfig" }, { "$ref": "#/components/schemas/OpenAI.CreateEvalLogsDataSourceConfig" }, { "$ref": "#/components/schemas/OpenAI.CreateEvalStoredCompletionsDataSourceConfig" }, { "$ref": "#/components/schemas/AzureAIDataSourceConfig" }, { "$ref": "#/components/schemas/AzureAIBenchmarkDataSourceConfig" } ], "description": "Configuration of data sources used in runs of the evaluation." }, "testing_criteria": { "type": "array", "items": { "anyOf": [ { "$ref": "#/components/schemas/OpenAI.EvalGraderLabelModel" }, { "$ref": "#/components/schemas/OpenAI.EvalGraderStringCheck" }, { "$ref": "#/components/schemas/OpenAI.EvalGraderTextSimilarity" }, { "$ref": "#/components/schemas/OpenAI.EvalGraderPython" }, { "$ref": "#/components/schemas/OpenAI.EvalGraderScoreModel" }, { "$ref": "#/components/schemas/EvalGraderAzureAIEvaluator" }, { "$ref": "#/components/schemas/EvalGraderInspectAI" } ] }, "description": "A list of testing criteria." }, "created_at": { "type": "integer", "format": "unixtime", "description": "The Unix timestamp (in seconds) for when the eval was created." }, "metadata": { "type": "object", "allOf": [ { "$ref": "#/components/schemas/OpenAI.Metadata" } ], "nullable": true }, "modified_at": { "allOf": [ { "$ref": "#/components/schemas/integer" } ], "description": "Unix timestamp (in seconds) when the evaluation run was last modified." }, "created_by": { "type": "string", "description": "the name of the person who created the run." }, "properties": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Set of immutable 16 key-value pairs that can be attached to an object for storing additional information.\n Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters." } }, "description": "An Eval object with a data source config and testing criteria.\nAn Eval represents a task to be done for your LLM integration.\nLike:\n- Improve the quality of my chatbot\n- See how well my chatbot handles customer support\n- Check if o4-mini is better at my usecase than gpt-4o", "title": "Eval", "x-oaiMeta": { "name": "The eval object", "group": "evals", "example": "{\n \"object\": \"eval\",\n \"id\": \"eval_67abd54d9b0081909a86353f6fb9317a\",\n \"data_source_config\": {\n \"type\": \"custom\",\n \"item_schema\": {\n \"type\": \"object\",\n \"properties\": {\n \"label\": {\"type\": \"string\"},\n },\n \"required\": [\"label\"]\n },\n \"include_sample_schema\": true\n },\n \"testing_criteria\": [\n {\n \"name\": \"My string check grader\",\n \"type\": \"string_check\",\n \"input\": \"{{sample.output_text}}\",\n \"reference\": \"{{item.label}}\",\n \"operation\": \"eq\",\n }\n ],\n \"name\": \"External Data Eval\",\n \"created_at\": 1739314509,\n \"metadata\": {\n \"test\": \"synthetics\",\n }\n}\n" } }, "EvalCsvFileIdSource": { "type": "object", "required": [ "type", "id" ], "properties": { "type": { "type": "string", "enum": [ "file_id" ], "description": "The type of source, always `file_id`." }, "id": { "type": "string", "description": "The identifier of the uploaded CSV file." } }, "description": "Represents a reference to an uploaded CSV file used as a source for evaluation data." }, "EvalCsvRunDataSource": { "type": "object", "required": [ "type", "source" ], "properties": { "type": { "type": "string", "enum": [ "csv" ], "description": "The type of data source, always `csv`." }, "source": { "allOf": [ { "$ref": "#/components/schemas/EvalCsvFileIdSource" } ], "description": "The source of the CSV data, either inline content or a file reference." } }, "allOf": [ { "$ref": "#/components/schemas/EvalRunDataSource" } ], "description": "Represents a CSV data source for evaluation runs." }, "EvalGraderAzureAIEvaluator": { "type": "object", "required": [ "type", "name", "evaluator_name" ], "properties": { "type": { "type": "string", "enum": [ "azure_ai_evaluator" ], "description": "The object type, which is always `azure_ai_evaluator`." }, "name": { "type": "string", "description": "The name of the grader." }, "evaluator_name": { "type": "string", "description": "The name of the evaluator." }, "evaluator_version": { "type": "string", "description": "The version of the evaluator. Latest version if not specified." }, "initialization_parameters": { "type": "object", "additionalProperties": {}, "description": "The initialization parameters for the evaluation. Must support structured outputs." }, "data_mapping": { "type": "object", "additionalProperties": { "type": "string" }, "description": "The model to use for the evaluation. Must support structured outputs." } }, "title": "AzureAIEvaluatorGrader" }, "EvalGraderInspectAI": { "type": "object", "required": [ "type", "name", "task_name" ], "properties": { "type": { "type": "string", "enum": [ "inspect_ai" ], "description": "The object type, which is always `inspect_ai`." }, "name": { "type": "string", "description": "The display name of the benchmark." }, "task_name": { "type": "string", "description": "The inspect_ai task module path (e.g., `inspect_evals/gpqa_diamond`)." } }, "description": "Grader inspect_ai definition for inspect_ai benchmark evaluators." }, "EvalResult": { "type": "object", "required": [ "name", "type", "score", "passed" ], "properties": { "name": { "type": "string", "description": "name of the check" }, "type": { "type": "string", "description": "type of the check" }, "score": { "type": "number", "format": "float", "description": "score" }, "passed": { "type": "boolean", "description": "indicates if the check passed or failed" } }, "description": "Result of the evaluation." }, "EvalRun": { "type": "object", "required": [ "object", "id", "eval_id", "status", "model", "name", "created_at", "report_url", "result_counts", "per_model_usage", "per_testing_criteria_results", "data_source", "metadata", "error" ], "properties": { "object": { "type": "string", "enum": [ "eval.run" ], "description": "The type of the object. Always \"eval.run\".", "x-stainless-const": true, "default": "eval.run" }, "id": { "type": "string", "description": "Unique identifier for the evaluation run." }, "eval_id": { "type": "string", "description": "The identifier of the associated evaluation." }, "status": { "type": "string", "description": "The status of the evaluation run." }, "model": { "type": "string", "description": "The model that is evaluated, if applicable." }, "name": { "type": "string", "description": "The name of the evaluation run." }, "created_at": { "type": "integer", "format": "unixtime", "description": "Unix timestamp (in seconds) when the evaluation run was created." }, "report_url": { "type": "string", "format": "uri", "description": "The URL to the rendered evaluation run report on the UI dashboard." }, "result_counts": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.EvalRunResultCounts" } ], "description": "Counters summarizing the outcomes of the evaluation run." }, "per_model_usage": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.EvalRunPerModelUsage" }, "description": "Usage statistics for each model during the evaluation run." }, "per_testing_criteria_results": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.EvalRunPerTestingCriteriaResults" }, "description": "Results per testing criteria applied during the evaluation run." }, "data_source": { "oneOf": [ { "$ref": "#/components/schemas/OpenAI.CreateEvalJsonlRunDataSource" }, { "$ref": "#/components/schemas/OpenAI.CreateEvalCompletionsRunDataSource" }, { "$ref": "#/components/schemas/OpenAI.CreateEvalResponsesRunDataSource" }, { "$ref": "#/components/schemas/EvalRunDataSource" } ], "description": "Information about the run's data source." }, "metadata": { "type": "object", "allOf": [ { "$ref": "#/components/schemas/OpenAI.Metadata" } ], "nullable": true }, "error": { "$ref": "#/components/schemas/OpenAI.EvalApiError" }, "modified_at": { "allOf": [ { "$ref": "#/components/schemas/integer" } ], "description": "Unix timestamp (in seconds) when the evaluation run was last modified." }, "created_by": { "type": "string", "description": "the name of the person who created the run." }, "properties": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Set of immutable 16 key-value pairs that can be attached to an object for storing additional information.\n Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters." } }, "description": "A schema representing an evaluation run.", "title": "EvalRun", "x-oaiMeta": { "name": "The eval run object", "group": "evals", "example": "{\n \"object\": \"eval.run\",\n \"id\": \"evalrun_67e57965b480819094274e3a32235e4c\",\n \"eval_id\": \"eval_67e579652b548190aaa83ada4b125f47\",\n \"report_url\": \"https://platform.openai.com/evaluations/eval_67e579652b548190aaa83ada4b125f47?run_id=evalrun_67e57965b480819094274e3a32235e4c\",\n \"status\": \"queued\",\n \"model\": \"gpt-4o-mini\",\n \"name\": \"gpt-4o-mini\",\n \"created_at\": 1743092069,\n \"result_counts\": {\n \"total\": 0,\n \"errored\": 0,\n \"failed\": 0,\n \"passed\": 0\n },\n \"per_model_usage\": null,\n \"per_testing_criteria_results\": null,\n \"data_source\": {\n \"type\": \"completions\",\n \"source\": {\n \"type\": \"file_content\",\n \"content\": [\n {\n \"item\": {\n \"input\": \"Tech Company Launches Advanced Artificial Intelligence Platform\",\n \"ground_truth\": \"Technology\"\n }\n },\n {\n \"item\": {\n \"input\": \"Central Bank Increases Interest Rates Amid Inflation Concerns\",\n \"ground_truth\": \"Markets\"\n }\n },\n {\n \"item\": {\n \"input\": \"International Summit Addresses Climate Change Strategies\",\n \"ground_truth\": \"World\"\n }\n },\n {\n \"item\": {\n \"input\": \"Major Retailer Reports Record-Breaking Holiday Sales\",\n \"ground_truth\": \"Business\"\n }\n },\n {\n \"item\": {\n \"input\": \"National Team Qualifies for World Championship Finals\",\n \"ground_truth\": \"Sports\"\n }\n },\n {\n \"item\": {\n \"input\": \"Stock Markets Rally After Positive Economic Data Released\",\n \"ground_truth\": \"Markets\"\n }\n },\n {\n \"item\": {\n \"input\": \"Global Manufacturer Announces Merger with Competitor\",\n \"ground_truth\": \"Business\"\n }\n },\n {\n \"item\": {\n \"input\": \"Breakthrough in Renewable Energy Technology Unveiled\",\n \"ground_truth\": \"Technology\"\n }\n },\n {\n \"item\": {\n \"input\": \"World Leaders Sign Historic Climate Agreement\",\n \"ground_truth\": \"World\"\n }\n },\n {\n \"item\": {\n \"input\": \"Professional Athlete Sets New Record in Championship Event\",\n \"ground_truth\": \"Sports\"\n }\n },\n {\n \"item\": {\n \"input\": \"Financial Institutions Adapt to New Regulatory Requirements\",\n \"ground_truth\": \"Business\"\n }\n },\n {\n \"item\": {\n \"input\": \"Tech Conference Showcases Advances in Artificial Intelligence\",\n \"ground_truth\": \"Technology\"\n }\n },\n {\n \"item\": {\n \"input\": \"Global Markets Respond to Oil Price Fluctuations\",\n \"ground_truth\": \"Markets\"\n }\n },\n {\n \"item\": {\n \"input\": \"International Cooperation Strengthened Through New Treaty\",\n \"ground_truth\": \"World\"\n }\n },\n {\n \"item\": {\n \"input\": \"Sports League Announces Revised Schedule for Upcoming Season\",\n \"ground_truth\": \"Sports\"\n }\n }\n ]\n },\n \"input_messages\": {\n \"type\": \"template\",\n \"template\": [\n {\n \"type\": \"message\",\n \"role\": \"developer\",\n \"content\": {\n \"type\": \"input_text\",\n \"text\": \"Categorize a given news headline into one of the following topics: Technology, Markets, World, Business, or Sports.\n\n# Steps\n\n1. Analyze the content of the news headline to understand its primary focus.\n2. Extract the subject matter, identifying any key indicators or keywords.\n3. Use the identified indicators to determine the most suitable category out of the five options: Technology, Markets, World, Business, or Sports.\n4. Ensure only one category is selected per headline.\n\n# Output Format\n\nRespond with the chosen category as a single word. For instance: \"Technology\", \"Markets\", \"World\", \"Business\", or \"Sports\".\n\n# Examples\n\n**Input**: \"Apple Unveils New iPhone Model, Featuring Advanced AI Features\"\n**Output**: \"Technology\"\n\n**Input**: \"Global Stocks Mixed as Investors Await Central Bank Decisions\"\n**Output**: \"Markets\"\n\n**Input**: \"War in Ukraine: Latest Updates on Negotiation Status\"\n**Output**: \"World\"\n\n**Input**: \"Microsoft in Talks to Acquire Gaming Company for $2 Billion\"\n**Output**: \"Business\"\n\n**Input**: \"Manchester United Secures Win in Premier League Football Match\"\n**Output**: \"Sports\"\n\n# Notes\n\n- If the headline appears to fit into more than one category, choose the most dominant theme.\n- Keywords or phrases such as \"stocks\", \"company acquisition\", \"match\", or technological brands can be good indicators for classification.\n\"\n }\n },\n {\n \"type\": \"message\",\n \"role\": \"user\",\n \"content\": {\n \"type\": \"input_text\",\n \"text\": \"{{item.input}}\"\n }\n }\n ]\n },\n \"model\": \"gpt-4o-mini\",\n \"sampling_params\": {\n \"seed\": 42,\n \"temperature\": 1.0,\n \"top_p\": 1.0,\n \"max_completions_tokens\": 2048\n }\n },\n \"error\": null,\n \"metadata\": {}\n}\n" } }, "EvalRunDataSource": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "description": "The data source type discriminator." } }, "discriminator": { "propertyName": "type", "mapping": { "azure_ai_traces_preview": "#/components/schemas/TracesPreviewEvalRunDataSource", "azure_ai_synthetic_data_gen_preview": "#/components/schemas/SyntheticDataGenerationPreviewEvalRunDataSource", "azure_ai_responses": "#/components/schemas/AzureAIResponsesEvalRunDataSource", "azure_ai_target_completions": "#/components/schemas/TargetCompletionEvalRunDataSource", "csv": "#/components/schemas/EvalCsvRunDataSource", "azure_ai_red_team": "#/components/schemas/RedTeamEvalRunDataSource", "azure_ai_benchmark_preview": "#/components/schemas/AzureAIBenchmarkPreviewEvalRunDataSource" } }, "description": "Base class for run data sources with discriminator support." }, "EvalRunOutputItem": { "type": "object", "required": [ "object", "id", "run_id", "eval_id", "created_at", "status", "datasource_item_id", "datasource_item", "results", "sample" ], "properties": { "object": { "type": "string", "enum": [ "eval.run.output_item" ], "description": "The type of the object. Always \"eval.run.output_item\".", "x-stainless-const": true, "default": "eval.run.output_item" }, "id": { "type": "string", "description": "Unique identifier for the evaluation run output item." }, "run_id": { "type": "string", "description": "The identifier of the evaluation run associated with this output item." }, "eval_id": { "type": "string", "description": "The identifier of the evaluation group." }, "created_at": { "type": "integer", "format": "unixtime", "description": "Unix timestamp (in seconds) when the evaluation run was created." }, "status": { "type": "string", "description": "The status of the evaluation run." }, "datasource_item_id": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The identifier for the data source item." }, "datasource_item": { "type": "object", "additionalProperties": {}, "description": "Details of the input data source item." }, "results": { "type": "array", "items": { "$ref": "#/components/schemas/EvalRunOutputItemResult" }, "description": "A list of grader results for this output item." }, "sample": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.EvalRunOutputItemSample" } ], "description": "A sample containing the input and output of the evaluation run." } }, "description": "A schema representing an evaluation run output item.", "title": "EvalRunOutputItem", "x-oaiMeta": { "name": "The eval run output item object", "group": "evals", "example": "{\n \"object\": \"eval.run.output_item\",\n \"id\": \"outputitem_67abd55eb6548190bb580745d5644a33\",\n \"run_id\": \"evalrun_67abd54d60ec8190832b46859da808f7\",\n \"eval_id\": \"eval_67abd54d9b0081909a86353f6fb9317a\",\n \"created_at\": 1739314509,\n \"status\": \"pass\",\n \"datasource_item_id\": 137,\n \"datasource_item\": {\n \"teacher\": \"To grade essays, I only check for style, content, and grammar.\",\n \"student\": \"I am a student who is trying to write the best essay.\"\n },\n \"results\": [\n {\n \"name\": \"String Check Grader\",\n \"type\": \"string-check-grader\",\n \"score\": 1.0,\n \"passed\": true,\n }\n ],\n \"sample\": {\n \"input\": [\n {\n \"role\": \"system\",\n \"content\": \"You are an evaluator bot...\"\n },\n {\n \"role\": \"user\",\n \"content\": \"You are assessing...\"\n }\n ],\n \"output\": [\n {\n \"role\": \"assistant\",\n \"content\": \"The rubric is not clear nor concise.\"\n }\n ],\n \"finish_reason\": \"stop\",\n \"model\": \"gpt-4o-2024-08-06\",\n \"usage\": {\n \"total_tokens\": 521,\n \"completion_tokens\": 2,\n \"prompt_tokens\": 519,\n \"cached_tokens\": 0\n },\n \"error\": null,\n \"temperature\": 1.0,\n \"max_completion_tokens\": 2048,\n \"top_p\": 1.0,\n \"seed\": 42\n }\n}\n" } }, "EvalRunOutputItemResult": { "type": "object", "required": [ "name", "score", "passed" ], "properties": { "name": { "type": "string", "description": "The name of the grader." }, "type": { "type": "string", "description": "The grader type (for example, \"string-check-grader\")." }, "score": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.numeric" } ], "description": "The numeric score produced by the grader." }, "passed": { "type": "boolean", "description": "Whether the grader considered the output a pass." }, "sample": { "type": "object", "additionalProperties": {}, "nullable": true, "description": "Optional sample or intermediate data produced by the grader." }, "metric": { "type": "string", "description": "The name of the metric (e.g., \"fluency\", \"f1_score\")." }, "label": { "type": "string", "description": "The label associated with the test criteria metric (e.g., \"pass\", \"fail\", \"good\", \"bad\")." }, "threshold": { "type": "number", "format": "float", "description": "The threshold used to determine pass/fail for this test criteria, if it is numerical." }, "reason": { "type": "string", "description": "The reason for the test criteria metric." }, "properties": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Additional details about the test criteria metric." } }, "additionalProperties": {}, "description": "A single grader result for an evaluation run output item.", "title": "EvalRunOutputItemResult" }, "EvalRunOutputItemSampleInput": { "type": "object", "required": [ "role", "content", "tool_calls" ], "properties": { "role": { "type": "string" }, "content": { "type": "string" }, "tool_calls": { "type": "array", "items": { "$ref": "#/components/schemas/CompletionMessageToolCallChunk" }, "description": "Tool calls made within the message, if any." } }, "description": "A message in the evaluation run." }, "EvalRunOutputItemSampleOutput": { "type": "object", "required": [ "tool_calls" ], "properties": { "role": { "type": "string" }, "content": { "type": "string" }, "tool_calls": { "type": "array", "items": { "$ref": "#/components/schemas/CompletionMessageToolCallChunk" }, "description": "Tool calls made within the message, if any." } }, "description": "A message in the evaluation run." }, "EvalRunResultCompareItem": { "type": "object", "required": [ "treatmentRunId", "treatmentRunSummary", "deltaEstimate", "pValue", "treatmentEffect" ], "properties": { "treatmentRunId": { "type": "string", "description": "The treatment run ID." }, "treatmentRunSummary": { "allOf": [ { "$ref": "#/components/schemas/EvalRunResultSummary" } ], "description": "Summary statistics of the treatment run." }, "deltaEstimate": { "type": "number", "format": "float", "description": "Estimated difference between treatment and baseline." }, "pValue": { "type": "number", "format": "float", "description": "P-value for the treatment effect." }, "treatmentEffect": { "allOf": [ { "$ref": "#/components/schemas/TreatmentEffectType" } ], "description": "Type of treatment effect." } }, "description": "Metric comparison for a treatment against the baseline." }, "EvalRunResultComparison": { "type": "object", "required": [ "testingCriteria", "metric", "evaluator", "baselineRunSummary", "compareItems" ], "properties": { "testingCriteria": { "type": "string", "description": "Name of the testing criteria." }, "metric": { "type": "string", "description": "Metric being evaluated." }, "evaluator": { "type": "string", "description": "Name of the evaluator for this testing criteria." }, "baselineRunSummary": { "allOf": [ { "$ref": "#/components/schemas/EvalRunResultSummary" } ], "description": "Summary statistics of the baseline run." }, "compareItems": { "type": "array", "items": { "$ref": "#/components/schemas/EvalRunResultCompareItem" }, "description": "List of comparison results for each treatment run." } }, "description": "Comparison results for treatment runs against the baseline." }, "EvalRunResultSummary": { "type": "object", "required": [ "runId", "sampleCount", "average", "standardDeviation" ], "properties": { "runId": { "type": "string", "description": "The evaluation run ID." }, "sampleCount": { "type": "integer", "format": "int32", "description": "Number of samples in the evaluation run." }, "average": { "type": "number", "format": "float", "description": "Average value of the metric in the evaluation run." }, "standardDeviation": { "type": "number", "format": "float", "description": "Standard deviation of the metric in the evaluation run." } }, "description": "Summary statistics of a metric in an evaluation run." }, "EvaluationComparisonInsightRequest": { "type": "object", "required": [ "type", "evalId", "baselineRunId", "treatmentRunIds" ], "properties": { "type": { "type": "string", "enum": [ "EvaluationComparison" ], "description": "The type of request." }, "evalId": { "type": "string", "description": "Identifier for the evaluation." }, "baselineRunId": { "type": "string", "description": "The baseline run ID for comparison." }, "treatmentRunIds": { "type": "array", "items": { "type": "string" }, "description": "List of treatment run IDs for comparison." } }, "allOf": [ { "$ref": "#/components/schemas/InsightRequest" } ], "description": "Evaluation Comparison Request" }, "EvaluationComparisonInsightResult": { "type": "object", "required": [ "type", "comparisons", "method" ], "properties": { "type": { "type": "string", "enum": [ "EvaluationComparison" ], "description": "The type of insights result." }, "comparisons": { "type": "array", "items": { "$ref": "#/components/schemas/EvalRunResultComparison" }, "description": "Comparison results for each treatment run against the baseline." }, "method": { "type": "string", "description": "The statistical method used for comparison." } }, "allOf": [ { "$ref": "#/components/schemas/InsightResult" } ], "description": "Insights from the evaluation comparison." }, "EvaluationResultSample": { "type": "object", "required": [ "type", "evaluationResult" ], "properties": { "type": { "type": "string", "enum": [ "EvaluationResultSample" ], "description": "Evaluation Result Sample Type" }, "evaluationResult": { "allOf": [ { "$ref": "#/components/schemas/EvalResult" } ], "description": "Evaluation result for the analysis sample." } }, "allOf": [ { "$ref": "#/components/schemas/InsightSample" } ], "description": "A sample from the evaluation result." }, "EvaluationRule": { "type": "object", "required": [ "id", "action", "eventType", "enabled", "systemData" ], "properties": { "id": { "type": "string", "description": "Unique identifier for the evaluation rule.", "readOnly": true }, "displayName": { "type": "string", "description": "Display Name for the evaluation rule." }, "description": { "type": "string", "description": "Description for the evaluation rule." }, "action": { "allOf": [ { "$ref": "#/components/schemas/EvaluationRuleAction" } ], "description": "Definition of the evaluation rule action.", "x-ms-foundry-meta": { "conditional_previews": [ "Evaluations=V1Preview" ] } }, "filter": { "allOf": [ { "$ref": "#/components/schemas/EvaluationRuleFilter" } ], "description": "Filter condition of the evaluation rule." }, "eventType": { "allOf": [ { "$ref": "#/components/schemas/EvaluationRuleEventType" } ], "description": "Event type that the evaluation rule applies to." }, "enabled": { "type": "boolean", "description": "Indicates whether the evaluation rule is enabled. Default is true." }, "systemData": { "type": "object", "additionalProperties": { "type": "string" }, "description": "System metadata for the evaluation rule.", "readOnly": true } }, "description": "Evaluation rule model." }, "EvaluationRuleAction": { "type": "object", "required": [ "type" ], "properties": { "type": { "allOf": [ { "$ref": "#/components/schemas/EvaluationRuleActionType" } ], "description": "Type of the evaluation action." } }, "discriminator": { "propertyName": "type", "mapping": { "continuousEvaluation": "#/components/schemas/ContinuousEvaluationRuleAction", "humanEvaluationPreview": "#/components/schemas/HumanEvaluationPreviewRuleAction" } }, "description": "Evaluation action model." }, "EvaluationRuleActionType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "continuousEvaluation", "humanEvaluationPreview" ] } ], "description": "Type of the evaluation action." }, "EvaluationRuleEventType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "responseCompleted", "manual" ] } ], "description": "Type of the evaluation rule event." }, "EvaluationRuleFilter": { "type": "object", "required": [ "agentName" ], "properties": { "agentName": { "type": "string", "description": "Filter by agent name." } }, "description": "Evaluation filter model." }, "EvaluationRunClusterInsightRequest": { "type": "object", "required": [ "type", "evalId", "runIds" ], "properties": { "type": { "type": "string", "enum": [ "EvaluationRunClusterInsight" ], "description": "The type of insights request." }, "evalId": { "type": "string", "description": "Evaluation Id for the insights." }, "runIds": { "type": "array", "items": { "type": "string" }, "description": "List of evaluation run IDs for the insights." }, "modelConfiguration": { "allOf": [ { "$ref": "#/components/schemas/InsightModelConfiguration" } ], "description": "Configuration of the model used in the insight generation." } }, "allOf": [ { "$ref": "#/components/schemas/InsightRequest" } ], "description": "Insights on set of Evaluation Results" }, "EvaluationRunClusterInsightResult": { "type": "object", "required": [ "type", "clusterInsight" ], "properties": { "type": { "type": "string", "enum": [ "EvaluationRunClusterInsight" ], "description": "The type of insights result." }, "clusterInsight": { "$ref": "#/components/schemas/ClusterInsightResult" } }, "allOf": [ { "$ref": "#/components/schemas/InsightResult" } ], "description": "Insights from the evaluation run cluster analysis." }, "EvaluationScheduleTask": { "type": "object", "required": [ "type", "evalId", "evalRun" ], "properties": { "type": { "type": "string", "enum": [ "Evaluation" ] }, "evalId": { "type": "string", "description": "Identifier of the evaluation group." }, "evalRun": { "type": "object", "description": "The evaluation run payload." } }, "allOf": [ { "$ref": "#/components/schemas/ScheduleTask" } ], "description": "Evaluation task for the schedule." }, "EvaluationTaxonomy": { "type": "object", "required": [ "name", "version", "taxonomyInput" ], "properties": { "id": { "type": "string", "description": "Asset ID, a unique identifier for the asset", "readOnly": true }, "name": { "type": "string", "description": "The name of the resource", "readOnly": true }, "version": { "type": "string", "description": "The version of the resource", "readOnly": true }, "taxonomyInput": { "allOf": [ { "$ref": "#/components/schemas/EvaluationTaxonomyInput" } ], "description": "Input configuration for the evaluation taxonomy." }, "taxonomyCategories": { "type": "array", "items": { "$ref": "#/components/schemas/TaxonomyCategory" }, "description": "List of taxonomy categories." }, "properties": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Additional properties for the evaluation taxonomy." } }, "description": "Evaluation Taxonomy Definition" }, "EvaluationTaxonomyCreateOrUpdate": { "type": "object", "required": [ "taxonomyInput" ], "properties": { "description": { "type": "string", "description": "The asset description text." }, "tags": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Tag dictionary. Tags can be added, removed, and updated." }, "taxonomyInput": { "allOf": [ { "$ref": "#/components/schemas/EvaluationTaxonomyInput" } ], "description": "Input configuration for the evaluation taxonomy." }, "taxonomyCategories": { "type": "array", "items": { "$ref": "#/components/schemas/TaxonomyCategory" }, "description": "List of taxonomy categories." }, "properties": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Additional properties for the evaluation taxonomy." } }, "description": "Evaluation Taxonomy Definition" }, "EvaluationTaxonomyInput": { "type": "object", "required": [ "type" ], "properties": { "type": { "allOf": [ { "$ref": "#/components/schemas/EvaluationTaxonomyInputType" } ], "description": "Input type of the evaluation taxonomy." } }, "discriminator": { "propertyName": "type", "mapping": { "agent": "#/components/schemas/AgentTaxonomyInput" } }, "description": "Input configuration for the evaluation taxonomy." }, "EvaluationTaxonomyInputType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "agent", "policy" ] } ], "description": "Type of the evaluation taxonomy input." }, "EvaluationTaxonomyInputUpdate": { "type": "object", "required": [ "type" ], "properties": { "type": { "allOf": [ { "$ref": "#/components/schemas/EvaluationTaxonomyInputType" } ], "description": "Input type of the evaluation taxonomy." } }, "discriminator": { "propertyName": "type", "mapping": { "agent": "#/components/schemas/AgentTaxonomyInputUpdate" } }, "description": "Input configuration for the evaluation taxonomy." }, "EvaluationTaxonomyUpdate": { "type": "object", "properties": { "description": { "type": "string", "description": "The asset description text." }, "tags": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Tag dictionary. Tags can be added, removed, and updated." }, "taxonomyInput": { "allOf": [ { "$ref": "#/components/schemas/EvaluationTaxonomyInputUpdate" } ], "description": "Input configuration for the evaluation taxonomy." }, "taxonomyCategories": { "type": "array", "items": { "$ref": "#/components/schemas/TaxonomyCategory" }, "description": "List of taxonomy categories." }, "properties": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Additional properties for the evaluation taxonomy." } }, "description": "Evaluation Taxonomy Definition" }, "EvaluatorCategory": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "quality", "safety", "agents" ] } ], "description": "The category of the evaluator" }, "EvaluatorCredentialRequest": { "type": "object", "required": [ "blobUri" ], "properties": { "blobUri": { "type": "string", "format": "uri", "description": "The blob URI for the evaluator storage. Example: `https://account.blob.core.windows.net:443/container`" } }, "description": "Request body for getting evaluator credentials" }, "EvaluatorDefinition": { "type": "object", "required": [ "type" ], "properties": { "type": { "allOf": [ { "$ref": "#/components/schemas/EvaluatorDefinitionType" } ], "description": "The type of evaluator definition" }, "init_parameters": { "type": "object", "additionalProperties": {}, "description": "The JSON schema (Draft 2020-12) for the evaluator's input parameters. This includes parameters like type, properties, required." }, "data_schema": { "type": "object", "additionalProperties": {}, "description": "The JSON schema (Draft 2020-12) for the evaluator's input data. This includes parameters like type, properties, required." }, "metrics": { "type": "object", "additionalProperties": { "$ref": "#/components/schemas/EvaluatorMetric" }, "description": "List of output metrics produced by this evaluator" } }, "discriminator": { "propertyName": "type", "mapping": { "code": "#/components/schemas/CodeBasedEvaluatorDefinition", "prompt": "#/components/schemas/PromptBasedEvaluatorDefinition" } }, "description": "Base evaluator configuration with discriminator" }, "EvaluatorDefinitionType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "prompt", "code", "prompt_and_code", "service", "openai_graders" ] } ], "description": "The type of evaluator definition" }, "EvaluatorMetric": { "type": "object", "properties": { "type": { "allOf": [ { "$ref": "#/components/schemas/EvaluatorMetricType" } ], "description": "Type of the metric." }, "desirable_direction": { "allOf": [ { "$ref": "#/components/schemas/EvaluatorMetricDirection" } ], "description": "It indicates whether a higher value is better or a lower value is better for this metric." }, "min_value": { "type": "number", "format": "float", "description": "Minimum value for the metric" }, "max_value": { "type": "number", "format": "float", "description": "Maximum value for the metric. If not specified, it is assumed to be unbounded." }, "threshold": { "type": "number", "format": "float", "description": "Default pass/fail threshold for this metric." }, "is_primary": { "type": "boolean", "description": "Indicates if this metric is primary when there are multiple metrics." } }, "description": "Evaluator Metric" }, "EvaluatorMetricDirection": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "increase", "decrease", "neutral" ] } ], "description": "The direction of the metric indicating whether a higher value is better, a lower value is better, or neutral" }, "EvaluatorMetricType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "ordinal", "continuous", "boolean" ] } ], "description": "The type of the evaluator" }, "EvaluatorType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "builtin", "custom" ] } ], "description": "The type of the evaluator" }, "EvaluatorVersion": { "type": "object", "required": [ "evaluator_type", "categories", "definition", "created_by", "created_at", "modified_at", "name", "version" ], "properties": { "display_name": { "type": "string", "description": "Display Name for evaluator. It helps to find the evaluator easily in AI Foundry. It does not need to be unique." }, "metadata": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Metadata about the evaluator" }, "evaluator_type": { "allOf": [ { "$ref": "#/components/schemas/EvaluatorType" } ], "description": "The type of the evaluator" }, "categories": { "type": "array", "items": { "$ref": "#/components/schemas/EvaluatorCategory" }, "description": "The categories of the evaluator" }, "definition": { "allOf": [ { "$ref": "#/components/schemas/EvaluatorDefinition" } ], "description": "Definition of the evaluator" }, "created_by": { "type": "string", "description": "Creator of the evaluator", "readOnly": true }, "created_at": { "type": "string", "description": "Creation date/time of the evaluator", "readOnly": true }, "modified_at": { "type": "string", "description": "Last modified date/time of the evaluator", "readOnly": true }, "id": { "type": "string", "description": "Asset ID, a unique identifier for the asset", "readOnly": true }, "name": { "type": "string", "description": "The name of the resource", "readOnly": true }, "version": { "type": "string", "description": "The version of the resource", "readOnly": true } }, "description": "Evaluator Definition" }, "EvaluatorVersionCreate": { "type": "object", "required": [ "evaluator_type", "categories", "definition" ], "properties": { "display_name": { "type": "string", "description": "Display Name for evaluator. It helps to find the evaluator easily in AI Foundry. It does not need to be unique." }, "metadata": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Metadata about the evaluator" }, "evaluator_type": { "allOf": [ { "$ref": "#/components/schemas/EvaluatorType" } ], "description": "The type of the evaluator" }, "categories": { "type": "array", "items": { "$ref": "#/components/schemas/EvaluatorCategory" }, "description": "The categories of the evaluator" }, "definition": { "allOf": [ { "$ref": "#/components/schemas/EvaluatorDefinition" } ], "description": "Definition of the evaluator" }, "description": { "type": "string", "description": "The asset description text." }, "tags": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Tag dictionary. Tags can be added, removed, and updated." } }, "description": "Evaluator Definition" }, "EvaluatorVersionUpdate": { "type": "object", "properties": { "display_name": { "type": "string", "description": "Display Name for evaluator. It helps to find the evaluator easily in AI Foundry. It does not need to be unique." }, "metadata": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Metadata about the evaluator" }, "categories": { "type": "array", "items": { "$ref": "#/components/schemas/EvaluatorCategory" }, "description": "The categories of the evaluator" }, "description": { "type": "string", "description": "The asset description text." }, "tags": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Tag dictionary. Tags can be added, removed, and updated." } }, "description": "Evaluator Definition" }, "ExplicitModelReferenceConfiguration": { "type": "object", "required": [ "kind", "model" ], "properties": { "kind": { "type": "string", "enum": [ "model" ], "description": "Reference policy kind, always 'model'." }, "model": { "type": "string", "description": "Reference model asset URI." } }, "allOf": [ { "$ref": "#/components/schemas/ModelTrainingReferenceConfiguration" } ], "description": "Use an explicit model as the reference policy." }, "FabricDataAgentToolCall": { "type": "object", "required": [ "type", "call_id", "arguments", "status" ], "properties": { "type": { "type": "string", "enum": [ "fabric_dataagent_preview_call" ] }, "call_id": { "type": "string", "description": "The unique ID of the tool call generated by the model." }, "arguments": { "type": "string", "description": "A JSON string of the arguments to pass to the tool." }, "status": { "allOf": [ { "$ref": "#/components/schemas/ToolCallStatus" } ], "description": "The status of the tool call." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ], "description": "A Fabric data agent tool call." }, "FabricDataAgentToolCallOutput": { "type": "object", "required": [ "type", "call_id", "status" ], "properties": { "type": { "type": "string", "enum": [ "fabric_dataagent_preview_call_output" ] }, "call_id": { "type": "string", "description": "The unique ID of the tool call generated by the model." }, "output": { "allOf": [ { "$ref": "#/components/schemas/ToolCallOutputContent" } ], "description": "The output from the Fabric data agent tool call." }, "status": { "allOf": [ { "$ref": "#/components/schemas/ToolCallStatus" } ], "description": "The status of the tool call." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ], "description": "The output of a Fabric data agent tool call." }, "FabricDataAgentToolParameters": { "type": "object", "properties": { "name": { "type": "string", "description": "Optional user-defined name for this tool or configuration." }, "description": { "type": "string", "description": "Optional user-defined description for this tool or configuration." }, "project_connections": { "type": "array", "items": { "$ref": "#/components/schemas/ToolProjectConnection" }, "maxItems": 1, "description": "The project connections attached to this tool. There can be a maximum of 1 connection\nresource attached to the tool." } }, "description": "The fabric data agent tool parameters." }, "FileDatasetVersion": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "uri_file" ], "description": "Dataset type" } }, "allOf": [ { "$ref": "#/components/schemas/DatasetVersion" } ], "description": "FileDatasetVersion Definition" }, "FileDatasetVersionUpdate": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "uri_file" ], "description": "Dataset type" } }, "allOf": [ { "$ref": "#/components/schemas/DatasetVersionUpdate" } ], "description": "FileDatasetVersion Definition" }, "FolderDatasetVersion": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "uri_folder" ], "description": "Dataset type" } }, "allOf": [ { "$ref": "#/components/schemas/DatasetVersion" } ], "description": "FileDatasetVersion Definition" }, "FolderDatasetVersionUpdate": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "uri_folder" ], "description": "Dataset type" } }, "allOf": [ { "$ref": "#/components/schemas/DatasetVersionUpdate" } ], "description": "FileDatasetVersion Definition" }, "FoundryTimestamp": { "type": "integer", "format": "unixtime", "description": "Unix timestamp in seconds used by Foundry data-plane resources." }, "FunctionToolCall": { "type": "object", "required": [ "name", "arguments" ], "properties": { "name": { "type": "string", "description": "The name of the function to call." }, "arguments": { "type": "string", "description": "The arguments to call the function with, as generated by the model in JSON format." } }, "description": "Details of a function tool call." }, "GrpoTrainingColumnMapping": { "type": "object", "required": [ "prompt" ], "properties": { "prompt": { "type": "string", "description": "Actual dataset column name containing prompts for rollout generation, for example 'prompt', 'question', or 'problem'." }, "reference": { "type": "string", "description": "Actual dataset column name containing reference answers or reward context passed to the judge, for example 'answer' or 'reference'." } }, "description": "Column mapping for managed online RL prompt datasets. Keys are logical fields expected by GRPO, RLOO, REINFORCE++, and PPO; values are the exact column names in the referenced dataset asset. The training dataset must contain prompts; reference answers or reward context can be passed to the judge." }, "GrpoTrainingConfiguration": { "type": "object", "required": [ "algorithm", "reward" ], "properties": { "algorithm": { "type": "string", "enum": [ "grpo" ], "description": "Training algorithm, always 'grpo'." }, "reward": { "allOf": [ { "$ref": "#/components/schemas/TrainingRewardConfiguration" } ], "description": "Reward signal configuration." }, "lora": { "allOf": [ { "$ref": "#/components/schemas/TrainingLoraConfiguration" } ], "description": "LoRA adapter configuration." }, "rollout": { "allOf": [ { "$ref": "#/components/schemas/TrainingRolloutConfiguration" } ], "description": "Rollout generation configuration." }, "eval": { "allOf": [ { "$ref": "#/components/schemas/TrainingEvalConfiguration" } ], "description": "Evaluation configuration." } }, "allOf": [ { "$ref": "#/components/schemas/TrainingConfiguration" } ], "description": "Group relative policy optimization training recipe." }, "GrpoTrainingDatasetConfiguration": { "type": "object", "required": [ "train", "columns" ], "properties": { "train": { "type": "string", "description": "Training dataset asset reference." }, "eval": { "type": "string", "description": "Optional evaluation dataset asset reference." }, "columns": { "allOf": [ { "$ref": "#/components/schemas/GrpoTrainingColumnMapping" } ], "description": "Mapping from online RL logical fields to actual dataset column names. GRPO, policy-gradient, and PPO require the 'prompt' logical field and can optionally map 'reference'." }, "data_format": { "allOf": [ { "$ref": "#/components/schemas/TrainingDataFormatConfiguration" } ], "description": "Conversational data formatting options." } }, "description": "Dataset configuration for managed GRPO training." }, "GrpoTrainingJob": { "type": "object", "required": [ "type", "dataset", "runtime" ], "properties": { "type": { "type": "string", "enum": [ "grpo" ], "description": "Managed training job type, always 'grpo'." }, "dataset": { "allOf": [ { "$ref": "#/components/schemas/GrpoTrainingDatasetConfiguration" } ], "description": "Training and optional evaluation datasets." }, "runtime": { "allOf": [ { "$ref": "#/components/schemas/GrpoTrainingRuntimeConfiguration" } ], "description": "Runtime options for managed GRPO." } }, "allOf": [ { "$ref": "#/components/schemas/ModelTrainingJobCreate" } ], "description": "Request body for creating a managed GRPO training job from a base model." }, "GrpoTrainingRuntimeConfiguration": { "type": "object", "required": [ "judge" ], "properties": { "framework": { "allOf": [ { "$ref": "#/components/schemas/TrainingFramework" } ], "description": "Training framework implementation. If omitted, the service selects a compatible framework." }, "hyperparameters": { "type": "object", "additionalProperties": {}, "description": "Algorithm-specific hyperparameters passed through to the selected framework." }, "judge": { "allOf": [ { "$ref": "#/components/schemas/TrainingRewardConfiguration" } ], "description": "Judge used to score generated completions during GRPO training. Required for GRPO." }, "lora": { "allOf": [ { "$ref": "#/components/schemas/TrainingLoraConfiguration" } ], "description": "LoRA adapter configuration." }, "rollout": { "allOf": [ { "$ref": "#/components/schemas/TrainingRolloutConfiguration" } ], "description": "Rollout generation configuration." }, "eval": { "allOf": [ { "$ref": "#/components/schemas/TrainingEvalConfiguration" } ], "description": "Evaluation configuration." }, "reference": { "allOf": [ { "$ref": "#/components/schemas/ModelTrainingReferenceConfiguration" } ], "description": "Reference policy used for KL anchoring." }, "packaging": { "allOf": [ { "$ref": "#/components/schemas/ModelTrainingPackagingConfiguration" } ], "description": "Model artifact packaging options." } }, "description": "Runtime options for managed GRPO training." }, "HostedAgentDefinition": { "type": "object", "required": [ "kind", "container_protocol_versions", "cpu", "memory" ], "properties": { "kind": { "type": "string", "enum": [ "hosted" ] }, "tools": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.Tool" }, "description": "An array of tools the hosted agent's model may call while generating a response. You\ncan specify which tool to use by setting the `tool_choice` parameter." }, "container_protocol_versions": { "type": "array", "items": { "$ref": "#/components/schemas/ProtocolVersionRecord" }, "description": "The protocols that the agent supports for ingress communication of the containers.", "example": [ { "protocol": "responses", "version": "v0.1.1" }, { "protocol": "a2a", "version": "v0.3.0" } ] }, "cpu": { "type": "string", "description": "The CPU configuration for the hosted agent.", "example": "0.25" }, "memory": { "type": "string", "description": "The memory configuration for the hosted agent.", "example": "0.5Gi" }, "environment_variables": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Environment variables to set in the hosted agent container.", "example": { "name": "LOG_LEVEL", "value": "debug" } }, "image": { "type": "string", "description": "The image ID for the agent, applicable to image-based hosted agents.", "example": "my-registry.azurecr.io/my-hosted-agent:latest" } }, "allOf": [ { "$ref": "#/components/schemas/AgentDefinition" } ], "description": "The hosted agent definition.", "x-ms-foundry-meta": { "required_previews": [ "HostedAgents=V1Preview" ] } }, "HourlyRecurrenceSchedule": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "Hourly" ] } }, "allOf": [ { "$ref": "#/components/schemas/RecurrenceSchedule" } ], "description": "Hourly recurrence schedule." }, "HumanEvaluationPreviewRuleAction": { "type": "object", "required": [ "type", "templateId" ], "properties": { "type": { "type": "string", "enum": [ "humanEvaluationPreview" ] }, "templateId": { "allOf": [ { "$ref": "#/components/schemas/AssetId" } ], "description": "Human evaluation template Id." } }, "allOf": [ { "$ref": "#/components/schemas/EvaluationRuleAction" } ], "description": "Evaluation rule action for human evaluation." }, "Index": { "type": "object", "required": [ "type", "name", "version" ], "properties": { "type": { "allOf": [ { "$ref": "#/components/schemas/IndexType" } ], "description": "Type of index" }, "id": { "type": "string", "description": "Asset ID, a unique identifier for the asset", "readOnly": true }, "name": { "type": "string", "description": "The name of the resource", "readOnly": true }, "version": { "type": "string", "description": "The version of the resource", "readOnly": true } }, "discriminator": { "propertyName": "type", "mapping": { "AzureSearch": "#/components/schemas/AzureAISearchIndex", "ManagedAzureSearch": "#/components/schemas/ManagedAzureAISearchIndex", "CosmosDBNoSqlVectorStore": "#/components/schemas/CosmosDBIndex" } }, "description": "Index resource Definition" }, "IndexType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "AzureSearch", "CosmosDBNoSqlVectorStore", "ManagedAzureSearch" ] } ] }, "IndexUpdate": { "type": "object", "required": [ "type" ], "properties": { "type": { "allOf": [ { "$ref": "#/components/schemas/IndexType" } ], "description": "Type of index" }, "description": { "type": "string", "description": "The asset description text." }, "tags": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Tag dictionary. Tags can be added, removed, and updated." } }, "discriminator": { "propertyName": "type", "mapping": { "AzureSearch": "#/components/schemas/AzureAISearchIndexUpdate", "ManagedAzureSearch": "#/components/schemas/ManagedAzureAISearchIndexUpdate", "CosmosDBNoSqlVectorStore": "#/components/schemas/CosmosDBIndexUpdate" } }, "description": "Index resource Definition" }, "Input": { "type": "object", "required": [ "job_input_type" ], "properties": { "job_input_type": { "allOf": [ { "$ref": "#/components/schemas/AssetTypes" } ], "description": "Specifies the type of job input." }, "uri": { "type": "string", "description": "Input Asset URI. Required for uri_file, uri_folder, and safetensors_model types." }, "mode": { "allOf": [ { "$ref": "#/components/schemas/InputOutputModes" } ], "description": "Input Asset Delivery Mode. Applies to uri-based inputs." }, "value": { "type": "string", "description": "Literal value. Required for literal type." } }, "description": "Job input definition." }, "InputOutputModes": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "read_only_mount", "read_write_mount", "download", "direct", "upload" ] } ], "description": "Enum to determine the input/output data delivery mode." }, "Insight": { "type": "object", "required": [ "id", "metadata", "state", "displayName", "request" ], "properties": { "id": { "type": "string", "description": "The unique identifier for the insights report.", "readOnly": true }, "metadata": { "allOf": [ { "$ref": "#/components/schemas/InsightsMetadata" } ], "description": "Metadata about the insights report.", "readOnly": true }, "state": { "allOf": [ { "$ref": "#/components/schemas/Azure.Core.Foundations.OperationState" } ], "description": "The current state of the insights.", "readOnly": true }, "displayName": { "type": "string", "description": "User friendly display name for the insight." }, "request": { "allOf": [ { "$ref": "#/components/schemas/InsightRequest" } ], "description": "Request for the insights analysis." }, "result": { "allOf": [ { "$ref": "#/components/schemas/InsightResult" } ], "description": "The result of the insights report.", "readOnly": true } }, "description": "The response body for cluster insights." }, "InsightCluster": { "type": "object", "required": [ "id", "label", "suggestion", "suggestionTitle", "description", "weight" ], "properties": { "id": { "type": "string", "description": "The id of the analysis cluster." }, "label": { "type": "string", "description": "Label for the cluster" }, "suggestion": { "type": "string", "description": "Suggestion for the cluster" }, "suggestionTitle": { "type": "string", "description": "The title of the suggestion for the cluster" }, "description": { "type": "string", "description": "Description of the analysis cluster." }, "weight": { "type": "integer", "format": "int32", "description": "The weight of the analysis cluster. This indicate number of samples in the cluster." }, "subClusters": { "description": "List of subclusters within this cluster. Empty if no subclusters exist.", "type": "array", "items": { "$ref": "#/components/schemas/InsightCluster" } }, "samples": { "type": "array", "items": { "$ref": "#/components/schemas/InsightSample" }, "description": "List of samples that belong to this cluster. Empty if samples are part of subclusters." } }, "description": "A cluster of analysis samples." }, "InsightModelConfiguration": { "type": "object", "required": [ "modelDeploymentName" ], "properties": { "modelDeploymentName": { "type": "string", "description": "The model deployment to be evaluated. Accepts either the deployment name alone or with the connection name as '{connectionName}/'." } }, "description": "Configuration of the model used in the insight generation." }, "InsightRequest": { "type": "object", "required": [ "type" ], "properties": { "type": { "allOf": [ { "$ref": "#/components/schemas/InsightType" } ], "description": "The type of request." } }, "discriminator": { "propertyName": "type", "mapping": { "EvaluationRunClusterInsight": "#/components/schemas/EvaluationRunClusterInsightRequest", "AgentClusterInsight": "#/components/schemas/AgentClusterInsightRequest", "EvaluationComparison": "#/components/schemas/EvaluationComparisonInsightRequest" } }, "description": "The request of the insights report." }, "InsightResult": { "type": "object", "required": [ "type" ], "properties": { "type": { "allOf": [ { "$ref": "#/components/schemas/InsightType" } ], "description": "The type of insights result." } }, "discriminator": { "propertyName": "type", "mapping": { "EvaluationComparison": "#/components/schemas/EvaluationComparisonInsightResult", "EvaluationRunClusterInsight": "#/components/schemas/EvaluationRunClusterInsightResult", "AgentClusterInsight": "#/components/schemas/AgentClusterInsightResult" } }, "description": "The result of the insights." }, "InsightSample": { "type": "object", "required": [ "id", "type", "features", "correlationInfo" ], "properties": { "id": { "type": "string", "description": "The unique identifier for the analysis sample." }, "type": { "allOf": [ { "$ref": "#/components/schemas/SampleType" } ], "description": "Sample type" }, "features": { "type": "object", "additionalProperties": {}, "description": "Features to help with additional filtering of data in UX." }, "correlationInfo": { "type": "object", "additionalProperties": {}, "description": "Info about the correlation for the analysis sample." } }, "discriminator": { "propertyName": "type", "mapping": { "EvaluationResultSample": "#/components/schemas/EvaluationResultSample" } }, "description": "A sample from the analysis." }, "InsightScheduleTask": { "type": "object", "required": [ "type", "insight" ], "properties": { "type": { "type": "string", "enum": [ "Insight" ] }, "insight": { "allOf": [ { "$ref": "#/components/schemas/Insight" } ], "description": "The insight payload." } }, "allOf": [ { "$ref": "#/components/schemas/ScheduleTask" } ], "description": "Insight task for the schedule." }, "InsightSummary": { "type": "object", "required": [ "sampleCount", "uniqueSubclusterCount", "uniqueClusterCount", "method", "usage" ], "properties": { "sampleCount": { "type": "integer", "format": "int32", "description": "Total number of samples analyzed." }, "uniqueSubclusterCount": { "type": "integer", "format": "int32", "description": "Total number of unique subcluster labels." }, "uniqueClusterCount": { "type": "integer", "format": "int32", "description": "Total number of unique clusters." }, "method": { "type": "string", "description": "Method used for clustering." }, "usage": { "allOf": [ { "$ref": "#/components/schemas/ClusterTokenUsage" } ], "description": "Token usage while performing clustering analysis" } }, "description": "Summary of the error cluster analysis." }, "InsightType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "EvaluationRunClusterInsight", "AgentClusterInsight", "EvaluationComparison" ] } ], "description": "The request of the insights." }, "InsightsMetadata": { "type": "object", "required": [ "createdAt" ], "properties": { "createdAt": { "type": "string", "format": "date-time", "description": "The timestamp when the insights were created." }, "completedAt": { "type": "string", "format": "date-time", "description": "The timestamp when the insights were completed." } }, "description": "Metadata about the insights." }, "ItemGenerationParams": { "type": "object", "required": [ "type" ], "properties": { "type": { "allOf": [ { "$ref": "#/components/schemas/ItemGenerationParamsType" } ], "description": "The type of item generation parameters to use." } }, "discriminator": { "propertyName": "type", "mapping": { "red_team": "#/components/schemas/RedTeamItemGenerationParams", "red_team_seed_prompts": "#/components/schemas/RedTeamSeedPromptsItemGenerationParams", "red_team_taxonomy": "#/components/schemas/RedTeamTaxonomyItemGenerationParams", "response_retrieval": "#/components/schemas/ResponseRetrievalItemGenerationParams" } }, "description": "Represents the set of parameters used to control item generation operations." }, "ItemGenerationParamsType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "red_team", "response_retrieval", "red_team_seed_prompts", "red_team_taxonomy", "synthetic_data_gen_preview" ] } ], "description": "The types of parameters for red team item generation." }, "Job": { "type": "object", "required": [ "name", "properties" ], "properties": { "name": { "type": "string", "description": "The name of the training job. This is case-sensitive.", "readOnly": true }, "id": { "type": "string", "description": "The resource ID.", "readOnly": true }, "type": { "type": "string", "description": "The resource type.", "readOnly": true }, "properties": { "allOf": [ { "$ref": "#/components/schemas/JobProperties" } ], "description": "Properties of the job." }, "system_data": { "allOf": [ { "$ref": "#/components/schemas/SystemData" } ], "description": "Metadata pertaining to creation and last modification of the resource.", "readOnly": true } }, "description": "Training job resource." }, "JobArtifact": { "type": "object", "required": [ "path", "type" ], "properties": { "path": { "type": "string", "description": "Artifact path relative to the job artifact root.", "readOnly": true }, "type": { "allOf": [ { "$ref": "#/components/schemas/JobArtifactType" } ], "description": "Artifact type.", "readOnly": true }, "size": { "type": "integer", "format": "int64", "description": "Artifact size in bytes.", "readOnly": true }, "created_at": { "allOf": [ { "$ref": "#/components/schemas/FoundryTimestamp" } ], "description": "Time the artifact was created.", "readOnly": true }, "updated_at": { "allOf": [ { "$ref": "#/components/schemas/FoundryTimestamp" } ], "description": "Time the artifact was last updated.", "readOnly": true } }, "description": "Metadata for an artifact produced by or attached to a job." }, "JobArtifactContentInfo": { "type": "object", "required": [ "path", "content_uri" ], "properties": { "path": { "type": "string", "description": "Artifact path relative to the job artifact root.", "readOnly": true }, "content_uri": { "type": "string", "format": "uri", "description": "Download URI for the artifact content.", "readOnly": true }, "content_type": { "type": "string", "description": "MIME type of the content.", "readOnly": true }, "expires_at": { "allOf": [ { "$ref": "#/components/schemas/FoundryTimestamp" } ], "description": "Time the content URI expires.", "readOnly": true } }, "description": "Content access information for a job artifact." }, "JobArtifactType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "file", "directory" ] } ], "description": "Type of a job artifact." }, "JobAttempt": { "type": "object", "required": [ "id", "job_name" ], "properties": { "id": { "type": "string", "description": "The attempt identifier.", "readOnly": true }, "job_name": { "type": "string", "description": "The job name this attempt belongs to.", "readOnly": true }, "status": { "allOf": [ { "$ref": "#/components/schemas/JobAttemptStatus" } ], "description": "The attempt status.", "readOnly": true }, "status_reason": { "type": "string", "description": "Additional status reason.", "readOnly": true }, "started_at": { "allOf": [ { "$ref": "#/components/schemas/FoundryTimestamp" } ], "description": "Time the attempt started.", "readOnly": true }, "ended_at": { "allOf": [ { "$ref": "#/components/schemas/FoundryTimestamp" } ], "description": "Time the attempt ended.", "readOnly": true }, "last_started_at": { "allOf": [ { "$ref": "#/components/schemas/FoundryTimestamp" } ], "description": "Most recent time the attempt started running.", "readOnly": true }, "compute_duration": { "type": "string", "format": "duration", "description": "Total compute duration consumed by the attempt.", "readOnly": true }, "queueing_info": { "type": "object", "additionalProperties": {}, "description": "Queueing details associated with the attempt.", "readOnly": true }, "compute_details": { "allOf": [ { "$ref": "#/components/schemas/JobAttemptComputeDetails" } ], "description": "Compute details associated with the attempt.", "readOnly": true }, "error": { "allOf": [ { "$ref": "#/components/schemas/JobAttemptError" } ], "description": "Terminal error for the attempt, if any.", "readOnly": true }, "warnings": { "type": "array", "items": { "$ref": "#/components/schemas/JobAttemptWarning" }, "description": "Warnings emitted for the attempt.", "readOnly": true }, "is_latest": { "type": "boolean", "description": "Whether this attempt is the current attempt for the job.", "readOnly": true } }, "description": "One execution attempt of a training job." }, "JobAttemptComputeDetails": { "type": "object", "properties": { "vm_size": { "type": "string", "description": "Virtual machine size used for this attempt.", "readOnly": true }, "instance_type": { "type": "string", "description": "Instance type used for this attempt.", "readOnly": true }, "instance_count": { "type": "integer", "format": "int32", "description": "Number of instances allocated to this attempt.", "readOnly": true }, "gpu_count": { "type": "integer", "format": "int32", "description": "Number of GPUs allocated to this attempt.", "readOnly": true }, "region": { "type": "string", "description": "Region where this attempt was placed.", "readOnly": true }, "properties": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Additional backend-specific compute placement properties.", "readOnly": true } }, "description": "Compute placement details for a job attempt." }, "JobAttemptError": { "type": "object", "properties": { "code": { "type": "string", "description": "Machine-readable error code." }, "message": { "type": "string", "description": "Human-readable error message." }, "details": { "type": "object", "additionalProperties": {}, "description": "Additional error details." } }, "description": "Error emitted during a job attempt." }, "JobAttemptIdentifier": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "latest" ] } ], "description": "Training job attempt identifier. Use 'latest' for the latest attempt." }, "JobAttemptStatus": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "queued", "running", "completed", "failed", "canceled" ] } ], "description": "Status of a job execution attempt." }, "JobAttemptWarning": { "type": "object", "properties": { "code": { "type": "string", "description": "Machine-readable warning code." }, "message": { "type": "string", "description": "Human-readable warning message." }, "details": { "type": "object", "additionalProperties": {}, "description": "Additional warning details." } }, "description": "Warning emitted during a job attempt." }, "JobCreate": { "type": "object", "required": [ "name", "properties" ], "properties": { "name": { "type": "string", "description": "The name of the training job. This is case-sensitive." }, "properties": { "allOf": [ { "$ref": "#/components/schemas/JobProperties" } ], "description": "Properties of the job." } }, "description": "Request body for creating a training job." }, "JobMetric": { "type": "object", "required": [ "name" ], "properties": { "name": { "type": "string", "description": "Metric name.", "readOnly": true }, "metric_type": { "allOf": [ { "$ref": "#/components/schemas/JobMetricType" } ], "description": "Metric type.", "readOnly": true }, "columns": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Column metadata for structured metric values.", "readOnly": true } }, "description": "Metadata for a metric emitted by a job or run." }, "JobMetricAggregate": { "type": "object", "required": [ "name" ], "properties": { "name": { "type": "string", "description": "Metric name.", "readOnly": true }, "started_at": { "allOf": [ { "$ref": "#/components/schemas/FoundryTimestamp" } ], "description": "Aggregate window start.", "readOnly": true }, "ended_at": { "allOf": [ { "$ref": "#/components/schemas/FoundryTimestamp" } ], "description": "Aggregate window end.", "readOnly": true }, "values": { "type": "object", "additionalProperties": {}, "description": "Aggregate values.", "readOnly": true } }, "description": "Aggregated values for a metric." }, "JobMetricLastValue": { "type": "object", "required": [ "name" ], "properties": { "name": { "type": "string", "description": "Metric name.", "readOnly": true }, "value": { "allOf": [ { "$ref": "#/components/schemas/JobMetricPoint" } ], "description": "Latest metric point.", "readOnly": true } }, "description": "Latest value for a metric." }, "JobMetricPoint": { "type": "object", "properties": { "metric_id": { "type": "string", "description": "Metric identifier.", "readOnly": true }, "step": { "type": "integer", "format": "int64", "description": "Metric step.", "readOnly": true }, "created_at": { "allOf": [ { "$ref": "#/components/schemas/FoundryTimestamp" } ], "description": "Time the metric point was created.", "readOnly": true }, "data": { "type": "object", "additionalProperties": {}, "description": "Metric data values.", "readOnly": true } }, "description": "A metric data point." }, "JobMetricSample": { "type": "object", "required": [ "name", "points" ], "properties": { "name": { "type": "string", "description": "Metric name.", "readOnly": true }, "points": { "type": "array", "items": { "$ref": "#/components/schemas/JobMetricPoint" }, "description": "Sampled metric points.", "readOnly": true } }, "description": "Sampled values for a metric." }, "JobMetricType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "scalar", "table", "image" ] } ], "description": "The kind of metric emitted by a job." }, "JobOperationError": { "type": "object", "properties": { "code": { "type": "string", "description": "Machine-readable error code." }, "message": { "type": "string", "description": "Human-readable error message." }, "details": { "type": "object", "additionalProperties": {}, "description": "Additional error information." } }, "description": "Error details for an asynchronous training job operation." }, "JobOperationResource": { "type": "object", "required": [ "status" ], "properties": { "id": { "type": "string", "description": "Operation resource ID.", "readOnly": true }, "name": { "type": "string", "description": "Operation name.", "readOnly": true }, "status": { "allOf": [ { "$ref": "#/components/schemas/JobOperationStatus" } ], "description": "Operation status.", "readOnly": true }, "properties": { "type": "object", "additionalProperties": {}, "description": "Operation result properties.", "readOnly": true }, "started_at": { "allOf": [ { "$ref": "#/components/schemas/FoundryTimestamp" } ], "description": "Operation start time.", "readOnly": true }, "ended_at": { "allOf": [ { "$ref": "#/components/schemas/FoundryTimestamp" } ], "description": "Operation end time.", "readOnly": true }, "percent_complete": { "type": "number", "format": "double", "description": "Operation completion percentage from 0 to 100.", "readOnly": true }, "error": { "allOf": [ { "$ref": "#/components/schemas/JobOperationError" } ], "description": "Operation error information.", "readOnly": true } }, "description": "Asynchronous training job operation resource." }, "JobOperationStatus": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "in_progress", "deleting", "succeeded", "failed", "canceled" ] } ], "description": "Status of an asynchronous training job operation." }, "JobOutputReference": { "type": "object", "required": [ "name" ], "properties": { "name": { "type": "string", "description": "Output name.", "readOnly": true }, "type": { "allOf": [ { "$ref": "#/components/schemas/AssetTypes" } ], "description": "Output asset type.", "readOnly": true }, "mode": { "allOf": [ { "$ref": "#/components/schemas/InputOutputModes" } ], "description": "Output delivery mode.", "readOnly": true }, "uri": { "type": "string", "description": "Output storage URI.", "readOnly": true }, "asset_name": { "type": "string", "description": "Registered asset name, if the output produced an asset.", "readOnly": true }, "asset_version": { "type": "string", "description": "Registered asset version, if the output produced an asset.", "readOnly": true }, "base_model_id": { "type": "string", "description": "Base model ID for model outputs.", "readOnly": true }, "description": { "type": "string", "description": "Output description.", "readOnly": true } }, "description": "Named output produced by a job." }, "JobProperties": { "type": "object", "required": [ "job_type" ], "properties": { "job_type": { "type": "string", "description": "Job type." } }, "discriminator": { "propertyName": "job_type", "mapping": { "command": "#/components/schemas/CommandJob" } }, "description": "Base properties of a Job." }, "JobResourceConfiguration": { "type": "object", "properties": { "instance_count": { "type": "integer", "format": "int32", "description": "Optional number of instances or nodes used by the compute target." }, "instance_type": { "type": "string", "description": "Optional type of VM used as supported by the compute target." }, "properties": { "type": "object", "additionalProperties": {}, "description": "Additional properties bag." }, "shm_size": { "type": "string", "description": "Size of the docker container's shared memory block. This should be in the format of (number)(unit) where number as to be greater than 0 and the unit can be one of b(bytes), k(kilobytes), m(megabytes), or g(gigabytes)." }, "docker_args": { "type": "string", "description": "Extra arguments to pass to the Docker run command. This would override any parameters that have already been set by the system, or in this section. This parameter is only supported for Azure ML compute types." } }, "description": "Compute Resource configuration for the job." }, "JobServiceType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "studio", "tracking" ] } ], "description": "Job service endpoint type." }, "JobType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "command" ] } ], "description": "Type of a job." }, "KtoFeedbackColumnMapping": { "type": "object", "required": [ "prompt", "response", "label" ], "properties": { "prompt": { "type": "string", "description": "Actual dataset column name containing prompts, for example 'prompt' or 'question'." }, "response": { "type": "string", "description": "Actual dataset column name containing responses, for example 'response', 'completion', or 'answer'." }, "label": { "type": "string", "description": "Actual dataset column name containing the binary desirability label, for example 'label' or 'is_desirable'." } }, "description": "Column mapping for KTO feedback datasets. Keys are logical fields expected by KTO; values are the exact column names in the referenced dataset asset." }, "KtoTrainingConfiguration": { "type": "object", "required": [ "algorithm" ], "properties": { "algorithm": { "type": "string", "enum": [ "kto" ], "description": "Training algorithm, always 'kto'." }, "lora": { "allOf": [ { "$ref": "#/components/schemas/TrainingLoraConfiguration" } ], "description": "LoRA adapter configuration." }, "eval": { "allOf": [ { "$ref": "#/components/schemas/TrainingEvalConfiguration" } ], "description": "Evaluation configuration." } }, "allOf": [ { "$ref": "#/components/schemas/TrainingConfiguration" } ], "description": "Kahneman-Tversky optimization training recipe." }, "KtoTrainingDatasetConfiguration": { "type": "object", "required": [ "train", "columns" ], "properties": { "train": { "type": "string", "description": "Training dataset asset reference." }, "eval": { "type": "string", "description": "Optional evaluation dataset asset reference." }, "columns": { "allOf": [ { "$ref": "#/components/schemas/KtoFeedbackColumnMapping" } ], "description": "Mapping from KTO logical fields to actual dataset column names. KTO requires 'prompt', 'response', and 'label'." }, "data_format": { "allOf": [ { "$ref": "#/components/schemas/TrainingDataFormatConfiguration" } ], "description": "Conversational data formatting options." } }, "description": "Dataset configuration for managed KTO training." }, "KtoTrainingJob": { "type": "object", "required": [ "type", "dataset" ], "properties": { "type": { "type": "string", "enum": [ "kto" ], "description": "Managed training job type, always 'kto'." }, "dataset": { "allOf": [ { "$ref": "#/components/schemas/KtoTrainingDatasetConfiguration" } ], "description": "Training and optional evaluation datasets." }, "runtime": { "allOf": [ { "$ref": "#/components/schemas/KtoTrainingRuntimeConfiguration" } ], "description": "Runtime options for managed KTO." } }, "allOf": [ { "$ref": "#/components/schemas/ModelTrainingJobCreate" } ], "description": "Request body for creating a managed KTO training job from a base model." }, "KtoTrainingRuntimeConfiguration": { "type": "object", "properties": { "framework": { "allOf": [ { "$ref": "#/components/schemas/TrainingFramework" } ], "description": "Training framework implementation. If omitted, the service selects a compatible framework." }, "hyperparameters": { "type": "object", "additionalProperties": {}, "description": "Algorithm-specific hyperparameters passed through to the selected framework." }, "desirable_weight": { "type": "number", "format": "double", "description": "Weight applied to desirable examples." }, "undesirable_weight": { "type": "number", "format": "double", "description": "Weight applied to undesirable examples." }, "lora": { "allOf": [ { "$ref": "#/components/schemas/TrainingLoraConfiguration" } ], "description": "LoRA adapter configuration." }, "eval": { "allOf": [ { "$ref": "#/components/schemas/TrainingEvalConfiguration" } ], "description": "Evaluation configuration." }, "packaging": { "allOf": [ { "$ref": "#/components/schemas/ModelTrainingPackagingConfiguration" } ], "description": "Model artifact packaging options." } }, "description": "Runtime options for managed KTO training." }, "ListViewType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "active_only", "archived_only", "all" ] } ], "description": "Specifies which jobs to include in a list result based on their lifecycle state." }, "ManagedAzureAISearchIndex": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "ManagedAzureSearch" ], "description": "Type of index" } }, "allOf": [ { "$ref": "#/components/schemas/Index" } ], "description": "Managed Azure AI Search Index Definition" }, "ManagedAzureAISearchIndexUpdate": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "ManagedAzureSearch" ], "description": "Type of index" } }, "allOf": [ { "$ref": "#/components/schemas/IndexUpdate" } ], "description": "Managed Azure AI Search Index Definition" }, "MemoryItem": { "type": "object", "required": [ "memory_id", "updated_at", "scope", "content", "kind" ], "properties": { "memory_id": { "type": "string", "description": "The unique ID of the memory item." }, "updated_at": { "type": "integer", "format": "unixtime", "description": "The last update time of the memory item." }, "scope": { "type": "string", "description": "The namespace that logically groups and isolates memories, such as a user ID." }, "content": { "type": "string", "description": "The content of the memory." }, "kind": { "allOf": [ { "$ref": "#/components/schemas/MemoryItemKind" } ], "description": "The kind of the memory item." } }, "discriminator": { "propertyName": "kind", "mapping": { "user_profile": "#/components/schemas/UserProfileMemoryItem", "chat_summary": "#/components/schemas/ChatSummaryMemoryItem" } }, "description": "A single memory item stored in the memory store, containing content and metadata.", "x-ms-foundry-meta": { "conditional_previews": [ "MemoryStores=V1Preview" ] } }, "MemoryItemKind": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "user_profile", "chat_summary" ] } ], "description": "Memory item kind.", "x-ms-foundry-meta": { "conditional_previews": [ "MemoryStores=V1Preview" ] } }, "MemoryOperation": { "type": "object", "required": [ "kind", "memory_item" ], "properties": { "kind": { "allOf": [ { "$ref": "#/components/schemas/MemoryOperationKind" } ], "description": "The type of memory operation being performed." }, "memory_item": { "allOf": [ { "$ref": "#/components/schemas/MemoryItem" } ], "description": "The memory item to create, update, or delete." } }, "description": "Represents a single memory operation (create, update, or delete) performed on a memory item.", "x-ms-foundry-meta": { "conditional_previews": [ "MemoryStores=V1Preview" ] } }, "MemoryOperationKind": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "create", "update", "delete" ] } ], "description": "Memory operation kind.", "x-ms-foundry-meta": { "conditional_previews": [ "MemoryStores=V1Preview" ] } }, "MemorySearchItem": { "type": "object", "required": [ "memory_item" ], "properties": { "memory_item": { "allOf": [ { "$ref": "#/components/schemas/MemoryItem" } ], "description": "Retrieved memory item." } }, "description": "A retrieved memory item from memory search.", "x-ms-foundry-meta": { "conditional_previews": [ "MemoryStores=V1Preview" ] } }, "MemorySearchOptions": { "type": "object", "properties": { "max_memories": { "type": "integer", "format": "int32", "description": "Maximum number of memory items to return." } }, "description": "Memory search options.", "x-ms-foundry-meta": { "conditional_previews": [ "MemoryStores=V1Preview" ] } }, "MemorySearchPreviewTool": { "type": "object", "required": [ "type", "memory_store_name", "scope" ], "properties": { "type": { "type": "string", "enum": [ "memory_search_preview" ], "description": "The type of the tool. Always `memory_search_preview`." }, "name": { "type": "string", "description": "Optional user-defined name for this tool or configuration." }, "description": { "type": "string", "description": "Optional user-defined description for this tool or configuration." }, "memory_store_name": { "type": "string", "description": "The name of the memory store to use." }, "scope": { "type": "string", "description": "The namespace used to group and isolate memories, such as a user ID.\nLimits which memories can be retrieved or updated.\nUse special variable `{{$userId}}` to scope memories to the current signed-in user." }, "search_options": { "allOf": [ { "$ref": "#/components/schemas/MemorySearchOptions" } ], "description": "Options for searching the memory store." }, "update_delay": { "type": "integer", "format": "int32", "description": "Time to wait before updating memories after inactivity (seconds). Default 300.", "default": 300 } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Tool" } ], "description": "A tool for integrating memories into the agent." }, "MemorySearchToolCallItemParam": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "memory_search_call" ] }, "results": { "type": "array", "items": { "$ref": "#/components/schemas/MemorySearchItem" }, "nullable": true, "description": "The results returned from the memory search." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Item" } ] }, "MemorySearchToolCallItemResource": { "type": "object", "required": [ "type", "status" ], "properties": { "type": { "type": "string", "enum": [ "memory_search_call" ] }, "status": { "type": "string", "enum": [ "in_progress", "searching", "completed", "incomplete", "failed" ], "description": "The status of the memory search tool call. One of `in_progress`,\n`searching`, `completed`, `incomplete` or `failed`," }, "results": { "type": "array", "items": { "$ref": "#/components/schemas/MemorySearchItem" }, "nullable": true, "description": "The results returned from the memory search." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ] }, "MemoryStoreDefaultDefinition": { "type": "object", "required": [ "kind", "chat_model", "embedding_model" ], "properties": { "kind": { "type": "string", "enum": [ "default" ], "description": "The kind of the memory store." }, "chat_model": { "type": "string", "description": "The name or identifier of the chat completion model deployment used for memory processing." }, "embedding_model": { "type": "string", "description": "The name or identifier of the embedding model deployment used for memory processing." }, "options": { "allOf": [ { "$ref": "#/components/schemas/MemoryStoreDefaultOptions" } ], "description": "Default memory store options." } }, "allOf": [ { "$ref": "#/components/schemas/MemoryStoreDefinition" } ], "description": "Default memory store implementation.", "x-ms-foundry-meta": { "conditional_previews": [ "MemoryStores=V1Preview" ] } }, "MemoryStoreDefaultOptions": { "type": "object", "required": [ "user_profile_enabled", "chat_summary_enabled" ], "properties": { "user_profile_enabled": { "type": "boolean", "description": "Whether to enable user profile extraction and storage. Default is true.", "default": true }, "user_profile_details": { "type": "string", "description": "Specific categories or types of user profile information to extract and store." }, "chat_summary_enabled": { "type": "boolean", "description": "Whether to enable chat summary extraction and storage. Default is true.", "default": true } }, "description": "Default memory store configurations.", "x-ms-foundry-meta": { "conditional_previews": [ "MemoryStores=V1Preview" ] } }, "MemoryStoreDefinition": { "type": "object", "required": [ "kind" ], "properties": { "kind": { "allOf": [ { "$ref": "#/components/schemas/MemoryStoreKind" } ], "description": "The kind of the memory store." } }, "discriminator": { "propertyName": "kind", "mapping": { "default": "#/components/schemas/MemoryStoreDefaultDefinition" } }, "description": "Base definition for memory store configurations.", "x-ms-foundry-meta": { "conditional_previews": [ "MemoryStores=V1Preview" ] } }, "MemoryStoreDeleteScopeResponse": { "type": "object", "required": [ "object", "name", "scope", "deleted" ], "properties": { "object": { "type": "string", "enum": [ "memory_store.scope.deleted" ], "description": "The object type. Always 'memory_store.scope.deleted'." }, "name": { "type": "string", "description": "The name of the memory store." }, "scope": { "type": "string", "description": "The scope from which memories were deleted." }, "deleted": { "type": "boolean", "description": "Whether the deletion operation was successful." } }, "description": "Response for deleting memories from a scope.", "x-ms-foundry-meta": { "conditional_previews": [ "MemoryStores=V1Preview" ] } }, "MemoryStoreKind": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "default" ] } ], "description": "The type of memory store implementation to use.", "x-ms-foundry-meta": { "conditional_previews": [ "MemoryStores=V1Preview" ] } }, "MemoryStoreObject": { "type": "object", "required": [ "object", "id", "created_at", "updated_at", "name", "definition" ], "properties": { "object": { "type": "string", "enum": [ "memory_store" ], "description": "The object type, which is always 'memory_store'." }, "id": { "type": "string", "description": "The unique identifier of the memory store." }, "created_at": { "type": "integer", "format": "unixtime", "description": "The Unix timestamp (seconds) when the memory store was created." }, "updated_at": { "type": "integer", "format": "unixtime", "description": "The Unix timestamp (seconds) when the memory store was last updated." }, "name": { "type": "string", "maxLength": 256, "description": "The name of the memory store." }, "description": { "type": "string", "maxLength": 512, "description": "A human-readable description of the memory store." }, "metadata": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Arbitrary key-value metadata to associate with the memory store." }, "definition": { "allOf": [ { "$ref": "#/components/schemas/MemoryStoreDefinition" } ], "description": "The definition of the memory store." } }, "description": "A memory store that can store and retrieve user memories.", "x-ms-foundry-meta": { "conditional_previews": [ "MemoryStores=V1Preview" ] } }, "MemoryStoreOperationUsage": { "type": "object", "required": [ "embedding_tokens", "input_tokens", "input_tokens_details", "output_tokens", "output_tokens_details", "total_tokens" ], "properties": { "embedding_tokens": { "type": "integer", "format": "int32", "description": "The number of embedding tokens." }, "input_tokens": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The number of input tokens." }, "input_tokens_details": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ResponseUsageInputTokensDetails" } ], "description": "A detailed breakdown of the input tokens." }, "output_tokens": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The number of output tokens." }, "output_tokens_details": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ResponseUsageOutputTokensDetails" } ], "description": "A detailed breakdown of the output tokens." }, "total_tokens": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The total number of tokens used." } }, "description": "Usage statistics of a memory store operation.", "x-ms-foundry-meta": { "conditional_previews": [ "MemoryStores=V1Preview" ] } }, "MemoryStoreSearchResponse": { "type": "object", "required": [ "search_id", "memories", "usage" ], "properties": { "search_id": { "type": "string", "description": "The unique ID of this search request. Use this value as previous_search_id in subsequent requests to perform incremental searches." }, "memories": { "type": "array", "items": { "$ref": "#/components/schemas/MemorySearchItem" }, "description": "Related memory items found during the search operation." }, "usage": { "allOf": [ { "$ref": "#/components/schemas/MemoryStoreOperationUsage" } ], "description": "Usage statistics associated with the memory search operation." } }, "description": "Memory search response.", "x-ms-foundry-meta": { "conditional_previews": [ "MemoryStores=V1Preview" ] } }, "MemoryStoreUpdateCompletedResult": { "type": "object", "required": [ "memory_operations", "usage" ], "properties": { "memory_operations": { "type": "array", "items": { "$ref": "#/components/schemas/MemoryOperation" }, "description": "A list of individual memory operations that were performed during the update." }, "usage": { "allOf": [ { "$ref": "#/components/schemas/MemoryStoreOperationUsage" } ], "description": "Usage statistics associated with the memory update operation." } }, "description": "Memory update result.", "x-ms-foundry-meta": { "conditional_previews": [ "MemoryStores=V1Preview" ] } }, "MemoryStoreUpdateResponse": { "type": "object", "required": [ "update_id", "status" ], "properties": { "update_id": { "type": "string", "description": "The unique ID of this update request. Use this value as previous_update_id in subsequent requests to perform incremental updates." }, "status": { "allOf": [ { "$ref": "#/components/schemas/MemoryStoreUpdateStatus" } ], "description": "The status of the memory update operation. One of \"queued\", \"in_progress\", \"completed\", \"failed\", or \"superseded\"." }, "superseded_by": { "type": "string", "description": "The update_id the operation was superseded by when status is \"superseded\"." }, "result": { "allOf": [ { "$ref": "#/components/schemas/MemoryStoreUpdateCompletedResult" } ], "description": "The result of memory store update operation when status is \"completed\"." }, "error": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.Error" } ], "description": "Error object that describes the error when status is \"failed\"." } }, "description": "Provides the status of a memory store update operation.", "x-ms-foundry-meta": { "conditional_previews": [ "MemoryStores=V1Preview" ] } }, "MemoryStoreUpdateStatus": { "type": "string", "enum": [ "queued", "in_progress", "completed", "failed", "superseded" ], "description": "Status of a memory store update operation.", "x-ms-foundry-meta": { "conditional_previews": [ "MemoryStores=V1Preview" ] } }, "MicrosoftFabricPreviewTool": { "type": "object", "required": [ "type", "fabric_dataagent_preview" ], "properties": { "type": { "type": "string", "enum": [ "fabric_dataagent_preview" ], "description": "The object type, which is always 'fabric_dataagent_preview'." }, "name": { "type": "string", "description": "Optional user-defined name for this tool or configuration." }, "description": { "type": "string", "description": "Optional user-defined description for this tool or configuration." }, "fabric_dataagent_preview": { "allOf": [ { "$ref": "#/components/schemas/FabricDataAgentToolParameters" } ], "description": "The fabric data agent tool parameters." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Tool" } ], "description": "The input definition information for a Microsoft Fabric tool as used to configure an agent." }, "Mlflow.MlflowPayload": { "type": "object", "additionalProperties": {}, "description": "Generic MLflow compatibility request payload." }, "Mlflow.MlflowResponse": { "type": "object", "additionalProperties": {}, "description": "Generic MLflow compatibility response payload." }, "Model": { "type": "object", "required": [ "name", "version" ], "properties": { "id": { "type": "string", "description": "Asset ID, a unique identifier for the model asset.", "readOnly": true }, "name": { "type": "string", "description": "The name of the model asset.", "readOnly": true }, "version": { "type": "string", "description": "The version of the model asset.", "readOnly": true }, "description": { "type": "string", "description": "The model asset description text.", "readOnly": true }, "tags": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Tags associated with the model asset.", "readOnly": true }, "uri": { "type": "string", "description": "URI of the registered model artifact.", "readOnly": true }, "base_model": { "type": "string", "description": "Base model used to create this model, when the model was produced by managed training.", "readOnly": true }, "training_job": { "type": "string", "description": "Backing training job that produced this model, when available.", "readOnly": true } }, "description": "Model asset produced by managed model training." }, "ModelDeployment": { "type": "object", "required": [ "type", "modelName", "modelVersion", "modelPublisher", "capabilities", "sku" ], "properties": { "type": { "type": "string", "enum": [ "ModelDeployment" ], "description": "The type of the deployment" }, "modelName": { "type": "string", "description": "Publisher-specific name of the deployed model", "readOnly": true }, "modelVersion": { "type": "string", "description": "Publisher-specific version of the deployed model", "readOnly": true }, "modelPublisher": { "type": "string", "description": "Name of the deployed model's publisher", "readOnly": true }, "capabilities": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Capabilities of deployed model", "readOnly": true }, "sku": { "allOf": [ { "$ref": "#/components/schemas/Sku" } ], "description": "Sku of the model deployment", "readOnly": true }, "connectionName": { "type": "string", "description": "Name of the connection the deployment comes from", "readOnly": true } }, "allOf": [ { "$ref": "#/components/schemas/Deployment" } ], "description": "Model Deployment Definition" }, "ModelSamplingParams": { "type": "object", "required": [ "temperature", "top_p", "seed", "max_completion_tokens" ], "properties": { "temperature": { "type": "number", "format": "float", "description": "The temperature parameter for sampling." }, "top_p": { "type": "number", "format": "float", "description": "The top-p parameter for nucleus sampling." }, "seed": { "type": "integer", "format": "int32", "description": "The random seed for reproducibility." }, "max_completion_tokens": { "type": "integer", "format": "int32", "description": "The maximum number of tokens allowed in the completion." } }, "description": "Represents a set of parameters used to control the sampling behavior of a language model during text generation." }, "ModelSamplingParamsUpdate": { "type": "object", "properties": { "temperature": { "type": "number", "format": "float", "description": "The temperature parameter for sampling." }, "top_p": { "type": "number", "format": "float", "description": "The top-p parameter for nucleus sampling." }, "seed": { "type": "integer", "format": "int32", "description": "The random seed for reproducibility." }, "max_completion_tokens": { "type": "integer", "format": "int32", "description": "The maximum number of tokens allowed in the completion." } }, "description": "Represents a set of parameters used to control the sampling behavior of a language model during text generation." }, "ModelTrainingComputeConfiguration": { "type": "object", "required": [ "id" ], "properties": { "id": { "type": "string", "description": "Compute resource ID used to run the managed training job." }, "resources": { "allOf": [ { "$ref": "#/components/schemas/JobResourceConfiguration" } ], "description": "Compute resource configuration for the managed training job." }, "gpu_count": { "type": "integer", "format": "int32", "description": "Number of GPUs requested by the managed training job." }, "distribution": { "allOf": [ { "$ref": "#/components/schemas/DistributionConfiguration" } ], "description": "Distribution configuration for the managed training job." }, "queue_settings": { "allOf": [ { "$ref": "#/components/schemas/QueueSettings" } ], "description": "Queue settings for the managed training job." }, "user_assigned_identity_id": { "type": "string", "description": "ARM resource ID of a user-assigned managed identity attached to the Foundry project." } }, "description": "Compute placement for a managed model training job." }, "ModelTrainingJobCreate": { "type": "object", "required": [ "type", "model", "compute" ], "properties": { "type": { "type": "string", "description": "Managed training job type." }, "name": { "type": "string", "description": "Optional name of the model to create. If omitted, the service generates one." }, "version": { "type": "string", "description": "Optional version of the model to create. If omitted, the service generates one." }, "description": { "type": "string", "description": "Optional description for the model to create." }, "tags": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Optional tags for the model to create." }, "model": { "type": "string", "description": "Base model asset reference." }, "compute": { "allOf": [ { "$ref": "#/components/schemas/ModelTrainingComputeConfiguration" } ], "description": "Compute placement for the managed training job." } }, "discriminator": { "propertyName": "type", "mapping": { "sft": "#/components/schemas/SftTrainingJob", "preference": "#/components/schemas/PreferenceTrainingJob", "kto": "#/components/schemas/KtoTrainingJob", "reward_model": "#/components/schemas/RewardModelTrainingJob", "grpo": "#/components/schemas/GrpoTrainingJob", "policy_gradient": "#/components/schemas/PolicyGradientTrainingJob", "ppo": "#/components/schemas/PpoTrainingJob" } }, "description": "Base request body for creating a managed training job from a base model." }, "ModelTrainingOperation": { "type": "object", "required": [ "operation_id", "status" ], "properties": { "operation_id": { "type": "string", "description": "Operation identifier for the managed model training request." }, "status": { "allOf": [ { "$ref": "#/components/schemas/ModelTrainingOperationStatus" } ], "description": "Managed model training operation status." }, "result": { "allOf": [ { "$ref": "#/components/schemas/Model" } ], "description": "The model produced by managed training when the operation succeeds." }, "error": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.Error" } ], "description": "Error object that describes the failure when status is 'failed'." } }, "description": "Status resource for a managed model training operation." }, "ModelTrainingOperationStatus": { "type": "string", "enum": [ "queued", "in_progress", "succeeded", "failed", "canceled" ], "description": "Status of a managed model training operation." }, "ModelTrainingPackagingConfiguration": { "type": "object", "properties": { "mode": { "allOf": [ { "$ref": "#/components/schemas/ModelTrainingPackagingMode" } ], "description": "How the trained model artifact should be packaged.", "default": "merged_model" } }, "description": "Model artifact packaging options." }, "ModelTrainingPackagingMode": { "type": "string", "enum": [ "merged_model", "adapter", "model_and_adapter" ], "description": "Output packaging for a managed model training job." }, "ModelTrainingReferenceConfiguration": { "type": "object", "required": [ "kind" ], "properties": { "kind": { "type": "string", "description": "Reference policy kind." } }, "discriminator": { "propertyName": "kind", "mapping": { "base_model": "#/components/schemas/BaseModelReferenceConfiguration", "model": "#/components/schemas/ExplicitModelReferenceConfiguration", "none": "#/components/schemas/NoReferenceConfiguration" } }, "description": "Reference policy used for preference optimization or online reinforcement training." }, "MonthlyRecurrenceSchedule": { "type": "object", "required": [ "type", "daysOfMonth" ], "properties": { "type": { "type": "string", "enum": [ "Monthly" ], "description": "Monthly recurrence type." }, "daysOfMonth": { "type": "array", "items": { "type": "integer", "format": "int32" }, "description": "Days of the month for the recurrence schedule." } }, "allOf": [ { "$ref": "#/components/schemas/RecurrenceSchedule" } ], "description": "Monthly recurrence schedule." }, "MpiDistribution": { "type": "object", "required": [ "distribution_type" ], "properties": { "distribution_type": { "type": "string", "enum": [ "mpi" ], "description": "Specifies the type of distribution framework." }, "process_count_per_node": { "type": "integer", "format": "int32", "description": "Number of processes per MPI node." } }, "allOf": [ { "$ref": "#/components/schemas/DistributionConfiguration" } ], "description": "MPI distribution configuration." }, "NoAuthenticationCredentials": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "None" ], "description": "The credential type ", "readOnly": true } }, "allOf": [ { "$ref": "#/components/schemas/BaseCredentials" } ], "description": "Credentials that do not require authentication" }, "NoReferenceConfiguration": { "type": "object", "required": [ "kind" ], "properties": { "kind": { "type": "string", "enum": [ "none" ], "description": "Reference policy kind, always 'none'." } }, "allOf": [ { "$ref": "#/components/schemas/ModelTrainingReferenceConfiguration" } ], "description": "Disable reference policy or KL anchoring." }, "OAuthConsentRequestOutputItem": { "type": "object", "required": [ "id", "type", "consent_link", "server_label" ], "properties": { "id": { "type": "string" }, "type": { "type": "string", "enum": [ "oauth_consent_request" ] }, "consent_link": { "type": "string", "description": "The link the user can use to perform OAuth consent." }, "server_label": { "type": "string", "description": "The server label for the OAuth consent request." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ], "description": "Request from the service for the user to perform OAuth consent." }, "OneTimeTrigger": { "type": "object", "required": [ "type", "triggerAt" ], "properties": { "type": { "type": "string", "enum": [ "OneTime" ] }, "triggerAt": { "type": "string", "description": "Date and time for the one-time trigger in ISO 8601 format." }, "timeZone": { "type": "string", "description": "Time zone for the one-time trigger.", "default": "UTC" } }, "allOf": [ { "$ref": "#/components/schemas/Trigger" } ], "description": "One-time trigger." }, "OpenAI.Annotation": { "type": "object", "required": [ "type" ], "properties": { "type": { "$ref": "#/components/schemas/OpenAI.AnnotationType" } }, "discriminator": { "propertyName": "type", "mapping": { "file_citation": "#/components/schemas/OpenAI.FileCitationBody", "url_citation": "#/components/schemas/OpenAI.UrlCitationBody", "container_file_citation": "#/components/schemas/OpenAI.ContainerFileCitationBody", "file_path": "#/components/schemas/OpenAI.FilePath" } }, "description": "An annotation that applies to a span of output text." }, "OpenAI.AnnotationType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "file_citation", "url_citation", "container_file_citation", "file_path" ] } ] }, "OpenAI.ApplyPatchCallOutputStatus": { "type": "string", "enum": [ "completed", "failed" ] }, "OpenAI.ApplyPatchCallOutputStatusParam": { "type": "string", "enum": [ "completed", "failed" ], "description": "Outcome values reported for apply_patch tool call outputs.", "title": "Apply patch call output status" }, "OpenAI.ApplyPatchCallStatus": { "type": "string", "enum": [ "in_progress", "completed" ] }, "OpenAI.ApplyPatchCallStatusParam": { "type": "string", "enum": [ "in_progress", "completed" ], "description": "Status values reported for apply_patch tool calls.", "title": "Apply patch call status" }, "OpenAI.ApplyPatchCreateFileOperation": { "type": "object", "required": [ "type", "path", "diff" ], "properties": { "type": { "type": "string", "enum": [ "create_file" ], "description": "Create a new file with the provided diff.", "x-stainless-const": true, "default": "create_file" }, "path": { "type": "string", "description": "Path of the file to create." }, "diff": { "type": "string", "description": "Diff to apply." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ApplyPatchFileOperation" } ], "description": "Instruction describing how to create a file via the apply_patch tool.", "title": "Apply patch create file operation" }, "OpenAI.ApplyPatchCreateFileOperationParam": { "type": "object", "required": [ "type", "path", "diff" ], "properties": { "type": { "type": "string", "enum": [ "create_file" ], "description": "The operation type. Always `create_file`.", "x-stainless-const": true, "default": "create_file" }, "path": { "type": "string", "minLength": 1, "description": "Path of the file to create relative to the workspace root." }, "diff": { "type": "string", "maxLength": 10485760, "description": "Unified diff content to apply when creating the file." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ApplyPatchOperationParam" } ], "description": "Instruction for creating a new file via the apply_patch tool.", "title": "Apply patch create file operation" }, "OpenAI.ApplyPatchDeleteFileOperation": { "type": "object", "required": [ "type", "path" ], "properties": { "type": { "type": "string", "enum": [ "delete_file" ], "description": "Delete the specified file.", "x-stainless-const": true, "default": "delete_file" }, "path": { "type": "string", "description": "Path of the file to delete." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ApplyPatchFileOperation" } ], "description": "Instruction describing how to delete a file via the apply_patch tool.", "title": "Apply patch delete file operation" }, "OpenAI.ApplyPatchDeleteFileOperationParam": { "type": "object", "required": [ "type", "path" ], "properties": { "type": { "type": "string", "enum": [ "delete_file" ], "description": "The operation type. Always `delete_file`.", "x-stainless-const": true, "default": "delete_file" }, "path": { "type": "string", "minLength": 1, "description": "Path of the file to delete relative to the workspace root." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ApplyPatchOperationParam" } ], "description": "Instruction for deleting an existing file via the apply_patch tool.", "title": "Apply patch delete file operation" }, "OpenAI.ApplyPatchFileOperation": { "type": "object", "required": [ "type" ], "properties": { "type": { "$ref": "#/components/schemas/OpenAI.ApplyPatchFileOperationType" } }, "discriminator": { "propertyName": "type", "mapping": { "create_file": "#/components/schemas/OpenAI.ApplyPatchCreateFileOperation", "delete_file": "#/components/schemas/OpenAI.ApplyPatchDeleteFileOperation", "update_file": "#/components/schemas/OpenAI.ApplyPatchUpdateFileOperation" } }, "description": "One of the create_file, delete_file, or update_file operations applied via apply_patch.", "title": "Apply patch operation" }, "OpenAI.ApplyPatchFileOperationType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "create_file", "delete_file", "update_file" ] } ] }, "OpenAI.ApplyPatchOperationParam": { "type": "object", "required": [ "type" ], "properties": { "type": { "$ref": "#/components/schemas/OpenAI.ApplyPatchOperationParamType" } }, "discriminator": { "propertyName": "type", "mapping": { "create_file": "#/components/schemas/OpenAI.ApplyPatchCreateFileOperationParam", "delete_file": "#/components/schemas/OpenAI.ApplyPatchDeleteFileOperationParam", "update_file": "#/components/schemas/OpenAI.ApplyPatchUpdateFileOperationParam" } }, "description": "One of the create_file, delete_file, or update_file operations supplied to the apply_patch tool.", "title": "Apply patch operation" }, "OpenAI.ApplyPatchOperationParamType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "create_file", "delete_file", "update_file" ] } ] }, "OpenAI.ApplyPatchToolParam": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "apply_patch" ], "description": "The type of the tool. Always `apply_patch`.", "x-stainless-const": true, "default": "apply_patch" } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Tool" } ], "description": "Allows the assistant to create, delete, or update files using unified diffs.", "title": "Apply patch tool" }, "OpenAI.ApplyPatchUpdateFileOperation": { "type": "object", "required": [ "type", "path", "diff" ], "properties": { "type": { "type": "string", "enum": [ "update_file" ], "description": "Update an existing file with the provided diff.", "x-stainless-const": true, "default": "update_file" }, "path": { "type": "string", "description": "Path of the file to update." }, "diff": { "type": "string", "description": "Diff to apply." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ApplyPatchFileOperation" } ], "description": "Instruction describing how to update a file via the apply_patch tool.", "title": "Apply patch update file operation" }, "OpenAI.ApplyPatchUpdateFileOperationParam": { "type": "object", "required": [ "type", "path", "diff" ], "properties": { "type": { "type": "string", "enum": [ "update_file" ], "description": "The operation type. Always `update_file`.", "x-stainless-const": true, "default": "update_file" }, "path": { "type": "string", "minLength": 1, "description": "Path of the file to update relative to the workspace root." }, "diff": { "type": "string", "maxLength": 10485760, "description": "Unified diff content to apply to the existing file." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ApplyPatchOperationParam" } ], "description": "Instruction for updating an existing file via the apply_patch tool.", "title": "Apply patch update file operation" }, "OpenAI.ApproximateLocation": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "approximate" ], "description": "The type of location approximation. Always `approximate`.", "x-stainless-const": true, "default": "approximate" }, "country": { "type": "string", "nullable": true }, "region": { "type": "string", "nullable": true }, "city": { "type": "string", "nullable": true }, "timezone": { "type": "string", "nullable": true } } }, "OpenAI.AutoCodeInterpreterToolParam": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "auto" ], "description": "Always `auto`.", "x-stainless-const": true, "default": "auto" }, "file_ids": { "type": "array", "items": { "type": "string" }, "maxItems": 50, "description": "An optional list of uploaded files to make available to your code." }, "memory_limit": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ContainerMemoryLimit" } ], "nullable": true }, "network_policy": { "$ref": "#/components/schemas/OpenAI.ContainerNetworkPolicyParam" } }, "description": "Configuration for a code interpreter container. Optionally specify the IDs of the files to run the code on.", "title": "Automatic Code Interpreter Tool Parameters" }, "OpenAI.ChatCompletionTool": { "type": "object", "required": [ "type", "function" ], "properties": { "type": { "type": "string", "enum": [ "function" ], "description": "The type of the tool. Currently, only `function` is supported.", "x-stainless-const": true }, "function": { "$ref": "#/components/schemas/OpenAI.FunctionObject" } }, "description": "A function tool that can be used to generate a response.", "title": "Function tool" }, "OpenAI.ChatModel": { "type": "string", "enum": [ "gpt-5.2", "gpt-5.2-2025-12-11", "gpt-5.2-chat-latest", "gpt-5.2-pro", "gpt-5.2-pro-2025-12-11", "gpt-5.1", "gpt-5.1-2025-11-13", "gpt-5.1-codex", "gpt-5.1-mini", "gpt-5.1-chat-latest", "gpt-5", "gpt-5-mini", "gpt-5-nano", "gpt-5-2025-08-07", "gpt-5-mini-2025-08-07", "gpt-5-nano-2025-08-07", "gpt-5-chat-latest", "gpt-4.1", "gpt-4.1-mini", "gpt-4.1-nano", "gpt-4.1-2025-04-14", "gpt-4.1-mini-2025-04-14", "gpt-4.1-nano-2025-04-14", "o4-mini", "o4-mini-2025-04-16", "o3", "o3-2025-04-16", "o3-mini", "o3-mini-2025-01-31", "o1", "o1-2024-12-17", "o1-preview", "o1-preview-2024-09-12", "o1-mini", "o1-mini-2024-09-12", "gpt-4o", "gpt-4o-2024-11-20", "gpt-4o-2024-08-06", "gpt-4o-2024-05-13", "gpt-4o-audio-preview", "gpt-4o-audio-preview-2024-10-01", "gpt-4o-audio-preview-2024-12-17", "gpt-4o-audio-preview-2025-06-03", "gpt-4o-mini-audio-preview", "gpt-4o-mini-audio-preview-2024-12-17", "gpt-4o-search-preview", "gpt-4o-mini-search-preview", "gpt-4o-search-preview-2025-03-11", "gpt-4o-mini-search-preview-2025-03-11", "chatgpt-4o-latest", "codex-mini-latest", "gpt-4o-mini", "gpt-4o-mini-2024-07-18", "gpt-4-turbo", "gpt-4-turbo-2024-04-09", "gpt-4-0125-preview", "gpt-4-turbo-preview", "gpt-4-1106-preview", "gpt-4-vision-preview", "gpt-4", "gpt-4-0314", "gpt-4-0613", "gpt-4-32k", "gpt-4-32k-0314", "gpt-4-32k-0613", "gpt-3.5-turbo", "gpt-3.5-turbo-16k", "gpt-3.5-turbo-0301", "gpt-3.5-turbo-0613", "gpt-3.5-turbo-1106", "gpt-3.5-turbo-0125", "gpt-3.5-turbo-16k-0613" ] }, "OpenAI.ClickButtonType": { "type": "string", "enum": [ "left", "right", "wheel", "back", "forward" ] }, "OpenAI.ClickParam": { "type": "object", "required": [ "type", "button", "x", "y" ], "properties": { "type": { "type": "string", "enum": [ "click" ], "description": "Specifies the event type. For a click action, this property is always `click`.", "x-stainless-const": true, "default": "click" }, "button": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ClickButtonType" } ], "description": "Indicates which mouse button was pressed during the click. One of `left`, `right`, `wheel`, `back`, or `forward`." }, "x": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The x-coordinate where the click occurred." }, "y": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The y-coordinate where the click occurred." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ComputerAction" } ], "description": "A click action.", "title": "Click" }, "OpenAI.CodeInterpreterOutputImage": { "type": "object", "required": [ "type", "url" ], "properties": { "type": { "type": "string", "enum": [ "image" ], "description": "The type of the output. Always `image`.", "x-stainless-const": true, "default": "image" }, "url": { "type": "string", "format": "uri", "description": "The URL of the image output from the code interpreter." } }, "description": "The image output from the code interpreter.", "title": "Code interpreter output image" }, "OpenAI.CodeInterpreterOutputLogs": { "type": "object", "required": [ "type", "logs" ], "properties": { "type": { "type": "string", "enum": [ "logs" ], "description": "The type of the output. Always `logs`.", "x-stainless-const": true, "default": "logs" }, "logs": { "type": "string", "description": "The logs output from the code interpreter." } }, "description": "The logs output from the code interpreter.", "title": "Code interpreter output logs" }, "OpenAI.CodeInterpreterTool": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "code_interpreter" ], "description": "The type of the code interpreter tool. Always `code_interpreter`.", "x-stainless-const": true }, "name": { "type": "string", "description": "Optional user-defined name for this tool or configuration." }, "description": { "type": "string", "description": "Optional user-defined description for this tool or configuration." }, "container": { "anyOf": [ { "type": "string" }, { "$ref": "#/components/schemas/OpenAI.AutoCodeInterpreterToolParam" } ], "description": "The code interpreter container. Can be a container ID or an object that\nspecifies uploaded file IDs to make available to your code, along with an\noptional `memory_limit` setting.\nIf not provided, the service assumes auto." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Tool" } ], "description": "A tool that runs Python code to help generate a response to a prompt.", "title": "Code interpreter" }, "OpenAI.CompactResource": { "type": "object", "required": [ "id", "object", "output", "created_at", "usage" ], "properties": { "id": { "type": "string", "description": "The unique identifier for the compacted response." }, "object": { "type": "string", "enum": [ "response.compaction" ], "description": "The object type. Always `response.compaction`.", "x-stainless-const": true, "default": "response.compaction" }, "output": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.ItemField" }, "description": "The compacted list of output items." }, "created_at": { "type": "integer", "format": "unixtime", "description": "Unix timestamp (in seconds) when the compacted conversation was created." }, "usage": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ResponseUsage" } ], "description": "Token accounting for the compaction pass, including cached, reasoning, and total tokens." } }, "title": "The compacted response object" }, "OpenAI.CompactResponseMethodPublicBody": { "type": "object", "required": [ "model" ], "properties": { "model": { "$ref": "#/components/schemas/OpenAI.ModelIdsCompaction" }, "input": { "anyOf": [ { "type": "string" }, { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.InputItem" } } ], "nullable": true }, "previous_response_id": { "type": "string", "nullable": true }, "instructions": { "type": "string", "nullable": true } } }, "OpenAI.ComparisonFilter": { "type": "object", "required": [ "type", "key", "value" ], "properties": { "type": { "type": "string", "enum": [ "eq", "ne", "gt", "gte", "lt", "lte" ], "description": "Specifies the comparison operator: `eq`, `ne`, `gt`, `gte`, `lt`, `lte`, `in`, `nin`.\n - `eq`: equals\n - `ne`: not equal\n - `gt`: greater than\n - `gte`: greater than or equal\n - `lt`: less than\n - `lte`: less than or equal\n - `in`: in\n - `nin`: not in", "default": "eq" }, "key": { "type": "string", "description": "The key to compare against the value." }, "value": { "oneOf": [ { "type": "string" }, { "$ref": "#/components/schemas/OpenAI.numeric" }, { "type": "boolean" }, { "type": "array", "items": { "anyOf": [ { "type": "string" }, { "$ref": "#/components/schemas/OpenAI.numeric" } ] } } ], "description": "The value to compare against the attribute key; supports string, number, or boolean types." } }, "description": "A filter used to compare a specified attribute key to a given value using a defined comparison operation.", "title": "Comparison Filter", "x-oaiMeta": { "name": "ComparisonFilter" } }, "OpenAI.CompoundFilter": { "type": "object", "required": [ "type", "filters" ], "properties": { "type": { "type": "string", "enum": [ "and", "or" ], "description": "Type of operation: `and` or `or`." }, "filters": { "type": "array", "items": { "anyOf": [ { "$ref": "#/components/schemas/OpenAI.ComparisonFilter" }, {} ] }, "description": "Array of filters to combine. Items can be `ComparisonFilter` or `CompoundFilter`." } }, "description": "Combine multiple filters using `and` or `or`.", "title": "Compound Filter", "x-oaiMeta": { "name": "CompoundFilter" } }, "OpenAI.ComputerAction": { "type": "object", "required": [ "type" ], "properties": { "type": { "$ref": "#/components/schemas/OpenAI.ComputerActionType" } }, "discriminator": { "propertyName": "type", "mapping": { "click": "#/components/schemas/OpenAI.ClickParam", "double_click": "#/components/schemas/OpenAI.DoubleClickAction", "drag": "#/components/schemas/OpenAI.DragParam", "keypress": "#/components/schemas/OpenAI.KeyPressAction", "move": "#/components/schemas/OpenAI.MoveParam", "screenshot": "#/components/schemas/OpenAI.ScreenshotParam", "scroll": "#/components/schemas/OpenAI.ScrollParam", "type": "#/components/schemas/OpenAI.TypeParam", "wait": "#/components/schemas/OpenAI.WaitParam" } } }, "OpenAI.ComputerActionType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "click", "double_click", "drag", "keypress", "move", "screenshot", "scroll", "type", "wait" ] } ] }, "OpenAI.ComputerCallSafetyCheckParam": { "type": "object", "required": [ "id" ], "properties": { "id": { "type": "string", "description": "The ID of the pending safety check." }, "code": { "type": "string", "nullable": true }, "message": { "type": "string", "nullable": true } }, "description": "A pending safety check for the computer call." }, "OpenAI.ComputerEnvironment": { "type": "string", "enum": [ "windows", "mac", "linux", "ubuntu", "browser" ] }, "OpenAI.ComputerScreenshotContent": { "type": "object", "required": [ "type", "image_url", "file_id" ], "properties": { "type": { "type": "string", "enum": [ "computer_screenshot" ], "description": "Specifies the event type. For a computer screenshot, this property is always set to `computer_screenshot`.", "x-stainless-const": true, "default": "computer_screenshot" }, "image_url": { "type": "string", "format": "uri", "nullable": true }, "file_id": { "type": "string", "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.MessageContent" } ], "description": "A screenshot of a computer.", "title": "Computer screenshot" }, "OpenAI.ComputerScreenshotImage": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "computer_screenshot" ], "description": "Specifies the event type. For a computer screenshot, this property is\n always set to `computer_screenshot`.", "x-stainless-const": true, "default": "computer_screenshot" }, "image_url": { "type": "string", "format": "uri", "description": "The URL of the screenshot image." }, "file_id": { "type": "string", "description": "The identifier of an uploaded file that contains the screenshot." } }, "description": "A computer screenshot image used with the computer use tool." }, "OpenAI.ComputerUsePreviewTool": { "type": "object", "required": [ "type", "environment", "display_width", "display_height" ], "properties": { "type": { "type": "string", "enum": [ "computer_use_preview" ], "description": "The type of the computer use tool. Always `computer_use_preview`.", "x-stainless-const": true, "default": "computer_use_preview" }, "environment": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ComputerEnvironment" } ], "description": "The type of computer environment to control." }, "display_width": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The width of the computer display." }, "display_height": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The height of the computer display." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Tool" } ], "description": "A tool that controls a virtual computer. Learn more about the [computer tool](https://platform.openai.com/docs/guides/tools-computer-use).", "title": "Computer use preview" }, "OpenAI.ContainerAutoParam": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "container_auto" ], "description": "Automatically creates a container for this request", "x-stainless-const": true, "default": "container_auto" }, "file_ids": { "type": "array", "items": { "type": "string" }, "maxItems": 50, "description": "An optional list of uploaded files to make available to your code." }, "memory_limit": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ContainerMemoryLimit" } ], "nullable": true }, "skills": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.ContainerSkill" }, "maxItems": 200, "description": "An optional list of skills referenced by id or inline data." }, "network_policy": { "$ref": "#/components/schemas/OpenAI.ContainerNetworkPolicyParam" } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.FunctionShellToolParamEnvironment" } ] }, "OpenAI.ContainerFileCitationBody": { "type": "object", "required": [ "type", "container_id", "file_id", "start_index", "end_index", "filename" ], "properties": { "type": { "type": "string", "enum": [ "container_file_citation" ], "description": "The type of the container file citation. Always `container_file_citation`.", "x-stainless-const": true, "default": "container_file_citation" }, "container_id": { "type": "string", "description": "The ID of the container file." }, "file_id": { "type": "string", "description": "The ID of the file." }, "start_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the first character of the container file citation in the message." }, "end_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the last character of the container file citation in the message." }, "filename": { "type": "string", "description": "The filename of the container file cited." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Annotation" } ], "description": "A citation for a container file used to generate a model response.", "title": "Container file citation" }, "OpenAI.ContainerMemoryLimit": { "type": "string", "enum": [ "1g", "4g", "16g", "64g" ] }, "OpenAI.ContainerNetworkPolicyAllowlistParam": { "type": "object", "required": [ "type", "allowed_domains" ], "properties": { "type": { "type": "string", "enum": [ "allowlist" ], "description": "Allow outbound network access only to specified domains. Always `allowlist`.", "x-stainless-const": true, "default": "allowlist" }, "allowed_domains": { "type": "array", "items": { "type": "string" }, "minItems": 1, "description": "A list of allowed domains when type is `allowlist`." }, "domain_secrets": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.ContainerNetworkPolicyDomainSecretParam" }, "minItems": 1, "description": "Optional domain-scoped secrets for allowlisted domains." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ContainerNetworkPolicyParam" } ] }, "OpenAI.ContainerNetworkPolicyDisabledParam": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "disabled" ], "description": "Disable outbound network access. Always `disabled`.", "x-stainless-const": true, "default": "disabled" } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ContainerNetworkPolicyParam" } ] }, "OpenAI.ContainerNetworkPolicyDomainSecretParam": { "type": "object", "required": [ "domain", "name", "value" ], "properties": { "domain": { "type": "string", "minLength": 1, "description": "The domain associated with the secret." }, "name": { "type": "string", "minLength": 1, "description": "The name of the secret to inject for the domain." }, "value": { "type": "string", "minLength": 1, "maxLength": 10485760, "description": "The secret value to inject for the domain." } } }, "OpenAI.ContainerNetworkPolicyParam": { "type": "object", "required": [ "type" ], "properties": { "type": { "$ref": "#/components/schemas/OpenAI.ContainerNetworkPolicyParamType" } }, "discriminator": { "propertyName": "type", "mapping": { "disabled": "#/components/schemas/OpenAI.ContainerNetworkPolicyDisabledParam", "allowlist": "#/components/schemas/OpenAI.ContainerNetworkPolicyAllowlistParam" } }, "description": "Network access policy for the container." }, "OpenAI.ContainerNetworkPolicyParamType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "disabled", "allowlist" ] } ] }, "OpenAI.ContainerReferenceResource": { "type": "object", "required": [ "type", "container_id" ], "properties": { "type": { "type": "string", "enum": [ "container_reference" ], "description": "The environment type. Always `container_reference`.", "x-stainless-const": true, "default": "container_reference" }, "container_id": { "type": "string" } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.FunctionShellCallEnvironment" } ], "description": "Represents a container created with /v1/containers.", "title": "Container Reference" }, "OpenAI.ContainerSkill": { "type": "object", "required": [ "type" ], "properties": { "type": { "$ref": "#/components/schemas/OpenAI.ContainerSkillType" } }, "discriminator": { "propertyName": "type", "mapping": { "skill_reference": "#/components/schemas/OpenAI.SkillReferenceParam", "inline": "#/components/schemas/OpenAI.InlineSkillParam" } } }, "OpenAI.ContainerSkillType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "skill_reference", "inline" ] } ] }, "OpenAI.ContextManagementParam": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "description": "The context management entry type. Currently only 'compaction' is supported." }, "compact_threshold": { "type": "integer", "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "nullable": true } } }, "OpenAI.ConversationItem": { "type": "object", "required": [ "type" ], "properties": { "type": { "$ref": "#/components/schemas/OpenAI.ConversationItemType" } }, "discriminator": { "propertyName": "type", "mapping": { "message": "#/components/schemas/OpenAI.ConversationItemMessage", "function_call": "#/components/schemas/OpenAI.ConversationItemFunctionToolCallResource", "function_call_output": "#/components/schemas/OpenAI.ConversationItemFunctionToolCallOutputResource", "file_search_call": "#/components/schemas/OpenAI.ConversationItemFileSearchToolCall", "web_search_call": "#/components/schemas/OpenAI.ConversationItemWebSearchToolCall", "image_generation_call": "#/components/schemas/OpenAI.ConversationItemImageGenToolCall", "computer_call": "#/components/schemas/OpenAI.ConversationItemComputerToolCall", "computer_call_output": "#/components/schemas/OpenAI.ConversationItemComputerToolCallOutputResource", "reasoning": "#/components/schemas/OpenAI.ConversationItemReasoningItem", "code_interpreter_call": "#/components/schemas/OpenAI.ConversationItemCodeInterpreterToolCall", "local_shell_call": "#/components/schemas/OpenAI.ConversationItemLocalShellToolCall", "local_shell_call_output": "#/components/schemas/OpenAI.ConversationItemLocalShellToolCallOutput", "shell_call": "#/components/schemas/OpenAI.ConversationItemFunctionShellCall", "shell_call_output": "#/components/schemas/OpenAI.ConversationItemFunctionShellCallOutput", "apply_patch_call": "#/components/schemas/OpenAI.ConversationItemApplyPatchToolCall", "apply_patch_call_output": "#/components/schemas/OpenAI.ConversationItemApplyPatchToolCallOutput", "mcp_list_tools": "#/components/schemas/OpenAI.ConversationItemMcpListTools", "mcp_approval_request": "#/components/schemas/OpenAI.ConversationItemMcpApprovalRequest", "mcp_approval_response": "#/components/schemas/OpenAI.ConversationItemMcpApprovalResponseResource", "mcp_call": "#/components/schemas/OpenAI.ConversationItemMcpToolCall", "custom_tool_call": "#/components/schemas/OpenAI.ConversationItemCustomToolCall", "custom_tool_call_output": "#/components/schemas/OpenAI.ConversationItemCustomToolCallOutput" } }, "description": "A single item within a conversation. The set of possible types are the same as the `output` type of a [Response object](/docs/api-reference/responses/object#responses/object-output).", "title": "Conversation item" }, "OpenAI.ConversationItemApplyPatchToolCall": { "type": "object", "required": [ "type", "id", "call_id", "status", "operation" ], "properties": { "type": { "type": "string", "enum": [ "apply_patch_call" ], "description": "The type of the item. Always `apply_patch_call`.", "x-stainless-const": true, "default": "apply_patch_call" }, "id": { "type": "string", "description": "The unique ID of the apply patch tool call. Populated when this item is returned via API." }, "call_id": { "type": "string", "description": "The unique ID of the apply patch tool call generated by the model." }, "status": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ApplyPatchCallStatus" } ], "description": "The status of the apply patch tool call. One of `in_progress` or `completed`." }, "operation": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ApplyPatchFileOperation" } ], "description": "One of the create_file, delete_file, or update_file operations applied via apply_patch.", "title": "Apply patch operation" }, "created_by": { "type": "string", "description": "The ID of the entity that created this tool call." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ConversationItem" } ], "description": "A tool call that applies file diffs by creating, deleting, or updating files.", "title": "Apply patch tool call" }, "OpenAI.ConversationItemApplyPatchToolCallOutput": { "type": "object", "required": [ "type", "id", "call_id", "status" ], "properties": { "type": { "type": "string", "enum": [ "apply_patch_call_output" ], "description": "The type of the item. Always `apply_patch_call_output`.", "x-stainless-const": true, "default": "apply_patch_call_output" }, "id": { "type": "string", "description": "The unique ID of the apply patch tool call output. Populated when this item is returned via API." }, "call_id": { "type": "string", "description": "The unique ID of the apply patch tool call generated by the model." }, "status": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ApplyPatchCallOutputStatus" } ], "description": "The status of the apply patch tool call output. One of `completed` or `failed`." }, "output": { "type": "string", "nullable": true }, "created_by": { "type": "string", "description": "The ID of the entity that created this tool call output." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ConversationItem" } ], "description": "The output emitted by an apply patch tool call.", "title": "Apply patch tool call output" }, "OpenAI.ConversationItemCodeInterpreterToolCall": { "type": "object", "required": [ "type", "id", "status", "container_id", "code", "outputs" ], "properties": { "type": { "type": "string", "enum": [ "code_interpreter_call" ], "description": "The type of the code interpreter tool call. Always `code_interpreter_call`.", "x-stainless-const": true, "default": "code_interpreter_call" }, "id": { "type": "string", "description": "The unique ID of the code interpreter tool call." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete", "interpreting", "failed" ], "description": "The status of the code interpreter tool call. Valid values are `in_progress`, `completed`, `incomplete`, `interpreting`, and `failed`." }, "container_id": { "type": "string", "description": "The ID of the container used to run the code." }, "code": { "type": "string", "nullable": true }, "outputs": { "type": "array", "items": { "anyOf": [ { "$ref": "#/components/schemas/OpenAI.CodeInterpreterOutputLogs" }, { "$ref": "#/components/schemas/OpenAI.CodeInterpreterOutputImage" } ] }, "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ConversationItem" } ], "description": "A tool call to run code.", "title": "Code interpreter tool call" }, "OpenAI.ConversationItemComputerToolCall": { "type": "object", "required": [ "type", "id", "call_id", "action", "pending_safety_checks", "status" ], "properties": { "type": { "type": "string", "enum": [ "computer_call" ], "description": "The type of the computer call. Always `computer_call`.", "default": "computer_call" }, "id": { "type": "string", "description": "The unique ID of the computer call." }, "call_id": { "type": "string", "description": "An identifier used when responding to the tool call with output." }, "action": { "$ref": "#/components/schemas/OpenAI.ComputerAction" }, "pending_safety_checks": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.ComputerCallSafetyCheckParam" }, "description": "The pending safety checks for the computer call." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "description": "The status of the item. One of `in_progress`, `completed`, or\n `incomplete`. Populated when items are returned via API." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ConversationItem" } ], "description": "A tool call to a computer use tool. See the\n[computer use guide](/docs/guides/tools-computer-use) for more information.", "title": "Computer tool call" }, "OpenAI.ConversationItemComputerToolCallOutputResource": { "type": "object", "required": [ "type", "call_id", "output" ], "properties": { "type": { "type": "string", "enum": [ "computer_call_output" ], "description": "The type of the computer tool call output. Always `computer_call_output`.", "x-stainless-const": true, "default": "computer_call_output" }, "id": { "type": "string", "description": "The ID of the computer tool call output." }, "call_id": { "type": "string", "description": "The ID of the computer tool call that produced the output." }, "acknowledged_safety_checks": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.ComputerCallSafetyCheckParam" }, "description": "The safety checks reported by the API that have been acknowledged by the\n developer." }, "output": { "$ref": "#/components/schemas/OpenAI.ComputerScreenshotImage" }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "description": "The status of the message input. One of `in_progress`, `completed`, or\n `incomplete`. Populated when input items are returned via API." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ConversationItem" } ] }, "OpenAI.ConversationItemCustomToolCall": { "type": "object", "required": [ "type", "call_id", "name", "input" ], "properties": { "type": { "type": "string", "enum": [ "custom_tool_call" ], "description": "The type of the custom tool call. Always `custom_tool_call`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the custom tool call in the OpenAI platform." }, "call_id": { "type": "string", "description": "An identifier used to map this custom tool call to a tool call output." }, "name": { "type": "string", "description": "The name of the custom tool being called." }, "input": { "type": "string", "description": "The input for the custom tool call generated by the model." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ConversationItem" } ], "description": "A call to a custom tool created by the model.", "title": "Custom tool call" }, "OpenAI.ConversationItemCustomToolCallOutput": { "type": "object", "required": [ "type", "call_id", "output" ], "properties": { "type": { "type": "string", "enum": [ "custom_tool_call_output" ], "description": "The type of the custom tool call output. Always `custom_tool_call_output`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the custom tool call output in the OpenAI platform." }, "call_id": { "type": "string", "description": "The call ID, used to map this custom tool call output to a custom tool call." }, "output": { "oneOf": [ { "type": "string" }, { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.FunctionAndCustomToolCallOutput" } } ], "description": "The output from the custom tool call generated by your code.\n Can be a string or an list of output content." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ConversationItem" } ], "description": "The output of a custom tool call from your code, being sent back to the model.", "title": "Custom tool call output" }, "OpenAI.ConversationItemFileSearchToolCall": { "type": "object", "required": [ "id", "type", "status", "queries" ], "properties": { "id": { "type": "string", "description": "The unique ID of the file search tool call." }, "type": { "type": "string", "enum": [ "file_search_call" ], "description": "The type of the file search tool call. Always `file_search_call`.", "x-stainless-const": true }, "status": { "type": "string", "enum": [ "in_progress", "searching", "completed", "incomplete", "failed" ], "description": "The status of the file search tool call. One of `in_progress`,\n `searching`, `incomplete` or `failed`," }, "queries": { "type": "array", "items": { "type": "string" }, "description": "The queries used to search for files." }, "results": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.FileSearchToolCallResults" }, "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ConversationItem" } ], "description": "The results of a file search tool call. See the\n[file search guide](/docs/guides/tools-file-search) for more information.", "title": "File search tool call" }, "OpenAI.ConversationItemFunctionShellCall": { "type": "object", "required": [ "type", "id", "call_id", "action", "status", "environment" ], "properties": { "type": { "type": "string", "enum": [ "shell_call" ], "description": "The type of the item. Always `shell_call`.", "x-stainless-const": true, "default": "shell_call" }, "id": { "type": "string", "description": "The unique ID of the shell tool call. Populated when this item is returned via API." }, "call_id": { "type": "string", "description": "The unique ID of the shell tool call generated by the model." }, "action": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.FunctionShellAction" } ], "description": "The shell commands and limits that describe how to run the tool call." }, "status": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.LocalShellCallStatus" } ], "description": "The status of the shell call. One of `in_progress`, `completed`, or `incomplete`." }, "environment": { "type": "object", "allOf": [ { "$ref": "#/components/schemas/OpenAI.FunctionShellCallEnvironment" } ], "nullable": true }, "created_by": { "type": "string", "description": "The ID of the entity that created this tool call." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ConversationItem" } ], "description": "A tool call that executes one or more shell commands in a managed environment.", "title": "Shell tool call" }, "OpenAI.ConversationItemFunctionShellCallOutput": { "type": "object", "required": [ "type", "id", "call_id", "status", "output", "max_output_length" ], "properties": { "type": { "type": "string", "enum": [ "shell_call_output" ], "description": "The type of the shell call output. Always `shell_call_output`.", "x-stainless-const": true, "default": "shell_call_output" }, "id": { "type": "string", "description": "The unique ID of the shell call output. Populated when this item is returned via API." }, "call_id": { "type": "string", "description": "The unique ID of the shell tool call generated by the model." }, "status": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.LocalShellCallOutputStatusEnum" } ], "description": "The status of the shell call output. One of `in_progress`, `completed`, or `incomplete`." }, "output": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.FunctionShellCallOutputContent" }, "description": "An array of shell call output contents" }, "max_output_length": { "type": "integer", "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "nullable": true }, "created_by": { "type": "string", "description": "The identifier of the actor that created the item." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ConversationItem" } ], "description": "The output of a shell tool call that was emitted.", "title": "Shell call output" }, "OpenAI.ConversationItemFunctionToolCallOutputResource": { "type": "object", "required": [ "type", "call_id", "output" ], "properties": { "id": { "type": "string", "description": "The unique ID of the function tool call output. Populated when this item\n is returned via API." }, "type": { "type": "string", "enum": [ "function_call_output" ], "description": "The type of the function tool call output. Always `function_call_output`.", "x-stainless-const": true }, "call_id": { "type": "string", "description": "The unique ID of the function tool call generated by the model." }, "output": { "oneOf": [ { "type": "string" }, { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.FunctionAndCustomToolCallOutput" } } ], "description": "The output from the function call generated by your code.\n Can be a string or an list of output content." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "description": "The status of the item. One of `in_progress`, `completed`, or\n `incomplete`. Populated when items are returned via API." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ConversationItem" } ] }, "OpenAI.ConversationItemFunctionToolCallResource": { "type": "object", "required": [ "type", "call_id", "name", "arguments" ], "properties": { "id": { "type": "string", "description": "The unique ID of the function tool call." }, "type": { "type": "string", "enum": [ "function_call" ], "description": "The type of the function tool call. Always `function_call`.", "x-stainless-const": true }, "call_id": { "type": "string", "description": "The unique ID of the function tool call generated by the model." }, "name": { "type": "string", "description": "The name of the function to run." }, "arguments": { "type": "string", "description": "A JSON string of the arguments to pass to the function." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "description": "The status of the item. One of `in_progress`, `completed`, or\n `incomplete`. Populated when items are returned via API." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ConversationItem" } ] }, "OpenAI.ConversationItemImageGenToolCall": { "type": "object", "required": [ "type", "id", "status", "result" ], "properties": { "type": { "type": "string", "enum": [ "image_generation_call" ], "description": "The type of the image generation call. Always `image_generation_call`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the image generation call." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "generating", "failed" ], "description": "The status of the image generation call." }, "result": { "type": "string", "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ConversationItem" } ], "description": "An image generation request made by the model.", "title": "Image generation call" }, "OpenAI.ConversationItemList": { "type": "object", "required": [ "object", "data", "has_more", "first_id", "last_id" ], "properties": { "object": { "type": "string", "enum": [ "list" ], "description": "The type of object returned, must be `list`.", "x-stainless-const": true }, "data": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.ConversationItem" }, "description": "A list of conversation items.", "x-ms-list-page-items": true }, "has_more": { "type": "boolean", "description": "Whether there are more items available." }, "first_id": { "type": "string", "description": "The ID of the first item in the list." }, "last_id": { "type": "string", "description": "The ID of the last item in the list.", "x-ms-list-continuation-token": true } }, "description": "A list of Conversation items.", "title": "The conversation item list", "x-oaiMeta": { "name": "The item list", "group": "conversations" } }, "OpenAI.ConversationItemLocalShellToolCall": { "type": "object", "required": [ "type", "id", "call_id", "action", "status" ], "properties": { "type": { "type": "string", "enum": [ "local_shell_call" ], "description": "The type of the local shell call. Always `local_shell_call`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the local shell call." }, "call_id": { "type": "string", "description": "The unique ID of the local shell tool call generated by the model." }, "action": { "$ref": "#/components/schemas/OpenAI.LocalShellExecAction" }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "description": "The status of the local shell call." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ConversationItem" } ], "description": "A tool call to run a command on the local shell.", "title": "Local shell call" }, "OpenAI.ConversationItemLocalShellToolCallOutput": { "type": "object", "required": [ "type", "id", "output" ], "properties": { "type": { "type": "string", "enum": [ "local_shell_call_output" ], "description": "The type of the local shell tool call output. Always `local_shell_call_output`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the local shell tool call generated by the model." }, "output": { "type": "string", "description": "A JSON string of the output of the local shell tool call." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ConversationItem" } ], "description": "The output of a local shell tool call.", "title": "Local shell call output" }, "OpenAI.ConversationItemMcpApprovalRequest": { "type": "object", "required": [ "type", "id", "server_label", "name", "arguments" ], "properties": { "type": { "type": "string", "enum": [ "mcp_approval_request" ], "description": "The type of the item. Always `mcp_approval_request`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the approval request." }, "server_label": { "type": "string", "description": "The label of the MCP server making the request." }, "name": { "type": "string", "description": "The name of the tool to run." }, "arguments": { "type": "string", "description": "A JSON string of arguments for the tool." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ConversationItem" } ], "description": "A request for human approval of a tool invocation.", "title": "MCP approval request" }, "OpenAI.ConversationItemMcpApprovalResponseResource": { "type": "object", "required": [ "type", "id", "approval_request_id", "approve" ], "properties": { "type": { "type": "string", "enum": [ "mcp_approval_response" ], "description": "The type of the item. Always `mcp_approval_response`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the approval response" }, "approval_request_id": { "type": "string", "description": "The ID of the approval request being answered." }, "approve": { "type": "boolean", "description": "Whether the request was approved." }, "reason": { "type": "string", "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ConversationItem" } ], "description": "A response to an MCP approval request.", "title": "MCP approval response" }, "OpenAI.ConversationItemMcpListTools": { "type": "object", "required": [ "type", "id", "server_label", "tools" ], "properties": { "type": { "type": "string", "enum": [ "mcp_list_tools" ], "description": "The type of the item. Always `mcp_list_tools`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the list." }, "server_label": { "type": "string", "description": "The label of the MCP server." }, "tools": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.MCPListToolsTool" }, "description": "The tools available on the server." }, "error": { "type": "string", "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ConversationItem" } ], "description": "A list of tools available on an MCP server.", "title": "MCP list tools" }, "OpenAI.ConversationItemMcpToolCall": { "type": "object", "required": [ "type", "id", "server_label", "name", "arguments" ], "properties": { "type": { "type": "string", "enum": [ "mcp_call" ], "description": "The type of the item. Always `mcp_call`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the tool call." }, "server_label": { "type": "string", "description": "The label of the MCP server running the tool." }, "name": { "type": "string", "description": "The name of the tool that was run." }, "arguments": { "type": "string", "description": "A JSON string of the arguments passed to the tool." }, "output": { "type": "string", "nullable": true }, "error": { "type": "object", "additionalProperties": {} }, "status": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.MCPToolCallStatus" } ], "description": "The status of the tool call. One of `in_progress`, `completed`, `incomplete`, `calling`, or `failed`." }, "approval_request_id": { "type": "string", "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ConversationItem" } ], "description": "An invocation of a tool on an MCP server.", "title": "MCP tool call" }, "OpenAI.ConversationItemMessage": { "type": "object", "required": [ "type", "id", "status", "role", "content" ], "properties": { "type": { "type": "string", "enum": [ "message" ], "description": "The type of the message. Always set to `message`.", "x-stainless-const": true, "default": "message" }, "id": { "type": "string", "description": "The unique ID of the message." }, "status": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.MessageStatus" } ], "description": "The status of item. One of `in_progress`, `completed`, or `incomplete`. Populated when items are returned via API." }, "role": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.MessageRole" } ], "description": "The role of the message. One of `unknown`, `user`, `assistant`, `system`, `critic`, `discriminator`, `developer`, or `tool`." }, "content": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.MessageContent" }, "description": "The content of the message" } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ConversationItem" } ], "description": "A message to or from the model.", "title": "Message" }, "OpenAI.ConversationItemReasoningItem": { "type": "object", "required": [ "type", "id", "summary" ], "properties": { "type": { "type": "string", "enum": [ "reasoning" ], "description": "The type of the object. Always `reasoning`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique identifier of the reasoning content." }, "encrypted_content": { "type": "string", "nullable": true }, "summary": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.SummaryTextContent" }, "description": "Reasoning summary content." }, "content": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.ReasoningTextContent" }, "description": "Reasoning text content." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "description": "The status of the item. One of `in_progress`, `completed`, or\n `incomplete`. Populated when items are returned via API." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ConversationItem" } ], "description": "A description of the chain of thought used by a reasoning model while generating\na response. Be sure to include these items in your `input` to the Responses API\nfor subsequent turns of a conversation if you are manually\n[managing context](/docs/guides/conversation-state).", "title": "Reasoning" }, "OpenAI.ConversationItemType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "message", "function_call", "function_call_output", "file_search_call", "web_search_call", "image_generation_call", "computer_call", "computer_call_output", "reasoning", "code_interpreter_call", "local_shell_call", "local_shell_call_output", "shell_call", "shell_call_output", "apply_patch_call", "apply_patch_call_output", "mcp_list_tools", "mcp_approval_request", "mcp_approval_response", "mcp_call", "custom_tool_call", "custom_tool_call_output" ] } ] }, "OpenAI.ConversationItemWebSearchToolCall": { "type": "object", "required": [ "id", "type", "status", "action" ], "properties": { "id": { "type": "string", "description": "The unique ID of the web search tool call." }, "type": { "type": "string", "enum": [ "web_search_call" ], "description": "The type of the web search tool call. Always `web_search_call`.", "x-stainless-const": true }, "status": { "type": "string", "enum": [ "in_progress", "searching", "completed", "failed" ], "description": "The status of the web search tool call." }, "action": { "oneOf": [ { "$ref": "#/components/schemas/OpenAI.WebSearchActionSearch" }, { "$ref": "#/components/schemas/OpenAI.WebSearchActionOpenPage" }, { "$ref": "#/components/schemas/OpenAI.WebSearchActionFind" } ], "description": "An object describing the specific action taken in this web search call.\n Includes details on how the model used the web (search, open_page, find_in_page)." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ConversationItem" } ], "description": "The results of a web search tool call. See the\n[web search guide](/docs/guides/tools-web-search) for more information.", "title": "Web search tool call" }, "OpenAI.ConversationParam": { "oneOf": [ { "type": "string" }, { "$ref": "#/components/schemas/OpenAI.ConversationParam-2" } ], "description": "The conversation that this response belongs to. Items from this conversation are prepended to `input_items` for this response request.\nInput items and output items from this response are automatically added to this conversation after this response completes." }, "OpenAI.ConversationParam-2": { "type": "object", "required": [ "id" ], "properties": { "id": { "type": "string", "description": "The unique ID of the conversation." } }, "description": "The conversation that this response belongs to.", "title": "Conversation object" }, "OpenAI.ConversationReference": { "type": "object", "required": [ "id" ], "properties": { "id": { "type": "string", "description": "The unique ID of the conversation that this response was associated with." } }, "description": "The conversation that this response belonged to. Input items and output items from this response were automatically added to this conversation.", "title": "Conversation" }, "OpenAI.ConversationResource": { "type": "object", "required": [ "id", "object", "metadata", "created_at" ], "properties": { "id": { "type": "string", "description": "The unique ID of the conversation." }, "object": { "type": "string", "enum": [ "conversation" ], "description": "The object type, which is always `conversation`.", "x-stainless-const": true, "default": "conversation" }, "metadata": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.Metadata" } ], "description": "Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format, and querying for objects via API or the dashboard.\n Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters." }, "created_at": { "type": "integer", "format": "unixtime", "description": "The time at which the conversation was created, measured in seconds since the Unix epoch." } } }, "OpenAI.CoordParam": { "type": "object", "required": [ "x", "y" ], "properties": { "x": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The x-coordinate." }, "y": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The y-coordinate." } }, "description": "An x/y coordinate pair, e.g. `{ x: 100, y: 200 }`.", "title": "Coordinate" }, "OpenAI.CreateChatCompletionRequestResponseFormat": { "type": "object", "required": [ "type" ], "properties": { "type": { "$ref": "#/components/schemas/OpenAI.CreateChatCompletionRequestResponseFormatType" } }, "discriminator": { "propertyName": "type", "mapping": { "text": "#/components/schemas/OpenAI.CreateChatCompletionRequestResponseFormatResponseFormatText", "json_object": "#/components/schemas/OpenAI.CreateChatCompletionRequestResponseFormatResponseFormatJsonObject" } }, "description": "An object specifying the format that the model must output.\nSetting to `{ \"type\": \"json_schema\", \"json_schema\": {...} }` enables\nStructured Outputs which ensures the model will match your supplied JSON\nschema. Learn more in the [Structured Outputs\nguide](/docs/guides/structured-outputs).\nSetting to `{ \"type\": \"json_object\" }` enables the older JSON mode, which\nensures the message the model generates is valid JSON. Using `json_schema`\nis preferred for models that support it." }, "OpenAI.CreateChatCompletionRequestResponseFormatResponseFormatJsonObject": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "json_object" ], "description": "The type of response format being defined. Always `json_object`.", "x-stainless-const": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.CreateChatCompletionRequestResponseFormat" } ], "description": "JSON object response format. An older method of generating JSON responses.\nUsing `json_schema` is recommended for models that support it. Note that the\nmodel will not generate JSON without a system or user message instructing it\nto do so.", "title": "JSON object" }, "OpenAI.CreateChatCompletionRequestResponseFormatResponseFormatText": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "text" ], "description": "The type of response format being defined. Always `text`.", "x-stainless-const": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.CreateChatCompletionRequestResponseFormat" } ], "description": "Default response format. Used to generate text responses.", "title": "Text" }, "OpenAI.CreateChatCompletionRequestResponseFormatType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "text", "json_schema", "json_object" ] } ] }, "OpenAI.CreateConversationBody": { "type": "object", "properties": { "metadata": { "type": "object", "allOf": [ { "$ref": "#/components/schemas/OpenAI.Metadata" } ], "nullable": true }, "items": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.InputItem" }, "nullable": true } } }, "OpenAI.CreateEvalCompletionsRunDataSource": { "type": "object", "required": [ "type", "source" ], "properties": { "type": { "type": "string", "enum": [ "completions" ], "description": "The type of run data source. Always `completions`.", "default": "completions" }, "input_messages": { "oneOf": [ { "$ref": "#/components/schemas/OpenAI.CreateEvalCompletionsRunDataSourceInputMessagesTemplate" }, { "$ref": "#/components/schemas/OpenAI.CreateEvalCompletionsRunDataSourceInputMessagesItemReference" } ], "description": "Used when sampling from a model. Dictates the structure of the messages passed into the model. Can either be a reference to a prebuilt trajectory (ie, `item.input_trajectory`), or a template with variable references to the `item` namespace." }, "sampling_params": { "$ref": "#/components/schemas/OpenAI.CreateEvalCompletionsRunDataSourceSamplingParams" }, "model": { "type": "string", "description": "The name of the model to use for generating completions (e.g. \"o3-mini\")." }, "source": { "oneOf": [ { "$ref": "#/components/schemas/OpenAI.EvalJsonlFileContentSource" }, { "$ref": "#/components/schemas/OpenAI.EvalJsonlFileIdSource" }, { "$ref": "#/components/schemas/OpenAI.EvalStoredCompletionsSource" } ], "description": "Determines what populates the `item` namespace in this run's data source." } }, "description": "A CompletionsRunDataSource object describing a model sampling configuration.", "title": "CompletionsRunDataSource", "x-oaiMeta": { "name": "The completions data source object used to configure an individual run", "group": "eval runs", "example": "{\n \"name\": \"gpt-4o-mini-2024-07-18\",\n \"data_source\": {\n \"type\": \"completions\",\n \"input_messages\": {\n \"type\": \"item_reference\",\n \"item_reference\": \"item.input\"\n },\n \"model\": \"gpt-4o-mini-2024-07-18\",\n \"source\": {\n \"type\": \"stored_completions\",\n \"model\": \"gpt-4o-mini-2024-07-18\"\n }\n }\n}\n" } }, "OpenAI.CreateEvalCompletionsRunDataSourceInputMessagesItemReference": { "type": "object", "required": [ "type", "item_reference" ], "properties": { "type": { "type": "string", "enum": [ "item_reference" ] }, "item_reference": { "type": "string" } } }, "OpenAI.CreateEvalCompletionsRunDataSourceInputMessagesTemplate": { "type": "object", "required": [ "type", "template" ], "properties": { "type": { "type": "string", "enum": [ "template" ] }, "template": { "type": "array", "items": { "anyOf": [ { "$ref": "#/components/schemas/OpenAI.EasyInputMessage" }, { "$ref": "#/components/schemas/OpenAI.EvalItem" } ] } } } }, "OpenAI.CreateEvalCompletionsRunDataSourceSamplingParams": { "type": "object", "properties": { "reasoning_effort": { "$ref": "#/components/schemas/OpenAI.ReasoningEffort" }, "temperature": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.numeric" } ], "default": 1 }, "max_completion_tokens": { "$ref": "#/components/schemas/OpenAI.integer" }, "top_p": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.numeric" } ], "default": 1 }, "seed": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "default": 42 }, "response_format": { "oneOf": [ { "$ref": "#/components/schemas/OpenAI.ResponseFormatText" }, { "$ref": "#/components/schemas/OpenAI.ResponseFormatJsonSchema" }, { "$ref": "#/components/schemas/OpenAI.ResponseFormatJsonObject" } ] }, "tools": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.ChatCompletionTool" } } } }, "OpenAI.CreateEvalCustomDataSourceConfig": { "type": "object", "required": [ "type", "item_schema" ], "properties": { "type": { "type": "string", "enum": [ "custom" ], "description": "The type of data source. Always `custom`.", "x-stainless-const": true, "default": "custom" }, "item_schema": { "type": "object", "additionalProperties": {}, "description": "The json schema for each row in the data source." }, "include_sample_schema": { "type": "boolean", "description": "Whether the eval should expect you to populate the sample namespace (ie, by generating responses off of your data source)" } }, "description": "A CustomDataSourceConfig object that defines the schema for the data source used for the evaluation runs.\nThis schema is used to define the shape of the data that will be:\n- Used to define your testing criteria and\n- What data is required when creating a run", "title": "CustomDataSourceConfig", "x-oaiMeta": { "name": "The eval file data source config object", "group": "evals", "example": "{\n \"type\": \"custom\",\n \"item_schema\": {\n \"type\": \"object\",\n \"properties\": {\n \"name\": {\"type\": \"string\"},\n \"age\": {\"type\": \"integer\"}\n },\n \"required\": [\"name\", \"age\"]\n },\n \"include_sample_schema\": true\n}\n" } }, "OpenAI.CreateEvalJsonlRunDataSource": { "type": "object", "required": [ "type", "source" ], "properties": { "type": { "type": "string", "enum": [ "jsonl" ], "description": "The type of data source. Always `jsonl`.", "x-stainless-const": true, "default": "jsonl" }, "source": { "oneOf": [ { "$ref": "#/components/schemas/OpenAI.EvalJsonlFileContentSource" }, { "$ref": "#/components/schemas/OpenAI.EvalJsonlFileIdSource" } ], "description": "Determines what populates the `item` namespace in the data source." } }, "description": "A JsonlRunDataSource object with that specifies a JSONL file that matches the eval", "title": "JsonlRunDataSource", "x-oaiMeta": { "name": "The file data source object for the eval run configuration", "group": "evals", "example": "{\n \"type\": \"jsonl\",\n \"source\": {\n \"type\": \"file_id\",\n \"id\": \"file-9GYS6xbkWgWhmE7VoLUWFg\"\n }\n}\n" } }, "OpenAI.CreateEvalLogsDataSourceConfig": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "logs" ], "description": "The type of data source. Always `logs`.", "x-stainless-const": true, "default": "logs" }, "metadata": { "type": "object", "additionalProperties": {}, "description": "Metadata filters for the logs data source." } }, "description": "A data source config which specifies the metadata property of your logs query.\nThis is usually metadata like `usecase=chatbot` or `prompt-version=v2`, etc.", "title": "LogsDataSourceConfig", "x-oaiMeta": { "name": "The logs data source object for evals", "group": "evals", "example": "{\n \"type\": \"logs\",\n \"metadata\": {\n \"use_case\": \"customer_support_agent\"\n }\n}\n" } }, "OpenAI.CreateEvalResponsesRunDataSource": { "type": "object", "required": [ "type", "source" ], "properties": { "type": { "type": "string", "enum": [ "responses" ], "description": "The type of run data source. Always `responses`.", "default": "responses" }, "input_messages": { "oneOf": [ { "$ref": "#/components/schemas/OpenAI.CreateEvalResponsesRunDataSourceInputMessagesTemplate" }, { "$ref": "#/components/schemas/OpenAI.CreateEvalResponsesRunDataSourceInputMessagesItemReference" } ], "description": "Used when sampling from a model. Dictates the structure of the messages passed into the model. Can either be a reference to a prebuilt trajectory (ie, `item.input_trajectory`), or a template with variable references to the `item` namespace." }, "sampling_params": { "$ref": "#/components/schemas/OpenAI.CreateEvalResponsesRunDataSourceSamplingParams" }, "model": { "type": "string", "description": "The name of the model to use for generating completions (e.g. \"o3-mini\")." }, "source": { "oneOf": [ { "$ref": "#/components/schemas/OpenAI.EvalJsonlFileContentSource" }, { "$ref": "#/components/schemas/OpenAI.EvalJsonlFileIdSource" }, { "$ref": "#/components/schemas/OpenAI.EvalResponsesSource" } ], "description": "Determines what populates the `item` namespace in this run's data source." } }, "description": "A ResponsesRunDataSource object describing a model sampling configuration.", "title": "ResponsesRunDataSource", "x-oaiMeta": { "name": "The completions data source object used to configure an individual run", "group": "eval runs", "example": "{\n \"name\": \"gpt-4o-mini-2024-07-18\",\n \"data_source\": {\n \"type\": \"responses\",\n \"input_messages\": {\n \"type\": \"item_reference\",\n \"item_reference\": \"item.input\"\n },\n \"model\": \"gpt-4o-mini-2024-07-18\",\n \"source\": {\n \"type\": \"responses\",\n \"model\": \"gpt-4o-mini-2024-07-18\"\n }\n }\n}\n" } }, "OpenAI.CreateEvalResponsesRunDataSourceInputMessagesItemReference": { "type": "object", "required": [ "type", "item_reference" ], "properties": { "type": { "type": "string", "enum": [ "item_reference" ] }, "item_reference": { "type": "string" } } }, "OpenAI.CreateEvalResponsesRunDataSourceInputMessagesTemplate": { "type": "object", "required": [ "type", "template" ], "properties": { "type": { "type": "string", "enum": [ "template" ] }, "template": { "type": "array", "items": { "anyOf": [ { "type": "object", "properties": { "role": { "type": "string" }, "content": { "type": "string" } }, "required": [ "role", "content" ] }, { "$ref": "#/components/schemas/OpenAI.EvalItem" } ] } } } }, "OpenAI.CreateEvalResponsesRunDataSourceSamplingParams": { "type": "object", "properties": { "reasoning_effort": { "$ref": "#/components/schemas/OpenAI.ReasoningEffort" }, "temperature": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.numeric" } ], "default": 1 }, "max_completion_tokens": { "$ref": "#/components/schemas/OpenAI.integer" }, "top_p": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.numeric" } ], "default": 1 }, "seed": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "default": 42 }, "tools": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.Tool" } }, "text": { "$ref": "#/components/schemas/OpenAI.CreateEvalResponsesRunDataSourceSamplingParamsText" } } }, "OpenAI.CreateEvalResponsesRunDataSourceSamplingParamsText": { "type": "object", "properties": { "format": { "$ref": "#/components/schemas/OpenAI.TextResponseFormatConfiguration" } } }, "OpenAI.CreateEvalStoredCompletionsDataSourceConfig": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "stored_completions" ], "description": "The type of data source. Always `stored_completions`.", "x-stainless-const": true, "default": "stored_completions" }, "metadata": { "type": "object", "additionalProperties": {}, "description": "Metadata filters for the stored completions data source." } }, "description": "Deprecated in favor of LogsDataSourceConfig.", "title": "StoredCompletionsDataSourceConfig", "deprecated": true, "x-oaiMeta": { "name": "The stored completions data source object for evals", "group": "evals", "example": "{\n \"type\": \"stored_completions\",\n \"metadata\": {\n \"use_case\": \"customer_support_agent\"\n }\n}\n" } }, "OpenAI.CreateFineTuningJobRequest": { "type": "object", "required": [ "model", "training_file" ], "properties": { "model": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "babbage-002", "davinci-002", "gpt-3.5-turbo", "gpt-4o-mini" ] } ], "description": "The name of the model to fine-tune. You can select one of the\n [supported models](/docs/guides/fine-tuning#which-models-can-be-fine-tuned).", "x-oaiTypeLabel": "string" }, "training_file": { "type": "string", "description": "The ID of an uploaded file that contains training data.\n See [upload file](/docs/api-reference/files/create) for how to upload a file.\n Your dataset must be formatted as a JSONL file. Additionally, you must upload your file with the purpose `fine-tune`.\n The contents of the file should differ depending on if the model uses the [chat](/docs/api-reference/fine-tuning/chat-input), [completions](/docs/api-reference/fine-tuning/completions-input) format, or if the fine-tuning method uses the [preference](/docs/api-reference/fine-tuning/preference-input) format.\n See the [fine-tuning guide](/docs/guides/model-optimization) for more details." }, "hyperparameters": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.CreateFineTuningJobRequestHyperparameters" } ], "description": "The hyperparameters used for the fine-tuning job.\n This value is now deprecated in favor of `method`, and should be passed in under the `method` parameter.", "deprecated": true }, "suffix": { "type": "string", "nullable": true, "minLength": 1, "maxLength": 64, "description": "A string of up to 64 characters that will be added to your fine-tuned model name.\n For example, a `suffix` of \"custom-model-name\" would produce a model name like `ft:gpt-4o-mini:openai:custom-model-name:7p4lURel`." }, "validation_file": { "type": "string", "nullable": true, "description": "The ID of an uploaded file that contains validation data.\n If you provide this file, the data is used to generate validation\n metrics periodically during fine-tuning. These metrics can be viewed in\n the fine-tuning results file.\n The same data should not be present in both train and validation files.\n Your dataset must be formatted as a JSONL file. You must upload your file with the purpose `fine-tune`.\n See the [fine-tuning guide](/docs/guides/model-optimization) for more details." }, "integrations": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.CreateFineTuningJobRequestIntegrations" }, "nullable": true, "description": "A list of integrations to enable for your fine-tuning job." }, "seed": { "type": "integer", "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "nullable": true, "minimum": 0, "maximum": 2147483647, "description": "The seed controls the reproducibility of the job. Passing in the same seed and job parameters should produce the same results, but may differ in rare cases.\n If a seed is not specified, one will be generated for you." }, "method": { "$ref": "#/components/schemas/OpenAI.FineTuneMethod" }, "metadata": { "type": "object", "allOf": [ { "$ref": "#/components/schemas/OpenAI.Metadata" } ], "nullable": true } } }, "OpenAI.CreateFineTuningJobRequestHyperparameters": { "type": "object", "properties": { "batch_size": { "oneOf": [ { "type": "string", "enum": [ "auto" ] }, { "$ref": "#/components/schemas/OpenAI.integer" } ], "default": "auto" }, "learning_rate_multiplier": { "oneOf": [ { "type": "string", "enum": [ "auto" ] }, { "$ref": "#/components/schemas/OpenAI.numeric" } ], "default": "auto" }, "n_epochs": { "oneOf": [ { "type": "string", "enum": [ "auto" ] }, { "$ref": "#/components/schemas/OpenAI.integer" } ], "default": "auto" } } }, "OpenAI.CreateFineTuningJobRequestIntegrations": { "type": "object", "required": [ "type", "wandb" ], "properties": { "type": { "type": "string", "enum": [ "wandb" ], "x-stainless-const": true }, "wandb": { "$ref": "#/components/schemas/OpenAI.CreateFineTuningJobRequestIntegrationsWandb" } } }, "OpenAI.CreateFineTuningJobRequestIntegrationsWandb": { "type": "object", "required": [ "project" ], "properties": { "project": { "type": "string" }, "name": { "type": "string", "nullable": true }, "entity": { "type": "string", "nullable": true }, "tags": { "type": "array", "items": { "type": "string" } } } }, "OpenAI.CreateResponseStreamingResponse": { "anyOf": [ { "$ref": "#/components/schemas/OpenAI.ResponseAudioDeltaEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseAudioTranscriptDeltaEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseCodeInterpreterCallCodeDeltaEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseCodeInterpreterCallInProgressEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseCodeInterpreterCallInterpretingEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseContentPartAddedEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseCreatedEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseErrorEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseFileSearchCallInProgressEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseFileSearchCallSearchingEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseFunctionCallArgumentsDeltaEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseInProgressEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseFailedEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseIncompleteEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseOutputItemAddedEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseReasoningSummaryPartAddedEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseReasoningSummaryTextDeltaEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseReasoningTextDeltaEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseRefusalDeltaEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseTextDeltaEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseWebSearchCallInProgressEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseWebSearchCallSearchingEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseImageGenCallGeneratingEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseImageGenCallInProgressEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseImageGenCallPartialImageEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseMCPCallArgumentsDeltaEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseMCPCallFailedEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseMCPCallInProgressEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseMCPListToolsFailedEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseMCPListToolsInProgressEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseOutputTextAnnotationAddedEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseQueuedEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseCustomToolCallInputDeltaEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseAudioDoneEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseAudioTranscriptDoneEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseCodeInterpreterCallCodeDoneEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseCodeInterpreterCallCompletedEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseCompletedEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseContentPartDoneEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseFileSearchCallCompletedEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseFunctionCallArgumentsDoneEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseOutputItemDoneEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseReasoningSummaryPartDoneEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseReasoningSummaryTextDoneEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseReasoningTextDoneEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseRefusalDoneEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseTextDoneEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseWebSearchCallCompletedEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseImageGenCallCompletedEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseMCPCallArgumentsDoneEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseMCPCallCompletedEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseMCPListToolsCompletedEvent" }, { "$ref": "#/components/schemas/OpenAI.ResponseCustomToolCallInputDoneEvent" } ] }, "OpenAI.CustomGrammarFormatParam": { "type": "object", "required": [ "type", "syntax", "definition" ], "properties": { "type": { "type": "string", "enum": [ "grammar" ], "description": "Grammar format. Always `grammar`.", "x-stainless-const": true, "default": "grammar" }, "syntax": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.GrammarSyntax1" } ], "description": "The syntax of the grammar definition. One of `lark` or `regex`." }, "definition": { "type": "string", "description": "The grammar definition." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.CustomToolParamFormat" } ], "description": "A grammar defined by the user.", "title": "Grammar format" }, "OpenAI.CustomTextFormatParam": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "text" ], "description": "Unconstrained text format. Always `text`.", "x-stainless-const": true, "default": "text" } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.CustomToolParamFormat" } ], "description": "Unconstrained free-form text.", "title": "Text format" }, "OpenAI.CustomToolParam": { "type": "object", "required": [ "type", "name" ], "properties": { "type": { "type": "string", "enum": [ "custom" ], "description": "The type of the custom tool. Always `custom`.", "x-stainless-const": true, "default": "custom" }, "name": { "type": "string", "description": "The name of the custom tool, used to identify it in tool calls." }, "description": { "type": "string", "description": "Optional description of the custom tool, used to provide more context." }, "format": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.CustomToolParamFormat" } ], "description": "The input format for the custom tool. Default is unconstrained text." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Tool" } ], "description": "A custom tool that processes input using a specified format. Learn more about [custom tools](/docs/guides/function-calling#custom-tools)", "title": "Custom tool" }, "OpenAI.CustomToolParamFormat": { "type": "object", "required": [ "type" ], "properties": { "type": { "$ref": "#/components/schemas/OpenAI.CustomToolParamFormatType" } }, "discriminator": { "propertyName": "type", "mapping": { "text": "#/components/schemas/OpenAI.CustomTextFormatParam", "grammar": "#/components/schemas/OpenAI.CustomGrammarFormatParam" } }, "description": "The input format for the custom tool. Default is unconstrained text." }, "OpenAI.CustomToolParamFormatType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "text", "grammar" ] } ] }, "OpenAI.DeletedConversationResource": { "type": "object", "required": [ "object", "deleted", "id" ], "properties": { "object": { "type": "string", "enum": [ "conversation.deleted" ], "x-stainless-const": true, "default": "conversation.deleted" }, "deleted": { "type": "boolean" }, "id": { "type": "string" } } }, "OpenAI.DetailEnum": { "type": "string", "enum": [ "low", "high", "auto" ] }, "OpenAI.DoubleClickAction": { "type": "object", "required": [ "type", "x", "y" ], "properties": { "type": { "type": "string", "enum": [ "double_click" ], "description": "Specifies the event type. For a double click action, this property is always set to `double_click`.", "x-stainless-const": true, "default": "double_click" }, "x": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The x-coordinate where the double click occurred." }, "y": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The y-coordinate where the double click occurred." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ComputerAction" } ], "description": "A double click action.", "title": "DoubleClick" }, "OpenAI.DragParam": { "type": "object", "required": [ "type", "path" ], "properties": { "type": { "type": "string", "enum": [ "drag" ], "description": "Specifies the event type. For a drag action, this property is always set to `drag`.", "x-stainless-const": true, "default": "drag" }, "path": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.CoordParam" }, "description": "An array of coordinates representing the path of the drag action. Coordinates will appear as an array of objects, eg\n ```\n [\n { x: 100, y: 200 },\n { x: 200, y: 300 }\n ]\n ```" } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ComputerAction" } ], "description": "A drag action.", "title": "Drag" }, "OpenAI.EasyInputMessage": { "type": "object", "required": [ "role", "content", "type" ], "properties": { "role": { "type": "string", "enum": [ "user", "assistant", "system", "developer" ], "description": "The role of the message input. One of `user`, `assistant`, `system`, or\n `developer`." }, "content": { "oneOf": [ { "type": "string" }, { "$ref": "#/components/schemas/OpenAI.InputMessageContentList" } ], "description": "Text, image, or audio input to the model, used to generate a response.\n Can also contain previous assistant responses." }, "type": { "type": "string", "enum": [ "message" ], "description": "The type of the message input. Always `message`.", "x-stainless-const": true }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "description": "The status of item. One of `in_progress`, `completed`, or\n `incomplete`. Populated when items are returned via API." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.InputItem" } ], "description": "A message input to the model with a role indicating instruction following\nhierarchy. Instructions given with the `developer` or `system` role take\nprecedence over instructions given with the `user` role. Messages with the\n`assistant` role are presumed to have been generated by the model in previous\ninteractions.", "title": "Input message" }, "OpenAI.Error": { "type": "object", "required": [ "code", "message" ], "properties": { "code": { "type": "string", "nullable": true }, "message": { "type": "string" }, "param": { "type": "string", "nullable": true }, "type": { "type": "string" }, "details": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.Error" } }, "additionalInfo": { "type": "object", "additionalProperties": {} }, "debugInfo": { "type": "object", "additionalProperties": {} } } }, "OpenAI.EvalApiError": { "type": "object", "required": [ "code", "message" ], "properties": { "code": { "type": "string", "description": "The error code." }, "message": { "type": "string", "description": "The error message." } }, "description": "An object representing an error response from the Eval API.", "title": "EvalApiError", "x-oaiMeta": { "name": "The API error object", "group": "evals", "example": "{\n \"code\": \"internal_error\",\n \"message\": \"The eval run failed due to an internal error.\"\n}\n" } }, "OpenAI.EvalGraderLabelModel": { "type": "object", "required": [ "type", "name", "model", "input", "labels", "passing_labels" ], "properties": { "type": { "type": "string", "enum": [ "label_model" ], "description": "The object type, which is always `label_model`.", "x-stainless-const": true }, "name": { "type": "string", "description": "The name of the grader." }, "model": { "type": "string", "description": "The model to use for the evaluation. Must support structured outputs." }, "input": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.EvalItem" } }, "labels": { "type": "array", "items": { "type": "string" }, "description": "The labels to assign to each item in the evaluation." }, "passing_labels": { "type": "array", "items": { "type": "string" }, "description": "The labels that indicate a passing result. Must be a subset of labels." } }, "title": "LabelModelGrader" }, "OpenAI.EvalGraderPython": { "type": "object", "required": [ "type", "name", "source" ], "properties": { "type": { "type": "string", "enum": [ "python" ], "description": "The object type, which is always `python`.", "x-stainless-const": true }, "name": { "type": "string", "description": "The name of the grader." }, "source": { "type": "string", "description": "The source code of the python script." }, "image_tag": { "type": "string", "description": "The image tag to use for the python script." }, "pass_threshold": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.numeric" } ], "description": "The threshold for the score." } }, "title": "PythonGrader" }, "OpenAI.EvalGraderScoreModel": { "type": "object", "required": [ "type", "name", "model", "input" ], "properties": { "type": { "type": "string", "enum": [ "score_model" ], "description": "The object type, which is always `score_model`.", "x-stainless-const": true }, "name": { "type": "string", "description": "The name of the grader." }, "model": { "type": "string", "description": "The model to use for the evaluation." }, "sampling_params": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.EvalGraderScoreModelSamplingParams" } ], "description": "The sampling parameters for the model." }, "input": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.EvalItem" }, "description": "The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings." }, "range": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.numeric" }, "description": "The range of the score. Defaults to `[0, 1]`." }, "pass_threshold": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.numeric" } ], "description": "The threshold for the score." } }, "title": "ScoreModelGrader" }, "OpenAI.EvalGraderScoreModelSamplingParams": { "type": "object", "properties": { "seed": { "type": "integer", "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "nullable": true }, "top_p": { "type": "number", "allOf": [ { "$ref": "#/components/schemas/OpenAI.numeric" } ], "nullable": true, "default": 1 }, "temperature": { "type": "number", "allOf": [ { "$ref": "#/components/schemas/OpenAI.numeric" } ], "nullable": true }, "max_completions_tokens": { "type": "integer", "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "nullable": true }, "reasoning_effort": { "$ref": "#/components/schemas/OpenAI.ReasoningEffort" } } }, "OpenAI.EvalGraderStringCheck": { "type": "object", "required": [ "type", "name", "input", "reference", "operation" ], "properties": { "type": { "type": "string", "enum": [ "string_check" ], "description": "The object type, which is always `string_check`.", "x-stainless-const": true }, "name": { "type": "string", "description": "The name of the grader." }, "input": { "type": "string", "description": "The input text. This may include template strings." }, "reference": { "type": "string", "description": "The reference text. This may include template strings." }, "operation": { "type": "string", "enum": [ "eq", "ne", "like", "ilike" ], "description": "The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`." } }, "title": "StringCheckGrader" }, "OpenAI.EvalGraderTextSimilarity": { "type": "object", "required": [ "type", "name", "input", "reference", "evaluation_metric", "pass_threshold" ], "properties": { "type": { "type": "string", "enum": [ "text_similarity" ], "description": "The type of grader.", "x-stainless-const": true, "default": "text_similarity" }, "name": { "type": "string", "description": "The name of the grader." }, "input": { "type": "string", "description": "The text being graded." }, "reference": { "type": "string", "description": "The text being graded against." }, "evaluation_metric": { "type": "string", "enum": [ "cosine", "fuzzy_match", "bleu", "gleu", "meteor", "rouge_1", "rouge_2", "rouge_3", "rouge_4", "rouge_5", "rouge_l" ], "description": "The evaluation metric to use. One of `cosine`, `fuzzy_match`, `bleu`,\n `gleu`, `meteor`, `rouge_1`, `rouge_2`, `rouge_3`, `rouge_4`, `rouge_5`,\n or `rouge_l`." }, "pass_threshold": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.numeric" } ], "description": "The threshold for the score." } }, "title": "TextSimilarityGrader" }, "OpenAI.EvalItem": { "type": "object", "required": [ "role", "content" ], "properties": { "role": { "type": "string", "enum": [ "user", "assistant", "system", "developer" ], "description": "The role of the message input. One of `user`, `assistant`, `system`, or\n `developer`." }, "content": { "$ref": "#/components/schemas/OpenAI.EvalItemContent" }, "type": { "type": "string", "enum": [ "message" ], "description": "The type of the message input. Always `message`.", "x-stainless-const": true } }, "description": "A message input to the model with a role indicating instruction following\nhierarchy. Instructions given with the `developer` or `system` role take\nprecedence over instructions given with the `user` role. Messages with the\n`assistant` role are presumed to have been generated by the model in previous\ninteractions.", "title": "Eval message object" }, "OpenAI.EvalItemContent": { "oneOf": [ { "$ref": "#/components/schemas/OpenAI.EvalItemContentItem" }, { "$ref": "#/components/schemas/OpenAI.EvalItemContentArray" } ], "description": "Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items.", "title": "Eval content" }, "OpenAI.EvalItemContentArray": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.EvalItemContentItem" }, "description": "A list of inputs, each of which may be either an input text, output text, input\nimage, or input audio object.", "title": "An array of Input text, Output text, Input image, and Input audio" }, "OpenAI.EvalItemContentItem": { "oneOf": [ { "$ref": "#/components/schemas/OpenAI.EvalItemContentText" }, { "$ref": "#/components/schemas/OpenAI.EvalItemContentItemObject" } ], "description": "A single content item: input text, output text, input image, or input audio.", "title": "Eval content item" }, "OpenAI.EvalItemContentItemObject": { "type": "object", "required": [ "type" ], "properties": { "type": { "$ref": "#/components/schemas/OpenAI.EvalItemContentItemObjectType" } }, "discriminator": { "propertyName": "type", "mapping": { "output_text": "#/components/schemas/OpenAI.EvalItemContentOutputText", "input_image": "#/components/schemas/OpenAI.EvalItemInputImage", "input_audio": "#/components/schemas/OpenAI.InputAudio", "input_text": "#/components/schemas/OpenAI.EvalItemContentItemObjectInputTextContent" } }, "description": "A single content item: input text, output text, input image, or input audio.", "title": "Eval content item" }, "OpenAI.EvalItemContentItemObjectInputTextContent": { "type": "object", "required": [ "type", "text" ], "properties": { "type": { "type": "string", "enum": [ "input_text" ], "description": "The type of the input item. Always `input_text`.", "x-stainless-const": true, "default": "input_text" }, "text": { "type": "string", "description": "The text input to the model." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.EvalItemContentItemObject" } ], "description": "A text input to the model.", "title": "Input text" }, "OpenAI.EvalItemContentItemObjectType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "input_text", "output_text", "input_image", "input_audio" ] } ] }, "OpenAI.EvalItemContentOutputText": { "type": "object", "required": [ "type", "text" ], "properties": { "type": { "type": "string", "enum": [ "output_text" ], "description": "The type of the output text. Always `output_text`.", "x-stainless-const": true }, "text": { "type": "string", "description": "The text output from the model." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.EvalItemContentItemObject" } ], "description": "A text output from the model.", "title": "Output text" }, "OpenAI.EvalItemContentText": { "type": "string", "description": "A text input to the model.", "title": "Text input" }, "OpenAI.EvalItemInputImage": { "type": "object", "required": [ "type", "image_url" ], "properties": { "type": { "type": "string", "enum": [ "input_image" ], "description": "The type of the image input. Always `input_image`.", "x-stainless-const": true }, "image_url": { "type": "string", "format": "uri", "description": "The URL of the image input." }, "detail": { "type": "string", "description": "The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.EvalItemContentItemObject" } ], "description": "An image input block used within EvalItem content arrays.", "title": "Input image" }, "OpenAI.EvalJsonlFileContentSource": { "type": "object", "required": [ "type", "content" ], "properties": { "type": { "type": "string", "enum": [ "file_content" ], "description": "The type of jsonl source. Always `file_content`.", "x-stainless-const": true, "default": "file_content" }, "content": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.EvalJsonlFileContentSourceContent" }, "description": "The content of the jsonl file." } }, "title": "EvalJsonlFileContentSource" }, "OpenAI.EvalJsonlFileContentSourceContent": { "type": "object", "required": [ "item" ], "properties": { "item": { "type": "object", "additionalProperties": {} }, "sample": { "type": "object", "additionalProperties": {} } } }, "OpenAI.EvalJsonlFileIdSource": { "type": "object", "required": [ "type", "id" ], "properties": { "type": { "type": "string", "enum": [ "file_id" ], "description": "The type of jsonl source. Always `file_id`.", "x-stainless-const": true, "default": "file_id" }, "id": { "type": "string", "description": "The identifier of the file." } }, "title": "EvalJsonlFileIdSource" }, "OpenAI.EvalResponsesSource": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "responses" ], "description": "The type of run data source. Always `responses`." }, "metadata": { "type": "object", "additionalProperties": {}, "nullable": true }, "model": { "type": "string", "nullable": true }, "instructions_search": { "type": "string", "nullable": true }, "created_after": { "type": "integer", "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "nullable": true }, "created_before": { "type": "integer", "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "nullable": true }, "reasoning_effort": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ReasoningEffort" } ], "nullable": true }, "temperature": { "type": "number", "allOf": [ { "$ref": "#/components/schemas/OpenAI.numeric" } ], "nullable": true }, "top_p": { "type": "number", "allOf": [ { "$ref": "#/components/schemas/OpenAI.numeric" } ], "nullable": true }, "users": { "type": "array", "items": { "type": "string" }, "nullable": true }, "tools": { "type": "array", "items": { "type": "string" }, "nullable": true } }, "description": "A EvalResponsesSource object describing a run data source configuration.", "title": "EvalResponsesSource", "x-oaiMeta": { "name": "The run data source object used to configure an individual run", "group": "eval runs", "example": "{\n \"type\": \"responses\",\n \"model\": \"gpt-4o-mini-2024-07-18\",\n \"temperature\": 0.7,\n \"top_p\": 1.0,\n \"users\": [\"user1\", \"user2\"],\n \"tools\": [\"tool1\", \"tool2\"],\n \"instructions_search\": \"You are a coding assistant\"\n}\n" } }, "OpenAI.EvalRunOutputItemSample": { "type": "object", "required": [ "input", "output", "finish_reason", "model", "usage", "error", "temperature", "max_completion_tokens", "top_p", "seed" ], "properties": { "input": { "type": "array", "items": { "$ref": "#/components/schemas/EvalRunOutputItemSampleInput" } }, "output": { "type": "array", "items": { "$ref": "#/components/schemas/EvalRunOutputItemSampleOutput" } }, "finish_reason": { "type": "string" }, "model": { "type": "string" }, "usage": { "$ref": "#/components/schemas/OpenAI.EvalRunOutputItemSampleUsage" }, "error": { "$ref": "#/components/schemas/OpenAI.EvalApiError" }, "temperature": { "$ref": "#/components/schemas/OpenAI.numeric" }, "max_completion_tokens": { "$ref": "#/components/schemas/OpenAI.integer" }, "top_p": { "$ref": "#/components/schemas/OpenAI.numeric" }, "seed": { "$ref": "#/components/schemas/OpenAI.integer" } } }, "OpenAI.EvalRunOutputItemSampleUsage": { "type": "object", "required": [ "total_tokens", "completion_tokens", "prompt_tokens", "cached_tokens" ], "properties": { "total_tokens": { "$ref": "#/components/schemas/OpenAI.integer" }, "completion_tokens": { "$ref": "#/components/schemas/OpenAI.integer" }, "prompt_tokens": { "$ref": "#/components/schemas/OpenAI.integer" }, "cached_tokens": { "$ref": "#/components/schemas/OpenAI.integer" } } }, "OpenAI.EvalRunPerModelUsage": { "type": "object", "required": [ "model_name", "invocation_count", "prompt_tokens", "completion_tokens", "total_tokens", "cached_tokens" ], "properties": { "model_name": { "type": "string" }, "invocation_count": { "$ref": "#/components/schemas/OpenAI.integer" }, "prompt_tokens": { "$ref": "#/components/schemas/OpenAI.integer" }, "completion_tokens": { "$ref": "#/components/schemas/OpenAI.integer" }, "total_tokens": { "$ref": "#/components/schemas/OpenAI.integer" }, "cached_tokens": { "$ref": "#/components/schemas/OpenAI.integer" } } }, "OpenAI.EvalRunPerTestingCriteriaResults": { "type": "object", "required": [ "testing_criteria", "passed", "failed" ], "properties": { "testing_criteria": { "type": "string" }, "passed": { "$ref": "#/components/schemas/OpenAI.integer" }, "failed": { "$ref": "#/components/schemas/OpenAI.integer" } } }, "OpenAI.EvalRunResultCounts": { "type": "object", "required": [ "total", "errored", "failed", "passed" ], "properties": { "total": { "$ref": "#/components/schemas/OpenAI.integer" }, "errored": { "$ref": "#/components/schemas/OpenAI.integer" }, "failed": { "$ref": "#/components/schemas/OpenAI.integer" }, "passed": { "$ref": "#/components/schemas/OpenAI.integer" } } }, "OpenAI.EvalStoredCompletionsSource": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "stored_completions" ], "description": "The type of source. Always `stored_completions`.", "x-stainless-const": true, "default": "stored_completions" }, "metadata": { "type": "object", "allOf": [ { "$ref": "#/components/schemas/OpenAI.Metadata" } ], "nullable": true }, "model": { "type": "string", "nullable": true }, "created_after": { "type": "integer", "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "nullable": true }, "created_before": { "type": "integer", "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "nullable": true }, "limit": { "type": "integer", "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "nullable": true } }, "description": "A StoredCompletionsRunDataSource configuration describing a set of filters", "title": "StoredCompletionsRunDataSource", "x-oaiMeta": { "name": "The stored completions data source object used to configure an individual run", "group": "eval runs", "example": "{\n \"type\": \"stored_completions\",\n \"model\": \"gpt-4o\",\n \"created_after\": 1668124800,\n \"created_before\": 1668124900,\n \"limit\": 100,\n \"metadata\": {}\n}\n" } }, "OpenAI.FileCitationBody": { "type": "object", "required": [ "type", "file_id", "index", "filename" ], "properties": { "type": { "type": "string", "enum": [ "file_citation" ], "description": "The type of the file citation. Always `file_citation`.", "x-stainless-const": true, "default": "file_citation" }, "file_id": { "type": "string", "description": "The ID of the file." }, "index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the file in the list of files." }, "filename": { "type": "string", "description": "The filename of the file cited." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Annotation" } ], "description": "A citation to a file.", "title": "File citation" }, "OpenAI.FilePath": { "type": "object", "required": [ "type", "file_id", "index" ], "properties": { "type": { "type": "string", "enum": [ "file_path" ], "description": "The type of the file path. Always `file_path`.", "x-stainless-const": true }, "file_id": { "type": "string", "description": "The ID of the file." }, "index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the file in the list of files." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Annotation" } ], "description": "A path to a file.", "title": "File path" }, "OpenAI.FileSearchTool": { "type": "object", "required": [ "type", "vector_store_ids" ], "properties": { "type": { "type": "string", "enum": [ "file_search" ], "description": "The type of the file search tool. Always `file_search`.", "x-stainless-const": true, "default": "file_search" }, "vector_store_ids": { "type": "array", "items": { "type": "string" }, "description": "The IDs of the vector stores to search." }, "max_num_results": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The maximum number of results to return. This number should be between 1 and 50 inclusive." }, "ranking_options": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.RankingOptions" } ], "description": "Ranking options for search." }, "filters": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.Filters" } ], "nullable": true }, "name": { "type": "string", "description": "Optional user-defined name for this tool or configuration." }, "description": { "type": "string", "description": "Optional user-defined description for this tool or configuration." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Tool" } ], "description": "A tool that searches for relevant content from uploaded files. Learn more about the [file search tool](https://platform.openai.com/docs/guides/tools-file-search).", "title": "File search" }, "OpenAI.FileSearchToolCallResults": { "type": "object", "properties": { "file_id": { "type": "string" }, "text": { "type": "string" }, "filename": { "type": "string" }, "attributes": { "type": "object", "allOf": [ { "$ref": "#/components/schemas/OpenAI.VectorStoreFileAttributes" } ], "nullable": true }, "score": { "type": "number", "format": "float" } } }, "OpenAI.Filters": { "anyOf": [ { "$ref": "#/components/schemas/OpenAI.ComparisonFilter" }, { "$ref": "#/components/schemas/OpenAI.CompoundFilter" } ] }, "OpenAI.FineTuneDPOHyperparameters": { "type": "object", "properties": { "beta": { "oneOf": [ { "type": "string", "enum": [ "auto" ] }, { "$ref": "#/components/schemas/OpenAI.numeric" } ], "description": "The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model.", "default": "auto" }, "batch_size": { "oneOf": [ { "type": "string", "enum": [ "auto" ] }, { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.", "default": "auto" }, "learning_rate_multiplier": { "oneOf": [ { "type": "string", "enum": [ "auto" ] }, { "$ref": "#/components/schemas/OpenAI.numeric" } ], "description": "Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.", "default": "auto" }, "n_epochs": { "oneOf": [ { "type": "string", "enum": [ "auto" ] }, { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.", "default": "auto" } }, "description": "The hyperparameters used for the DPO fine-tuning job." }, "OpenAI.FineTuneDPOMethod": { "type": "object", "properties": { "hyperparameters": { "$ref": "#/components/schemas/OpenAI.FineTuneDPOHyperparameters" } }, "description": "Configuration for the DPO fine-tuning method." }, "OpenAI.FineTuneMethod": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "supervised", "dpo", "reinforcement" ], "description": "The type of method. Is either `supervised`, `dpo`, or `reinforcement`." }, "supervised": { "$ref": "#/components/schemas/OpenAI.FineTuneSupervisedMethod" }, "dpo": { "$ref": "#/components/schemas/OpenAI.FineTuneDPOMethod" }, "reinforcement": { "$ref": "#/components/schemas/OpenAI.FineTuneReinforcementMethod" } }, "description": "The method used for fine-tuning." }, "OpenAI.FineTuneReinforcementHyperparameters": { "type": "object", "properties": { "batch_size": { "oneOf": [ { "type": "string", "enum": [ "auto" ] }, { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.", "default": "auto" }, "learning_rate_multiplier": { "oneOf": [ { "type": "string", "enum": [ "auto" ] }, { "$ref": "#/components/schemas/OpenAI.numeric" } ], "description": "Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.", "default": "auto" }, "n_epochs": { "oneOf": [ { "type": "string", "enum": [ "auto" ] }, { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.", "default": "auto" }, "reasoning_effort": { "type": "string", "enum": [ "default", "low", "medium", "high" ], "description": "Level of reasoning effort.", "default": "default" }, "compute_multiplier": { "oneOf": [ { "type": "string", "enum": [ "auto" ] }, { "$ref": "#/components/schemas/OpenAI.numeric" } ], "description": "Multiplier on amount of compute used for exploring search space during training.", "default": "auto" }, "eval_interval": { "oneOf": [ { "type": "string", "enum": [ "auto" ] }, { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The number of training steps between evaluation runs.", "default": "auto" }, "eval_samples": { "oneOf": [ { "type": "string", "enum": [ "auto" ] }, { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "Number of evaluation samples to generate per training step.", "default": "auto" } }, "description": "The hyperparameters used for the reinforcement fine-tuning job." }, "OpenAI.FineTuneReinforcementMethod": { "type": "object", "required": [ "grader" ], "properties": { "grader": { "oneOf": [ { "$ref": "#/components/schemas/OpenAI.GraderStringCheck" }, { "$ref": "#/components/schemas/OpenAI.GraderTextSimilarity" }, { "$ref": "#/components/schemas/OpenAI.GraderPython" }, { "$ref": "#/components/schemas/OpenAI.GraderScoreModel" }, { "$ref": "#/components/schemas/OpenAI.GraderMulti" } ], "description": "The grader used for the fine-tuning job." }, "hyperparameters": { "$ref": "#/components/schemas/OpenAI.FineTuneReinforcementHyperparameters" } }, "description": "Configuration for the reinforcement fine-tuning method." }, "OpenAI.FineTuneSupervisedHyperparameters": { "type": "object", "properties": { "batch_size": { "oneOf": [ { "type": "string", "enum": [ "auto" ] }, { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.", "default": "auto" }, "learning_rate_multiplier": { "oneOf": [ { "type": "string", "enum": [ "auto" ] }, { "$ref": "#/components/schemas/OpenAI.numeric" } ], "description": "Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.", "default": "auto" }, "n_epochs": { "oneOf": [ { "type": "string", "enum": [ "auto" ] }, { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.", "default": "auto" } }, "description": "The hyperparameters used for the fine-tuning job." }, "OpenAI.FineTuneSupervisedMethod": { "type": "object", "properties": { "hyperparameters": { "$ref": "#/components/schemas/OpenAI.FineTuneSupervisedHyperparameters" } }, "description": "Configuration for the supervised fine-tuning method." }, "OpenAI.FineTuningIntegration": { "type": "object", "required": [ "type", "wandb" ], "properties": { "type": { "type": "string", "enum": [ "wandb" ], "description": "The type of the integration being enabled for the fine-tuning job", "x-stainless-const": true }, "wandb": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.FineTuningIntegrationWandb" } ], "description": "The settings for your integration with Weights and Biases. This payload specifies the project that\n metrics will be sent to. Optionally, you can set an explicit display name for your run, add tags\n to your run, and set a default entity (team, username, etc) to be associated with your run." } }, "title": "Fine-Tuning Job Integration" }, "OpenAI.FineTuningIntegrationWandb": { "type": "object", "required": [ "project" ], "properties": { "project": { "type": "string" }, "name": { "type": "string", "nullable": true }, "entity": { "type": "string", "nullable": true }, "tags": { "type": "array", "items": { "type": "string" } } } }, "OpenAI.FineTuningJob": { "type": "object", "required": [ "id", "created_at", "error", "fine_tuned_model", "finished_at", "hyperparameters", "model", "object", "organization_id", "result_files", "status", "trained_tokens", "training_file", "validation_file", "seed" ], "properties": { "id": { "type": "string", "description": "The object identifier, which can be referenced in the API endpoints." }, "created_at": { "type": "integer", "format": "unixtime", "description": "The Unix timestamp (in seconds) for when the fine-tuning job was created." }, "error": { "type": "object", "allOf": [ { "$ref": "#/components/schemas/OpenAI.FineTuningJobError" } ], "nullable": true }, "fine_tuned_model": { "type": "string", "nullable": true }, "finished_at": { "type": "integer", "format": "unixtime", "nullable": true }, "hyperparameters": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.FineTuningJobHyperparameters" } ], "description": "The hyperparameters used for the fine-tuning job. This value will only be returned when running `supervised` jobs." }, "model": { "type": "string", "description": "The base model that is being fine-tuned." }, "object": { "type": "string", "enum": [ "fine_tuning.job" ], "description": "The object type, which is always \"fine_tuning.job\".", "x-stainless-const": true }, "organization_id": { "type": "string", "description": "The organization that owns the fine-tuning job." }, "result_files": { "type": "array", "items": { "type": "string" }, "description": "The compiled results file ID(s) for the fine-tuning job. You can retrieve the results with the [Files API](/docs/api-reference/files/retrieve-contents)." }, "status": { "type": "string", "enum": [ "validating_files", "queued", "running", "succeeded", "failed", "cancelled" ], "description": "The current status of the fine-tuning job, which can be either `validating_files`, `queued`, `running`, `succeeded`, `failed`, or `cancelled`." }, "trained_tokens": { "type": "integer", "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "nullable": true }, "training_file": { "type": "string", "description": "The file ID used for training. You can retrieve the training data with the [Files API](/docs/api-reference/files/retrieve-contents)." }, "validation_file": { "type": "string", "nullable": true }, "integrations": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.FineTuningIntegration" }, "nullable": true }, "seed": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The seed used for the fine-tuning job." }, "estimated_finish": { "type": "integer", "format": "unixtime", "nullable": true }, "method": { "$ref": "#/components/schemas/OpenAI.FineTuneMethod" }, "metadata": { "type": "object", "allOf": [ { "$ref": "#/components/schemas/OpenAI.Metadata" } ], "nullable": true } }, "description": "The `fine_tuning.job` object represents a fine-tuning job that has been created through the API.", "title": "FineTuningJob", "x-oaiMeta": { "name": "The fine-tuning job object", "example": "{\n \"object\": \"fine_tuning.job\",\n \"id\": \"ftjob-abc123\",\n \"model\": \"davinci-002\",\n \"created_at\": 1692661014,\n \"finished_at\": 1692661190,\n \"fine_tuned_model\": \"ft:davinci-002:my-org:custom_suffix:7q8mpxmy\",\n \"organization_id\": \"org-123\",\n \"result_files\": [\n \"file-abc123\"\n ],\n \"status\": \"succeeded\",\n \"validation_file\": null,\n \"training_file\": \"file-abc123\",\n \"hyperparameters\": {\n \"n_epochs\": 4,\n \"batch_size\": 1,\n \"learning_rate_multiplier\": 1.0\n },\n \"trained_tokens\": 5768,\n \"integrations\": [],\n \"seed\": 0,\n \"estimated_finish\": 0,\n \"method\": {\n \"type\": \"supervised\",\n \"supervised\": {\n \"hyperparameters\": {\n \"n_epochs\": 4,\n \"batch_size\": 1,\n \"learning_rate_multiplier\": 1.0\n }\n }\n },\n \"metadata\": {\n \"key\": \"value\"\n }\n}\n" } }, "OpenAI.FineTuningJobCheckpoint": { "type": "object", "required": [ "id", "created_at", "fine_tuned_model_checkpoint", "step_number", "metrics", "fine_tuning_job_id", "object" ], "properties": { "id": { "type": "string", "description": "The checkpoint identifier, which can be referenced in the API endpoints." }, "created_at": { "type": "integer", "format": "unixtime", "description": "The Unix timestamp (in seconds) for when the checkpoint was created." }, "fine_tuned_model_checkpoint": { "type": "string", "description": "The name of the fine-tuned checkpoint model that is created." }, "step_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The step number that the checkpoint was created at." }, "metrics": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.FineTuningJobCheckpointMetrics" } ], "description": "Metrics at the step number during the fine-tuning job." }, "fine_tuning_job_id": { "type": "string", "description": "The name of the fine-tuning job that this checkpoint was created from." }, "object": { "type": "string", "enum": [ "fine_tuning.job.checkpoint" ], "description": "The object type, which is always \"fine_tuning.job.checkpoint\".", "x-stainless-const": true } }, "description": "The `fine_tuning.job.checkpoint` object represents a model checkpoint for a fine-tuning job that is ready to use.", "title": "FineTuningJobCheckpoint", "x-oaiMeta": { "name": "The fine-tuning job checkpoint object", "example": "{\n \"object\": \"fine_tuning.job.checkpoint\",\n \"id\": \"ftckpt_qtZ5Gyk4BLq1SfLFWp3RtO3P\",\n \"created_at\": 1712211699,\n \"fine_tuned_model_checkpoint\": \"ft:gpt-4o-mini-2024-07-18:my-org:custom_suffix:9ABel2dg:ckpt-step-88\",\n \"fine_tuning_job_id\": \"ftjob-fpbNQ3H1GrMehXRf8cO97xTN\",\n \"metrics\": {\n \"step\": 88,\n \"train_loss\": 0.478,\n \"train_mean_token_accuracy\": 0.924,\n \"valid_loss\": 10.112,\n \"valid_mean_token_accuracy\": 0.145,\n \"full_valid_loss\": 0.567,\n \"full_valid_mean_token_accuracy\": 0.944\n },\n \"step_number\": 88\n}\n" } }, "OpenAI.FineTuningJobCheckpointMetrics": { "type": "object", "properties": { "step": { "$ref": "#/components/schemas/OpenAI.numeric" }, "train_loss": { "$ref": "#/components/schemas/OpenAI.numeric" }, "train_mean_token_accuracy": { "$ref": "#/components/schemas/OpenAI.numeric" }, "valid_loss": { "$ref": "#/components/schemas/OpenAI.numeric" }, "valid_mean_token_accuracy": { "$ref": "#/components/schemas/OpenAI.numeric" }, "full_valid_loss": { "$ref": "#/components/schemas/OpenAI.numeric" }, "full_valid_mean_token_accuracy": { "$ref": "#/components/schemas/OpenAI.numeric" } } }, "OpenAI.FineTuningJobError": { "type": "object", "required": [ "code", "message", "param" ], "properties": { "code": { "type": "string" }, "message": { "type": "string" }, "param": { "type": "string", "nullable": true } } }, "OpenAI.FineTuningJobEvent": { "type": "object", "required": [ "object", "id", "created_at", "level", "message" ], "properties": { "object": { "type": "string", "enum": [ "fine_tuning.job.event" ], "description": "The object type, which is always \"fine_tuning.job.event\".", "x-stainless-const": true }, "id": { "type": "string", "description": "The object identifier." }, "created_at": { "type": "integer", "format": "unixtime", "description": "The Unix timestamp (in seconds) for when the fine-tuning job was created." }, "level": { "type": "string", "enum": [ "info", "warn", "error" ], "description": "The log level of the event." }, "message": { "type": "string", "description": "The message of the event." }, "type": { "type": "string", "enum": [ "message", "metrics" ], "description": "The type of event." }, "data": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.FineTuningJobEventData" } ], "description": "The data associated with the event." } }, "description": "Fine-tuning job event object", "x-oaiMeta": { "name": "The fine-tuning job event object", "example": "{\n \"object\": \"fine_tuning.job.event\",\n \"id\": \"ftevent-abc123\"\n \"created_at\": 1677610602,\n \"level\": \"info\",\n \"message\": \"Created fine-tuning job\",\n \"data\": {},\n \"type\": \"message\"\n}\n" } }, "OpenAI.FineTuningJobEventData": { "type": "object" }, "OpenAI.FineTuningJobHyperparameters": { "type": "object", "properties": { "batch_size": { "anyOf": [ { "type": "string", "enum": [ "auto" ], "nullable": true }, { "type": "integer", "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "nullable": true } ], "default": "auto" }, "learning_rate_multiplier": { "oneOf": [ { "type": "string", "enum": [ "auto" ] }, { "$ref": "#/components/schemas/OpenAI.numeric" } ], "default": "auto" }, "n_epochs": { "oneOf": [ { "type": "string", "enum": [ "auto" ] }, { "$ref": "#/components/schemas/OpenAI.integer" } ], "default": "auto" } } }, "OpenAI.FunctionAndCustomToolCallOutput": { "type": "object", "required": [ "type" ], "properties": { "type": { "$ref": "#/components/schemas/OpenAI.FunctionAndCustomToolCallOutputType" } }, "discriminator": { "propertyName": "type", "mapping": { "input_text": "#/components/schemas/OpenAI.FunctionAndCustomToolCallOutputInputTextContent", "input_image": "#/components/schemas/OpenAI.FunctionAndCustomToolCallOutputInputImageContent", "input_file": "#/components/schemas/OpenAI.FunctionAndCustomToolCallOutputInputFileContent" } } }, "OpenAI.FunctionAndCustomToolCallOutputInputFileContent": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "input_file" ], "description": "The type of the input item. Always `input_file`.", "x-stainless-const": true, "default": "input_file" }, "file_id": { "type": "string", "nullable": true }, "filename": { "type": "string", "description": "The name of the file to be sent to the model." }, "file_url": { "type": "string", "format": "uri", "description": "The URL of the file to be sent to the model." }, "file_data": { "type": "string", "description": "The content of the file to be sent to the model." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.FunctionAndCustomToolCallOutput" } ], "description": "A file input to the model.", "title": "Input file" }, "OpenAI.FunctionAndCustomToolCallOutputInputImageContent": { "type": "object", "required": [ "type", "detail" ], "properties": { "type": { "type": "string", "enum": [ "input_image" ], "description": "The type of the input item. Always `input_image`.", "x-stainless-const": true, "default": "input_image" }, "image_url": { "type": "string", "format": "uri", "nullable": true }, "file_id": { "type": "string", "nullable": true }, "detail": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ImageDetail" } ], "description": "The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.FunctionAndCustomToolCallOutput" } ], "description": "An image input to the model. Learn about [image inputs](/docs/guides/vision).", "title": "Input image" }, "OpenAI.FunctionAndCustomToolCallOutputInputTextContent": { "type": "object", "required": [ "type", "text" ], "properties": { "type": { "type": "string", "enum": [ "input_text" ], "description": "The type of the input item. Always `input_text`.", "x-stainless-const": true, "default": "input_text" }, "text": { "type": "string", "description": "The text input to the model." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.FunctionAndCustomToolCallOutput" } ], "description": "A text input to the model.", "title": "Input text" }, "OpenAI.FunctionAndCustomToolCallOutputType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "input_text", "input_image", "input_file" ] } ] }, "OpenAI.FunctionCallItemStatus": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ] }, "OpenAI.FunctionObject": { "type": "object", "required": [ "name" ], "properties": { "description": { "type": "string", "description": "A description of what the function does, used by the model to choose when and how to call the function." }, "name": { "type": "string", "description": "The name of the function to be called. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64." }, "parameters": { "$ref": "#/components/schemas/OpenAI.FunctionParameters" }, "strict": { "type": "boolean", "nullable": true } } }, "OpenAI.FunctionParameters": { "type": "object", "additionalProperties": {}, "description": "The parameters the functions accepts, described as a JSON Schema object. See the [guide](/docs/guides/function-calling) for examples, and the [JSON Schema reference](https://json-schema.org/understanding-json-schema/) for documentation about the format.\nOmitting `parameters` defines a function with an empty parameter list." }, "OpenAI.FunctionShellAction": { "type": "object", "required": [ "commands", "timeout_ms", "max_output_length" ], "properties": { "commands": { "type": "array", "items": { "type": "string" } }, "timeout_ms": { "type": "integer", "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "nullable": true }, "max_output_length": { "type": "integer", "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "nullable": true } }, "description": "Execute a shell command.", "title": "Shell exec action" }, "OpenAI.FunctionShellActionParam": { "type": "object", "required": [ "commands" ], "properties": { "commands": { "type": "array", "items": { "type": "string" }, "description": "Ordered shell commands for the execution environment to run." }, "timeout_ms": { "type": "integer", "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "nullable": true }, "max_output_length": { "type": "integer", "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "nullable": true } }, "description": "Commands and limits describing how to run the shell tool call.", "title": "Shell action" }, "OpenAI.FunctionShellCallEnvironment": { "type": "object", "required": [ "type" ], "properties": { "type": { "$ref": "#/components/schemas/OpenAI.FunctionShellCallEnvironmentType" } }, "discriminator": { "propertyName": "type", "mapping": { "local": "#/components/schemas/OpenAI.LocalEnvironmentResource", "container_reference": "#/components/schemas/OpenAI.ContainerReferenceResource" } } }, "OpenAI.FunctionShellCallEnvironmentType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "local", "container_reference" ] } ] }, "OpenAI.FunctionShellCallItemParamEnvironment": { "type": "object", "required": [ "type" ], "properties": { "type": { "$ref": "#/components/schemas/OpenAI.FunctionShellCallItemParamEnvironmentType" } }, "discriminator": { "propertyName": "type", "mapping": { "local": "#/components/schemas/OpenAI.FunctionShellCallItemParamEnvironmentLocalEnvironmentParam", "container_reference": "#/components/schemas/OpenAI.FunctionShellCallItemParamEnvironmentContainerReferenceParam" } }, "description": "The environment to execute the shell commands in." }, "OpenAI.FunctionShellCallItemParamEnvironmentContainerReferenceParam": { "type": "object", "required": [ "type", "container_id" ], "properties": { "type": { "type": "string", "enum": [ "container_reference" ], "description": "References a container created with the /v1/containers endpoint", "x-stainless-const": true, "default": "container_reference" }, "container_id": { "type": "string", "description": "The ID of the referenced container." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.FunctionShellCallItemParamEnvironment" } ] }, "OpenAI.FunctionShellCallItemParamEnvironmentLocalEnvironmentParam": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "local" ], "description": "Use a local computer environment.", "x-stainless-const": true, "default": "local" }, "skills": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.LocalSkillParam" }, "maxItems": 200, "description": "An optional list of skills." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.FunctionShellCallItemParamEnvironment" } ] }, "OpenAI.FunctionShellCallItemParamEnvironmentType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "local", "container_reference" ] } ] }, "OpenAI.FunctionShellCallItemStatus": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "description": "Status values reported for shell tool calls.", "title": "Shell call status" }, "OpenAI.FunctionShellCallOutputContent": { "type": "object", "required": [ "stdout", "stderr", "outcome" ], "properties": { "stdout": { "type": "string", "description": "The standard output that was captured." }, "stderr": { "type": "string", "description": "The standard error output that was captured." }, "outcome": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.FunctionShellCallOutputOutcome" } ], "description": "Represents either an exit outcome (with an exit code) or a timeout outcome for a shell call output chunk.", "title": "Shell call outcome" }, "created_by": { "type": "string", "description": "The identifier of the actor that created the item." } }, "description": "The content of a shell tool call output that was emitted.", "title": "Shell call output content" }, "OpenAI.FunctionShellCallOutputContentParam": { "type": "object", "required": [ "stdout", "stderr", "outcome" ], "properties": { "stdout": { "type": "string", "maxLength": 10485760, "description": "Captured stdout output for the shell call." }, "stderr": { "type": "string", "maxLength": 10485760, "description": "Captured stderr output for the shell call." }, "outcome": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.FunctionShellCallOutputOutcomeParam" } ], "description": "The exit or timeout outcome associated with this shell call." } }, "description": "Captured stdout and stderr for a portion of a shell tool call output.", "title": "Shell output content" }, "OpenAI.FunctionShellCallOutputExitOutcome": { "type": "object", "required": [ "type", "exit_code" ], "properties": { "type": { "type": "string", "enum": [ "exit" ], "description": "The outcome type. Always `exit`.", "x-stainless-const": true, "default": "exit" }, "exit_code": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "Exit code from the shell process." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.FunctionShellCallOutputOutcome" } ], "description": "Indicates that the shell commands finished and returned an exit code.", "title": "Shell call exit outcome" }, "OpenAI.FunctionShellCallOutputExitOutcomeParam": { "type": "object", "required": [ "type", "exit_code" ], "properties": { "type": { "type": "string", "enum": [ "exit" ], "description": "The outcome type. Always `exit`.", "x-stainless-const": true, "default": "exit" }, "exit_code": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The exit code returned by the shell process." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.FunctionShellCallOutputOutcomeParam" } ], "description": "Indicates that the shell commands finished and returned an exit code.", "title": "Shell call exit outcome" }, "OpenAI.FunctionShellCallOutputOutcome": { "type": "object", "required": [ "type" ], "properties": { "type": { "$ref": "#/components/schemas/OpenAI.FunctionShellCallOutputOutcomeType" } }, "discriminator": { "propertyName": "type", "mapping": { "timeout": "#/components/schemas/OpenAI.FunctionShellCallOutputTimeoutOutcome", "exit": "#/components/schemas/OpenAI.FunctionShellCallOutputExitOutcome" } }, "description": "Represents either an exit outcome (with an exit code) or a timeout outcome for a shell call output chunk.", "title": "Shell call outcome" }, "OpenAI.FunctionShellCallOutputOutcomeParam": { "type": "object", "required": [ "type" ], "properties": { "type": { "$ref": "#/components/schemas/OpenAI.FunctionShellCallOutputOutcomeParamType" } }, "discriminator": { "propertyName": "type", "mapping": { "timeout": "#/components/schemas/OpenAI.FunctionShellCallOutputTimeoutOutcomeParam", "exit": "#/components/schemas/OpenAI.FunctionShellCallOutputExitOutcomeParam" } }, "description": "The exit or timeout outcome associated with this shell call.", "title": "Shell call outcome" }, "OpenAI.FunctionShellCallOutputOutcomeParamType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "timeout", "exit" ] } ] }, "OpenAI.FunctionShellCallOutputOutcomeType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "timeout", "exit" ] } ] }, "OpenAI.FunctionShellCallOutputTimeoutOutcome": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "timeout" ], "description": "The outcome type. Always `timeout`.", "x-stainless-const": true, "default": "timeout" } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.FunctionShellCallOutputOutcome" } ], "description": "Indicates that the shell call exceeded its configured time limit.", "title": "Shell call timeout outcome" }, "OpenAI.FunctionShellCallOutputTimeoutOutcomeParam": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "timeout" ], "description": "The outcome type. Always `timeout`.", "x-stainless-const": true, "default": "timeout" } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.FunctionShellCallOutputOutcomeParam" } ], "description": "Indicates that the shell call exceeded its configured time limit.", "title": "Shell call timeout outcome" }, "OpenAI.FunctionShellToolParam": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "shell" ], "description": "The type of the shell tool. Always `shell`.", "x-stainless-const": true, "default": "shell" }, "environment": { "type": "object", "allOf": [ { "$ref": "#/components/schemas/OpenAI.FunctionShellToolParamEnvironment" } ], "nullable": true }, "name": { "type": "string", "description": "Optional user-defined name for this tool or configuration." }, "description": { "type": "string", "description": "Optional user-defined description for this tool or configuration." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Tool" } ], "description": "A tool that allows the model to execute shell commands.", "title": "Shell tool" }, "OpenAI.FunctionShellToolParamEnvironment": { "type": "object", "required": [ "type" ], "properties": { "type": { "$ref": "#/components/schemas/OpenAI.FunctionShellToolParamEnvironmentType" } }, "discriminator": { "propertyName": "type", "mapping": { "local": "#/components/schemas/OpenAI.FunctionShellToolParamEnvironmentLocalEnvironmentParam", "container_reference": "#/components/schemas/OpenAI.FunctionShellToolParamEnvironmentContainerReferenceParam", "container_auto": "#/components/schemas/OpenAI.ContainerAutoParam" } } }, "OpenAI.FunctionShellToolParamEnvironmentContainerReferenceParam": { "type": "object", "required": [ "type", "container_id" ], "properties": { "type": { "type": "string", "enum": [ "container_reference" ], "description": "References a container created with the /v1/containers endpoint", "x-stainless-const": true, "default": "container_reference" }, "container_id": { "type": "string", "description": "The ID of the referenced container." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.FunctionShellToolParamEnvironment" } ] }, "OpenAI.FunctionShellToolParamEnvironmentLocalEnvironmentParam": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "local" ], "description": "Use a local computer environment.", "x-stainless-const": true, "default": "local" }, "skills": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.LocalSkillParam" }, "maxItems": 200, "description": "An optional list of skills." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.FunctionShellToolParamEnvironment" } ] }, "OpenAI.FunctionShellToolParamEnvironmentType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "container_auto", "local", "container_reference" ] } ] }, "OpenAI.FunctionTool": { "type": "object", "required": [ "type", "name", "parameters", "strict" ], "properties": { "type": { "type": "string", "enum": [ "function" ], "description": "The type of the function tool. Always `function`.", "x-stainless-const": true, "default": "function" }, "name": { "type": "string", "description": "The name of the function to call." }, "description": { "type": "string", "nullable": true }, "parameters": { "type": "object", "additionalProperties": {}, "nullable": true }, "strict": { "type": "boolean", "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Tool" } ], "description": "Defines a function in your own code the model can choose to call. Learn more about [function calling](https://platform.openai.com/docs/guides/function-calling).", "title": "Function" }, "OpenAI.FunctionToolCallOutput": { "type": "object", "required": [ "type", "call_id", "output" ], "properties": { "id": { "type": "string", "description": "The unique ID of the function tool call output. Populated when this item\n is returned via API." }, "type": { "type": "string", "enum": [ "function_call_output" ], "description": "The type of the function tool call output. Always `function_call_output`.", "x-stainless-const": true }, "call_id": { "type": "string", "description": "The unique ID of the function tool call generated by the model." }, "output": { "oneOf": [ { "type": "string" }, { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.FunctionAndCustomToolCallOutput" } } ], "description": "The output from the function call generated by your code.\n Can be a string or an list of output content." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "description": "The status of the item. One of `in_progress`, `completed`, or\n `incomplete`. Populated when items are returned via API." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemField" } ], "description": "The output of a function tool call.", "title": "Function tool call output" }, "OpenAI.GraderLabelModel": { "type": "object", "required": [ "type", "name", "model", "input", "labels", "passing_labels" ], "properties": { "type": { "type": "string", "enum": [ "label_model" ], "description": "The object type, which is always `label_model`.", "x-stainless-const": true }, "name": { "type": "string", "description": "The name of the grader." }, "model": { "type": "string", "description": "The model to use for the evaluation. Must support structured outputs." }, "input": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.EvalItem" } }, "labels": { "type": "array", "items": { "type": "string" }, "description": "The labels to assign to each item in the evaluation." }, "passing_labels": { "type": "array", "items": { "type": "string" }, "description": "The labels that indicate a passing result. Must be a subset of labels." } }, "description": "A LabelModelGrader object which uses a model to assign labels to each item\nin the evaluation.", "title": "LabelModelGrader", "x-oaiMeta": { "name": "Label Model Grader", "group": "graders", "example": "{\n \"name\": \"First label grader\",\n \"type\": \"label_model\",\n \"model\": \"gpt-4o-2024-08-06\",\n \"input\": [\n {\n \"type\": \"message\",\n \"role\": \"system\",\n \"content\": {\n \"type\": \"input_text\",\n \"text\": \"Classify the sentiment of the following statement as one of positive, neutral, or negative\"\n }\n },\n {\n \"type\": \"message\",\n \"role\": \"user\",\n \"content\": {\n \"type\": \"input_text\",\n \"text\": \"Statement: {{item.response}}\"\n }\n }\n ],\n \"passing_labels\": [\n \"positive\"\n ],\n \"labels\": [\n \"positive\",\n \"neutral\",\n \"negative\"\n ]\n}\n" } }, "OpenAI.GraderMulti": { "type": "object", "required": [ "type", "name", "graders", "calculate_output" ], "properties": { "type": { "type": "string", "enum": [ "multi" ], "description": "The object type, which is always `multi`.", "x-stainless-const": true, "default": "multi" }, "name": { "type": "string", "description": "The name of the grader." }, "graders": { "oneOf": [ { "$ref": "#/components/schemas/OpenAI.GraderStringCheck" }, { "$ref": "#/components/schemas/OpenAI.GraderTextSimilarity" }, { "$ref": "#/components/schemas/OpenAI.GraderPython" }, { "$ref": "#/components/schemas/OpenAI.GraderScoreModel" }, { "$ref": "#/components/schemas/OpenAI.GraderLabelModel" } ] }, "calculate_output": { "type": "string", "description": "A formula to calculate the output based on grader results." } }, "description": "A MultiGrader object combines the output of multiple graders to produce a single score.", "title": "MultiGrader", "x-oaiMeta": { "name": "Multi Grader", "group": "graders", "example": "{\n \"type\": \"multi\",\n \"name\": \"example multi grader\",\n \"graders\": [\n {\n \"type\": \"text_similarity\",\n \"name\": \"example text similarity grader\",\n \"input\": \"The graded text\",\n \"reference\": \"The reference text\",\n \"evaluation_metric\": \"fuzzy_match\"\n },\n {\n \"type\": \"string_check\",\n \"name\": \"Example string check grader\",\n \"input\": \"{{sample.output_text}}\",\n \"reference\": \"{{item.label}}\",\n \"operation\": \"eq\"\n }\n ],\n \"calculate_output\": \"0.5 * text_similarity_score + 0.5 * string_check_score)\"\n}\n" } }, "OpenAI.GraderPython": { "type": "object", "required": [ "type", "name", "source" ], "properties": { "type": { "type": "string", "enum": [ "python" ], "description": "The object type, which is always `python`.", "x-stainless-const": true }, "name": { "type": "string", "description": "The name of the grader." }, "source": { "type": "string", "description": "The source code of the python script." }, "image_tag": { "type": "string", "description": "The image tag to use for the python script." } }, "description": "A PythonGrader object that runs a python script on the input.", "title": "PythonGrader", "x-oaiMeta": { "name": "Python Grader", "group": "graders", "example": "{\n \"type\": \"python\",\n \"name\": \"Example python grader\",\n \"image_tag\": \"2025-05-08\",\n \"source\": \"\"\"\ndef grade(sample: dict, item: dict) -> float:\n \"\"\"\n Returns 1.0 if `output_text` equals `label`, otherwise 0.0.\n \"\"\"\n output = sample.get(\"output_text\")\n label = item.get(\"label\")\n return 1.0 if output == label else 0.0\n\"\"\",\n}\n" } }, "OpenAI.GraderScoreModel": { "type": "object", "required": [ "type", "name", "model", "input" ], "properties": { "type": { "type": "string", "enum": [ "score_model" ], "description": "The object type, which is always `score_model`.", "x-stainless-const": true }, "name": { "type": "string", "description": "The name of the grader." }, "model": { "type": "string", "description": "The model to use for the evaluation." }, "sampling_params": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.EvalGraderScoreModelSamplingParams" } ], "description": "The sampling parameters for the model." }, "input": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.EvalItem" }, "description": "The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings." }, "range": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.numeric" }, "description": "The range of the score. Defaults to `[0, 1]`." } }, "description": "A ScoreModelGrader object that uses a model to assign a score to the input.", "title": "ScoreModelGrader", "x-oaiMeta": { "name": "Score Model Grader", "group": "graders", "example": "{\n \"type\": \"score_model\",\n \"name\": \"Example score model grader\",\n \"input\": [\n {\n \"role\": \"user\",\n \"content\": [\n {\n \"type\": \"input_text\",\n \"text\": (\n \"Score how close the reference answer is to the model answer. Score 1.0 if they are the same and 0.0 if they are different.\"\n \" Return just a floating point score\n\n\"\n \" Reference answer: {{item.label}}\n\n\"\n \" Model answer: {{sample.output_text}}\"\n )\n },\n {\n \"type\": \"input_image\",\n \"image_url\": \"https://example.com/reference.png\",\n \"file_id\": null,\n \"detail\": \"auto\"\n }\n ],\n }\n ],\n \"model\": \"gpt-5-mini\",\n \"sampling_params\": {\n \"temperature\": 1,\n \"top_p\": 1,\n \"seed\": 42,\n \"max_completions_tokens\": 32768,\n \"reasoning_effort\": \"medium\"\n },\n}\n" } }, "OpenAI.GraderStringCheck": { "type": "object", "required": [ "type", "name", "input", "reference", "operation" ], "properties": { "type": { "type": "string", "enum": [ "string_check" ], "description": "The object type, which is always `string_check`.", "x-stainless-const": true }, "name": { "type": "string", "description": "The name of the grader." }, "input": { "type": "string", "description": "The input text. This may include template strings." }, "reference": { "type": "string", "description": "The reference text. This may include template strings." }, "operation": { "type": "string", "enum": [ "eq", "ne", "like", "ilike" ], "description": "The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`." } }, "description": "A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.", "title": "StringCheckGrader", "x-oaiMeta": { "name": "String Check Grader", "group": "graders", "example": "{\n \"type\": \"string_check\",\n \"name\": \"Example string check grader\",\n \"input\": \"{{sample.output_text}}\",\n \"reference\": \"{{item.label}}\",\n \"operation\": \"eq\"\n}\n" } }, "OpenAI.GraderTextSimilarity": { "type": "object", "required": [ "type", "name", "input", "reference", "evaluation_metric" ], "properties": { "type": { "type": "string", "enum": [ "text_similarity" ], "description": "The type of grader.", "x-stainless-const": true, "default": "text_similarity" }, "name": { "type": "string", "description": "The name of the grader." }, "input": { "type": "string", "description": "The text being graded." }, "reference": { "type": "string", "description": "The text being graded against." }, "evaluation_metric": { "type": "string", "enum": [ "cosine", "fuzzy_match", "bleu", "gleu", "meteor", "rouge_1", "rouge_2", "rouge_3", "rouge_4", "rouge_5", "rouge_l" ], "description": "The evaluation metric to use. One of `cosine`, `fuzzy_match`, `bleu`,\n `gleu`, `meteor`, `rouge_1`, `rouge_2`, `rouge_3`, `rouge_4`, `rouge_5`,\n or `rouge_l`." } }, "description": "A TextSimilarityGrader object which grades text based on similarity metrics.", "title": "TextSimilarityGrader", "x-oaiMeta": { "name": "Text Similarity Grader", "group": "graders", "example": "{\n \"type\": \"text_similarity\",\n \"name\": \"Example text similarity grader\",\n \"input\": \"{{sample.output_text}}\",\n \"reference\": \"{{item.label}}\",\n \"evaluation_metric\": \"fuzzy_match\"\n}\n" } }, "OpenAI.GrammarSyntax1": { "type": "string", "enum": [ "lark", "regex" ] }, "OpenAI.HybridSearchOptions": { "type": "object", "required": [ "embedding_weight", "text_weight" ], "properties": { "embedding_weight": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.numeric" } ], "description": "The weight of the embedding in the reciprocal ranking fusion." }, "text_weight": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.numeric" } ], "description": "The weight of the text in the reciprocal ranking fusion." } } }, "OpenAI.ImageDetail": { "type": "string", "enum": [ "low", "high", "auto" ] }, "OpenAI.ImageGenActionEnum": { "type": "string", "enum": [ "generate", "edit", "auto" ] }, "OpenAI.ImageGenTool": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "image_generation" ], "description": "The type of the image generation tool. Always `image_generation`.", "x-stainless-const": true, "default": "image_generation" }, "model": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "gpt-image-1", "gpt-image-1-mini", "gpt-image-1.5" ] } ], "default": "gpt-image-1" }, "quality": { "type": "string", "enum": [ "low", "medium", "high", "auto" ], "description": "The quality of the generated image. One of `low`, `medium`, `high`,\n or `auto`. Default: `auto`.", "default": "auto" }, "size": { "type": "string", "enum": [ "1024x1024", "1024x1536", "1536x1024", "auto" ], "description": "The size of the generated image. One of `1024x1024`, `1024x1536`,\n `1536x1024`, or `auto`. Default: `auto`.", "default": "auto" }, "output_format": { "type": "string", "enum": [ "png", "webp", "jpeg" ], "description": "The output format of the generated image. One of `png`, `webp`, or\n `jpeg`. Default: `png`.", "default": "png" }, "output_compression": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "minimum": 0, "maximum": 100, "description": "Compression level for the output image. Default: 100.", "default": 100 }, "moderation": { "type": "string", "enum": [ "auto", "low" ], "description": "Moderation level for the generated image. Default: `auto`.", "default": "auto" }, "background": { "type": "string", "enum": [ "transparent", "opaque", "auto" ], "description": "Background type for the generated image. One of `transparent`,\n `opaque`, or `auto`. Default: `auto`.", "default": "auto" }, "input_fidelity": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.InputFidelity" } ], "nullable": true }, "input_image_mask": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ImageGenToolInputImageMask" } ], "description": "Optional mask for inpainting. Contains `image_url`\n (string, optional) and `file_id` (string, optional)." }, "partial_images": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "minimum": 0, "maximum": 3, "description": "Number of partial images to generate in streaming mode, from 0 (default value) to 3." }, "action": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ImageGenActionEnum" } ], "description": "Whether to generate a new image or edit an existing image. Default: `auto`." }, "name": { "type": "string", "description": "Optional user-defined name for this tool or configuration." }, "description": { "type": "string", "description": "Optional user-defined description for this tool or configuration." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Tool" } ], "description": "A tool that generates images using the GPT image models.", "title": "Image generation tool" }, "OpenAI.ImageGenToolInputImageMask": { "type": "object", "properties": { "image_url": { "type": "string", "format": "uri" }, "file_id": { "type": "string" } } }, "OpenAI.IncludeEnum": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "file_search_call.results", "web_search_call.results", "web_search_call.action.sources", "message.input_image.image_url", "computer_call_output.output.image_url", "code_interpreter_call.outputs", "reasoning.encrypted_content", "message.output_text.logprobs", "memory_search_call.results" ] } ], "description": "Specify additional output data to include in the model response. Currently supported values are:\n- `web_search_call.action.sources`: Include the sources of the web search tool call.\n- `code_interpreter_call.outputs`: Includes the outputs of python code execution in code interpreter tool call items.\n- `computer_call_output.output.image_url`: Include image urls from the computer call output.\n- `file_search_call.results`: Include the search results of the file search tool call.\n- `message.input_image.image_url`: Include image urls from the input message.\n- `message.output_text.logprobs`: Include logprobs with assistant messages.\n- `reasoning.encrypted_content`: Includes an encrypted version of reasoning tokens in reasoning item outputs. This enables reasoning items to be used in multi-turn conversations when using the Responses API statelessly (like when the `store` parameter is set to `false`, or when an organization is enrolled in the zero data retention program)." }, "OpenAI.InlineSkillParam": { "type": "object", "required": [ "type", "name", "description", "source" ], "properties": { "type": { "type": "string", "enum": [ "inline" ], "description": "Defines an inline skill for this request.", "x-stainless-const": true, "default": "inline" }, "name": { "type": "string", "description": "The name of the skill." }, "description": { "type": "string", "description": "The description of the skill." }, "source": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.InlineSkillSourceParam" } ], "description": "Inline skill payload" } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ContainerSkill" } ] }, "OpenAI.InlineSkillSourceParam": { "type": "object", "required": [ "type", "media_type", "data" ], "properties": { "type": { "type": "string", "enum": [ "base64" ], "description": "The type of the inline skill source. Must be `base64`.", "x-stainless-const": true, "default": "base64" }, "media_type": { "type": "string", "enum": [ "application/zip" ], "description": "The media type of the inline skill payload. Must be `application/zip`.", "x-stainless-const": true, "default": "application/zip" }, "data": { "type": "string", "minLength": 1, "maxLength": 70254592, "description": "Base64-encoded skill zip bundle." } }, "description": "Inline skill payload" }, "OpenAI.InputAudio": { "type": "object", "required": [ "type", "input_audio" ], "properties": { "type": { "type": "string", "enum": [ "input_audio" ], "description": "The type of the input item. Always `input_audio`.", "x-stainless-const": true }, "input_audio": { "$ref": "#/components/schemas/OpenAI.InputAudioInputAudio" } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.EvalItemContentItemObject" } ], "description": "An audio input to the model.", "title": "Input audio" }, "OpenAI.InputAudioInputAudio": { "type": "object", "required": [ "data", "format" ], "properties": { "data": { "type": "string" }, "format": { "type": "string", "enum": [ "mp3", "wav" ] } } }, "OpenAI.InputContent": { "type": "object", "required": [ "type" ], "properties": { "type": { "$ref": "#/components/schemas/OpenAI.InputContentType" } }, "discriminator": { "propertyName": "type", "mapping": { "input_text": "#/components/schemas/OpenAI.InputContentInputTextContent", "input_image": "#/components/schemas/OpenAI.InputContentInputImageContent", "input_file": "#/components/schemas/OpenAI.InputContentInputFileContent" } } }, "OpenAI.InputContentInputFileContent": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "input_file" ], "description": "The type of the input item. Always `input_file`.", "x-stainless-const": true, "default": "input_file" }, "file_id": { "type": "string", "nullable": true }, "filename": { "type": "string", "description": "The name of the file to be sent to the model." }, "file_url": { "type": "string", "format": "uri", "description": "The URL of the file to be sent to the model." }, "file_data": { "type": "string", "description": "The content of the file to be sent to the model." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.InputContent" } ], "description": "A file input to the model.", "title": "Input file" }, "OpenAI.InputContentInputImageContent": { "type": "object", "required": [ "type", "detail" ], "properties": { "type": { "type": "string", "enum": [ "input_image" ], "description": "The type of the input item. Always `input_image`.", "x-stainless-const": true, "default": "input_image" }, "image_url": { "type": "string", "format": "uri", "nullable": true }, "file_id": { "type": "string", "nullable": true }, "detail": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ImageDetail" } ], "description": "The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.InputContent" } ], "description": "An image input to the model. Learn about [image inputs](/docs/guides/vision).", "title": "Input image" }, "OpenAI.InputContentInputTextContent": { "type": "object", "required": [ "type", "text" ], "properties": { "type": { "type": "string", "enum": [ "input_text" ], "description": "The type of the input item. Always `input_text`.", "x-stainless-const": true, "default": "input_text" }, "text": { "type": "string", "description": "The text input to the model." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.InputContent" } ], "description": "A text input to the model.", "title": "Input text" }, "OpenAI.InputContentType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "input_text", "input_image", "input_file" ] } ] }, "OpenAI.InputFidelity": { "type": "string", "enum": [ "high", "low" ], "description": "Control how much effort the model will exert to match the style and features, especially facial features, of input images. This parameter is only supported for `gpt-image-1` and `gpt-image-1.5` and later models, unsupported for `gpt-image-1-mini`. Supports `high` and `low`. Defaults to `low`." }, "OpenAI.InputFileContent": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "input_file" ], "description": "The type of the input item. Always `input_file`.", "x-stainless-const": true, "default": "input_file" }, "file_id": { "type": "string", "nullable": true }, "filename": { "type": "string", "description": "The name of the file to be sent to the model." }, "file_url": { "type": "string", "format": "uri", "description": "The URL of the file to be sent to the model." }, "file_data": { "type": "string", "description": "The content of the file to be sent to the model." } }, "description": "A file input to the model.", "title": "Input file" }, "OpenAI.InputFileContentParam": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "input_file" ], "description": "The type of the input item. Always `input_file`.", "x-stainless-const": true, "default": "input_file" }, "file_id": { "type": "string", "nullable": true }, "filename": { "type": "string", "nullable": true }, "file_data": { "type": "string", "nullable": true }, "file_url": { "type": "string", "format": "uri", "nullable": true } }, "description": "A file input to the model.", "title": "Input file" }, "OpenAI.InputImageContent": { "type": "object", "required": [ "type", "detail" ], "properties": { "type": { "type": "string", "enum": [ "input_image" ], "description": "The type of the input item. Always `input_image`.", "x-stainless-const": true, "default": "input_image" }, "image_url": { "type": "string", "format": "uri", "nullable": true }, "file_id": { "type": "string", "nullable": true }, "detail": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ImageDetail" } ], "description": "The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`." } }, "description": "An image input to the model. Learn about [image inputs](/docs/guides/vision).", "title": "Input image" }, "OpenAI.InputImageContentParamAutoParam": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "input_image" ], "description": "The type of the input item. Always `input_image`.", "x-stainless-const": true, "default": "input_image" }, "image_url": { "type": "string", "format": "uri", "nullable": true }, "file_id": { "type": "string", "nullable": true }, "detail": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.DetailEnum" } ], "nullable": true } }, "description": "An image input to the model. Learn about [image inputs](/docs/guides/vision)", "title": "Input image" }, "OpenAI.InputItem": { "type": "object", "required": [ "type" ], "properties": { "type": { "$ref": "#/components/schemas/OpenAI.InputItemType" } }, "discriminator": { "propertyName": "type", "mapping": { "message": "#/components/schemas/OpenAI.EasyInputMessage", "item_reference": "#/components/schemas/OpenAI.ItemReferenceParam", "output_message": "#/components/schemas/OpenAI.InputItemOutputMessage", "file_search_call": "#/components/schemas/OpenAI.InputItemFileSearchToolCall", "computer_call": "#/components/schemas/OpenAI.InputItemComputerToolCall", "computer_call_output": "#/components/schemas/OpenAI.InputItemComputerCallOutputItemParam", "web_search_call": "#/components/schemas/OpenAI.InputItemWebSearchToolCall", "function_call": "#/components/schemas/OpenAI.InputItemFunctionToolCall", "function_call_output": "#/components/schemas/OpenAI.InputItemFunctionCallOutputItemParam", "reasoning": "#/components/schemas/OpenAI.InputItemReasoningItem", "compaction": "#/components/schemas/OpenAI.InputItemCompactionSummaryItemParam", "image_generation_call": "#/components/schemas/OpenAI.InputItemImageGenToolCall", "code_interpreter_call": "#/components/schemas/OpenAI.InputItemCodeInterpreterToolCall", "local_shell_call": "#/components/schemas/OpenAI.InputItemLocalShellToolCall", "local_shell_call_output": "#/components/schemas/OpenAI.InputItemLocalShellToolCallOutput", "shell_call": "#/components/schemas/OpenAI.InputItemFunctionShellCallItemParam", "shell_call_output": "#/components/schemas/OpenAI.InputItemFunctionShellCallOutputItemParam", "apply_patch_call": "#/components/schemas/OpenAI.InputItemApplyPatchToolCallItemParam", "apply_patch_call_output": "#/components/schemas/OpenAI.InputItemApplyPatchToolCallOutputItemParam", "mcp_list_tools": "#/components/schemas/OpenAI.InputItemMcpListTools", "mcp_approval_request": "#/components/schemas/OpenAI.InputItemMcpApprovalRequest", "mcp_approval_response": "#/components/schemas/OpenAI.InputItemMcpApprovalResponse", "mcp_call": "#/components/schemas/OpenAI.InputItemMcpToolCall", "custom_tool_call_output": "#/components/schemas/OpenAI.InputItemCustomToolCallOutput", "custom_tool_call": "#/components/schemas/OpenAI.InputItemCustomToolCall" } }, "description": "An item representing part of the context for the response to be\ngenerated by the model. Can contain text, images, and audio inputs,\nas well as previous assistant responses and tool call outputs." }, "OpenAI.InputItemApplyPatchToolCallItemParam": { "type": "object", "required": [ "type", "call_id", "status", "operation" ], "properties": { "type": { "type": "string", "enum": [ "apply_patch_call" ], "description": "The type of the item. Always `apply_patch_call`.", "x-stainless-const": true, "default": "apply_patch_call" }, "id": { "type": "string", "nullable": true }, "call_id": { "type": "string", "minLength": 1, "maxLength": 64, "description": "The unique ID of the apply patch tool call generated by the model." }, "status": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ApplyPatchCallStatusParam" } ], "description": "The status of the apply patch tool call. One of `in_progress` or `completed`." }, "operation": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ApplyPatchOperationParam" } ], "description": "The specific create, delete, or update instruction for the apply_patch tool call." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.InputItem" } ], "description": "A tool call representing a request to create, delete, or update files using diff patches.", "title": "Apply patch tool call" }, "OpenAI.InputItemApplyPatchToolCallOutputItemParam": { "type": "object", "required": [ "type", "call_id", "status" ], "properties": { "type": { "type": "string", "enum": [ "apply_patch_call_output" ], "description": "The type of the item. Always `apply_patch_call_output`.", "x-stainless-const": true, "default": "apply_patch_call_output" }, "id": { "type": "string", "nullable": true }, "call_id": { "type": "string", "minLength": 1, "maxLength": 64, "description": "The unique ID of the apply patch tool call generated by the model." }, "status": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ApplyPatchCallOutputStatusParam" } ], "description": "The status of the apply patch tool call output. One of `completed` or `failed`." }, "output": { "type": "string", "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.InputItem" } ], "description": "The streamed output emitted by an apply patch tool call.", "title": "Apply patch tool call output" }, "OpenAI.InputItemCodeInterpreterToolCall": { "type": "object", "required": [ "type", "id", "status", "container_id", "code", "outputs" ], "properties": { "type": { "type": "string", "enum": [ "code_interpreter_call" ], "description": "The type of the code interpreter tool call. Always `code_interpreter_call`.", "x-stainless-const": true, "default": "code_interpreter_call" }, "id": { "type": "string", "description": "The unique ID of the code interpreter tool call." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete", "interpreting", "failed" ], "description": "The status of the code interpreter tool call. Valid values are `in_progress`, `completed`, `incomplete`, `interpreting`, and `failed`." }, "container_id": { "type": "string", "description": "The ID of the container used to run the code." }, "code": { "type": "string", "nullable": true }, "outputs": { "type": "array", "items": { "anyOf": [ { "$ref": "#/components/schemas/OpenAI.CodeInterpreterOutputLogs" }, { "$ref": "#/components/schemas/OpenAI.CodeInterpreterOutputImage" } ] }, "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.InputItem" } ], "description": "A tool call to run code.", "title": "Code interpreter tool call" }, "OpenAI.InputItemCompactionSummaryItemParam": { "type": "object", "required": [ "type", "encrypted_content" ], "properties": { "id": { "type": "string", "nullable": true }, "type": { "type": "string", "enum": [ "compaction" ], "description": "The type of the item. Always `compaction`.", "x-stainless-const": true, "default": "compaction" }, "encrypted_content": { "type": "string", "maxLength": 10485760, "description": "The encrypted content of the compaction summary." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.InputItem" } ], "description": "A compaction item generated by the [`v1/responses/compact` API](/docs/api-reference/responses/compact).", "title": "Compaction item" }, "OpenAI.InputItemComputerCallOutputItemParam": { "type": "object", "required": [ "call_id", "type", "output" ], "properties": { "id": { "type": "string", "nullable": true }, "call_id": { "type": "string", "minLength": 1, "maxLength": 64, "description": "The ID of the computer tool call that produced the output." }, "type": { "type": "string", "enum": [ "computer_call_output" ], "description": "The type of the computer tool call output. Always `computer_call_output`.", "x-stainless-const": true, "default": "computer_call_output" }, "output": { "$ref": "#/components/schemas/OpenAI.ComputerScreenshotImage" }, "acknowledged_safety_checks": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.ComputerCallSafetyCheckParam" }, "nullable": true }, "status": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.FunctionCallItemStatus" } ], "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.InputItem" } ], "description": "The output of a computer tool call.", "title": "Computer tool call output" }, "OpenAI.InputItemComputerToolCall": { "type": "object", "required": [ "type", "id", "call_id", "action", "pending_safety_checks", "status" ], "properties": { "type": { "type": "string", "enum": [ "computer_call" ], "description": "The type of the computer call. Always `computer_call`.", "default": "computer_call" }, "id": { "type": "string", "description": "The unique ID of the computer call." }, "call_id": { "type": "string", "description": "An identifier used when responding to the tool call with output." }, "action": { "$ref": "#/components/schemas/OpenAI.ComputerAction" }, "pending_safety_checks": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.ComputerCallSafetyCheckParam" }, "description": "The pending safety checks for the computer call." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "description": "The status of the item. One of `in_progress`, `completed`, or\n `incomplete`. Populated when items are returned via API." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.InputItem" } ], "description": "A tool call to a computer use tool. See the\n[computer use guide](/docs/guides/tools-computer-use) for more information.", "title": "Computer tool call" }, "OpenAI.InputItemCustomToolCall": { "type": "object", "required": [ "type", "call_id", "name", "input" ], "properties": { "type": { "type": "string", "enum": [ "custom_tool_call" ], "description": "The type of the custom tool call. Always `custom_tool_call`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the custom tool call in the OpenAI platform." }, "call_id": { "type": "string", "description": "An identifier used to map this custom tool call to a tool call output." }, "name": { "type": "string", "description": "The name of the custom tool being called." }, "input": { "type": "string", "description": "The input for the custom tool call generated by the model." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.InputItem" } ], "description": "A call to a custom tool created by the model.", "title": "Custom tool call" }, "OpenAI.InputItemCustomToolCallOutput": { "type": "object", "required": [ "type", "call_id", "output" ], "properties": { "type": { "type": "string", "enum": [ "custom_tool_call_output" ], "description": "The type of the custom tool call output. Always `custom_tool_call_output`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the custom tool call output in the OpenAI platform." }, "call_id": { "type": "string", "description": "The call ID, used to map this custom tool call output to a custom tool call." }, "output": { "oneOf": [ { "type": "string" }, { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.FunctionAndCustomToolCallOutput" } } ], "description": "The output from the custom tool call generated by your code.\n Can be a string or an list of output content." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.InputItem" } ], "description": "The output of a custom tool call from your code, being sent back to the model.", "title": "Custom tool call output" }, "OpenAI.InputItemFileSearchToolCall": { "type": "object", "required": [ "id", "type", "status", "queries" ], "properties": { "id": { "type": "string", "description": "The unique ID of the file search tool call." }, "type": { "type": "string", "enum": [ "file_search_call" ], "description": "The type of the file search tool call. Always `file_search_call`.", "x-stainless-const": true }, "status": { "type": "string", "enum": [ "in_progress", "searching", "completed", "incomplete", "failed" ], "description": "The status of the file search tool call. One of `in_progress`,\n `searching`, `incomplete` or `failed`," }, "queries": { "type": "array", "items": { "type": "string" }, "description": "The queries used to search for files." }, "results": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.FileSearchToolCallResults" }, "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.InputItem" } ], "description": "The results of a file search tool call. See the\n[file search guide](/docs/guides/tools-file-search) for more information.", "title": "File search tool call" }, "OpenAI.InputItemFunctionCallOutputItemParam": { "type": "object", "required": [ "call_id", "type", "output" ], "properties": { "id": { "type": "string", "nullable": true }, "call_id": { "type": "string", "minLength": 1, "maxLength": 64, "description": "The unique ID of the function tool call generated by the model." }, "type": { "type": "string", "enum": [ "function_call_output" ], "description": "The type of the function tool call output. Always `function_call_output`.", "x-stainless-const": true, "default": "function_call_output" }, "output": { "oneOf": [ { "type": "string" }, { "type": "array", "items": { "anyOf": [ { "$ref": "#/components/schemas/OpenAI.InputTextContentParam" }, { "$ref": "#/components/schemas/OpenAI.InputImageContentParamAutoParam" }, { "$ref": "#/components/schemas/OpenAI.InputFileContentParam" } ] } } ], "description": "Text, image, or file output of the function tool call." }, "status": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.FunctionCallItemStatus" } ], "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.InputItem" } ], "description": "The output of a function tool call.", "title": "Function tool call output" }, "OpenAI.InputItemFunctionShellCallItemParam": { "type": "object", "required": [ "call_id", "type", "action" ], "properties": { "id": { "type": "string", "nullable": true }, "call_id": { "type": "string", "minLength": 1, "maxLength": 64, "description": "The unique ID of the shell tool call generated by the model." }, "type": { "type": "string", "enum": [ "shell_call" ], "description": "The type of the item. Always `shell_call`.", "x-stainless-const": true, "default": "shell_call" }, "action": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.FunctionShellActionParam" } ], "description": "The shell commands and limits that describe how to run the tool call." }, "status": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.FunctionShellCallItemStatus" } ], "nullable": true }, "environment": { "type": "object", "allOf": [ { "$ref": "#/components/schemas/OpenAI.FunctionShellCallItemParamEnvironment" } ], "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.InputItem" } ], "description": "A tool representing a request to execute one or more shell commands.", "title": "Shell tool call" }, "OpenAI.InputItemFunctionShellCallOutputItemParam": { "type": "object", "required": [ "call_id", "type", "output" ], "properties": { "id": { "type": "string", "nullable": true }, "call_id": { "type": "string", "minLength": 1, "maxLength": 64, "description": "The unique ID of the shell tool call generated by the model." }, "type": { "type": "string", "enum": [ "shell_call_output" ], "description": "The type of the item. Always `shell_call_output`.", "x-stainless-const": true, "default": "shell_call_output" }, "output": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.FunctionShellCallOutputContentParam" }, "description": "Captured chunks of stdout and stderr output, along with their associated outcomes." }, "status": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.FunctionShellCallItemStatus" } ], "nullable": true }, "max_output_length": { "type": "integer", "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.InputItem" } ], "description": "The streamed output items emitted by a shell tool call.", "title": "Shell tool call output" }, "OpenAI.InputItemFunctionToolCall": { "type": "object", "required": [ "type", "call_id", "name", "arguments" ], "properties": { "id": { "type": "string", "description": "The unique ID of the function tool call." }, "type": { "type": "string", "enum": [ "function_call" ], "description": "The type of the function tool call. Always `function_call`.", "x-stainless-const": true }, "call_id": { "type": "string", "description": "The unique ID of the function tool call generated by the model." }, "name": { "type": "string", "description": "The name of the function to run." }, "arguments": { "type": "string", "description": "A JSON string of the arguments to pass to the function." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "description": "The status of the item. One of `in_progress`, `completed`, or\n `incomplete`. Populated when items are returned via API." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.InputItem" } ], "description": "A tool call to run a function. See the\n[function calling guide](/docs/guides/function-calling) for more information.", "title": "Function tool call" }, "OpenAI.InputItemImageGenToolCall": { "type": "object", "required": [ "type", "id", "status", "result" ], "properties": { "type": { "type": "string", "enum": [ "image_generation_call" ], "description": "The type of the image generation call. Always `image_generation_call`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the image generation call." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "generating", "failed" ], "description": "The status of the image generation call." }, "result": { "type": "string", "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.InputItem" } ], "description": "An image generation request made by the model.", "title": "Image generation call" }, "OpenAI.InputItemLocalShellToolCall": { "type": "object", "required": [ "type", "id", "call_id", "action", "status" ], "properties": { "type": { "type": "string", "enum": [ "local_shell_call" ], "description": "The type of the local shell call. Always `local_shell_call`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the local shell call." }, "call_id": { "type": "string", "description": "The unique ID of the local shell tool call generated by the model." }, "action": { "$ref": "#/components/schemas/OpenAI.LocalShellExecAction" }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "description": "The status of the local shell call." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.InputItem" } ], "description": "A tool call to run a command on the local shell.", "title": "Local shell call" }, "OpenAI.InputItemLocalShellToolCallOutput": { "type": "object", "required": [ "type", "id", "output" ], "properties": { "type": { "type": "string", "enum": [ "local_shell_call_output" ], "description": "The type of the local shell tool call output. Always `local_shell_call_output`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the local shell tool call generated by the model." }, "output": { "type": "string", "description": "A JSON string of the output of the local shell tool call." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.InputItem" } ], "description": "The output of a local shell tool call.", "title": "Local shell call output" }, "OpenAI.InputItemMcpApprovalRequest": { "type": "object", "required": [ "type", "id", "server_label", "name", "arguments" ], "properties": { "type": { "type": "string", "enum": [ "mcp_approval_request" ], "description": "The type of the item. Always `mcp_approval_request`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the approval request." }, "server_label": { "type": "string", "description": "The label of the MCP server making the request." }, "name": { "type": "string", "description": "The name of the tool to run." }, "arguments": { "type": "string", "description": "A JSON string of arguments for the tool." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.InputItem" } ], "description": "A request for human approval of a tool invocation.", "title": "MCP approval request" }, "OpenAI.InputItemMcpApprovalResponse": { "type": "object", "required": [ "type", "approval_request_id", "approve" ], "properties": { "type": { "type": "string", "enum": [ "mcp_approval_response" ], "description": "The type of the item. Always `mcp_approval_response`.", "x-stainless-const": true }, "id": { "type": "string", "nullable": true }, "approval_request_id": { "type": "string", "description": "The ID of the approval request being answered." }, "approve": { "type": "boolean", "description": "Whether the request was approved." }, "reason": { "type": "string", "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.InputItem" } ], "description": "A response to an MCP approval request.", "title": "MCP approval response" }, "OpenAI.InputItemMcpListTools": { "type": "object", "required": [ "type", "id", "server_label", "tools" ], "properties": { "type": { "type": "string", "enum": [ "mcp_list_tools" ], "description": "The type of the item. Always `mcp_list_tools`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the list." }, "server_label": { "type": "string", "description": "The label of the MCP server." }, "tools": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.MCPListToolsTool" }, "description": "The tools available on the server." }, "error": { "type": "string", "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.InputItem" } ], "description": "A list of tools available on an MCP server.", "title": "MCP list tools" }, "OpenAI.InputItemMcpToolCall": { "type": "object", "required": [ "type", "id", "server_label", "name", "arguments" ], "properties": { "type": { "type": "string", "enum": [ "mcp_call" ], "description": "The type of the item. Always `mcp_call`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the tool call." }, "server_label": { "type": "string", "description": "The label of the MCP server running the tool." }, "name": { "type": "string", "description": "The name of the tool that was run." }, "arguments": { "type": "string", "description": "A JSON string of the arguments passed to the tool." }, "output": { "type": "string", "nullable": true }, "error": { "type": "object", "additionalProperties": {} }, "status": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.MCPToolCallStatus" } ], "description": "The status of the tool call. One of `in_progress`, `completed`, `incomplete`, `calling`, or `failed`." }, "approval_request_id": { "type": "string", "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.InputItem" } ], "description": "An invocation of a tool on an MCP server.", "title": "MCP tool call" }, "OpenAI.InputItemOutputMessage": { "type": "object", "required": [ "id", "type", "role", "content", "status" ], "properties": { "id": { "type": "string", "description": "The unique ID of the output message." }, "type": { "type": "string", "enum": [ "output_message" ], "description": "The type of the output message. Always `message`.", "x-stainless-const": true }, "role": { "type": "string", "enum": [ "assistant" ], "description": "The role of the output message. Always `assistant`.", "x-stainless-const": true }, "content": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.OutputMessageContent" }, "description": "The content of the output message." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "description": "The status of the message input. One of `in_progress`, `completed`, or\n `incomplete`. Populated when input items are returned via API." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.InputItem" } ], "description": "An output message from the model.", "title": "Output message" }, "OpenAI.InputItemReasoningItem": { "type": "object", "required": [ "type", "id", "summary" ], "properties": { "type": { "type": "string", "enum": [ "reasoning" ], "description": "The type of the object. Always `reasoning`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique identifier of the reasoning content." }, "encrypted_content": { "type": "string", "nullable": true }, "summary": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.SummaryTextContent" }, "description": "Reasoning summary content." }, "content": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.ReasoningTextContent" }, "description": "Reasoning text content." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "description": "The status of the item. One of `in_progress`, `completed`, or\n `incomplete`. Populated when items are returned via API." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.InputItem" } ], "description": "A description of the chain of thought used by a reasoning model while generating\na response. Be sure to include these items in your `input` to the Responses API\nfor subsequent turns of a conversation if you are manually\n[managing context](/docs/guides/conversation-state).", "title": "Reasoning" }, "OpenAI.InputItemType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "message", "output_message", "file_search_call", "computer_call", "computer_call_output", "web_search_call", "function_call", "function_call_output", "reasoning", "compaction", "image_generation_call", "code_interpreter_call", "local_shell_call", "local_shell_call_output", "shell_call", "shell_call_output", "apply_patch_call", "apply_patch_call_output", "mcp_list_tools", "mcp_approval_request", "mcp_approval_response", "mcp_call", "custom_tool_call_output", "custom_tool_call", "item_reference" ] } ] }, "OpenAI.InputItemWebSearchToolCall": { "type": "object", "required": [ "id", "type", "status", "action" ], "properties": { "id": { "type": "string", "description": "The unique ID of the web search tool call." }, "type": { "type": "string", "enum": [ "web_search_call" ], "description": "The type of the web search tool call. Always `web_search_call`.", "x-stainless-const": true }, "status": { "type": "string", "enum": [ "in_progress", "searching", "completed", "failed" ], "description": "The status of the web search tool call." }, "action": { "oneOf": [ { "$ref": "#/components/schemas/OpenAI.WebSearchActionSearch" }, { "$ref": "#/components/schemas/OpenAI.WebSearchActionOpenPage" }, { "$ref": "#/components/schemas/OpenAI.WebSearchActionFind" } ], "description": "An object describing the specific action taken in this web search call.\n Includes details on how the model used the web (search, open_page, find_in_page)." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.InputItem" } ], "description": "The results of a web search tool call. See the\n[web search guide](/docs/guides/tools-web-search) for more information.", "title": "Web search tool call" }, "OpenAI.InputMessage": { "type": "object", "required": [ "type", "role", "content" ], "properties": { "type": { "type": "string", "enum": [ "message" ], "description": "The type of the message input. Always set to `message`.", "x-stainless-const": true }, "role": { "type": "string", "enum": [ "user", "system", "developer" ], "description": "The role of the message input. One of `user`, `system`, or `developer`." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "description": "The status of item. One of `in_progress`, `completed`, or\n `incomplete`. Populated when items are returned via API." }, "content": { "$ref": "#/components/schemas/OpenAI.InputMessageContentList" } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Item" } ], "description": "A message input to the model with a role indicating instruction following\nhierarchy. Instructions given with the `developer` or `system` role take\nprecedence over instructions given with the `user` role.", "title": "Input message" }, "OpenAI.InputMessageContentList": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.InputContent" }, "description": "A list of one or many input items to the model, containing different content\ntypes.", "title": "Input item content list" }, "OpenAI.InputMessageResource": { "type": "object", "required": [ "type", "role", "content", "id" ], "properties": { "type": { "type": "string", "enum": [ "message" ], "description": "The type of the message input. Always set to `message`.", "x-stainless-const": true }, "role": { "type": "string", "enum": [ "user", "system", "developer" ], "description": "The role of the message input. One of `user`, `system`, or `developer`." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "description": "The status of item. One of `in_progress`, `completed`, or\n `incomplete`. Populated when items are returned via API." }, "content": { "$ref": "#/components/schemas/OpenAI.InputMessageContentList" }, "id": { "type": "string", "description": "The unique ID of the message input." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemResource" } ] }, "OpenAI.InputParam": { "oneOf": [ { "type": "string" }, { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.InputItem" } } ], "description": "Text, image, or file inputs to the model, used to generate a response.\nLearn more:\n- [Text inputs and outputs](/docs/guides/text)\n- [Image inputs](/docs/guides/images)\n- [File inputs](/docs/guides/pdf-files)\n- [Conversation state](/docs/guides/conversation-state)\n- [Function calling](/docs/guides/function-calling)" }, "OpenAI.InputTextContent": { "type": "object", "required": [ "type", "text" ], "properties": { "type": { "type": "string", "enum": [ "input_text" ], "description": "The type of the input item. Always `input_text`.", "x-stainless-const": true, "default": "input_text" }, "text": { "type": "string", "description": "The text input to the model." } }, "description": "A text input to the model.", "title": "Input text" }, "OpenAI.InputTextContentParam": { "type": "object", "required": [ "type", "text" ], "properties": { "type": { "type": "string", "enum": [ "input_text" ], "description": "The type of the input item. Always `input_text`.", "x-stainless-const": true, "default": "input_text" }, "text": { "type": "string", "maxLength": 10485760, "description": "The text input to the model." } }, "description": "A text input to the model.", "title": "Input text" }, "OpenAI.Item": { "type": "object", "required": [ "type" ], "properties": { "type": { "$ref": "#/components/schemas/OpenAI.ItemType" } }, "discriminator": { "propertyName": "type", "mapping": { "memory_search_call": "#/components/schemas/MemorySearchToolCallItemParam", "message": "#/components/schemas/OpenAI.InputMessage", "output_message": "#/components/schemas/OpenAI.ItemOutputMessage", "file_search_call": "#/components/schemas/OpenAI.ItemFileSearchToolCall", "computer_call": "#/components/schemas/OpenAI.ItemComputerToolCall", "computer_call_output": "#/components/schemas/OpenAI.ItemComputerCallOutputItemParam", "web_search_call": "#/components/schemas/OpenAI.ItemWebSearchToolCall", "function_call": "#/components/schemas/OpenAI.ItemFunctionToolCall", "function_call_output": "#/components/schemas/OpenAI.ItemFunctionCallOutputItemParam", "reasoning": "#/components/schemas/OpenAI.ItemReasoningItem", "compaction": "#/components/schemas/OpenAI.ItemCompactionSummaryItemParam", "image_generation_call": "#/components/schemas/OpenAI.ItemImageGenToolCall", "code_interpreter_call": "#/components/schemas/OpenAI.ItemCodeInterpreterToolCall", "local_shell_call": "#/components/schemas/OpenAI.ItemLocalShellToolCall", "local_shell_call_output": "#/components/schemas/OpenAI.ItemLocalShellToolCallOutput", "shell_call": "#/components/schemas/OpenAI.ItemFunctionShellCallItemParam", "shell_call_output": "#/components/schemas/OpenAI.ItemFunctionShellCallOutputItemParam", "apply_patch_call": "#/components/schemas/OpenAI.ItemApplyPatchToolCallItemParam", "apply_patch_call_output": "#/components/schemas/OpenAI.ItemApplyPatchToolCallOutputItemParam", "mcp_list_tools": "#/components/schemas/OpenAI.ItemMcpListTools", "mcp_approval_request": "#/components/schemas/OpenAI.ItemMcpApprovalRequest", "mcp_approval_response": "#/components/schemas/OpenAI.ItemMcpApprovalResponse", "mcp_call": "#/components/schemas/OpenAI.ItemMcpToolCall", "custom_tool_call_output": "#/components/schemas/OpenAI.ItemCustomToolCallOutput", "custom_tool_call": "#/components/schemas/OpenAI.ItemCustomToolCall" } }, "description": "Content item used to generate a response." }, "OpenAI.ItemApplyPatchToolCallItemParam": { "type": "object", "required": [ "type", "call_id", "status", "operation" ], "properties": { "type": { "type": "string", "enum": [ "apply_patch_call" ], "description": "The type of the item. Always `apply_patch_call`.", "x-stainless-const": true, "default": "apply_patch_call" }, "id": { "type": "string", "nullable": true }, "call_id": { "type": "string", "minLength": 1, "maxLength": 64, "description": "The unique ID of the apply patch tool call generated by the model." }, "status": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ApplyPatchCallStatusParam" } ], "description": "The status of the apply patch tool call. One of `in_progress` or `completed`." }, "operation": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ApplyPatchOperationParam" } ], "description": "The specific create, delete, or update instruction for the apply_patch tool call." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Item" } ], "description": "A tool call representing a request to create, delete, or update files using diff patches.", "title": "Apply patch tool call" }, "OpenAI.ItemApplyPatchToolCallOutputItemParam": { "type": "object", "required": [ "type", "call_id", "status" ], "properties": { "type": { "type": "string", "enum": [ "apply_patch_call_output" ], "description": "The type of the item. Always `apply_patch_call_output`.", "x-stainless-const": true, "default": "apply_patch_call_output" }, "id": { "type": "string", "nullable": true }, "call_id": { "type": "string", "minLength": 1, "maxLength": 64, "description": "The unique ID of the apply patch tool call generated by the model." }, "status": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ApplyPatchCallOutputStatusParam" } ], "description": "The status of the apply patch tool call output. One of `completed` or `failed`." }, "output": { "type": "string", "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Item" } ], "description": "The streamed output emitted by an apply patch tool call.", "title": "Apply patch tool call output" }, "OpenAI.ItemCodeInterpreterToolCall": { "type": "object", "required": [ "type", "id", "status", "container_id", "code", "outputs" ], "properties": { "type": { "type": "string", "enum": [ "code_interpreter_call" ], "description": "The type of the code interpreter tool call. Always `code_interpreter_call`.", "x-stainless-const": true, "default": "code_interpreter_call" }, "id": { "type": "string", "description": "The unique ID of the code interpreter tool call." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete", "interpreting", "failed" ], "description": "The status of the code interpreter tool call. Valid values are `in_progress`, `completed`, `incomplete`, `interpreting`, and `failed`." }, "container_id": { "type": "string", "description": "The ID of the container used to run the code." }, "code": { "type": "string", "nullable": true }, "outputs": { "type": "array", "items": { "anyOf": [ { "$ref": "#/components/schemas/OpenAI.CodeInterpreterOutputLogs" }, { "$ref": "#/components/schemas/OpenAI.CodeInterpreterOutputImage" } ] }, "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Item" } ], "description": "A tool call to run code.", "title": "Code interpreter tool call" }, "OpenAI.ItemCompactionSummaryItemParam": { "type": "object", "required": [ "type", "encrypted_content" ], "properties": { "id": { "type": "string", "nullable": true }, "type": { "type": "string", "enum": [ "compaction" ], "description": "The type of the item. Always `compaction`.", "x-stainless-const": true, "default": "compaction" }, "encrypted_content": { "type": "string", "maxLength": 10485760, "description": "The encrypted content of the compaction summary." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Item" } ], "description": "A compaction item generated by the [`v1/responses/compact` API](/docs/api-reference/responses/compact).", "title": "Compaction item" }, "OpenAI.ItemComputerCallOutputItemParam": { "type": "object", "required": [ "call_id", "type", "output" ], "properties": { "id": { "type": "string", "nullable": true }, "call_id": { "type": "string", "minLength": 1, "maxLength": 64, "description": "The ID of the computer tool call that produced the output." }, "type": { "type": "string", "enum": [ "computer_call_output" ], "description": "The type of the computer tool call output. Always `computer_call_output`.", "x-stainless-const": true, "default": "computer_call_output" }, "output": { "$ref": "#/components/schemas/OpenAI.ComputerScreenshotImage" }, "acknowledged_safety_checks": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.ComputerCallSafetyCheckParam" }, "nullable": true }, "status": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.FunctionCallItemStatus" } ], "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Item" } ], "description": "The output of a computer tool call.", "title": "Computer tool call output" }, "OpenAI.ItemComputerToolCall": { "type": "object", "required": [ "type", "id", "call_id", "action", "pending_safety_checks", "status" ], "properties": { "type": { "type": "string", "enum": [ "computer_call" ], "description": "The type of the computer call. Always `computer_call`.", "default": "computer_call" }, "id": { "type": "string", "description": "The unique ID of the computer call." }, "call_id": { "type": "string", "description": "An identifier used when responding to the tool call with output." }, "action": { "$ref": "#/components/schemas/OpenAI.ComputerAction" }, "pending_safety_checks": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.ComputerCallSafetyCheckParam" }, "description": "The pending safety checks for the computer call." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "description": "The status of the item. One of `in_progress`, `completed`, or\n `incomplete`. Populated when items are returned via API." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Item" } ], "description": "A tool call to a computer use tool. See the\n[computer use guide](/docs/guides/tools-computer-use) for more information.", "title": "Computer tool call" }, "OpenAI.ItemCustomToolCall": { "type": "object", "required": [ "type", "call_id", "name", "input" ], "properties": { "type": { "type": "string", "enum": [ "custom_tool_call" ], "description": "The type of the custom tool call. Always `custom_tool_call`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the custom tool call in the OpenAI platform." }, "call_id": { "type": "string", "description": "An identifier used to map this custom tool call to a tool call output." }, "name": { "type": "string", "description": "The name of the custom tool being called." }, "input": { "type": "string", "description": "The input for the custom tool call generated by the model." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Item" } ], "description": "A call to a custom tool created by the model.", "title": "Custom tool call" }, "OpenAI.ItemCustomToolCallOutput": { "type": "object", "required": [ "type", "call_id", "output" ], "properties": { "type": { "type": "string", "enum": [ "custom_tool_call_output" ], "description": "The type of the custom tool call output. Always `custom_tool_call_output`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the custom tool call output in the OpenAI platform." }, "call_id": { "type": "string", "description": "The call ID, used to map this custom tool call output to a custom tool call." }, "output": { "oneOf": [ { "type": "string" }, { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.FunctionAndCustomToolCallOutput" } } ], "description": "The output from the custom tool call generated by your code.\n Can be a string or an list of output content." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Item" } ], "description": "The output of a custom tool call from your code, being sent back to the model.", "title": "Custom tool call output" }, "OpenAI.ItemField": { "type": "object", "required": [ "type" ], "properties": { "type": { "$ref": "#/components/schemas/OpenAI.ItemFieldType" } }, "discriminator": { "propertyName": "type", "mapping": { "function_call_output": "#/components/schemas/OpenAI.FunctionToolCallOutput", "message": "#/components/schemas/OpenAI.ItemFieldMessage", "function_call": "#/components/schemas/OpenAI.ItemFieldFunctionToolCall", "file_search_call": "#/components/schemas/OpenAI.ItemFieldFileSearchToolCall", "web_search_call": "#/components/schemas/OpenAI.ItemFieldWebSearchToolCall", "image_generation_call": "#/components/schemas/OpenAI.ItemFieldImageGenToolCall", "computer_call": "#/components/schemas/OpenAI.ItemFieldComputerToolCall", "computer_call_output": "#/components/schemas/OpenAI.ItemFieldComputerToolCallOutputResource", "reasoning": "#/components/schemas/OpenAI.ItemFieldReasoningItem", "compaction": "#/components/schemas/OpenAI.ItemFieldCompactionBody", "code_interpreter_call": "#/components/schemas/OpenAI.ItemFieldCodeInterpreterToolCall", "local_shell_call": "#/components/schemas/OpenAI.ItemFieldLocalShellToolCall", "local_shell_call_output": "#/components/schemas/OpenAI.ItemFieldLocalShellToolCallOutput", "shell_call": "#/components/schemas/OpenAI.ItemFieldFunctionShellCall", "shell_call_output": "#/components/schemas/OpenAI.ItemFieldFunctionShellCallOutput", "apply_patch_call": "#/components/schemas/OpenAI.ItemFieldApplyPatchToolCall", "apply_patch_call_output": "#/components/schemas/OpenAI.ItemFieldApplyPatchToolCallOutput", "mcp_list_tools": "#/components/schemas/OpenAI.ItemFieldMcpListTools", "mcp_approval_request": "#/components/schemas/OpenAI.ItemFieldMcpApprovalRequest", "mcp_approval_response": "#/components/schemas/OpenAI.ItemFieldMcpApprovalResponseResource", "mcp_call": "#/components/schemas/OpenAI.ItemFieldMcpToolCall", "custom_tool_call": "#/components/schemas/OpenAI.ItemFieldCustomToolCall", "custom_tool_call_output": "#/components/schemas/OpenAI.ItemFieldCustomToolCallOutput" } }, "description": "An item representing a message, tool call, tool output, reasoning, or other response element." }, "OpenAI.ItemFieldApplyPatchToolCall": { "type": "object", "required": [ "type", "id", "call_id", "status", "operation" ], "properties": { "type": { "type": "string", "enum": [ "apply_patch_call" ], "description": "The type of the item. Always `apply_patch_call`.", "x-stainless-const": true, "default": "apply_patch_call" }, "id": { "type": "string", "description": "The unique ID of the apply patch tool call. Populated when this item is returned via API." }, "call_id": { "type": "string", "description": "The unique ID of the apply patch tool call generated by the model." }, "status": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ApplyPatchCallStatus" } ], "description": "The status of the apply patch tool call. One of `in_progress` or `completed`." }, "operation": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ApplyPatchFileOperation" } ], "description": "One of the create_file, delete_file, or update_file operations applied via apply_patch.", "title": "Apply patch operation" }, "created_by": { "type": "string", "description": "The ID of the entity that created this tool call." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemField" } ], "description": "A tool call that applies file diffs by creating, deleting, or updating files.", "title": "Apply patch tool call" }, "OpenAI.ItemFieldApplyPatchToolCallOutput": { "type": "object", "required": [ "type", "id", "call_id", "status" ], "properties": { "type": { "type": "string", "enum": [ "apply_patch_call_output" ], "description": "The type of the item. Always `apply_patch_call_output`.", "x-stainless-const": true, "default": "apply_patch_call_output" }, "id": { "type": "string", "description": "The unique ID of the apply patch tool call output. Populated when this item is returned via API." }, "call_id": { "type": "string", "description": "The unique ID of the apply patch tool call generated by the model." }, "status": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ApplyPatchCallOutputStatus" } ], "description": "The status of the apply patch tool call output. One of `completed` or `failed`." }, "output": { "type": "string", "nullable": true }, "created_by": { "type": "string", "description": "The ID of the entity that created this tool call output." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemField" } ], "description": "The output emitted by an apply patch tool call.", "title": "Apply patch tool call output" }, "OpenAI.ItemFieldCodeInterpreterToolCall": { "type": "object", "required": [ "type", "id", "status", "container_id", "code", "outputs" ], "properties": { "type": { "type": "string", "enum": [ "code_interpreter_call" ], "description": "The type of the code interpreter tool call. Always `code_interpreter_call`.", "x-stainless-const": true, "default": "code_interpreter_call" }, "id": { "type": "string", "description": "The unique ID of the code interpreter tool call." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete", "interpreting", "failed" ], "description": "The status of the code interpreter tool call. Valid values are `in_progress`, `completed`, `incomplete`, `interpreting`, and `failed`." }, "container_id": { "type": "string", "description": "The ID of the container used to run the code." }, "code": { "type": "string", "nullable": true }, "outputs": { "type": "array", "items": { "anyOf": [ { "$ref": "#/components/schemas/OpenAI.CodeInterpreterOutputLogs" }, { "$ref": "#/components/schemas/OpenAI.CodeInterpreterOutputImage" } ] }, "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemField" } ], "description": "A tool call to run code.", "title": "Code interpreter tool call" }, "OpenAI.ItemFieldCompactionBody": { "type": "object", "required": [ "type", "id", "encrypted_content" ], "properties": { "type": { "type": "string", "enum": [ "compaction" ], "description": "The type of the item. Always `compaction`.", "x-stainless-const": true, "default": "compaction" }, "id": { "type": "string", "description": "The unique ID of the compaction item." }, "encrypted_content": { "type": "string", "description": "The encrypted content that was produced by compaction." }, "created_by": { "type": "string", "description": "The identifier of the actor that created the item." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemField" } ], "description": "A compaction item generated by the [`v1/responses/compact` API](/docs/api-reference/responses/compact).", "title": "Compaction item" }, "OpenAI.ItemFieldComputerToolCall": { "type": "object", "required": [ "type", "id", "call_id", "action", "pending_safety_checks", "status" ], "properties": { "type": { "type": "string", "enum": [ "computer_call" ], "description": "The type of the computer call. Always `computer_call`.", "default": "computer_call" }, "id": { "type": "string", "description": "The unique ID of the computer call." }, "call_id": { "type": "string", "description": "An identifier used when responding to the tool call with output." }, "action": { "$ref": "#/components/schemas/OpenAI.ComputerAction" }, "pending_safety_checks": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.ComputerCallSafetyCheckParam" }, "description": "The pending safety checks for the computer call." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "description": "The status of the item. One of `in_progress`, `completed`, or\n `incomplete`. Populated when items are returned via API." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemField" } ], "description": "A tool call to a computer use tool. See the\n[computer use guide](/docs/guides/tools-computer-use) for more information.", "title": "Computer tool call" }, "OpenAI.ItemFieldComputerToolCallOutputResource": { "type": "object", "required": [ "type", "call_id", "output" ], "properties": { "type": { "type": "string", "enum": [ "computer_call_output" ], "description": "The type of the computer tool call output. Always `computer_call_output`.", "x-stainless-const": true, "default": "computer_call_output" }, "id": { "type": "string", "description": "The ID of the computer tool call output." }, "call_id": { "type": "string", "description": "The ID of the computer tool call that produced the output." }, "acknowledged_safety_checks": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.ComputerCallSafetyCheckParam" }, "description": "The safety checks reported by the API that have been acknowledged by the\n developer." }, "output": { "$ref": "#/components/schemas/OpenAI.ComputerScreenshotImage" }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "description": "The status of the message input. One of `in_progress`, `completed`, or\n `incomplete`. Populated when input items are returned via API." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemField" } ] }, "OpenAI.ItemFieldCustomToolCall": { "type": "object", "required": [ "type", "call_id", "name", "input" ], "properties": { "type": { "type": "string", "enum": [ "custom_tool_call" ], "description": "The type of the custom tool call. Always `custom_tool_call`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the custom tool call in the OpenAI platform." }, "call_id": { "type": "string", "description": "An identifier used to map this custom tool call to a tool call output." }, "name": { "type": "string", "description": "The name of the custom tool being called." }, "input": { "type": "string", "description": "The input for the custom tool call generated by the model." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemField" } ], "description": "A call to a custom tool created by the model.", "title": "Custom tool call" }, "OpenAI.ItemFieldCustomToolCallOutput": { "type": "object", "required": [ "type", "call_id", "output" ], "properties": { "type": { "type": "string", "enum": [ "custom_tool_call_output" ], "description": "The type of the custom tool call output. Always `custom_tool_call_output`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the custom tool call output in the OpenAI platform." }, "call_id": { "type": "string", "description": "The call ID, used to map this custom tool call output to a custom tool call." }, "output": { "oneOf": [ { "type": "string" }, { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.FunctionAndCustomToolCallOutput" } } ], "description": "The output from the custom tool call generated by your code.\n Can be a string or an list of output content." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemField" } ], "description": "The output of a custom tool call from your code, being sent back to the model.", "title": "Custom tool call output" }, "OpenAI.ItemFieldFileSearchToolCall": { "type": "object", "required": [ "id", "type", "status", "queries" ], "properties": { "id": { "type": "string", "description": "The unique ID of the file search tool call." }, "type": { "type": "string", "enum": [ "file_search_call" ], "description": "The type of the file search tool call. Always `file_search_call`.", "x-stainless-const": true }, "status": { "type": "string", "enum": [ "in_progress", "searching", "completed", "incomplete", "failed" ], "description": "The status of the file search tool call. One of `in_progress`,\n `searching`, `incomplete` or `failed`," }, "queries": { "type": "array", "items": { "type": "string" }, "description": "The queries used to search for files." }, "results": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.FileSearchToolCallResults" }, "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemField" } ], "description": "The results of a file search tool call. See the\n[file search guide](/docs/guides/tools-file-search) for more information.", "title": "File search tool call" }, "OpenAI.ItemFieldFunctionShellCall": { "type": "object", "required": [ "type", "id", "call_id", "action", "status", "environment" ], "properties": { "type": { "type": "string", "enum": [ "shell_call" ], "description": "The type of the item. Always `shell_call`.", "x-stainless-const": true, "default": "shell_call" }, "id": { "type": "string", "description": "The unique ID of the shell tool call. Populated when this item is returned via API." }, "call_id": { "type": "string", "description": "The unique ID of the shell tool call generated by the model." }, "action": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.FunctionShellAction" } ], "description": "The shell commands and limits that describe how to run the tool call." }, "status": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.LocalShellCallStatus" } ], "description": "The status of the shell call. One of `in_progress`, `completed`, or `incomplete`." }, "environment": { "type": "object", "allOf": [ { "$ref": "#/components/schemas/OpenAI.FunctionShellCallEnvironment" } ], "nullable": true }, "created_by": { "type": "string", "description": "The ID of the entity that created this tool call." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemField" } ], "description": "A tool call that executes one or more shell commands in a managed environment.", "title": "Shell tool call" }, "OpenAI.ItemFieldFunctionShellCallOutput": { "type": "object", "required": [ "type", "id", "call_id", "status", "output", "max_output_length" ], "properties": { "type": { "type": "string", "enum": [ "shell_call_output" ], "description": "The type of the shell call output. Always `shell_call_output`.", "x-stainless-const": true, "default": "shell_call_output" }, "id": { "type": "string", "description": "The unique ID of the shell call output. Populated when this item is returned via API." }, "call_id": { "type": "string", "description": "The unique ID of the shell tool call generated by the model." }, "status": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.LocalShellCallOutputStatusEnum" } ], "description": "The status of the shell call output. One of `in_progress`, `completed`, or `incomplete`." }, "output": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.FunctionShellCallOutputContent" }, "description": "An array of shell call output contents" }, "max_output_length": { "type": "integer", "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "nullable": true }, "created_by": { "type": "string", "description": "The identifier of the actor that created the item." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemField" } ], "description": "The output of a shell tool call that was emitted.", "title": "Shell call output" }, "OpenAI.ItemFieldFunctionToolCall": { "type": "object", "required": [ "type", "call_id", "name", "arguments" ], "properties": { "id": { "type": "string", "description": "The unique ID of the function tool call." }, "type": { "type": "string", "enum": [ "function_call" ], "description": "The type of the function tool call. Always `function_call`.", "x-stainless-const": true }, "call_id": { "type": "string", "description": "The unique ID of the function tool call generated by the model." }, "name": { "type": "string", "description": "The name of the function to run." }, "arguments": { "type": "string", "description": "A JSON string of the arguments to pass to the function." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "description": "The status of the item. One of `in_progress`, `completed`, or\n `incomplete`. Populated when items are returned via API." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemField" } ], "description": "A tool call to run a function. See the\n[function calling guide](/docs/guides/function-calling) for more information.", "title": "Function tool call" }, "OpenAI.ItemFieldImageGenToolCall": { "type": "object", "required": [ "type", "id", "status", "result" ], "properties": { "type": { "type": "string", "enum": [ "image_generation_call" ], "description": "The type of the image generation call. Always `image_generation_call`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the image generation call." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "generating", "failed" ], "description": "The status of the image generation call." }, "result": { "type": "string", "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemField" } ], "description": "An image generation request made by the model.", "title": "Image generation call" }, "OpenAI.ItemFieldLocalShellToolCall": { "type": "object", "required": [ "type", "id", "call_id", "action", "status" ], "properties": { "type": { "type": "string", "enum": [ "local_shell_call" ], "description": "The type of the local shell call. Always `local_shell_call`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the local shell call." }, "call_id": { "type": "string", "description": "The unique ID of the local shell tool call generated by the model." }, "action": { "$ref": "#/components/schemas/OpenAI.LocalShellExecAction" }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "description": "The status of the local shell call." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemField" } ], "description": "A tool call to run a command on the local shell.", "title": "Local shell call" }, "OpenAI.ItemFieldLocalShellToolCallOutput": { "type": "object", "required": [ "type", "id", "output" ], "properties": { "type": { "type": "string", "enum": [ "local_shell_call_output" ], "description": "The type of the local shell tool call output. Always `local_shell_call_output`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the local shell tool call generated by the model." }, "output": { "type": "string", "description": "A JSON string of the output of the local shell tool call." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemField" } ], "description": "The output of a local shell tool call.", "title": "Local shell call output" }, "OpenAI.ItemFieldMcpApprovalRequest": { "type": "object", "required": [ "type", "id", "server_label", "name", "arguments" ], "properties": { "type": { "type": "string", "enum": [ "mcp_approval_request" ], "description": "The type of the item. Always `mcp_approval_request`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the approval request." }, "server_label": { "type": "string", "description": "The label of the MCP server making the request." }, "name": { "type": "string", "description": "The name of the tool to run." }, "arguments": { "type": "string", "description": "A JSON string of arguments for the tool." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemField" } ], "description": "A request for human approval of a tool invocation.", "title": "MCP approval request" }, "OpenAI.ItemFieldMcpApprovalResponseResource": { "type": "object", "required": [ "type", "id", "approval_request_id", "approve" ], "properties": { "type": { "type": "string", "enum": [ "mcp_approval_response" ], "description": "The type of the item. Always `mcp_approval_response`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the approval response" }, "approval_request_id": { "type": "string", "description": "The ID of the approval request being answered." }, "approve": { "type": "boolean", "description": "Whether the request was approved." }, "reason": { "type": "string", "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemField" } ], "description": "A response to an MCP approval request.", "title": "MCP approval response" }, "OpenAI.ItemFieldMcpListTools": { "type": "object", "required": [ "type", "id", "server_label", "tools" ], "properties": { "type": { "type": "string", "enum": [ "mcp_list_tools" ], "description": "The type of the item. Always `mcp_list_tools`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the list." }, "server_label": { "type": "string", "description": "The label of the MCP server." }, "tools": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.MCPListToolsTool" }, "description": "The tools available on the server." }, "error": { "type": "string", "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemField" } ], "description": "A list of tools available on an MCP server.", "title": "MCP list tools" }, "OpenAI.ItemFieldMcpToolCall": { "type": "object", "required": [ "type", "id", "server_label", "name", "arguments" ], "properties": { "type": { "type": "string", "enum": [ "mcp_call" ], "description": "The type of the item. Always `mcp_call`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the tool call." }, "server_label": { "type": "string", "description": "The label of the MCP server running the tool." }, "name": { "type": "string", "description": "The name of the tool that was run." }, "arguments": { "type": "string", "description": "A JSON string of the arguments passed to the tool." }, "output": { "type": "string", "nullable": true }, "error": { "type": "object", "additionalProperties": {} }, "status": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.MCPToolCallStatus" } ], "description": "The status of the tool call. One of `in_progress`, `completed`, `incomplete`, `calling`, or `failed`." }, "approval_request_id": { "type": "string", "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemField" } ], "description": "An invocation of a tool on an MCP server.", "title": "MCP tool call" }, "OpenAI.ItemFieldMessage": { "type": "object", "required": [ "type", "id", "status", "role", "content" ], "properties": { "type": { "type": "string", "enum": [ "message" ], "description": "The type of the message. Always set to `message`.", "x-stainless-const": true, "default": "message" }, "id": { "type": "string", "description": "The unique ID of the message." }, "status": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.MessageStatus" } ], "description": "The status of item. One of `in_progress`, `completed`, or `incomplete`. Populated when items are returned via API." }, "role": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.MessageRole" } ], "description": "The role of the message. One of `unknown`, `user`, `assistant`, `system`, `critic`, `discriminator`, `developer`, or `tool`." }, "content": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.MessageContent" }, "description": "The content of the message" } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemField" } ], "description": "A message to or from the model.", "title": "Message" }, "OpenAI.ItemFieldReasoningItem": { "type": "object", "required": [ "type", "id", "summary" ], "properties": { "type": { "type": "string", "enum": [ "reasoning" ], "description": "The type of the object. Always `reasoning`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique identifier of the reasoning content." }, "encrypted_content": { "type": "string", "nullable": true }, "summary": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.SummaryTextContent" }, "description": "Reasoning summary content." }, "content": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.ReasoningTextContent" }, "description": "Reasoning text content." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "description": "The status of the item. One of `in_progress`, `completed`, or\n `incomplete`. Populated when items are returned via API." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemField" } ], "description": "A description of the chain of thought used by a reasoning model while generating\na response. Be sure to include these items in your `input` to the Responses API\nfor subsequent turns of a conversation if you are manually\n[managing context](/docs/guides/conversation-state).", "title": "Reasoning" }, "OpenAI.ItemFieldType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "message", "function_call", "function_call_output", "file_search_call", "web_search_call", "image_generation_call", "computer_call", "computer_call_output", "reasoning", "compaction", "code_interpreter_call", "local_shell_call", "local_shell_call_output", "shell_call", "shell_call_output", "apply_patch_call", "apply_patch_call_output", "mcp_list_tools", "mcp_approval_request", "mcp_approval_response", "mcp_call", "custom_tool_call", "custom_tool_call_output" ] } ] }, "OpenAI.ItemFieldWebSearchToolCall": { "type": "object", "required": [ "id", "type", "status", "action" ], "properties": { "id": { "type": "string", "description": "The unique ID of the web search tool call." }, "type": { "type": "string", "enum": [ "web_search_call" ], "description": "The type of the web search tool call. Always `web_search_call`.", "x-stainless-const": true }, "status": { "type": "string", "enum": [ "in_progress", "searching", "completed", "failed" ], "description": "The status of the web search tool call." }, "action": { "oneOf": [ { "$ref": "#/components/schemas/OpenAI.WebSearchActionSearch" }, { "$ref": "#/components/schemas/OpenAI.WebSearchActionOpenPage" }, { "$ref": "#/components/schemas/OpenAI.WebSearchActionFind" } ], "description": "An object describing the specific action taken in this web search call.\n Includes details on how the model used the web (search, open_page, find_in_page)." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemField" } ], "description": "The results of a web search tool call. See the\n[web search guide](/docs/guides/tools-web-search) for more information.", "title": "Web search tool call" }, "OpenAI.ItemFileSearchToolCall": { "type": "object", "required": [ "id", "type", "status", "queries" ], "properties": { "id": { "type": "string", "description": "The unique ID of the file search tool call." }, "type": { "type": "string", "enum": [ "file_search_call" ], "description": "The type of the file search tool call. Always `file_search_call`.", "x-stainless-const": true }, "status": { "type": "string", "enum": [ "in_progress", "searching", "completed", "incomplete", "failed" ], "description": "The status of the file search tool call. One of `in_progress`,\n `searching`, `incomplete` or `failed`," }, "queries": { "type": "array", "items": { "type": "string" }, "description": "The queries used to search for files." }, "results": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.FileSearchToolCallResults" }, "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Item" } ], "description": "The results of a file search tool call. See the\n[file search guide](/docs/guides/tools-file-search) for more information.", "title": "File search tool call" }, "OpenAI.ItemFunctionCallOutputItemParam": { "type": "object", "required": [ "call_id", "type", "output" ], "properties": { "id": { "type": "string", "nullable": true }, "call_id": { "type": "string", "minLength": 1, "maxLength": 64, "description": "The unique ID of the function tool call generated by the model." }, "type": { "type": "string", "enum": [ "function_call_output" ], "description": "The type of the function tool call output. Always `function_call_output`.", "x-stainless-const": true, "default": "function_call_output" }, "output": { "oneOf": [ { "type": "string" }, { "type": "array", "items": { "anyOf": [ { "$ref": "#/components/schemas/OpenAI.InputTextContentParam" }, { "$ref": "#/components/schemas/OpenAI.InputImageContentParamAutoParam" }, { "$ref": "#/components/schemas/OpenAI.InputFileContentParam" } ] } } ], "description": "Text, image, or file output of the function tool call." }, "status": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.FunctionCallItemStatus" } ], "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Item" } ], "description": "The output of a function tool call.", "title": "Function tool call output" }, "OpenAI.ItemFunctionShellCallItemParam": { "type": "object", "required": [ "call_id", "type", "action" ], "properties": { "id": { "type": "string", "nullable": true }, "call_id": { "type": "string", "minLength": 1, "maxLength": 64, "description": "The unique ID of the shell tool call generated by the model." }, "type": { "type": "string", "enum": [ "shell_call" ], "description": "The type of the item. Always `shell_call`.", "x-stainless-const": true, "default": "shell_call" }, "action": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.FunctionShellActionParam" } ], "description": "The shell commands and limits that describe how to run the tool call." }, "status": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.FunctionShellCallItemStatus" } ], "nullable": true }, "environment": { "type": "object", "allOf": [ { "$ref": "#/components/schemas/OpenAI.FunctionShellCallItemParamEnvironment" } ], "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Item" } ], "description": "A tool representing a request to execute one or more shell commands.", "title": "Shell tool call" }, "OpenAI.ItemFunctionShellCallOutputItemParam": { "type": "object", "required": [ "call_id", "type", "output" ], "properties": { "id": { "type": "string", "nullable": true }, "call_id": { "type": "string", "minLength": 1, "maxLength": 64, "description": "The unique ID of the shell tool call generated by the model." }, "type": { "type": "string", "enum": [ "shell_call_output" ], "description": "The type of the item. Always `shell_call_output`.", "x-stainless-const": true, "default": "shell_call_output" }, "output": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.FunctionShellCallOutputContentParam" }, "description": "Captured chunks of stdout and stderr output, along with their associated outcomes." }, "status": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.FunctionShellCallItemStatus" } ], "nullable": true }, "max_output_length": { "type": "integer", "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Item" } ], "description": "The streamed output items emitted by a shell tool call.", "title": "Shell tool call output" }, "OpenAI.ItemFunctionToolCall": { "type": "object", "required": [ "type", "call_id", "name", "arguments" ], "properties": { "id": { "type": "string", "description": "The unique ID of the function tool call." }, "type": { "type": "string", "enum": [ "function_call" ], "description": "The type of the function tool call. Always `function_call`.", "x-stainless-const": true }, "call_id": { "type": "string", "description": "The unique ID of the function tool call generated by the model." }, "name": { "type": "string", "description": "The name of the function to run." }, "arguments": { "type": "string", "description": "A JSON string of the arguments to pass to the function." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "description": "The status of the item. One of `in_progress`, `completed`, or\n `incomplete`. Populated when items are returned via API." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Item" } ], "description": "A tool call to run a function. See the\n[function calling guide](/docs/guides/function-calling) for more information.", "title": "Function tool call" }, "OpenAI.ItemImageGenToolCall": { "type": "object", "required": [ "type", "id", "status", "result" ], "properties": { "type": { "type": "string", "enum": [ "image_generation_call" ], "description": "The type of the image generation call. Always `image_generation_call`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the image generation call." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "generating", "failed" ], "description": "The status of the image generation call." }, "result": { "type": "string", "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Item" } ], "description": "An image generation request made by the model.", "title": "Image generation call" }, "OpenAI.ItemLocalShellToolCall": { "type": "object", "required": [ "type", "id", "call_id", "action", "status" ], "properties": { "type": { "type": "string", "enum": [ "local_shell_call" ], "description": "The type of the local shell call. Always `local_shell_call`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the local shell call." }, "call_id": { "type": "string", "description": "The unique ID of the local shell tool call generated by the model." }, "action": { "$ref": "#/components/schemas/OpenAI.LocalShellExecAction" }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "description": "The status of the local shell call." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Item" } ], "description": "A tool call to run a command on the local shell.", "title": "Local shell call" }, "OpenAI.ItemLocalShellToolCallOutput": { "type": "object", "required": [ "type", "id", "output" ], "properties": { "type": { "type": "string", "enum": [ "local_shell_call_output" ], "description": "The type of the local shell tool call output. Always `local_shell_call_output`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the local shell tool call generated by the model." }, "output": { "type": "string", "description": "A JSON string of the output of the local shell tool call." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Item" } ], "description": "The output of a local shell tool call.", "title": "Local shell call output" }, "OpenAI.ItemMcpApprovalRequest": { "type": "object", "required": [ "type", "id", "server_label", "name", "arguments" ], "properties": { "type": { "type": "string", "enum": [ "mcp_approval_request" ], "description": "The type of the item. Always `mcp_approval_request`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the approval request." }, "server_label": { "type": "string", "description": "The label of the MCP server making the request." }, "name": { "type": "string", "description": "The name of the tool to run." }, "arguments": { "type": "string", "description": "A JSON string of arguments for the tool." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Item" } ], "description": "A request for human approval of a tool invocation.", "title": "MCP approval request" }, "OpenAI.ItemMcpApprovalResponse": { "type": "object", "required": [ "type", "approval_request_id", "approve" ], "properties": { "type": { "type": "string", "enum": [ "mcp_approval_response" ], "description": "The type of the item. Always `mcp_approval_response`.", "x-stainless-const": true }, "id": { "type": "string", "nullable": true }, "approval_request_id": { "type": "string", "description": "The ID of the approval request being answered." }, "approve": { "type": "boolean", "description": "Whether the request was approved." }, "reason": { "type": "string", "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Item" } ], "description": "A response to an MCP approval request.", "title": "MCP approval response" }, "OpenAI.ItemMcpListTools": { "type": "object", "required": [ "type", "id", "server_label", "tools" ], "properties": { "type": { "type": "string", "enum": [ "mcp_list_tools" ], "description": "The type of the item. Always `mcp_list_tools`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the list." }, "server_label": { "type": "string", "description": "The label of the MCP server." }, "tools": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.MCPListToolsTool" }, "description": "The tools available on the server." }, "error": { "type": "string", "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Item" } ], "description": "A list of tools available on an MCP server.", "title": "MCP list tools" }, "OpenAI.ItemMcpToolCall": { "type": "object", "required": [ "type", "id", "server_label", "name", "arguments" ], "properties": { "type": { "type": "string", "enum": [ "mcp_call" ], "description": "The type of the item. Always `mcp_call`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the tool call." }, "server_label": { "type": "string", "description": "The label of the MCP server running the tool." }, "name": { "type": "string", "description": "The name of the tool that was run." }, "arguments": { "type": "string", "description": "A JSON string of the arguments passed to the tool." }, "output": { "type": "string", "nullable": true }, "error": { "type": "object", "additionalProperties": {} }, "status": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.MCPToolCallStatus" } ], "description": "The status of the tool call. One of `in_progress`, `completed`, `incomplete`, `calling`, or `failed`." }, "approval_request_id": { "type": "string", "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Item" } ], "description": "An invocation of a tool on an MCP server.", "title": "MCP tool call" }, "OpenAI.ItemOutputMessage": { "type": "object", "required": [ "id", "type", "role", "content", "status" ], "properties": { "id": { "type": "string", "description": "The unique ID of the output message." }, "type": { "type": "string", "enum": [ "output_message" ], "description": "The type of the output message. Always `message`.", "x-stainless-const": true }, "role": { "type": "string", "enum": [ "assistant" ], "description": "The role of the output message. Always `assistant`.", "x-stainless-const": true }, "content": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.OutputMessageContent" }, "description": "The content of the output message." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "description": "The status of the message input. One of `in_progress`, `completed`, or\n `incomplete`. Populated when input items are returned via API." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Item" } ], "description": "An output message from the model.", "title": "Output message" }, "OpenAI.ItemReasoningItem": { "type": "object", "required": [ "type", "id", "summary" ], "properties": { "type": { "type": "string", "enum": [ "reasoning" ], "description": "The type of the object. Always `reasoning`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique identifier of the reasoning content." }, "encrypted_content": { "type": "string", "nullable": true }, "summary": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.SummaryTextContent" }, "description": "Reasoning summary content." }, "content": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.ReasoningTextContent" }, "description": "Reasoning text content." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "description": "The status of the item. One of `in_progress`, `completed`, or\n `incomplete`. Populated when items are returned via API." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Item" } ], "description": "A description of the chain of thought used by a reasoning model while generating\na response. Be sure to include these items in your `input` to the Responses API\nfor subsequent turns of a conversation if you are manually\n[managing context](/docs/guides/conversation-state).", "title": "Reasoning" }, "OpenAI.ItemReferenceParam": { "type": "object", "required": [ "type", "id" ], "properties": { "type": { "type": "string", "enum": [ "item_reference" ], "description": "The type of item to reference. Always `item_reference`.", "x-stainless-const": true, "default": "item_reference" }, "id": { "type": "string", "description": "The ID of the item to reference." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.InputItem" } ], "description": "An internal identifier for an item to reference.", "title": "Item reference" }, "OpenAI.ItemResource": { "type": "object", "required": [ "type" ], "properties": { "type": { "$ref": "#/components/schemas/OpenAI.ItemResourceType" } }, "discriminator": { "propertyName": "type", "mapping": { "message": "#/components/schemas/OpenAI.InputMessageResource", "output_message": "#/components/schemas/OpenAI.ItemResourceOutputMessage", "file_search_call": "#/components/schemas/OpenAI.ItemResourceFileSearchToolCall", "computer_call": "#/components/schemas/OpenAI.ItemResourceComputerToolCall", "computer_call_output": "#/components/schemas/OpenAI.ItemResourceComputerToolCallOutputResource", "web_search_call": "#/components/schemas/OpenAI.ItemResourceWebSearchToolCall", "function_call": "#/components/schemas/OpenAI.ItemResourceFunctionToolCallResource", "function_call_output": "#/components/schemas/OpenAI.ItemResourceFunctionToolCallOutputResource", "image_generation_call": "#/components/schemas/OpenAI.ItemResourceImageGenToolCall", "code_interpreter_call": "#/components/schemas/OpenAI.ItemResourceCodeInterpreterToolCall", "local_shell_call": "#/components/schemas/OpenAI.ItemResourceLocalShellToolCall", "local_shell_call_output": "#/components/schemas/OpenAI.ItemResourceLocalShellToolCallOutput", "shell_call": "#/components/schemas/OpenAI.ItemResourceFunctionShellCall", "shell_call_output": "#/components/schemas/OpenAI.ItemResourceFunctionShellCallOutput", "apply_patch_call": "#/components/schemas/OpenAI.ItemResourceApplyPatchToolCall", "apply_patch_call_output": "#/components/schemas/OpenAI.ItemResourceApplyPatchToolCallOutput", "mcp_list_tools": "#/components/schemas/OpenAI.ItemResourceMcpListTools", "mcp_approval_request": "#/components/schemas/OpenAI.ItemResourceMcpApprovalRequest", "mcp_approval_response": "#/components/schemas/OpenAI.ItemResourceMcpApprovalResponseResource", "mcp_call": "#/components/schemas/OpenAI.ItemResourceMcpToolCall" } }, "description": "Content item used to generate a response." }, "OpenAI.ItemResourceApplyPatchToolCall": { "type": "object", "required": [ "type", "id", "call_id", "status", "operation" ], "properties": { "type": { "type": "string", "enum": [ "apply_patch_call" ], "description": "The type of the item. Always `apply_patch_call`.", "x-stainless-const": true, "default": "apply_patch_call" }, "id": { "type": "string", "description": "The unique ID of the apply patch tool call. Populated when this item is returned via API." }, "call_id": { "type": "string", "description": "The unique ID of the apply patch tool call generated by the model." }, "status": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ApplyPatchCallStatus" } ], "description": "The status of the apply patch tool call. One of `in_progress` or `completed`." }, "operation": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ApplyPatchFileOperation" } ], "description": "One of the create_file, delete_file, or update_file operations applied via apply_patch.", "title": "Apply patch operation" }, "created_by": { "type": "string", "description": "The ID of the entity that created this tool call." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemResource" } ], "description": "A tool call that applies file diffs by creating, deleting, or updating files.", "title": "Apply patch tool call" }, "OpenAI.ItemResourceApplyPatchToolCallOutput": { "type": "object", "required": [ "type", "id", "call_id", "status" ], "properties": { "type": { "type": "string", "enum": [ "apply_patch_call_output" ], "description": "The type of the item. Always `apply_patch_call_output`.", "x-stainless-const": true, "default": "apply_patch_call_output" }, "id": { "type": "string", "description": "The unique ID of the apply patch tool call output. Populated when this item is returned via API." }, "call_id": { "type": "string", "description": "The unique ID of the apply patch tool call generated by the model." }, "status": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ApplyPatchCallOutputStatus" } ], "description": "The status of the apply patch tool call output. One of `completed` or `failed`." }, "output": { "type": "string", "nullable": true }, "created_by": { "type": "string", "description": "The ID of the entity that created this tool call output." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemResource" } ], "description": "The output emitted by an apply patch tool call.", "title": "Apply patch tool call output" }, "OpenAI.ItemResourceCodeInterpreterToolCall": { "type": "object", "required": [ "type", "id", "status", "container_id", "code", "outputs" ], "properties": { "type": { "type": "string", "enum": [ "code_interpreter_call" ], "description": "The type of the code interpreter tool call. Always `code_interpreter_call`.", "x-stainless-const": true, "default": "code_interpreter_call" }, "id": { "type": "string", "description": "The unique ID of the code interpreter tool call." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete", "interpreting", "failed" ], "description": "The status of the code interpreter tool call. Valid values are `in_progress`, `completed`, `incomplete`, `interpreting`, and `failed`." }, "container_id": { "type": "string", "description": "The ID of the container used to run the code." }, "code": { "type": "string", "nullable": true }, "outputs": { "type": "array", "items": { "anyOf": [ { "$ref": "#/components/schemas/OpenAI.CodeInterpreterOutputLogs" }, { "$ref": "#/components/schemas/OpenAI.CodeInterpreterOutputImage" } ] }, "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemResource" } ], "description": "A tool call to run code.", "title": "Code interpreter tool call" }, "OpenAI.ItemResourceComputerToolCall": { "type": "object", "required": [ "type", "id", "call_id", "action", "pending_safety_checks", "status" ], "properties": { "type": { "type": "string", "enum": [ "computer_call" ], "description": "The type of the computer call. Always `computer_call`.", "default": "computer_call" }, "id": { "type": "string", "description": "The unique ID of the computer call." }, "call_id": { "type": "string", "description": "An identifier used when responding to the tool call with output." }, "action": { "$ref": "#/components/schemas/OpenAI.ComputerAction" }, "pending_safety_checks": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.ComputerCallSafetyCheckParam" }, "description": "The pending safety checks for the computer call." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "description": "The status of the item. One of `in_progress`, `completed`, or\n `incomplete`. Populated when items are returned via API." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemResource" } ], "description": "A tool call to a computer use tool. See the\n[computer use guide](/docs/guides/tools-computer-use) for more information.", "title": "Computer tool call" }, "OpenAI.ItemResourceComputerToolCallOutputResource": { "type": "object", "required": [ "type", "call_id", "output" ], "properties": { "type": { "type": "string", "enum": [ "computer_call_output" ], "description": "The type of the computer tool call output. Always `computer_call_output`.", "x-stainless-const": true, "default": "computer_call_output" }, "id": { "type": "string", "description": "The ID of the computer tool call output." }, "call_id": { "type": "string", "description": "The ID of the computer tool call that produced the output." }, "acknowledged_safety_checks": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.ComputerCallSafetyCheckParam" }, "description": "The safety checks reported by the API that have been acknowledged by the\n developer." }, "output": { "$ref": "#/components/schemas/OpenAI.ComputerScreenshotImage" }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "description": "The status of the message input. One of `in_progress`, `completed`, or\n `incomplete`. Populated when input items are returned via API." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemResource" } ] }, "OpenAI.ItemResourceFileSearchToolCall": { "type": "object", "required": [ "id", "type", "status", "queries" ], "properties": { "id": { "type": "string", "description": "The unique ID of the file search tool call." }, "type": { "type": "string", "enum": [ "file_search_call" ], "description": "The type of the file search tool call. Always `file_search_call`.", "x-stainless-const": true }, "status": { "type": "string", "enum": [ "in_progress", "searching", "completed", "incomplete", "failed" ], "description": "The status of the file search tool call. One of `in_progress`,\n `searching`, `incomplete` or `failed`," }, "queries": { "type": "array", "items": { "type": "string" }, "description": "The queries used to search for files." }, "results": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.FileSearchToolCallResults" }, "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemResource" } ], "description": "The results of a file search tool call. See the\n[file search guide](/docs/guides/tools-file-search) for more information.", "title": "File search tool call" }, "OpenAI.ItemResourceFunctionShellCall": { "type": "object", "required": [ "type", "id", "call_id", "action", "status", "environment" ], "properties": { "type": { "type": "string", "enum": [ "shell_call" ], "description": "The type of the item. Always `shell_call`.", "x-stainless-const": true, "default": "shell_call" }, "id": { "type": "string", "description": "The unique ID of the shell tool call. Populated when this item is returned via API." }, "call_id": { "type": "string", "description": "The unique ID of the shell tool call generated by the model." }, "action": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.FunctionShellAction" } ], "description": "The shell commands and limits that describe how to run the tool call." }, "status": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.LocalShellCallStatus" } ], "description": "The status of the shell call. One of `in_progress`, `completed`, or `incomplete`." }, "environment": { "type": "object", "allOf": [ { "$ref": "#/components/schemas/OpenAI.FunctionShellCallEnvironment" } ], "nullable": true }, "created_by": { "type": "string", "description": "The ID of the entity that created this tool call." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemResource" } ], "description": "A tool call that executes one or more shell commands in a managed environment.", "title": "Shell tool call" }, "OpenAI.ItemResourceFunctionShellCallOutput": { "type": "object", "required": [ "type", "id", "call_id", "status", "output", "max_output_length" ], "properties": { "type": { "type": "string", "enum": [ "shell_call_output" ], "description": "The type of the shell call output. Always `shell_call_output`.", "x-stainless-const": true, "default": "shell_call_output" }, "id": { "type": "string", "description": "The unique ID of the shell call output. Populated when this item is returned via API." }, "call_id": { "type": "string", "description": "The unique ID of the shell tool call generated by the model." }, "status": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.LocalShellCallOutputStatusEnum" } ], "description": "The status of the shell call output. One of `in_progress`, `completed`, or `incomplete`." }, "output": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.FunctionShellCallOutputContent" }, "description": "An array of shell call output contents" }, "max_output_length": { "type": "integer", "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "nullable": true }, "created_by": { "type": "string", "description": "The identifier of the actor that created the item." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemResource" } ], "description": "The output of a shell tool call that was emitted.", "title": "Shell call output" }, "OpenAI.ItemResourceFunctionToolCallOutputResource": { "type": "object", "required": [ "type", "call_id", "output" ], "properties": { "id": { "type": "string", "description": "The unique ID of the function tool call output. Populated when this item\n is returned via API." }, "type": { "type": "string", "enum": [ "function_call_output" ], "description": "The type of the function tool call output. Always `function_call_output`.", "x-stainless-const": true }, "call_id": { "type": "string", "description": "The unique ID of the function tool call generated by the model." }, "output": { "oneOf": [ { "type": "string" }, { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.FunctionAndCustomToolCallOutput" } } ], "description": "The output from the function call generated by your code.\n Can be a string or an list of output content." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "description": "The status of the item. One of `in_progress`, `completed`, or\n `incomplete`. Populated when items are returned via API." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemResource" } ] }, "OpenAI.ItemResourceFunctionToolCallResource": { "type": "object", "required": [ "type", "call_id", "name", "arguments" ], "properties": { "id": { "type": "string", "description": "The unique ID of the function tool call." }, "type": { "type": "string", "enum": [ "function_call" ], "description": "The type of the function tool call. Always `function_call`.", "x-stainless-const": true }, "call_id": { "type": "string", "description": "The unique ID of the function tool call generated by the model." }, "name": { "type": "string", "description": "The name of the function to run." }, "arguments": { "type": "string", "description": "A JSON string of the arguments to pass to the function." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "description": "The status of the item. One of `in_progress`, `completed`, or\n `incomplete`. Populated when items are returned via API." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemResource" } ] }, "OpenAI.ItemResourceImageGenToolCall": { "type": "object", "required": [ "type", "id", "status", "result" ], "properties": { "type": { "type": "string", "enum": [ "image_generation_call" ], "description": "The type of the image generation call. Always `image_generation_call`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the image generation call." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "generating", "failed" ], "description": "The status of the image generation call." }, "result": { "type": "string", "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemResource" } ], "description": "An image generation request made by the model.", "title": "Image generation call" }, "OpenAI.ItemResourceLocalShellToolCall": { "type": "object", "required": [ "type", "id", "call_id", "action", "status" ], "properties": { "type": { "type": "string", "enum": [ "local_shell_call" ], "description": "The type of the local shell call. Always `local_shell_call`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the local shell call." }, "call_id": { "type": "string", "description": "The unique ID of the local shell tool call generated by the model." }, "action": { "$ref": "#/components/schemas/OpenAI.LocalShellExecAction" }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "description": "The status of the local shell call." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemResource" } ], "description": "A tool call to run a command on the local shell.", "title": "Local shell call" }, "OpenAI.ItemResourceLocalShellToolCallOutput": { "type": "object", "required": [ "type", "id", "output" ], "properties": { "type": { "type": "string", "enum": [ "local_shell_call_output" ], "description": "The type of the local shell tool call output. Always `local_shell_call_output`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the local shell tool call generated by the model." }, "output": { "type": "string", "description": "A JSON string of the output of the local shell tool call." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemResource" } ], "description": "The output of a local shell tool call.", "title": "Local shell call output" }, "OpenAI.ItemResourceMcpApprovalRequest": { "type": "object", "required": [ "type", "id", "server_label", "name", "arguments" ], "properties": { "type": { "type": "string", "enum": [ "mcp_approval_request" ], "description": "The type of the item. Always `mcp_approval_request`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the approval request." }, "server_label": { "type": "string", "description": "The label of the MCP server making the request." }, "name": { "type": "string", "description": "The name of the tool to run." }, "arguments": { "type": "string", "description": "A JSON string of arguments for the tool." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemResource" } ], "description": "A request for human approval of a tool invocation.", "title": "MCP approval request" }, "OpenAI.ItemResourceMcpApprovalResponseResource": { "type": "object", "required": [ "type", "id", "approval_request_id", "approve" ], "properties": { "type": { "type": "string", "enum": [ "mcp_approval_response" ], "description": "The type of the item. Always `mcp_approval_response`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the approval response" }, "approval_request_id": { "type": "string", "description": "The ID of the approval request being answered." }, "approve": { "type": "boolean", "description": "Whether the request was approved." }, "reason": { "type": "string", "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemResource" } ], "description": "A response to an MCP approval request.", "title": "MCP approval response" }, "OpenAI.ItemResourceMcpListTools": { "type": "object", "required": [ "type", "id", "server_label", "tools" ], "properties": { "type": { "type": "string", "enum": [ "mcp_list_tools" ], "description": "The type of the item. Always `mcp_list_tools`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the list." }, "server_label": { "type": "string", "description": "The label of the MCP server." }, "tools": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.MCPListToolsTool" }, "description": "The tools available on the server." }, "error": { "type": "string", "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemResource" } ], "description": "A list of tools available on an MCP server.", "title": "MCP list tools" }, "OpenAI.ItemResourceMcpToolCall": { "type": "object", "required": [ "type", "id", "server_label", "name", "arguments" ], "properties": { "type": { "type": "string", "enum": [ "mcp_call" ], "description": "The type of the item. Always `mcp_call`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the tool call." }, "server_label": { "type": "string", "description": "The label of the MCP server running the tool." }, "name": { "type": "string", "description": "The name of the tool that was run." }, "arguments": { "type": "string", "description": "A JSON string of the arguments passed to the tool." }, "output": { "type": "string", "nullable": true }, "error": { "type": "object", "additionalProperties": {} }, "status": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.MCPToolCallStatus" } ], "description": "The status of the tool call. One of `in_progress`, `completed`, `incomplete`, `calling`, or `failed`." }, "approval_request_id": { "type": "string", "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemResource" } ], "description": "An invocation of a tool on an MCP server.", "title": "MCP tool call" }, "OpenAI.ItemResourceOutputMessage": { "type": "object", "required": [ "id", "type", "role", "content", "status" ], "properties": { "id": { "type": "string", "description": "The unique ID of the output message." }, "type": { "type": "string", "enum": [ "output_message" ], "description": "The type of the output message. Always `message`.", "x-stainless-const": true }, "role": { "type": "string", "enum": [ "assistant" ], "description": "The role of the output message. Always `assistant`.", "x-stainless-const": true }, "content": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.OutputMessageContent" }, "description": "The content of the output message." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "description": "The status of the message input. One of `in_progress`, `completed`, or\n `incomplete`. Populated when input items are returned via API." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemResource" } ], "description": "An output message from the model.", "title": "Output message" }, "OpenAI.ItemResourceType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "message", "output_message", "file_search_call", "computer_call", "computer_call_output", "web_search_call", "function_call", "function_call_output", "image_generation_call", "code_interpreter_call", "local_shell_call", "local_shell_call_output", "shell_call", "shell_call_output", "apply_patch_call", "apply_patch_call_output", "mcp_list_tools", "mcp_approval_request", "mcp_approval_response", "mcp_call", "structured_outputs", "oauth_consent_request", "memory_search_call", "workflow_action", "a2a_preview_call", "a2a_preview_call_output", "bing_grounding_call", "bing_grounding_call_output", "sharepoint_grounding_preview_call", "sharepoint_grounding_preview_call_output", "azure_ai_search_call", "azure_ai_search_call_output", "bing_custom_search_preview_call", "bing_custom_search_preview_call_output", "openapi_call", "openapi_call_output", "browser_automation_preview_call", "browser_automation_preview_call_output", "fabric_dataagent_preview_call", "fabric_dataagent_preview_call_output", "azure_function_call", "azure_function_call_output" ] } ] }, "OpenAI.ItemResourceWebSearchToolCall": { "type": "object", "required": [ "id", "type", "status", "action" ], "properties": { "id": { "type": "string", "description": "The unique ID of the web search tool call." }, "type": { "type": "string", "enum": [ "web_search_call" ], "description": "The type of the web search tool call. Always `web_search_call`.", "x-stainless-const": true }, "status": { "type": "string", "enum": [ "in_progress", "searching", "completed", "failed" ], "description": "The status of the web search tool call." }, "action": { "oneOf": [ { "$ref": "#/components/schemas/OpenAI.WebSearchActionSearch" }, { "$ref": "#/components/schemas/OpenAI.WebSearchActionOpenPage" }, { "$ref": "#/components/schemas/OpenAI.WebSearchActionFind" } ], "description": "An object describing the specific action taken in this web search call.\n Includes details on how the model used the web (search, open_page, find_in_page)." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ItemResource" } ], "description": "The results of a web search tool call. See the\n[web search guide](/docs/guides/tools-web-search) for more information.", "title": "Web search tool call" }, "OpenAI.ItemType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "message", "output_message", "file_search_call", "computer_call", "computer_call_output", "web_search_call", "function_call", "function_call_output", "reasoning", "compaction", "image_generation_call", "code_interpreter_call", "local_shell_call", "local_shell_call_output", "shell_call", "shell_call_output", "apply_patch_call", "apply_patch_call_output", "mcp_list_tools", "mcp_approval_request", "mcp_approval_response", "mcp_call", "custom_tool_call_output", "custom_tool_call", "structured_outputs", "oauth_consent_request", "memory_search_call", "workflow_action", "a2a_preview_call", "a2a_preview_call_output", "bing_grounding_call", "bing_grounding_call_output", "sharepoint_grounding_preview_call", "sharepoint_grounding_preview_call_output", "azure_ai_search_call", "azure_ai_search_call_output", "bing_custom_search_preview_call", "bing_custom_search_preview_call_output", "openapi_call", "openapi_call_output", "browser_automation_preview_call", "browser_automation_preview_call_output", "fabric_dataagent_preview_call", "fabric_dataagent_preview_call_output", "azure_function_call", "azure_function_call_output" ] } ] }, "OpenAI.ItemWebSearchToolCall": { "type": "object", "required": [ "id", "type", "status", "action" ], "properties": { "id": { "type": "string", "description": "The unique ID of the web search tool call." }, "type": { "type": "string", "enum": [ "web_search_call" ], "description": "The type of the web search tool call. Always `web_search_call`.", "x-stainless-const": true }, "status": { "type": "string", "enum": [ "in_progress", "searching", "completed", "failed" ], "description": "The status of the web search tool call." }, "action": { "oneOf": [ { "$ref": "#/components/schemas/OpenAI.WebSearchActionSearch" }, { "$ref": "#/components/schemas/OpenAI.WebSearchActionOpenPage" }, { "$ref": "#/components/schemas/OpenAI.WebSearchActionFind" } ], "description": "An object describing the specific action taken in this web search call.\n Includes details on how the model used the web (search, open_page, find_in_page)." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Item" } ], "description": "The results of a web search tool call. See the\n[web search guide](/docs/guides/tools-web-search) for more information.", "title": "Web search tool call" }, "OpenAI.KeyPressAction": { "type": "object", "required": [ "type", "keys" ], "properties": { "type": { "type": "string", "enum": [ "keypress" ], "description": "Specifies the event type. For a keypress action, this property is always set to `keypress`.", "x-stainless-const": true, "default": "keypress" }, "keys": { "type": "array", "items": { "type": "string" }, "description": "The combination of keys the model is requesting to be pressed. This is an array of strings, each representing a key." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ComputerAction" } ], "description": "A collection of keypresses the model would like to perform.", "title": "KeyPress" }, "OpenAI.ListFineTuningJobCheckpointsResponse": { "type": "object", "required": [ "data", "object", "has_more" ], "properties": { "data": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.FineTuningJobCheckpoint" }, "x-ms-list-page-items": true }, "object": { "type": "string", "enum": [ "list" ], "x-stainless-const": true }, "first_id": { "type": "string", "nullable": true }, "last_id": { "type": "string", "nullable": true, "x-ms-list-continuation-token": true }, "has_more": { "type": "boolean" } } }, "OpenAI.ListFineTuningJobEventsResponse": { "type": "object", "required": [ "data", "object", "has_more" ], "properties": { "data": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.FineTuningJobEvent" }, "x-ms-list-page-items": true }, "object": { "type": "string", "enum": [ "list" ], "x-stainless-const": true }, "has_more": { "type": "boolean" } } }, "OpenAI.ListPaginatedFineTuningJobsResponse": { "type": "object", "required": [ "data", "has_more", "object" ], "properties": { "data": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.FineTuningJob" }, "x-ms-list-page-items": true }, "has_more": { "type": "boolean" }, "object": { "type": "string", "enum": [ "list" ], "x-stainless-const": true } } }, "OpenAI.LocalEnvironmentResource": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "local" ], "description": "The environment type. Always `local`.", "x-stainless-const": true, "default": "local" } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.FunctionShellCallEnvironment" } ], "description": "Represents the use of a local environment to perform shell actions.", "title": "Local Environment" }, "OpenAI.LocalShellCallOutputStatusEnum": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ] }, "OpenAI.LocalShellCallStatus": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ] }, "OpenAI.LocalShellExecAction": { "type": "object", "required": [ "type", "command", "env" ], "properties": { "type": { "type": "string", "enum": [ "exec" ], "description": "The type of the local shell action. Always `exec`.", "x-stainless-const": true, "default": "exec" }, "command": { "type": "array", "items": { "type": "string" }, "description": "The command to run." }, "timeout_ms": { "type": "integer", "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "nullable": true }, "working_directory": { "type": "string", "nullable": true }, "env": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Environment variables to set for the command.", "x-oaiTypeLabel": "map" }, "user": { "type": "string", "nullable": true } }, "description": "Execute a shell command on the server.", "title": "Local shell exec action" }, "OpenAI.LocalShellToolParam": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "local_shell" ], "description": "The type of the local shell tool. Always `local_shell`.", "x-stainless-const": true, "default": "local_shell" }, "name": { "type": "string", "description": "Optional user-defined name for this tool or configuration." }, "description": { "type": "string", "description": "Optional user-defined description for this tool or configuration." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Tool" } ], "description": "A tool that allows the model to execute shell commands in a local environment.", "title": "Local shell tool" }, "OpenAI.LocalSkillParam": { "type": "object", "required": [ "name", "description", "path" ], "properties": { "name": { "type": "string", "description": "The name of the skill." }, "description": { "type": "string", "description": "The description of the skill." }, "path": { "type": "string", "description": "The path to the directory containing the skill." } } }, "OpenAI.LogProb": { "type": "object", "required": [ "token", "logprob", "bytes", "top_logprobs" ], "properties": { "token": { "type": "string" }, "logprob": { "$ref": "#/components/schemas/OpenAI.numeric" }, "bytes": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.integer" } }, "top_logprobs": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.TopLogProb" } } }, "description": "The log probability of a token.", "title": "Log probability" }, "OpenAI.MCPListToolsTool": { "type": "object", "required": [ "name", "input_schema" ], "properties": { "name": { "type": "string", "description": "The name of the tool." }, "description": { "type": "string", "nullable": true }, "input_schema": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.MCPListToolsToolInputSchema" } ], "description": "The JSON schema describing the tool's input." }, "annotations": { "type": "object", "allOf": [ { "$ref": "#/components/schemas/OpenAI.MCPListToolsToolAnnotations" } ], "nullable": true } }, "description": "A tool available on an MCP server.", "title": "MCP list tools tool" }, "OpenAI.MCPListToolsToolAnnotations": { "type": "object" }, "OpenAI.MCPListToolsToolInputSchema": { "type": "object" }, "OpenAI.MCPTool": { "type": "object", "required": [ "type", "server_label" ], "properties": { "type": { "type": "string", "enum": [ "mcp" ], "description": "The type of the MCP tool. Always `mcp`.", "x-stainless-const": true }, "server_label": { "type": "string", "description": "A label for this MCP server, used to identify it in tool calls." }, "server_url": { "type": "string", "format": "uri", "description": "The URL for the MCP server. One of `server_url` or `connector_id` must be\n provided." }, "connector_id": { "type": "string", "enum": [ "connector_dropbox", "connector_gmail", "connector_googlecalendar", "connector_googledrive", "connector_microsoftteams", "connector_outlookcalendar", "connector_outlookemail", "connector_sharepoint" ], "description": "Identifier for service connectors, like those available in ChatGPT. One of\n `server_url` or `connector_id` must be provided. Learn more about service\n connectors [here](/docs/guides/tools-remote-mcp#connectors).\n Currently supported `connector_id` values are:\n - Dropbox: `connector_dropbox`\n - Gmail: `connector_gmail`\n - Google Calendar: `connector_googlecalendar`\n - Google Drive: `connector_googledrive`\n - Microsoft Teams: `connector_microsoftteams`\n - Outlook Calendar: `connector_outlookcalendar`\n - Outlook Email: `connector_outlookemail`\n - SharePoint: `connector_sharepoint`" }, "authorization": { "type": "string", "description": "An OAuth access token that can be used with a remote MCP server, either\n with a custom MCP server URL or a service connector. Your application\n must handle the OAuth authorization flow and provide the token here." }, "server_description": { "type": "string", "description": "Optional description of the MCP server, used to provide more context." }, "headers": { "type": "object", "additionalProperties": { "type": "string" }, "nullable": true }, "allowed_tools": { "anyOf": [ { "type": "array", "items": { "type": "string" }, "nullable": true }, { "type": "object", "allOf": [ { "$ref": "#/components/schemas/OpenAI.MCPToolFilter" } ], "nullable": true } ] }, "require_approval": { "anyOf": [ { "type": "object", "allOf": [ { "$ref": "#/components/schemas/OpenAI.MCPToolRequireApproval" } ], "nullable": true }, { "type": "string", "enum": [ "always", "never" ], "nullable": true } ], "default": "always" }, "project_connection_id": { "type": "string", "description": "The connection ID in the project for the MCP server. The connection stores authentication and other connection details needed to connect to the MCP server." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Tool" } ], "description": "Give the model access to additional tools via remote Model Context Protocol\n(MCP) servers. [Learn more about MCP](/docs/guides/tools-remote-mcp).", "title": "MCP tool" }, "OpenAI.MCPToolCallStatus": { "type": "string", "enum": [ "in_progress", "completed", "incomplete", "calling", "failed" ] }, "OpenAI.MCPToolFilter": { "type": "object", "properties": { "tool_names": { "type": "array", "items": { "type": "string" }, "description": "List of allowed tool names.", "title": "MCP allowed tools" }, "read_only": { "type": "boolean", "description": "Indicates whether or not a tool modifies data or is read-only. If an\n MCP server is [annotated with `readOnlyHint`](https://modelcontextprotocol.io/specification/2025-06-18/schema#toolannotations-readonlyhint),\n it will match this filter." } }, "description": "A filter object to specify which tools are allowed.", "title": "MCP tool filter" }, "OpenAI.MCPToolRequireApproval": { "type": "object", "properties": { "always": { "$ref": "#/components/schemas/OpenAI.MCPToolFilter" }, "never": { "$ref": "#/components/schemas/OpenAI.MCPToolFilter" } } }, "OpenAI.MessageContent": { "type": "object", "required": [ "type" ], "properties": { "type": { "$ref": "#/components/schemas/OpenAI.MessageContentType" } }, "discriminator": { "propertyName": "type", "mapping": { "text": "#/components/schemas/OpenAI.TextContent", "computer_screenshot": "#/components/schemas/OpenAI.ComputerScreenshotContent", "input_text": "#/components/schemas/OpenAI.MessageContentInputTextContent", "output_text": "#/components/schemas/OpenAI.MessageContentOutputTextContent", "reasoning_text": "#/components/schemas/OpenAI.MessageContentReasoningTextContent", "refusal": "#/components/schemas/OpenAI.MessageContentRefusalContent", "input_image": "#/components/schemas/OpenAI.MessageContentInputImageContent", "input_file": "#/components/schemas/OpenAI.MessageContentInputFileContent" } }, "description": "A content part that makes up an input or output item." }, "OpenAI.MessageContentInputFileContent": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "input_file" ], "description": "The type of the input item. Always `input_file`.", "x-stainless-const": true, "default": "input_file" }, "file_id": { "type": "string", "nullable": true }, "filename": { "type": "string", "description": "The name of the file to be sent to the model." }, "file_url": { "type": "string", "format": "uri", "description": "The URL of the file to be sent to the model." }, "file_data": { "type": "string", "description": "The content of the file to be sent to the model." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.MessageContent" } ], "description": "A file input to the model.", "title": "Input file" }, "OpenAI.MessageContentInputImageContent": { "type": "object", "required": [ "type", "detail" ], "properties": { "type": { "type": "string", "enum": [ "input_image" ], "description": "The type of the input item. Always `input_image`.", "x-stainless-const": true, "default": "input_image" }, "image_url": { "type": "string", "format": "uri", "nullable": true }, "file_id": { "type": "string", "nullable": true }, "detail": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ImageDetail" } ], "description": "The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.MessageContent" } ], "description": "An image input to the model. Learn about [image inputs](/docs/guides/vision).", "title": "Input image" }, "OpenAI.MessageContentInputTextContent": { "type": "object", "required": [ "type", "text" ], "properties": { "type": { "type": "string", "enum": [ "input_text" ], "description": "The type of the input item. Always `input_text`.", "x-stainless-const": true, "default": "input_text" }, "text": { "type": "string", "description": "The text input to the model." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.MessageContent" } ], "description": "A text input to the model.", "title": "Input text" }, "OpenAI.MessageContentOutputTextContent": { "type": "object", "required": [ "type", "text", "annotations", "logprobs" ], "properties": { "type": { "type": "string", "enum": [ "output_text" ], "description": "The type of the output text. Always `output_text`.", "x-stainless-const": true, "default": "output_text" }, "text": { "type": "string", "description": "The text output from the model." }, "annotations": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.Annotation" }, "description": "The annotations of the text output." }, "logprobs": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.LogProb" } } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.MessageContent" } ], "description": "A text output from the model.", "title": "Output text" }, "OpenAI.MessageContentReasoningTextContent": { "type": "object", "required": [ "type", "text" ], "properties": { "type": { "type": "string", "enum": [ "reasoning_text" ], "description": "The type of the reasoning text. Always `reasoning_text`.", "x-stainless-const": true, "default": "reasoning_text" }, "text": { "type": "string", "description": "The reasoning text from the model." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.MessageContent" } ], "description": "Reasoning text from the model.", "title": "Reasoning text" }, "OpenAI.MessageContentRefusalContent": { "type": "object", "required": [ "type", "refusal" ], "properties": { "type": { "type": "string", "enum": [ "refusal" ], "description": "The type of the refusal. Always `refusal`.", "x-stainless-const": true, "default": "refusal" }, "refusal": { "type": "string", "description": "The refusal explanation from the model." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.MessageContent" } ], "description": "A refusal from the model.", "title": "Refusal" }, "OpenAI.MessageContentType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "input_text", "output_text", "text", "summary_text", "reasoning_text", "refusal", "input_image", "computer_screenshot", "input_file" ] } ] }, "OpenAI.MessageRole": { "type": "string", "enum": [ "unknown", "user", "assistant", "system", "critic", "discriminator", "developer", "tool" ] }, "OpenAI.MessageStatus": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ] }, "OpenAI.Metadata": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Set of 16 key-value pairs that can be attached to an object. This can be\nuseful for storing additional information about the object in a structured\nformat, and querying for objects via API or the dashboard.\nKeys are strings with a maximum length of 64 characters. Values are strings\nwith a maximum length of 512 characters.", "x-oaiTypeLabel": "map" }, "OpenAI.ModelIdsCompaction": { "anyOf": [ { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ModelIdsResponses" } ], "description": "Model ID used to generate the response, like `gpt-5` or `o3`. OpenAI offers a wide range of models with different capabilities, performance characteristics, and price points. Refer to the [model guide](/docs/models) to browse and compare available models.", "nullable": true }, { "type": "string", "description": "Model ID used to generate the response, like `gpt-5` or `o3`. OpenAI offers a wide range of models with different capabilities, performance characteristics, and price points. Refer to the [model guide](/docs/models) to browse and compare available models.", "nullable": true } ], "description": "Model ID used to generate the response, like `gpt-5` or `o3`. OpenAI offers a wide range of models with different capabilities, performance characteristics, and price points. Refer to the [model guide](/docs/models) to browse and compare available models." }, "OpenAI.ModelIdsResponses": { "anyOf": [ { "$ref": "#/components/schemas/OpenAI.ModelIdsShared" }, { "type": "string", "enum": [ "o1-pro", "o1-pro-2025-03-19", "o3-pro", "o3-pro-2025-06-10", "o3-deep-research", "o3-deep-research-2025-06-26", "o4-mini-deep-research", "o4-mini-deep-research-2025-06-26", "computer-use-preview", "computer-use-preview-2025-03-11", "gpt-5-codex", "gpt-5-pro", "gpt-5-pro-2025-10-06", "gpt-5.1-codex-max" ] } ] }, "OpenAI.ModelIdsShared": { "anyOf": [ { "type": "string" }, { "$ref": "#/components/schemas/OpenAI.ChatModel" } ] }, "OpenAI.MoveParam": { "type": "object", "required": [ "type", "x", "y" ], "properties": { "type": { "type": "string", "enum": [ "move" ], "description": "Specifies the event type. For a move action, this property is always set to `move`.", "x-stainless-const": true, "default": "move" }, "x": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The x-coordinate to move to." }, "y": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The y-coordinate to move to." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ComputerAction" } ], "description": "A mouse move action.", "title": "Move" }, "OpenAI.OutputContent": { "type": "object", "required": [ "type" ], "properties": { "type": { "$ref": "#/components/schemas/OpenAI.OutputContentType" } }, "discriminator": { "propertyName": "type", "mapping": { "output_text": "#/components/schemas/OpenAI.OutputContentOutputTextContent", "refusal": "#/components/schemas/OpenAI.OutputContentRefusalContent", "reasoning_text": "#/components/schemas/OpenAI.OutputContentReasoningTextContent" } } }, "OpenAI.OutputContentOutputTextContent": { "type": "object", "required": [ "type", "text", "annotations", "logprobs" ], "properties": { "type": { "type": "string", "enum": [ "output_text" ], "description": "The type of the output text. Always `output_text`.", "x-stainless-const": true, "default": "output_text" }, "text": { "type": "string", "description": "The text output from the model." }, "annotations": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.Annotation" }, "description": "The annotations of the text output." }, "logprobs": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.LogProb" } } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputContent" } ], "description": "A text output from the model.", "title": "Output text" }, "OpenAI.OutputContentReasoningTextContent": { "type": "object", "required": [ "type", "text" ], "properties": { "type": { "type": "string", "enum": [ "reasoning_text" ], "description": "The type of the reasoning text. Always `reasoning_text`.", "x-stainless-const": true, "default": "reasoning_text" }, "text": { "type": "string", "description": "The reasoning text from the model." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputContent" } ], "description": "Reasoning text from the model.", "title": "Reasoning text" }, "OpenAI.OutputContentRefusalContent": { "type": "object", "required": [ "type", "refusal" ], "properties": { "type": { "type": "string", "enum": [ "refusal" ], "description": "The type of the refusal. Always `refusal`.", "x-stainless-const": true, "default": "refusal" }, "refusal": { "type": "string", "description": "The refusal explanation from the model." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputContent" } ], "description": "A refusal from the model.", "title": "Refusal" }, "OpenAI.OutputContentType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "output_text", "refusal", "reasoning_text" ] } ] }, "OpenAI.OutputItem": { "type": "object", "required": [ "type" ], "properties": { "type": { "$ref": "#/components/schemas/OpenAI.OutputItemType" }, "agent_reference": { "allOf": [ { "$ref": "#/components/schemas/AgentReference" } ], "description": "The agent that created the item." }, "response_id": { "type": "string", "description": "The response on which the item is created." } }, "discriminator": { "propertyName": "type", "mapping": { "structured_outputs": "#/components/schemas/StructuredOutputsOutputItem", "workflow_action": "#/components/schemas/WorkflowActionOutputItem", "oauth_consent_request": "#/components/schemas/OAuthConsentRequestOutputItem", "memory_search_call": "#/components/schemas/MemorySearchToolCallItemResource", "bing_grounding_call": "#/components/schemas/BingGroundingToolCall", "bing_grounding_call_output": "#/components/schemas/BingGroundingToolCallOutput", "sharepoint_grounding_preview_call": "#/components/schemas/SharepointGroundingToolCall", "sharepoint_grounding_preview_call_output": "#/components/schemas/SharepointGroundingToolCallOutput", "azure_ai_search_call": "#/components/schemas/AzureAISearchToolCall", "azure_ai_search_call_output": "#/components/schemas/AzureAISearchToolCallOutput", "bing_custom_search_preview_call": "#/components/schemas/BingCustomSearchToolCall", "bing_custom_search_preview_call_output": "#/components/schemas/BingCustomSearchToolCallOutput", "openapi_call": "#/components/schemas/OpenApiToolCall", "openapi_call_output": "#/components/schemas/OpenApiToolCallOutput", "browser_automation_preview_call": "#/components/schemas/BrowserAutomationToolCall", "browser_automation_preview_call_output": "#/components/schemas/BrowserAutomationToolCallOutput", "fabric_dataagent_preview_call": "#/components/schemas/FabricDataAgentToolCall", "fabric_dataagent_preview_call_output": "#/components/schemas/FabricDataAgentToolCallOutput", "azure_function_call": "#/components/schemas/AzureFunctionToolCall", "azure_function_call_output": "#/components/schemas/AzureFunctionToolCallOutput", "a2a_preview_call": "#/components/schemas/A2AToolCall", "a2a_preview_call_output": "#/components/schemas/A2AToolCallOutput", "output_message": "#/components/schemas/OpenAI.OutputItemOutputMessage", "file_search_call": "#/components/schemas/OpenAI.OutputItemFileSearchToolCall", "function_call": "#/components/schemas/OpenAI.OutputItemFunctionToolCall", "web_search_call": "#/components/schemas/OpenAI.OutputItemWebSearchToolCall", "computer_call": "#/components/schemas/OpenAI.OutputItemComputerToolCall", "reasoning": "#/components/schemas/OpenAI.OutputItemReasoningItem", "compaction": "#/components/schemas/OpenAI.OutputItemCompactionBody", "image_generation_call": "#/components/schemas/OpenAI.OutputItemImageGenToolCall", "code_interpreter_call": "#/components/schemas/OpenAI.OutputItemCodeInterpreterToolCall", "local_shell_call": "#/components/schemas/OpenAI.OutputItemLocalShellToolCall", "shell_call": "#/components/schemas/OpenAI.OutputItemFunctionShellCall", "shell_call_output": "#/components/schemas/OpenAI.OutputItemFunctionShellCallOutput", "apply_patch_call": "#/components/schemas/OpenAI.OutputItemApplyPatchToolCall", "apply_patch_call_output": "#/components/schemas/OpenAI.OutputItemApplyPatchToolCallOutput", "mcp_call": "#/components/schemas/OpenAI.OutputItemMcpToolCall", "mcp_list_tools": "#/components/schemas/OpenAI.OutputItemMcpListTools", "mcp_approval_request": "#/components/schemas/OpenAI.OutputItemMcpApprovalRequest", "custom_tool_call": "#/components/schemas/OpenAI.OutputItemCustomToolCall" } } }, "OpenAI.OutputItemApplyPatchToolCall": { "type": "object", "required": [ "type", "id", "call_id", "status", "operation" ], "properties": { "type": { "type": "string", "enum": [ "apply_patch_call" ], "description": "The type of the item. Always `apply_patch_call`.", "x-stainless-const": true, "default": "apply_patch_call" }, "id": { "type": "string", "description": "The unique ID of the apply patch tool call. Populated when this item is returned via API." }, "call_id": { "type": "string", "description": "The unique ID of the apply patch tool call generated by the model." }, "status": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ApplyPatchCallStatus" } ], "description": "The status of the apply patch tool call. One of `in_progress` or `completed`." }, "operation": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ApplyPatchFileOperation" } ], "description": "One of the create_file, delete_file, or update_file operations applied via apply_patch.", "title": "Apply patch operation" }, "created_by": { "type": "string", "description": "The ID of the entity that created this tool call." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ], "description": "A tool call that applies file diffs by creating, deleting, or updating files.", "title": "Apply patch tool call" }, "OpenAI.OutputItemApplyPatchToolCallOutput": { "type": "object", "required": [ "type", "id", "call_id", "status" ], "properties": { "type": { "type": "string", "enum": [ "apply_patch_call_output" ], "description": "The type of the item. Always `apply_patch_call_output`.", "x-stainless-const": true, "default": "apply_patch_call_output" }, "id": { "type": "string", "description": "The unique ID of the apply patch tool call output. Populated when this item is returned via API." }, "call_id": { "type": "string", "description": "The unique ID of the apply patch tool call generated by the model." }, "status": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ApplyPatchCallOutputStatus" } ], "description": "The status of the apply patch tool call output. One of `completed` or `failed`." }, "output": { "type": "string", "nullable": true }, "created_by": { "type": "string", "description": "The ID of the entity that created this tool call output." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ], "description": "The output emitted by an apply patch tool call.", "title": "Apply patch tool call output" }, "OpenAI.OutputItemCodeInterpreterToolCall": { "type": "object", "required": [ "type", "id", "status", "container_id", "code", "outputs" ], "properties": { "type": { "type": "string", "enum": [ "code_interpreter_call" ], "description": "The type of the code interpreter tool call. Always `code_interpreter_call`.", "x-stainless-const": true, "default": "code_interpreter_call" }, "id": { "type": "string", "description": "The unique ID of the code interpreter tool call." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete", "interpreting", "failed" ], "description": "The status of the code interpreter tool call. Valid values are `in_progress`, `completed`, `incomplete`, `interpreting`, and `failed`." }, "container_id": { "type": "string", "description": "The ID of the container used to run the code." }, "code": { "type": "string", "nullable": true }, "outputs": { "type": "array", "items": { "anyOf": [ { "$ref": "#/components/schemas/OpenAI.CodeInterpreterOutputLogs" }, { "$ref": "#/components/schemas/OpenAI.CodeInterpreterOutputImage" } ] }, "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ], "description": "A tool call to run code.", "title": "Code interpreter tool call" }, "OpenAI.OutputItemCompactionBody": { "type": "object", "required": [ "type", "id", "encrypted_content" ], "properties": { "type": { "type": "string", "enum": [ "compaction" ], "description": "The type of the item. Always `compaction`.", "x-stainless-const": true, "default": "compaction" }, "id": { "type": "string", "description": "The unique ID of the compaction item." }, "encrypted_content": { "type": "string", "description": "The encrypted content that was produced by compaction." }, "created_by": { "type": "string", "description": "The identifier of the actor that created the item." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ], "description": "A compaction item generated by the [`v1/responses/compact` API](/docs/api-reference/responses/compact).", "title": "Compaction item" }, "OpenAI.OutputItemComputerToolCall": { "type": "object", "required": [ "type", "id", "call_id", "action", "pending_safety_checks", "status" ], "properties": { "type": { "type": "string", "enum": [ "computer_call" ], "description": "The type of the computer call. Always `computer_call`.", "default": "computer_call" }, "id": { "type": "string", "description": "The unique ID of the computer call." }, "call_id": { "type": "string", "description": "An identifier used when responding to the tool call with output." }, "action": { "$ref": "#/components/schemas/OpenAI.ComputerAction" }, "pending_safety_checks": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.ComputerCallSafetyCheckParam" }, "description": "The pending safety checks for the computer call." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "description": "The status of the item. One of `in_progress`, `completed`, or\n `incomplete`. Populated when items are returned via API." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ], "description": "A tool call to a computer use tool. See the\n[computer use guide](/docs/guides/tools-computer-use) for more information.", "title": "Computer tool call" }, "OpenAI.OutputItemCustomToolCall": { "type": "object", "required": [ "type", "call_id", "name", "input" ], "properties": { "type": { "type": "string", "enum": [ "custom_tool_call" ], "description": "The type of the custom tool call. Always `custom_tool_call`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the custom tool call in the OpenAI platform." }, "call_id": { "type": "string", "description": "An identifier used to map this custom tool call to a tool call output." }, "name": { "type": "string", "description": "The name of the custom tool being called." }, "input": { "type": "string", "description": "The input for the custom tool call generated by the model." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ], "description": "A call to a custom tool created by the model.", "title": "Custom tool call" }, "OpenAI.OutputItemFileSearchToolCall": { "type": "object", "required": [ "id", "type", "status", "queries" ], "properties": { "id": { "type": "string", "description": "The unique ID of the file search tool call." }, "type": { "type": "string", "enum": [ "file_search_call" ], "description": "The type of the file search tool call. Always `file_search_call`.", "x-stainless-const": true }, "status": { "type": "string", "enum": [ "in_progress", "searching", "completed", "incomplete", "failed" ], "description": "The status of the file search tool call. One of `in_progress`,\n `searching`, `incomplete` or `failed`," }, "queries": { "type": "array", "items": { "type": "string" }, "description": "The queries used to search for files." }, "results": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.FileSearchToolCallResults" }, "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ], "description": "The results of a file search tool call. See the\n[file search guide](/docs/guides/tools-file-search) for more information.", "title": "File search tool call" }, "OpenAI.OutputItemFunctionShellCall": { "type": "object", "required": [ "type", "id", "call_id", "action", "status", "environment" ], "properties": { "type": { "type": "string", "enum": [ "shell_call" ], "description": "The type of the item. Always `shell_call`.", "x-stainless-const": true, "default": "shell_call" }, "id": { "type": "string", "description": "The unique ID of the shell tool call. Populated when this item is returned via API." }, "call_id": { "type": "string", "description": "The unique ID of the shell tool call generated by the model." }, "action": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.FunctionShellAction" } ], "description": "The shell commands and limits that describe how to run the tool call." }, "status": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.LocalShellCallStatus" } ], "description": "The status of the shell call. One of `in_progress`, `completed`, or `incomplete`." }, "environment": { "type": "object", "allOf": [ { "$ref": "#/components/schemas/OpenAI.FunctionShellCallEnvironment" } ], "nullable": true }, "created_by": { "type": "string", "description": "The ID of the entity that created this tool call." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ], "description": "A tool call that executes one or more shell commands in a managed environment.", "title": "Shell tool call" }, "OpenAI.OutputItemFunctionShellCallOutput": { "type": "object", "required": [ "type", "id", "call_id", "status", "output", "max_output_length" ], "properties": { "type": { "type": "string", "enum": [ "shell_call_output" ], "description": "The type of the shell call output. Always `shell_call_output`.", "x-stainless-const": true, "default": "shell_call_output" }, "id": { "type": "string", "description": "The unique ID of the shell call output. Populated when this item is returned via API." }, "call_id": { "type": "string", "description": "The unique ID of the shell tool call generated by the model." }, "status": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.LocalShellCallOutputStatusEnum" } ], "description": "The status of the shell call output. One of `in_progress`, `completed`, or `incomplete`." }, "output": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.FunctionShellCallOutputContent" }, "description": "An array of shell call output contents" }, "max_output_length": { "type": "integer", "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "nullable": true }, "created_by": { "type": "string", "description": "The identifier of the actor that created the item." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ], "description": "The output of a shell tool call that was emitted.", "title": "Shell call output" }, "OpenAI.OutputItemFunctionToolCall": { "type": "object", "required": [ "type", "call_id", "name", "arguments" ], "properties": { "id": { "type": "string", "description": "The unique ID of the function tool call." }, "type": { "type": "string", "enum": [ "function_call" ], "description": "The type of the function tool call. Always `function_call`.", "x-stainless-const": true }, "call_id": { "type": "string", "description": "The unique ID of the function tool call generated by the model." }, "name": { "type": "string", "description": "The name of the function to run." }, "arguments": { "type": "string", "description": "A JSON string of the arguments to pass to the function." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "description": "The status of the item. One of `in_progress`, `completed`, or\n `incomplete`. Populated when items are returned via API." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ], "description": "A tool call to run a function. See the\n[function calling guide](/docs/guides/function-calling) for more information.", "title": "Function tool call" }, "OpenAI.OutputItemImageGenToolCall": { "type": "object", "required": [ "type", "id", "status", "result" ], "properties": { "type": { "type": "string", "enum": [ "image_generation_call" ], "description": "The type of the image generation call. Always `image_generation_call`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the image generation call." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "generating", "failed" ], "description": "The status of the image generation call." }, "result": { "type": "string", "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ], "description": "An image generation request made by the model.", "title": "Image generation call" }, "OpenAI.OutputItemLocalShellToolCall": { "type": "object", "required": [ "type", "id", "call_id", "action", "status" ], "properties": { "type": { "type": "string", "enum": [ "local_shell_call" ], "description": "The type of the local shell call. Always `local_shell_call`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the local shell call." }, "call_id": { "type": "string", "description": "The unique ID of the local shell tool call generated by the model." }, "action": { "$ref": "#/components/schemas/OpenAI.LocalShellExecAction" }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "description": "The status of the local shell call." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ], "description": "A tool call to run a command on the local shell.", "title": "Local shell call" }, "OpenAI.OutputItemMcpApprovalRequest": { "type": "object", "required": [ "type", "id", "server_label", "name", "arguments" ], "properties": { "type": { "type": "string", "enum": [ "mcp_approval_request" ], "description": "The type of the item. Always `mcp_approval_request`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the approval request." }, "server_label": { "type": "string", "description": "The label of the MCP server making the request." }, "name": { "type": "string", "description": "The name of the tool to run." }, "arguments": { "type": "string", "description": "A JSON string of arguments for the tool." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ], "description": "A request for human approval of a tool invocation.", "title": "MCP approval request" }, "OpenAI.OutputItemMcpListTools": { "type": "object", "required": [ "type", "id", "server_label", "tools" ], "properties": { "type": { "type": "string", "enum": [ "mcp_list_tools" ], "description": "The type of the item. Always `mcp_list_tools`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the list." }, "server_label": { "type": "string", "description": "The label of the MCP server." }, "tools": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.MCPListToolsTool" }, "description": "The tools available on the server." }, "error": { "type": "string", "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ], "description": "A list of tools available on an MCP server.", "title": "MCP list tools" }, "OpenAI.OutputItemMcpToolCall": { "type": "object", "required": [ "type", "id", "server_label", "name", "arguments" ], "properties": { "type": { "type": "string", "enum": [ "mcp_call" ], "description": "The type of the item. Always `mcp_call`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique ID of the tool call." }, "server_label": { "type": "string", "description": "The label of the MCP server running the tool." }, "name": { "type": "string", "description": "The name of the tool that was run." }, "arguments": { "type": "string", "description": "A JSON string of the arguments passed to the tool." }, "output": { "type": "string", "nullable": true }, "error": { "type": "object", "additionalProperties": {} }, "status": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.MCPToolCallStatus" } ], "description": "The status of the tool call. One of `in_progress`, `completed`, `incomplete`, `calling`, or `failed`." }, "approval_request_id": { "type": "string", "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ], "description": "An invocation of a tool on an MCP server.", "title": "MCP tool call" }, "OpenAI.OutputItemOutputMessage": { "type": "object", "required": [ "id", "type", "role", "content", "status" ], "properties": { "id": { "type": "string", "description": "The unique ID of the output message." }, "type": { "type": "string", "enum": [ "output_message" ], "description": "The type of the output message. Always `message`.", "x-stainless-const": true }, "role": { "type": "string", "enum": [ "assistant" ], "description": "The role of the output message. Always `assistant`.", "x-stainless-const": true }, "content": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.OutputMessageContent" }, "description": "The content of the output message." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "description": "The status of the message input. One of `in_progress`, `completed`, or\n `incomplete`. Populated when input items are returned via API." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ], "description": "An output message from the model.", "title": "Output message" }, "OpenAI.OutputItemReasoningItem": { "type": "object", "required": [ "type", "id", "summary" ], "properties": { "type": { "type": "string", "enum": [ "reasoning" ], "description": "The type of the object. Always `reasoning`.", "x-stainless-const": true }, "id": { "type": "string", "description": "The unique identifier of the reasoning content." }, "encrypted_content": { "type": "string", "nullable": true }, "summary": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.SummaryTextContent" }, "description": "Reasoning summary content." }, "content": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.ReasoningTextContent" }, "description": "Reasoning text content." }, "status": { "type": "string", "enum": [ "in_progress", "completed", "incomplete" ], "description": "The status of the item. One of `in_progress`, `completed`, or\n `incomplete`. Populated when items are returned via API." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ], "description": "A description of the chain of thought used by a reasoning model while generating\na response. Be sure to include these items in your `input` to the Responses API\nfor subsequent turns of a conversation if you are manually\n[managing context](/docs/guides/conversation-state).", "title": "Reasoning" }, "OpenAI.OutputItemType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "output_message", "file_search_call", "function_call", "web_search_call", "computer_call", "reasoning", "compaction", "image_generation_call", "code_interpreter_call", "local_shell_call", "shell_call", "shell_call_output", "apply_patch_call", "apply_patch_call_output", "mcp_call", "mcp_list_tools", "mcp_approval_request", "custom_tool_call", "structured_outputs", "oauth_consent_request", "memory_search_call", "workflow_action", "a2a_preview_call", "a2a_preview_call_output", "bing_grounding_call", "bing_grounding_call_output", "sharepoint_grounding_preview_call", "sharepoint_grounding_preview_call_output", "azure_ai_search_call", "azure_ai_search_call_output", "bing_custom_search_preview_call", "bing_custom_search_preview_call_output", "openapi_call", "openapi_call_output", "browser_automation_preview_call", "browser_automation_preview_call_output", "fabric_dataagent_preview_call", "fabric_dataagent_preview_call_output", "azure_function_call", "azure_function_call_output" ] } ] }, "OpenAI.OutputItemWebSearchToolCall": { "type": "object", "required": [ "id", "type", "status", "action" ], "properties": { "id": { "type": "string", "description": "The unique ID of the web search tool call." }, "type": { "type": "string", "enum": [ "web_search_call" ], "description": "The type of the web search tool call. Always `web_search_call`.", "x-stainless-const": true }, "status": { "type": "string", "enum": [ "in_progress", "searching", "completed", "failed" ], "description": "The status of the web search tool call." }, "action": { "oneOf": [ { "$ref": "#/components/schemas/OpenAI.WebSearchActionSearch" }, { "$ref": "#/components/schemas/OpenAI.WebSearchActionOpenPage" }, { "$ref": "#/components/schemas/OpenAI.WebSearchActionFind" } ], "description": "An object describing the specific action taken in this web search call.\n Includes details on how the model used the web (search, open_page, find_in_page)." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ], "description": "The results of a web search tool call. See the\n[web search guide](/docs/guides/tools-web-search) for more information.", "title": "Web search tool call" }, "OpenAI.OutputMessageContent": { "type": "object", "required": [ "type" ], "properties": { "type": { "$ref": "#/components/schemas/OpenAI.OutputMessageContentType" } }, "discriminator": { "propertyName": "type", "mapping": { "output_text": "#/components/schemas/OpenAI.OutputMessageContentOutputTextContent", "refusal": "#/components/schemas/OpenAI.OutputMessageContentRefusalContent" } } }, "OpenAI.OutputMessageContentOutputTextContent": { "type": "object", "required": [ "type", "text", "annotations", "logprobs" ], "properties": { "type": { "type": "string", "enum": [ "output_text" ], "description": "The type of the output text. Always `output_text`.", "x-stainless-const": true, "default": "output_text" }, "text": { "type": "string", "description": "The text output from the model." }, "annotations": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.Annotation" }, "description": "The annotations of the text output." }, "logprobs": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.LogProb" } } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputMessageContent" } ], "description": "A text output from the model.", "title": "Output text" }, "OpenAI.OutputMessageContentRefusalContent": { "type": "object", "required": [ "type", "refusal" ], "properties": { "type": { "type": "string", "enum": [ "refusal" ], "description": "The type of the refusal. Always `refusal`.", "x-stainless-const": true, "default": "refusal" }, "refusal": { "type": "string", "description": "The refusal explanation from the model." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputMessageContent" } ], "description": "A refusal from the model.", "title": "Refusal" }, "OpenAI.OutputMessageContentType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "output_text", "refusal" ] } ] }, "OpenAI.Prompt": { "type": "object", "required": [ "id" ], "properties": { "id": { "type": "string", "description": "The unique identifier of the prompt template to use." }, "version": { "type": "string", "nullable": true }, "variables": { "type": "object", "allOf": [ { "$ref": "#/components/schemas/OpenAI.ResponsePromptVariables" } ], "nullable": true } }, "description": "Reference to a prompt template and its variables.\n[Learn more](/docs/guides/text?api-mode=responses#reusable-prompts)." }, "OpenAI.RankerVersionType": { "type": "string", "enum": [ "auto", "default-2024-11-15" ] }, "OpenAI.RankingOptions": { "type": "object", "properties": { "ranker": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.RankerVersionType" } ], "description": "The ranker to use for the file search." }, "score_threshold": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.numeric" } ], "description": "The score threshold for the file search, a number between 0 and 1. Numbers closer to 1 will attempt to return only the most relevant results, but may return fewer results." }, "hybrid_search": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.HybridSearchOptions" } ], "description": "Weights that control how reciprocal rank fusion balances semantic embedding matches versus sparse keyword matches when hybrid search is enabled." } } }, "OpenAI.Reasoning": { "type": "object", "properties": { "effort": { "$ref": "#/components/schemas/OpenAI.ReasoningEffort" }, "summary": { "type": "string", "enum": [ "auto", "concise", "detailed" ], "nullable": true }, "generate_summary": { "type": "string", "enum": [ "auto", "concise", "detailed" ], "nullable": true } }, "description": "**gpt-5 and o-series models only**\nConfiguration options for\n[reasoning models](https://platform.openai.com/docs/guides/reasoning).", "title": "Reasoning" }, "OpenAI.ReasoningEffort": { "type": "string", "enum": [ "none", "minimal", "low", "medium", "high", "xhigh" ], "description": "Constrains effort on reasoning for\n[reasoning models](https://platform.openai.com/docs/guides/reasoning).\nCurrently supported values are `none`, `minimal`, `low`, `medium`, `high`, and `xhigh`. Reducing\nreasoning effort can result in faster responses and fewer tokens used\non reasoning in a response.\n- `gpt-5.1` defaults to `none`, which does not perform reasoning. The supported reasoning values for `gpt-5.1` are `none`, `low`, `medium`, and `high`. Tool calls are supported for all reasoning values in gpt-5.1.\n- All models before `gpt-5.1` default to `medium` reasoning effort, and do not support `none`.\n- The `gpt-5-pro` model defaults to (and only supports) `high` reasoning effort.\n- `xhigh` is supported for all models after `gpt-5.1-codex-max`.", "nullable": true }, "OpenAI.ReasoningTextContent": { "type": "object", "required": [ "type", "text" ], "properties": { "type": { "type": "string", "enum": [ "reasoning_text" ], "description": "The type of the reasoning text. Always `reasoning_text`.", "x-stainless-const": true, "default": "reasoning_text" }, "text": { "type": "string", "description": "The reasoning text from the model." } }, "description": "Reasoning text from the model.", "title": "Reasoning text" }, "OpenAI.Response": { "type": "object", "required": [ "id", "object", "created_at", "error", "incomplete_details", "output", "instructions", "parallel_tool_calls", "agent_reference" ], "properties": { "metadata": { "type": "object", "allOf": [ { "$ref": "#/components/schemas/OpenAI.Metadata" } ], "nullable": true }, "top_logprobs": { "type": "integer", "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "nullable": true }, "temperature": { "type": "number", "allOf": [ { "$ref": "#/components/schemas/OpenAI.numeric" } ], "nullable": true, "default": 1 }, "top_p": { "type": "number", "allOf": [ { "$ref": "#/components/schemas/OpenAI.numeric" } ], "nullable": true, "default": 1 }, "user": { "type": "string", "description": "This field is being replaced by `safety_identifier` and `prompt_cache_key`. Use `prompt_cache_key` instead to maintain caching optimizations.\n A stable identifier for your end-users.\n Used to boost cache hit rates by better bucketing similar requests and to help OpenAI detect and prevent abuse. [Learn more](/docs/guides/safety-best-practices#safety-identifiers).", "deprecated": true }, "safety_identifier": { "type": "string", "description": "A stable identifier used to help detect users of your application that may be violating OpenAI's usage policies.\n The IDs should be a string that uniquely identifies each user. We recommend hashing their username or email address, in order to avoid sending us any identifying information. [Learn more](/docs/guides/safety-best-practices#safety-identifiers)." }, "prompt_cache_key": { "type": "string", "description": "Used by OpenAI to cache responses for similar requests to optimize your cache hit rates. Replaces the `user` field. [Learn more](/docs/guides/prompt-caching)." }, "service_tier": { "$ref": "#/components/schemas/OpenAI.ServiceTier" }, "prompt_cache_retention": { "type": "string", "enum": [ "in-memory", "24h" ], "nullable": true }, "previous_response_id": { "type": "string", "nullable": true }, "model": { "type": "string", "description": "The model deployment to use for the creation of this response." }, "reasoning": { "type": "object", "allOf": [ { "$ref": "#/components/schemas/OpenAI.Reasoning" } ], "nullable": true }, "background": { "type": "boolean", "nullable": true }, "max_output_tokens": { "type": "integer", "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "nullable": true }, "max_tool_calls": { "type": "integer", "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "nullable": true }, "text": { "$ref": "#/components/schemas/OpenAI.ResponseTextParam" }, "tools": { "$ref": "#/components/schemas/OpenAI.ToolsArray" }, "tool_choice": { "oneOf": [ { "$ref": "#/components/schemas/OpenAI.ToolChoiceOptions" }, { "$ref": "#/components/schemas/OpenAI.ToolChoiceParam" } ] }, "prompt": { "$ref": "#/components/schemas/OpenAI.Prompt" }, "truncation": { "type": "string", "enum": [ "auto", "disabled" ], "nullable": true, "default": "disabled" }, "id": { "type": "string", "description": "Unique identifier for this Response." }, "object": { "type": "string", "enum": [ "response" ], "description": "The object type of this resource - always set to `response`.", "x-stainless-const": true }, "status": { "type": "string", "enum": [ "completed", "failed", "in_progress", "cancelled", "queued", "incomplete" ], "description": "The status of the response generation. One of `completed`, `failed`,\n `in_progress`, `cancelled`, `queued`, or `incomplete`." }, "created_at": { "type": "integer", "format": "unixtime", "description": "Unix timestamp (in seconds) of when this Response was created." }, "completed_at": { "type": "integer", "format": "unixtime", "nullable": true }, "error": { "type": "object", "allOf": [ { "$ref": "#/components/schemas/OpenAI.ResponseError" } ], "nullable": true }, "incomplete_details": { "type": "object", "allOf": [ { "$ref": "#/components/schemas/OpenAI.ResponseIncompleteDetails" } ], "nullable": true }, "output": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.OutputItem" }, "description": "An array of content items generated by the model.\n - The length and order of items in the `output` array is dependent\n on the model's response.\n - Rather than accessing the first item in the `output` array and\n assuming it's an `assistant` message with the content generated by\n the model, you might consider using the `output_text` property where\n supported in SDKs." }, "instructions": { "anyOf": [ { "type": "string" }, { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.InputItem" } } ], "nullable": true }, "output_text": { "type": "string", "nullable": true }, "usage": { "$ref": "#/components/schemas/OpenAI.ResponseUsage" }, "parallel_tool_calls": { "type": "boolean", "description": "Whether to allow the model to run tool calls in parallel.", "default": true }, "conversation": { "type": "object", "allOf": [ { "$ref": "#/components/schemas/OpenAI.ConversationReference" } ], "nullable": true }, "agent_reference": { "type": "object", "allOf": [ { "$ref": "#/components/schemas/AgentReference" } ], "nullable": true, "description": "The agent used for this response" }, "content_filters": { "type": "array", "items": { "$ref": "#/components/schemas/ContentFilterResult" }, "description": "The content filter evaluation results." } }, "title": "The response object" }, "OpenAI.ResponseAudioDeltaEvent": { "type": "object", "required": [ "type", "sequence_number", "delta" ], "properties": { "type": { "type": "string", "enum": [ "response.audio.delta" ], "description": "The type of the event. Always `response.audio.delta`.", "x-stainless-const": true }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "A sequence number for this chunk of the stream response." }, "delta": { "type": "string", "format": "base64", "description": "A chunk of Base64 encoded response audio bytes." } }, "description": "Emitted when there is a partial audio response.", "x-oaiMeta": { "name": "response.audio.delta", "group": "responses", "example": "{\n \"type\": \"response.audio.delta\",\n \"response_id\": \"resp_123\",\n \"delta\": \"base64encoded...\",\n \"sequence_number\": 1\n}\n" } }, "OpenAI.ResponseAudioDoneEvent": { "type": "object", "required": [ "type", "sequence_number" ], "properties": { "type": { "type": "string", "enum": [ "response.audio.done" ], "description": "The type of the event. Always `response.audio.done`.", "x-stainless-const": true }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of the delta." } }, "description": "Emitted when the audio response is complete.", "x-oaiMeta": { "name": "response.audio.done", "group": "responses", "example": "{\n \"type\": \"response.audio.done\",\n \"response_id\": \"resp-123\",\n \"sequence_number\": 1\n}\n" } }, "OpenAI.ResponseAudioTranscriptDeltaEvent": { "type": "object", "required": [ "type", "delta", "sequence_number" ], "properties": { "type": { "type": "string", "enum": [ "response.audio.transcript.delta" ], "description": "The type of the event. Always `response.audio.transcript.delta`.", "x-stainless-const": true }, "delta": { "type": "string", "description": "The partial transcript of the audio response." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event." } }, "description": "Emitted when there is a partial transcript of audio.", "x-oaiMeta": { "name": "response.audio.transcript.delta", "group": "responses", "example": "{\n \"type\": \"response.audio.transcript.delta\",\n \"response_id\": \"resp_123\",\n \"delta\": \" ... partial transcript ... \",\n \"sequence_number\": 1\n}\n" } }, "OpenAI.ResponseAudioTranscriptDoneEvent": { "type": "object", "required": [ "type", "sequence_number" ], "properties": { "type": { "type": "string", "enum": [ "response.audio.transcript.done" ], "description": "The type of the event. Always `response.audio.transcript.done`.", "x-stainless-const": true }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event." } }, "description": "Emitted when the full audio transcript is completed.", "x-oaiMeta": { "name": "response.audio.transcript.done", "group": "responses", "example": "{\n \"type\": \"response.audio.transcript.done\",\n \"response_id\": \"resp_123\",\n \"sequence_number\": 1\n}\n" } }, "OpenAI.ResponseCodeInterpreterCallCodeDeltaEvent": { "type": "object", "required": [ "type", "output_index", "item_id", "delta", "sequence_number" ], "properties": { "type": { "type": "string", "enum": [ "response.code_interpreter_call_code.delta" ], "description": "The type of the event. Always `response.code_interpreter_call_code.delta`.", "x-stainless-const": true }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item in the response for which the code is being streamed." }, "item_id": { "type": "string", "description": "The unique identifier of the code interpreter tool call item." }, "delta": { "type": "string", "description": "The partial code snippet being streamed by the code interpreter." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event, used to order streaming events." } }, "description": "Emitted when a partial code snippet is streamed by the code interpreter.", "x-oaiMeta": { "name": "response.code_interpreter_call_code.delta", "group": "responses", "example": "{\n \"type\": \"response.code_interpreter_call_code.delta\",\n \"output_index\": 0,\n \"item_id\": \"ci_12345\",\n \"delta\": \"print('Hello, world')\",\n \"sequence_number\": 1\n}\n" } }, "OpenAI.ResponseCodeInterpreterCallCodeDoneEvent": { "type": "object", "required": [ "type", "output_index", "item_id", "code", "sequence_number" ], "properties": { "type": { "type": "string", "enum": [ "response.code_interpreter_call_code.done" ], "description": "The type of the event. Always `response.code_interpreter_call_code.done`.", "x-stainless-const": true }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item in the response for which the code is finalized." }, "item_id": { "type": "string", "description": "The unique identifier of the code interpreter tool call item." }, "code": { "type": "string", "description": "The final code snippet output by the code interpreter." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event, used to order streaming events." } }, "description": "Emitted when the code snippet is finalized by the code interpreter.", "x-oaiMeta": { "name": "response.code_interpreter_call_code.done", "group": "responses", "example": "{\n \"type\": \"response.code_interpreter_call_code.done\",\n \"output_index\": 3,\n \"item_id\": \"ci_12345\",\n \"code\": \"print('done')\",\n \"sequence_number\": 1\n}\n" } }, "OpenAI.ResponseCodeInterpreterCallCompletedEvent": { "type": "object", "required": [ "type", "output_index", "item_id", "sequence_number" ], "properties": { "type": { "type": "string", "enum": [ "response.code_interpreter_call.completed" ], "description": "The type of the event. Always `response.code_interpreter_call.completed`.", "x-stainless-const": true }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item in the response for which the code interpreter call is completed." }, "item_id": { "type": "string", "description": "The unique identifier of the code interpreter tool call item." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event, used to order streaming events." } }, "description": "Emitted when the code interpreter call is completed.", "x-oaiMeta": { "name": "response.code_interpreter_call.completed", "group": "responses", "example": "{\n \"type\": \"response.code_interpreter_call.completed\",\n \"output_index\": 5,\n \"item_id\": \"ci_12345\",\n \"sequence_number\": 1\n}\n" } }, "OpenAI.ResponseCodeInterpreterCallInProgressEvent": { "type": "object", "required": [ "type", "output_index", "item_id", "sequence_number" ], "properties": { "type": { "type": "string", "enum": [ "response.code_interpreter_call.in_progress" ], "description": "The type of the event. Always `response.code_interpreter_call.in_progress`.", "x-stainless-const": true }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item in the response for which the code interpreter call is in progress." }, "item_id": { "type": "string", "description": "The unique identifier of the code interpreter tool call item." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event, used to order streaming events." } }, "description": "Emitted when a code interpreter call is in progress.", "x-oaiMeta": { "name": "response.code_interpreter_call.in_progress", "group": "responses", "example": "{\n \"type\": \"response.code_interpreter_call.in_progress\",\n \"output_index\": 0,\n \"item_id\": \"ci_12345\",\n \"sequence_number\": 1\n}\n" } }, "OpenAI.ResponseCodeInterpreterCallInterpretingEvent": { "type": "object", "required": [ "type", "output_index", "item_id", "sequence_number" ], "properties": { "type": { "type": "string", "enum": [ "response.code_interpreter_call.interpreting" ], "description": "The type of the event. Always `response.code_interpreter_call.interpreting`.", "x-stainless-const": true }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item in the response for which the code interpreter is interpreting code." }, "item_id": { "type": "string", "description": "The unique identifier of the code interpreter tool call item." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event, used to order streaming events." } }, "description": "Emitted when the code interpreter is actively interpreting the code snippet.", "x-oaiMeta": { "name": "response.code_interpreter_call.interpreting", "group": "responses", "example": "{\n \"type\": \"response.code_interpreter_call.interpreting\",\n \"output_index\": 4,\n \"item_id\": \"ci_12345\",\n \"sequence_number\": 1\n}\n" } }, "OpenAI.ResponseCompletedEvent": { "type": "object", "required": [ "type", "response", "sequence_number" ], "properties": { "type": { "type": "string", "enum": [ "response.completed" ], "description": "The type of the event. Always `response.completed`.", "x-stainless-const": true }, "response": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.Response" } ], "description": "Properties of the completed response." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number for this event." } }, "description": "Emitted when the model response is complete.", "x-oaiMeta": { "name": "response.completed", "group": "responses", "example": "{\n \"type\": \"response.completed\",\n \"response\": {\n \"id\": \"resp_123\",\n \"object\": \"response\",\n \"created_at\": 1740855869,\n \"status\": \"completed\",\n \"completed_at\": 1740855870,\n \"error\": null,\n \"incomplete_details\": null,\n \"input\": [],\n \"instructions\": null,\n \"max_output_tokens\": null,\n \"model\": \"gpt-4o-mini-2024-07-18\",\n \"output\": [\n {\n \"id\": \"msg_123\",\n \"type\": \"message\",\n \"role\": \"assistant\",\n \"content\": [\n {\n \"type\": \"output_text\",\n \"text\": \"In a shimmering forest under a sky full of stars, a lonely unicorn named Lila discovered a hidden pond that glowed with moonlight. Every night, she would leave sparkling, magical flowers by the water's edge, hoping to share her beauty with others. One enchanting evening, she woke to find a group of friendly animals gathered around, eager to be friends and share in her magic.\",\n \"annotations\": []\n }\n ]\n }\n ],\n \"previous_response_id\": null,\n \"reasoning_effort\": null,\n \"store\": false,\n \"temperature\": 1,\n \"text\": {\n \"format\": {\n \"type\": \"text\"\n }\n },\n \"tool_choice\": \"auto\",\n \"tools\": [],\n \"top_p\": 1,\n \"truncation\": \"disabled\",\n \"usage\": {\n \"input_tokens\": 0,\n \"output_tokens\": 0,\n \"output_tokens_details\": {\n \"reasoning_tokens\": 0\n },\n \"total_tokens\": 0\n },\n \"user\": null,\n \"metadata\": {}\n },\n \"sequence_number\": 1\n}\n" } }, "OpenAI.ResponseContentPartAddedEvent": { "type": "object", "required": [ "type", "item_id", "output_index", "content_index", "part", "sequence_number" ], "properties": { "type": { "type": "string", "enum": [ "response.content_part.added" ], "description": "The type of the event. Always `response.content_part.added`.", "x-stainless-const": true }, "item_id": { "type": "string", "description": "The ID of the output item that the content part was added to." }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item that the content part was added to." }, "content_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the content part that was added." }, "part": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputContent" } ], "description": "The content part that was added." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event." } }, "description": "Emitted when a new content part is added.", "x-oaiMeta": { "name": "response.content_part.added", "group": "responses", "example": "{\n \"type\": \"response.content_part.added\",\n \"item_id\": \"msg_123\",\n \"output_index\": 0,\n \"content_index\": 0,\n \"part\": {\n \"type\": \"output_text\",\n \"text\": \"\",\n \"annotations\": []\n },\n \"sequence_number\": 1\n}\n" } }, "OpenAI.ResponseContentPartDoneEvent": { "type": "object", "required": [ "type", "item_id", "output_index", "content_index", "sequence_number", "part" ], "properties": { "type": { "type": "string", "enum": [ "response.content_part.done" ], "description": "The type of the event. Always `response.content_part.done`.", "x-stainless-const": true }, "item_id": { "type": "string", "description": "The ID of the output item that the content part was added to." }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item that the content part was added to." }, "content_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the content part that is done." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event." }, "part": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputContent" } ], "description": "The content part that is done." } }, "description": "Emitted when a content part is done.", "x-oaiMeta": { "name": "response.content_part.done", "group": "responses", "example": "{\n \"type\": \"response.content_part.done\",\n \"item_id\": \"msg_123\",\n \"output_index\": 0,\n \"content_index\": 0,\n \"sequence_number\": 1,\n \"part\": {\n \"type\": \"output_text\",\n \"text\": \"In a shimmering forest under a sky full of stars, a lonely unicorn named Lila discovered a hidden pond that glowed with moonlight. Every night, she would leave sparkling, magical flowers by the water's edge, hoping to share her beauty with others. One enchanting evening, she woke to find a group of friendly animals gathered around, eager to be friends and share in her magic.\",\n \"annotations\": []\n }\n}\n" } }, "OpenAI.ResponseCreatedEvent": { "type": "object", "required": [ "type", "response", "sequence_number" ], "properties": { "type": { "type": "string", "enum": [ "response.created" ], "description": "The type of the event. Always `response.created`.", "x-stainless-const": true }, "response": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.Response" } ], "description": "The response that was created." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number for this event." } }, "description": "An event that is emitted when a response is created.", "x-oaiMeta": { "name": "response.created", "group": "responses", "example": "{\n \"type\": \"response.created\",\n \"response\": {\n \"id\": \"resp_67ccfcdd16748190a91872c75d38539e09e4d4aac714747c\",\n \"object\": \"response\",\n \"created_at\": 1741487325,\n \"status\": \"in_progress\",\n \"completed_at\": null,\n \"error\": null,\n \"incomplete_details\": null,\n \"instructions\": null,\n \"max_output_tokens\": null,\n \"model\": \"gpt-4o-2024-08-06\",\n \"output\": [],\n \"parallel_tool_calls\": true,\n \"previous_response_id\": null,\n \"reasoning\": {\n \"effort\": null,\n \"summary\": null\n },\n \"store\": true,\n \"temperature\": 1,\n \"text\": {\n \"format\": {\n \"type\": \"text\"\n }\n },\n \"tool_choice\": \"auto\",\n \"tools\": [],\n \"top_p\": 1,\n \"truncation\": \"disabled\",\n \"usage\": null,\n \"user\": null,\n \"metadata\": {}\n },\n \"sequence_number\": 1\n}\n" } }, "OpenAI.ResponseCustomToolCallInputDeltaEvent": { "type": "object", "required": [ "type", "sequence_number", "output_index", "item_id", "delta" ], "properties": { "type": { "type": "string", "enum": [ "response.custom_tool_call_input.delta" ], "description": "The event type identifier.", "x-stainless-const": true }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event." }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output this delta applies to." }, "item_id": { "type": "string", "description": "Unique identifier for the API item associated with this event." }, "delta": { "type": "string", "description": "The incremental input data (delta) for the custom tool call." } }, "description": "Event representing a delta (partial update) to the input of a custom tool call.", "title": "ResponseCustomToolCallInputDelta", "x-oaiMeta": { "name": "response.custom_tool_call_input.delta", "group": "responses", "example": "{\n \"type\": \"response.custom_tool_call_input.delta\",\n \"output_index\": 0,\n \"item_id\": \"ctc_1234567890abcdef\",\n \"delta\": \"partial input text\"\n}\n" } }, "OpenAI.ResponseCustomToolCallInputDoneEvent": { "type": "object", "required": [ "type", "sequence_number", "output_index", "item_id", "input" ], "properties": { "type": { "type": "string", "enum": [ "response.custom_tool_call_input.done" ], "description": "The event type identifier.", "x-stainless-const": true }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event." }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output this event applies to." }, "item_id": { "type": "string", "description": "Unique identifier for the API item associated with this event." }, "input": { "type": "string", "description": "The complete input data for the custom tool call." } }, "description": "Event indicating that input for a custom tool call is complete.", "title": "ResponseCustomToolCallInputDone", "x-oaiMeta": { "name": "response.custom_tool_call_input.done", "group": "responses", "example": "{\n \"type\": \"response.custom_tool_call_input.done\",\n \"output_index\": 0,\n \"item_id\": \"ctc_1234567890abcdef\",\n \"input\": \"final complete input text\"\n}\n" } }, "OpenAI.ResponseError": { "type": "object", "required": [ "code", "message" ], "properties": { "code": { "$ref": "#/components/schemas/OpenAI.ResponseErrorCode" }, "message": { "type": "string", "description": "A human-readable description of the error." } }, "description": "An error object returned when the model fails to generate a Response." }, "OpenAI.ResponseErrorCode": { "type": "string", "enum": [ "server_error", "rate_limit_exceeded", "invalid_prompt", "vector_store_timeout", "invalid_image", "invalid_image_format", "invalid_base64_image", "invalid_image_url", "image_too_large", "image_too_small", "image_parse_error", "image_content_policy_violation", "invalid_image_mode", "image_file_too_large", "unsupported_image_media_type", "empty_image_file", "failed_to_download_image", "image_file_not_found" ], "description": "The error code for the response." }, "OpenAI.ResponseErrorEvent": { "type": "object", "required": [ "type", "code", "message", "param", "sequence_number" ], "properties": { "type": { "type": "string", "enum": [ "error" ], "description": "The type of the event. Always `error`.", "x-stainless-const": true }, "code": { "type": "string", "nullable": true }, "message": { "type": "string", "description": "The error message." }, "param": { "type": "string", "nullable": true }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event." } }, "description": "Emitted when an error occurs.", "x-oaiMeta": { "name": "error", "group": "responses", "example": "{\n \"type\": \"error\",\n \"code\": \"ERR_SOMETHING\",\n \"message\": \"Something went wrong\",\n \"param\": null,\n \"sequence_number\": 1\n}\n" } }, "OpenAI.ResponseFailedEvent": { "type": "object", "required": [ "type", "sequence_number", "response" ], "properties": { "type": { "type": "string", "enum": [ "response.failed" ], "description": "The type of the event. Always `response.failed`.", "x-stainless-const": true }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event." }, "response": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.Response" } ], "description": "The response that failed." } }, "description": "An event that is emitted when a response fails.", "x-oaiMeta": { "name": "response.failed", "group": "responses", "example": "{\n \"type\": \"response.failed\",\n \"response\": {\n \"id\": \"resp_123\",\n \"object\": \"response\",\n \"created_at\": 1740855869,\n \"status\": \"failed\",\n \"completed_at\": null,\n \"error\": {\n \"code\": \"server_error\",\n \"message\": \"The model failed to generate a response.\"\n },\n \"incomplete_details\": null,\n \"instructions\": null,\n \"max_output_tokens\": null,\n \"model\": \"gpt-4o-mini-2024-07-18\",\n \"output\": [],\n \"previous_response_id\": null,\n \"reasoning_effort\": null,\n \"store\": false,\n \"temperature\": 1,\n \"text\": {\n \"format\": {\n \"type\": \"text\"\n }\n },\n \"tool_choice\": \"auto\",\n \"tools\": [],\n \"top_p\": 1,\n \"truncation\": \"disabled\",\n \"usage\": null,\n \"user\": null,\n \"metadata\": {}\n }\n}\n" } }, "OpenAI.ResponseFileSearchCallCompletedEvent": { "type": "object", "required": [ "type", "output_index", "item_id", "sequence_number" ], "properties": { "type": { "type": "string", "enum": [ "response.file_search_call.completed" ], "description": "The type of the event. Always `response.file_search_call.completed`.", "x-stainless-const": true }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item that the file search call is initiated." }, "item_id": { "type": "string", "description": "The ID of the output item that the file search call is initiated." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event." } }, "description": "Emitted when a file search call is completed (results found).", "x-oaiMeta": { "name": "response.file_search_call.completed", "group": "responses", "example": "{\n \"type\": \"response.file_search_call.completed\",\n \"output_index\": 0,\n \"item_id\": \"fs_123\",\n \"sequence_number\": 1\n}\n" } }, "OpenAI.ResponseFileSearchCallInProgressEvent": { "type": "object", "required": [ "type", "output_index", "item_id", "sequence_number" ], "properties": { "type": { "type": "string", "enum": [ "response.file_search_call.in_progress" ], "description": "The type of the event. Always `response.file_search_call.in_progress`.", "x-stainless-const": true }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item that the file search call is initiated." }, "item_id": { "type": "string", "description": "The ID of the output item that the file search call is initiated." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event." } }, "description": "Emitted when a file search call is initiated.", "x-oaiMeta": { "name": "response.file_search_call.in_progress", "group": "responses", "example": "{\n \"type\": \"response.file_search_call.in_progress\",\n \"output_index\": 0,\n \"item_id\": \"fs_123\",\n \"sequence_number\": 1\n}\n" } }, "OpenAI.ResponseFileSearchCallSearchingEvent": { "type": "object", "required": [ "type", "output_index", "item_id", "sequence_number" ], "properties": { "type": { "type": "string", "enum": [ "response.file_search_call.searching" ], "description": "The type of the event. Always `response.file_search_call.searching`.", "x-stainless-const": true }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item that the file search call is searching." }, "item_id": { "type": "string", "description": "The ID of the output item that the file search call is initiated." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event." } }, "description": "Emitted when a file search is currently searching.", "x-oaiMeta": { "name": "response.file_search_call.searching", "group": "responses", "example": "{\n \"type\": \"response.file_search_call.searching\",\n \"output_index\": 0,\n \"item_id\": \"fs_123\",\n \"sequence_number\": 1\n}\n" } }, "OpenAI.ResponseFormatJsonObject": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "json_object" ], "description": "The type of response format being defined. Always `json_object`.", "x-stainless-const": true } }, "description": "JSON object response format. An older method of generating JSON responses.\nUsing `json_schema` is recommended for models that support it. Note that the\nmodel will not generate JSON without a system or user message instructing it\nto do so.", "title": "JSON object" }, "OpenAI.ResponseFormatJsonSchema": { "type": "object", "required": [ "type", "json_schema" ], "properties": { "type": { "type": "string", "enum": [ "json_schema" ], "description": "The type of response format being defined. Always `json_schema`.", "x-stainless-const": true }, "json_schema": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ResponseFormatJsonSchemaJsonSchema" } ], "description": "Structured Outputs configuration options, including a JSON Schema.", "title": "JSON schema" } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.CreateChatCompletionRequestResponseFormat" } ], "description": "JSON Schema response format. Used to generate structured JSON responses.\nLearn more about [Structured Outputs](/docs/guides/structured-outputs).", "title": "JSON schema" }, "OpenAI.ResponseFormatJsonSchemaJsonSchema": { "type": "object", "required": [ "name" ], "properties": { "description": { "type": "string" }, "name": { "type": "string" }, "schema": { "$ref": "#/components/schemas/OpenAI.ResponseFormatJsonSchemaSchema" }, "strict": { "type": "boolean", "nullable": true } } }, "OpenAI.ResponseFormatJsonSchemaSchema": { "type": "object", "additionalProperties": {}, "description": "The schema for the response format, described as a JSON Schema object.\nLearn how to build JSON schemas [here](https://json-schema.org/).", "title": "JSON schema" }, "OpenAI.ResponseFormatText": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "text" ], "description": "The type of response format being defined. Always `text`.", "x-stainless-const": true } }, "description": "Default response format. Used to generate text responses.", "title": "Text" }, "OpenAI.ResponseFunctionCallArgumentsDeltaEvent": { "type": "object", "required": [ "type", "item_id", "output_index", "sequence_number", "delta" ], "properties": { "type": { "type": "string", "enum": [ "response.function_call_arguments.delta" ], "description": "The type of the event. Always `response.function_call_arguments.delta`.", "x-stainless-const": true }, "item_id": { "type": "string", "description": "The ID of the output item that the function-call arguments delta is added to." }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item that the function-call arguments delta is added to." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event." }, "delta": { "type": "string", "description": "The function-call arguments delta that is added." } }, "description": "Emitted when there is a partial function-call arguments delta.", "x-oaiMeta": { "name": "response.function_call_arguments.delta", "group": "responses", "example": "{\n \"type\": \"response.function_call_arguments.delta\",\n \"item_id\": \"item-abc\",\n \"output_index\": 0,\n \"delta\": \"{ \"arg\":\"\n \"sequence_number\": 1\n}\n" } }, "OpenAI.ResponseFunctionCallArgumentsDoneEvent": { "type": "object", "required": [ "type", "item_id", "name", "output_index", "sequence_number", "arguments" ], "properties": { "type": { "type": "string", "enum": [ "response.function_call_arguments.done" ], "x-stainless-const": true }, "item_id": { "type": "string", "description": "The ID of the item." }, "name": { "type": "string", "description": "The name of the function that was called." }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event." }, "arguments": { "type": "string", "description": "The function-call arguments." } }, "description": "Emitted when function-call arguments are finalized.", "x-oaiMeta": { "name": "response.function_call_arguments.done", "group": "responses", "example": "{\n \"type\": \"response.function_call_arguments.done\",\n \"item_id\": \"item-abc\",\n \"name\": \"get_weather\",\n \"output_index\": 1,\n \"arguments\": \"{ \"arg\": 123 }\",\n \"sequence_number\": 1\n}\n" } }, "OpenAI.ResponseImageGenCallCompletedEvent": { "type": "object", "required": [ "type", "output_index", "sequence_number", "item_id" ], "properties": { "type": { "type": "string", "enum": [ "response.image_generation_call.completed" ], "description": "The type of the event. Always 'response.image_generation_call.completed'.", "x-stainless-const": true }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item in the response's output array." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event." }, "item_id": { "type": "string", "description": "The unique identifier of the image generation item being processed." } }, "description": "Emitted when an image generation tool call has completed and the final image is available.", "title": "ResponseImageGenCallCompletedEvent", "x-oaiMeta": { "name": "response.image_generation_call.completed", "group": "responses", "example": "{\n \"type\": \"response.image_generation_call.completed\",\n \"output_index\": 0,\n \"item_id\": \"item-123\",\n \"sequence_number\": 1\n}\n" } }, "OpenAI.ResponseImageGenCallGeneratingEvent": { "type": "object", "required": [ "type", "output_index", "item_id", "sequence_number" ], "properties": { "type": { "type": "string", "enum": [ "response.image_generation_call.generating" ], "description": "The type of the event. Always 'response.image_generation_call.generating'.", "x-stainless-const": true }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item in the response's output array." }, "item_id": { "type": "string", "description": "The unique identifier of the image generation item being processed." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of the image generation item being processed." } }, "description": "Emitted when an image generation tool call is actively generating an image (intermediate state).", "title": "ResponseImageGenCallGeneratingEvent", "x-oaiMeta": { "name": "response.image_generation_call.generating", "group": "responses", "example": "{\n \"type\": \"response.image_generation_call.generating\",\n \"output_index\": 0,\n \"item_id\": \"item-123\",\n \"sequence_number\": 0\n}\n" } }, "OpenAI.ResponseImageGenCallInProgressEvent": { "type": "object", "required": [ "type", "output_index", "item_id", "sequence_number" ], "properties": { "type": { "type": "string", "enum": [ "response.image_generation_call.in_progress" ], "description": "The type of the event. Always 'response.image_generation_call.in_progress'.", "x-stainless-const": true }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item in the response's output array." }, "item_id": { "type": "string", "description": "The unique identifier of the image generation item being processed." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of the image generation item being processed." } }, "description": "Emitted when an image generation tool call is in progress.", "title": "ResponseImageGenCallInProgressEvent", "x-oaiMeta": { "name": "response.image_generation_call.in_progress", "group": "responses", "example": "{\n \"type\": \"response.image_generation_call.in_progress\",\n \"output_index\": 0,\n \"item_id\": \"item-123\",\n \"sequence_number\": 0\n}\n" } }, "OpenAI.ResponseImageGenCallPartialImageEvent": { "type": "object", "required": [ "type", "output_index", "item_id", "sequence_number", "partial_image_index", "partial_image_b64" ], "properties": { "type": { "type": "string", "enum": [ "response.image_generation_call.partial_image" ], "description": "The type of the event. Always 'response.image_generation_call.partial_image'.", "x-stainless-const": true }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item in the response's output array." }, "item_id": { "type": "string", "description": "The unique identifier of the image generation item being processed." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of the image generation item being processed." }, "partial_image_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "0-based index for the partial image (backend is 1-based, but this is 0-based for the user)." }, "partial_image_b64": { "type": "string", "description": "Base64-encoded partial image data, suitable for rendering as an image." } }, "description": "Emitted when a partial image is available during image generation streaming.", "title": "ResponseImageGenCallPartialImageEvent", "x-oaiMeta": { "name": "response.image_generation_call.partial_image", "group": "responses", "example": "{\n \"type\": \"response.image_generation_call.partial_image\",\n \"output_index\": 0,\n \"item_id\": \"item-123\",\n \"sequence_number\": 0,\n \"partial_image_index\": 0,\n \"partial_image_b64\": \"...\"\n}\n" } }, "OpenAI.ResponseInProgressEvent": { "type": "object", "required": [ "type", "response", "sequence_number" ], "properties": { "type": { "type": "string", "enum": [ "response.in_progress" ], "description": "The type of the event. Always `response.in_progress`.", "x-stainless-const": true }, "response": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.Response" } ], "description": "The response that is in progress." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event." } }, "description": "Emitted when the response is in progress.", "x-oaiMeta": { "name": "response.in_progress", "group": "responses", "example": "{\n \"type\": \"response.in_progress\",\n \"response\": {\n \"id\": \"resp_67ccfcdd16748190a91872c75d38539e09e4d4aac714747c\",\n \"object\": \"response\",\n \"created_at\": 1741487325,\n \"status\": \"in_progress\",\n \"completed_at\": null,\n \"error\": null,\n \"incomplete_details\": null,\n \"instructions\": null,\n \"max_output_tokens\": null,\n \"model\": \"gpt-4o-2024-08-06\",\n \"output\": [],\n \"parallel_tool_calls\": true,\n \"previous_response_id\": null,\n \"reasoning\": {\n \"effort\": null,\n \"summary\": null\n },\n \"store\": true,\n \"temperature\": 1,\n \"text\": {\n \"format\": {\n \"type\": \"text\"\n }\n },\n \"tool_choice\": \"auto\",\n \"tools\": [],\n \"top_p\": 1,\n \"truncation\": \"disabled\",\n \"usage\": null,\n \"user\": null,\n \"metadata\": {}\n },\n \"sequence_number\": 1\n}\n" } }, "OpenAI.ResponseIncompleteDetails": { "type": "object", "properties": { "reason": { "type": "string", "enum": [ "max_output_tokens", "content_filter" ] } } }, "OpenAI.ResponseIncompleteEvent": { "type": "object", "required": [ "type", "response", "sequence_number" ], "properties": { "type": { "type": "string", "enum": [ "response.incomplete" ], "description": "The type of the event. Always `response.incomplete`.", "x-stainless-const": true }, "response": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.Response" } ], "description": "The response that was incomplete." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event." } }, "description": "An event that is emitted when a response finishes as incomplete.", "x-oaiMeta": { "name": "response.incomplete", "group": "responses", "example": "{\n \"type\": \"response.incomplete\",\n \"response\": {\n \"id\": \"resp_123\",\n \"object\": \"response\",\n \"created_at\": 1740855869,\n \"status\": \"incomplete\",\n \"completed_at\": null,\n \"error\": null,\n \"incomplete_details\": {\n \"reason\": \"max_tokens\"\n },\n \"instructions\": null,\n \"max_output_tokens\": null,\n \"model\": \"gpt-4o-mini-2024-07-18\",\n \"output\": [],\n \"previous_response_id\": null,\n \"reasoning_effort\": null,\n \"store\": false,\n \"temperature\": 1,\n \"text\": {\n \"format\": {\n \"type\": \"text\"\n }\n },\n \"tool_choice\": \"auto\",\n \"tools\": [],\n \"top_p\": 1,\n \"truncation\": \"disabled\",\n \"usage\": null,\n \"user\": null,\n \"metadata\": {}\n },\n \"sequence_number\": 1\n}\n" } }, "OpenAI.ResponseLogProb": { "type": "object", "required": [ "token", "logprob" ], "properties": { "token": { "type": "string", "description": "A possible text token." }, "logprob": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.numeric" } ], "description": "The log probability of this token." }, "top_logprobs": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.ResponseLogProbTopLogprobs" }, "description": "The log probability of the top 20 most likely tokens." } }, "description": "A logprob is the logarithmic probability that the model assigns to producing\na particular token at a given position in the sequence. Less-negative (higher)\nlogprob values indicate greater model confidence in that token choice." }, "OpenAI.ResponseLogProbTopLogprobs": { "type": "object", "properties": { "token": { "type": "string" }, "logprob": { "$ref": "#/components/schemas/OpenAI.numeric" } } }, "OpenAI.ResponseMCPCallArgumentsDeltaEvent": { "type": "object", "required": [ "type", "output_index", "item_id", "delta", "sequence_number" ], "properties": { "type": { "type": "string", "enum": [ "response.mcp_call_arguments.delta" ], "description": "The type of the event. Always 'response.mcp_call_arguments.delta'.", "x-stainless-const": true }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item in the response's output array." }, "item_id": { "type": "string", "description": "The unique identifier of the MCP tool call item being processed." }, "delta": { "type": "string", "description": "A JSON string containing the partial update to the arguments for the MCP tool call." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event." } }, "description": "Emitted when there is a delta (partial update) to the arguments of an MCP tool call.", "title": "ResponseMCPCallArgumentsDeltaEvent", "x-oaiMeta": { "name": "response.mcp_call_arguments.delta", "group": "responses", "example": "{\n \"type\": \"response.mcp_call_arguments.delta\",\n \"output_index\": 0,\n \"item_id\": \"item-abc\",\n \"delta\": \"{\",\n \"sequence_number\": 1\n}\n" } }, "OpenAI.ResponseMCPCallArgumentsDoneEvent": { "type": "object", "required": [ "type", "output_index", "item_id", "arguments", "sequence_number" ], "properties": { "type": { "type": "string", "enum": [ "response.mcp_call_arguments.done" ], "description": "The type of the event. Always 'response.mcp_call_arguments.done'.", "x-stainless-const": true }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item in the response's output array." }, "item_id": { "type": "string", "description": "The unique identifier of the MCP tool call item being processed." }, "arguments": { "type": "string", "description": "A JSON string containing the finalized arguments for the MCP tool call." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event." } }, "description": "Emitted when the arguments for an MCP tool call are finalized.", "title": "ResponseMCPCallArgumentsDoneEvent", "x-oaiMeta": { "name": "response.mcp_call_arguments.done", "group": "responses", "example": "{\n \"type\": \"response.mcp_call_arguments.done\",\n \"output_index\": 0,\n \"item_id\": \"item-abc\",\n \"arguments\": \"{\"arg1\": \"value1\", \"arg2\": \"value2\"}\",\n \"sequence_number\": 1\n}\n" } }, "OpenAI.ResponseMCPCallCompletedEvent": { "type": "object", "required": [ "type", "item_id", "output_index", "sequence_number" ], "properties": { "type": { "type": "string", "enum": [ "response.mcp_call.completed" ], "description": "The type of the event. Always 'response.mcp_call.completed'.", "x-stainless-const": true }, "item_id": { "type": "string", "description": "The ID of the MCP tool call item that completed." }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item that completed." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event." } }, "description": "Emitted when an MCP tool call has completed successfully.", "title": "ResponseMCPCallCompletedEvent", "x-oaiMeta": { "name": "response.mcp_call.completed", "group": "responses", "example": "{\n \"type\": \"response.mcp_call.completed\",\n \"sequence_number\": 1,\n \"item_id\": \"mcp_682d437d90a88191bf88cd03aae0c3e503937d5f622d7a90\",\n \"output_index\": 0\n}\n" } }, "OpenAI.ResponseMCPCallFailedEvent": { "type": "object", "required": [ "type", "item_id", "output_index", "sequence_number" ], "properties": { "type": { "type": "string", "enum": [ "response.mcp_call.failed" ], "description": "The type of the event. Always 'response.mcp_call.failed'.", "x-stainless-const": true }, "item_id": { "type": "string", "description": "The ID of the MCP tool call item that failed." }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item that failed." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event." } }, "description": "Emitted when an MCP tool call has failed.", "title": "ResponseMCPCallFailedEvent", "x-oaiMeta": { "name": "response.mcp_call.failed", "group": "responses", "example": "{\n \"type\": \"response.mcp_call.failed\",\n \"sequence_number\": 1,\n \"item_id\": \"mcp_682d437d90a88191bf88cd03aae0c3e503937d5f622d7a90\",\n \"output_index\": 0\n}\n" } }, "OpenAI.ResponseMCPCallInProgressEvent": { "type": "object", "required": [ "type", "sequence_number", "output_index", "item_id" ], "properties": { "type": { "type": "string", "enum": [ "response.mcp_call.in_progress" ], "description": "The type of the event. Always 'response.mcp_call.in_progress'.", "x-stainless-const": true }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event." }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item in the response's output array." }, "item_id": { "type": "string", "description": "The unique identifier of the MCP tool call item being processed." } }, "description": "Emitted when an MCP tool call is in progress.", "title": "ResponseMCPCallInProgressEvent", "x-oaiMeta": { "name": "response.mcp_call.in_progress", "group": "responses", "example": "{\n \"type\": \"response.mcp_call.in_progress\",\n \"sequence_number\": 1,\n \"output_index\": 0,\n \"item_id\": \"mcp_682d437d90a88191bf88cd03aae0c3e503937d5f622d7a90\"\n}\n" } }, "OpenAI.ResponseMCPListToolsCompletedEvent": { "type": "object", "required": [ "type", "item_id", "output_index", "sequence_number" ], "properties": { "type": { "type": "string", "enum": [ "response.mcp_list_tools.completed" ], "description": "The type of the event. Always 'response.mcp_list_tools.completed'.", "x-stainless-const": true }, "item_id": { "type": "string", "description": "The ID of the MCP tool call item that produced this output." }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item that was processed." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event." } }, "description": "Emitted when the list of available MCP tools has been successfully retrieved.", "title": "ResponseMCPListToolsCompletedEvent", "x-oaiMeta": { "name": "response.mcp_list_tools.completed", "group": "responses", "example": "{\n \"type\": \"response.mcp_list_tools.completed\",\n \"sequence_number\": 1,\n \"output_index\": 0,\n \"item_id\": \"mcpl_682d4379df088191886b70f4ec39f90403937d5f622d7a90\"\n}\n" } }, "OpenAI.ResponseMCPListToolsFailedEvent": { "type": "object", "required": [ "type", "item_id", "output_index", "sequence_number" ], "properties": { "type": { "type": "string", "enum": [ "response.mcp_list_tools.failed" ], "description": "The type of the event. Always 'response.mcp_list_tools.failed'.", "x-stainless-const": true }, "item_id": { "type": "string", "description": "The ID of the MCP tool call item that failed." }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item that failed." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event." } }, "description": "Emitted when the attempt to list available MCP tools has failed.", "title": "ResponseMCPListToolsFailedEvent", "x-oaiMeta": { "name": "response.mcp_list_tools.failed", "group": "responses", "example": "{\n \"type\": \"response.mcp_list_tools.failed\",\n \"sequence_number\": 1,\n \"output_index\": 0,\n \"item_id\": \"mcpl_682d4379df088191886b70f4ec39f90403937d5f622d7a90\"\n}\n" } }, "OpenAI.ResponseMCPListToolsInProgressEvent": { "type": "object", "required": [ "type", "item_id", "output_index", "sequence_number" ], "properties": { "type": { "type": "string", "enum": [ "response.mcp_list_tools.in_progress" ], "description": "The type of the event. Always 'response.mcp_list_tools.in_progress'.", "x-stainless-const": true }, "item_id": { "type": "string", "description": "The ID of the MCP tool call item that is being processed." }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item that is being processed." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event." } }, "description": "Emitted when the system is in the process of retrieving the list of available MCP tools.", "title": "ResponseMCPListToolsInProgressEvent", "x-oaiMeta": { "name": "response.mcp_list_tools.in_progress", "group": "responses", "example": "{\n \"type\": \"response.mcp_list_tools.in_progress\",\n \"sequence_number\": 1,\n \"output_index\": 0,\n \"item_id\": \"mcpl_682d4379df088191886b70f4ec39f90403937d5f622d7a90\"\n}\n" } }, "OpenAI.ResponseOutputItemAddedEvent": { "type": "object", "required": [ "type", "output_index", "sequence_number", "item" ], "properties": { "type": { "type": "string", "enum": [ "response.output_item.added" ], "description": "The type of the event. Always `response.output_item.added`.", "x-stainless-const": true }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item that was added." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event." }, "item": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ], "description": "The output item that was added." } }, "description": "Emitted when a new output item is added.", "x-oaiMeta": { "name": "response.output_item.added", "group": "responses", "example": "{\n \"type\": \"response.output_item.added\",\n \"output_index\": 0,\n \"item\": {\n \"id\": \"msg_123\",\n \"status\": \"in_progress\",\n \"type\": \"message\",\n \"role\": \"assistant\",\n \"content\": []\n },\n \"sequence_number\": 1\n}\n" } }, "OpenAI.ResponseOutputItemDoneEvent": { "type": "object", "required": [ "type", "output_index", "sequence_number", "item" ], "properties": { "type": { "type": "string", "enum": [ "response.output_item.done" ], "description": "The type of the event. Always `response.output_item.done`.", "x-stainless-const": true }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item that was marked done." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event." }, "item": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ], "description": "The output item that was marked done." } }, "description": "Emitted when an output item is marked done.", "x-oaiMeta": { "name": "response.output_item.done", "group": "responses", "example": "{\n \"type\": \"response.output_item.done\",\n \"output_index\": 0,\n \"item\": {\n \"id\": \"msg_123\",\n \"status\": \"completed\",\n \"type\": \"message\",\n \"role\": \"assistant\",\n \"content\": [\n {\n \"type\": \"output_text\",\n \"text\": \"In a shimmering forest under a sky full of stars, a lonely unicorn named Lila discovered a hidden pond that glowed with moonlight. Every night, she would leave sparkling, magical flowers by the water's edge, hoping to share her beauty with others. One enchanting evening, she woke to find a group of friendly animals gathered around, eager to be friends and share in her magic.\",\n \"annotations\": []\n }\n ]\n },\n \"sequence_number\": 1\n}\n" } }, "OpenAI.ResponseOutputTextAnnotationAddedEvent": { "type": "object", "required": [ "type", "item_id", "output_index", "content_index", "annotation_index", "sequence_number", "annotation" ], "properties": { "type": { "type": "string", "enum": [ "response.output_text.annotation.added" ], "description": "The type of the event. Always 'response.output_text.annotation.added'.", "x-stainless-const": true }, "item_id": { "type": "string", "description": "The unique identifier of the item to which the annotation is being added." }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item in the response's output array." }, "content_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the content part within the output item." }, "annotation_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the annotation within the content part." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event." }, "annotation": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.Annotation" } ], "description": "The annotation object being added. (See annotation schema for details.)" } }, "description": "Emitted when an annotation is added to output text content.", "title": "ResponseOutputTextAnnotationAddedEvent", "x-oaiMeta": { "name": "response.output_text.annotation.added", "group": "responses", "example": "{\n \"type\": \"response.output_text.annotation.added\",\n \"item_id\": \"item-abc\",\n \"output_index\": 0,\n \"content_index\": 0,\n \"annotation_index\": 0,\n \"annotation\": {\n \"type\": \"text_annotation\",\n \"text\": \"This is a test annotation\",\n \"start\": 0,\n \"end\": 10\n },\n \"sequence_number\": 1\n}\n" } }, "OpenAI.ResponsePromptVariables": { "type": "object", "additionalProperties": { "anyOf": [ { "type": "string" }, { "$ref": "#/components/schemas/OpenAI.InputTextContent" }, { "$ref": "#/components/schemas/OpenAI.InputImageContent" }, { "$ref": "#/components/schemas/OpenAI.InputFileContent" } ] }, "description": "Optional map of values to substitute in for variables in your\nprompt. The substitution values can either be strings, or other\nResponse input types like images or files.", "title": "Prompt Variables", "x-oaiExpandable": true, "x-oaiTypeLabel": "map" }, "OpenAI.ResponseQueuedEvent": { "type": "object", "required": [ "type", "response", "sequence_number" ], "properties": { "type": { "type": "string", "enum": [ "response.queued" ], "description": "The type of the event. Always 'response.queued'.", "x-stainless-const": true }, "response": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.Response" } ], "description": "The full response object that is queued." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number for this event." } }, "description": "Emitted when a response is queued and waiting to be processed.", "title": "ResponseQueuedEvent", "x-oaiMeta": { "name": "response.queued", "group": "responses", "example": "{\n \"type\": \"response.queued\",\n \"response\": {\n \"id\": \"res_123\",\n \"status\": \"queued\",\n \"created_at\": \"2021-01-01T00:00:00Z\",\n \"updated_at\": \"2021-01-01T00:00:00Z\"\n },\n \"sequence_number\": 1\n}\n" } }, "OpenAI.ResponseReasoningSummaryPartAddedEvent": { "type": "object", "required": [ "type", "item_id", "output_index", "summary_index", "sequence_number", "part" ], "properties": { "type": { "type": "string", "enum": [ "response.reasoning_summary_part.added" ], "description": "The type of the event. Always `response.reasoning_summary_part.added`.", "x-stainless-const": true }, "item_id": { "type": "string", "description": "The ID of the item this summary part is associated with." }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item this summary part is associated with." }, "summary_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the summary part within the reasoning summary." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event." }, "part": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ResponseReasoningSummaryPartAddedEventPart" } ], "description": "The summary part that was added." } }, "description": "Emitted when a new reasoning summary part is added.", "x-oaiMeta": { "name": "response.reasoning_summary_part.added", "group": "responses", "example": "{\n \"type\": \"response.reasoning_summary_part.added\",\n \"item_id\": \"rs_6806bfca0b2481918a5748308061a2600d3ce51bdffd5476\",\n \"output_index\": 0,\n \"summary_index\": 0,\n \"part\": {\n \"type\": \"summary_text\",\n \"text\": \"\"\n },\n \"sequence_number\": 1\n}\n" } }, "OpenAI.ResponseReasoningSummaryPartAddedEventPart": { "type": "object", "required": [ "type", "text" ], "properties": { "type": { "type": "string", "enum": [ "summary_text" ], "x-stainless-const": true }, "text": { "type": "string" } } }, "OpenAI.ResponseReasoningSummaryPartDoneEvent": { "type": "object", "required": [ "type", "item_id", "output_index", "summary_index", "sequence_number", "part" ], "properties": { "type": { "type": "string", "enum": [ "response.reasoning_summary_part.done" ], "description": "The type of the event. Always `response.reasoning_summary_part.done`.", "x-stainless-const": true }, "item_id": { "type": "string", "description": "The ID of the item this summary part is associated with." }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item this summary part is associated with." }, "summary_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the summary part within the reasoning summary." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event." }, "part": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ResponseReasoningSummaryPartDoneEventPart" } ], "description": "The completed summary part." } }, "description": "Emitted when a reasoning summary part is completed.", "x-oaiMeta": { "name": "response.reasoning_summary_part.done", "group": "responses", "example": "{\n \"type\": \"response.reasoning_summary_part.done\",\n \"item_id\": \"rs_6806bfca0b2481918a5748308061a2600d3ce51bdffd5476\",\n \"output_index\": 0,\n \"summary_index\": 0,\n \"part\": {\n \"type\": \"summary_text\",\n \"text\": \"**Responding to a greeting**\n\nThe user just said, \"Hello!\" So, it seems I need to engage. I'll greet them back and offer help since they're looking to chat. I could say something like, \"Hello! How can I assist you today?\" That feels friendly and open. They didn't ask a specific question, so this approach will work well for starting a conversation. Let's see where it goes from there!\"\n },\n \"sequence_number\": 1\n}\n" } }, "OpenAI.ResponseReasoningSummaryPartDoneEventPart": { "type": "object", "required": [ "type", "text" ], "properties": { "type": { "type": "string", "enum": [ "summary_text" ], "x-stainless-const": true }, "text": { "type": "string" } } }, "OpenAI.ResponseReasoningSummaryTextDeltaEvent": { "type": "object", "required": [ "type", "item_id", "output_index", "summary_index", "delta", "sequence_number" ], "properties": { "type": { "type": "string", "enum": [ "response.reasoning_summary_text.delta" ], "description": "The type of the event. Always `response.reasoning_summary_text.delta`.", "x-stainless-const": true }, "item_id": { "type": "string", "description": "The ID of the item this summary text delta is associated with." }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item this summary text delta is associated with." }, "summary_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the summary part within the reasoning summary." }, "delta": { "type": "string", "description": "The text delta that was added to the summary." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event." } }, "description": "Emitted when a delta is added to a reasoning summary text.", "x-oaiMeta": { "name": "response.reasoning_summary_text.delta", "group": "responses", "example": "{\n \"type\": \"response.reasoning_summary_text.delta\",\n \"item_id\": \"rs_6806bfca0b2481918a5748308061a2600d3ce51bdffd5476\",\n \"output_index\": 0,\n \"summary_index\": 0,\n \"delta\": \"**Responding to a greeting**\n\nThe user just said, \"Hello!\" So, it seems I need to engage. I'll greet them back and offer help since they're looking to chat. I could say something like, \"Hello! How can I assist you today?\" That feels friendly and open. They didn't ask a specific question, so this approach will work well for starting a conversation. Let's see where it goes from there!\",\n \"sequence_number\": 1\n}\n" } }, "OpenAI.ResponseReasoningSummaryTextDoneEvent": { "type": "object", "required": [ "type", "item_id", "output_index", "summary_index", "text", "sequence_number" ], "properties": { "type": { "type": "string", "enum": [ "response.reasoning_summary_text.done" ], "description": "The type of the event. Always `response.reasoning_summary_text.done`.", "x-stainless-const": true }, "item_id": { "type": "string", "description": "The ID of the item this summary text is associated with." }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item this summary text is associated with." }, "summary_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the summary part within the reasoning summary." }, "text": { "type": "string", "description": "The full text of the completed reasoning summary." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event." } }, "description": "Emitted when a reasoning summary text is completed.", "x-oaiMeta": { "name": "response.reasoning_summary_text.done", "group": "responses", "example": "{\n \"type\": \"response.reasoning_summary_text.done\",\n \"item_id\": \"rs_6806bfca0b2481918a5748308061a2600d3ce51bdffd5476\",\n \"output_index\": 0,\n \"summary_index\": 0,\n \"text\": \"**Responding to a greeting**\n\nThe user just said, \"Hello!\" So, it seems I need to engage. I'll greet them back and offer help since they're looking to chat. I could say something like, \"Hello! How can I assist you today?\" That feels friendly and open. They didn't ask a specific question, so this approach will work well for starting a conversation. Let's see where it goes from there!\",\n \"sequence_number\": 1\n}\n" } }, "OpenAI.ResponseReasoningTextDeltaEvent": { "type": "object", "required": [ "type", "item_id", "output_index", "content_index", "delta", "sequence_number" ], "properties": { "type": { "type": "string", "enum": [ "response.reasoning_text.delta" ], "description": "The type of the event. Always `response.reasoning_text.delta`.", "x-stainless-const": true }, "item_id": { "type": "string", "description": "The ID of the item this reasoning text delta is associated with." }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item this reasoning text delta is associated with." }, "content_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the reasoning content part this delta is associated with." }, "delta": { "type": "string", "description": "The text delta that was added to the reasoning content." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event." } }, "description": "Emitted when a delta is added to a reasoning text.", "x-oaiMeta": { "name": "response.reasoning_text.delta", "group": "responses", "example": "{\n \"type\": \"response.reasoning_text.delta\",\n \"item_id\": \"rs_123\",\n \"output_index\": 0,\n \"content_index\": 0,\n \"delta\": \"The\",\n \"sequence_number\": 1\n}\n" } }, "OpenAI.ResponseReasoningTextDoneEvent": { "type": "object", "required": [ "type", "item_id", "output_index", "content_index", "text", "sequence_number" ], "properties": { "type": { "type": "string", "enum": [ "response.reasoning_text.done" ], "description": "The type of the event. Always `response.reasoning_text.done`.", "x-stainless-const": true }, "item_id": { "type": "string", "description": "The ID of the item this reasoning text is associated with." }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item this reasoning text is associated with." }, "content_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the reasoning content part." }, "text": { "type": "string", "description": "The full text of the completed reasoning content." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event." } }, "description": "Emitted when a reasoning text is completed.", "x-oaiMeta": { "name": "response.reasoning_text.done", "group": "responses", "example": "{\n \"type\": \"response.reasoning_text.done\",\n \"item_id\": \"rs_123\",\n \"output_index\": 0,\n \"content_index\": 0,\n \"text\": \"The user is asking...\",\n \"sequence_number\": 4\n}\n" } }, "OpenAI.ResponseRefusalDeltaEvent": { "type": "object", "required": [ "type", "item_id", "output_index", "content_index", "delta", "sequence_number" ], "properties": { "type": { "type": "string", "enum": [ "response.refusal.delta" ], "description": "The type of the event. Always `response.refusal.delta`.", "x-stainless-const": true }, "item_id": { "type": "string", "description": "The ID of the output item that the refusal text is added to." }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item that the refusal text is added to." }, "content_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the content part that the refusal text is added to." }, "delta": { "type": "string", "description": "The refusal text that is added." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event." } }, "description": "Emitted when there is a partial refusal text.", "x-oaiMeta": { "name": "response.refusal.delta", "group": "responses", "example": "{\n \"type\": \"response.refusal.delta\",\n \"item_id\": \"msg_123\",\n \"output_index\": 0,\n \"content_index\": 0,\n \"delta\": \"refusal text so far\",\n \"sequence_number\": 1\n}\n" } }, "OpenAI.ResponseRefusalDoneEvent": { "type": "object", "required": [ "type", "item_id", "output_index", "content_index", "refusal", "sequence_number" ], "properties": { "type": { "type": "string", "enum": [ "response.refusal.done" ], "description": "The type of the event. Always `response.refusal.done`.", "x-stainless-const": true }, "item_id": { "type": "string", "description": "The ID of the output item that the refusal text is finalized." }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item that the refusal text is finalized." }, "content_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the content part that the refusal text is finalized." }, "refusal": { "type": "string", "description": "The refusal text that is finalized." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of this event." } }, "description": "Emitted when refusal text is finalized.", "x-oaiMeta": { "name": "response.refusal.done", "group": "responses", "example": "{\n \"type\": \"response.refusal.done\",\n \"item_id\": \"item-abc\",\n \"output_index\": 1,\n \"content_index\": 2,\n \"refusal\": \"final refusal text\",\n \"sequence_number\": 1\n}\n" } }, "OpenAI.ResponseStreamOptions": { "type": "object", "properties": { "include_obfuscation": { "type": "boolean", "description": "When true, stream obfuscation will be enabled. Stream obfuscation adds\n random characters to an `obfuscation` field on streaming delta events to\n normalize payload sizes as a mitigation to certain side-channel attacks.\n These obfuscation fields are included by default, but add a small amount\n of overhead to the data stream. You can set `include_obfuscation` to\n false to optimize for bandwidth if you trust the network links between\n your application and the OpenAI API." } }, "description": "Options for streaming responses. Only set this when you set `stream: true`." }, "OpenAI.ResponseTextDeltaEvent": { "type": "object", "required": [ "type", "item_id", "output_index", "content_index", "delta", "sequence_number", "logprobs" ], "properties": { "type": { "type": "string", "enum": [ "response.output_text.delta" ], "description": "The type of the event. Always `response.output_text.delta`.", "x-stainless-const": true }, "item_id": { "type": "string", "description": "The ID of the output item that the text delta was added to." }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item that the text delta was added to." }, "content_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the content part that the text delta was added to." }, "delta": { "type": "string", "description": "The text delta that was added." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number for this event." }, "logprobs": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.ResponseLogProb" }, "description": "The log probabilities of the tokens in the delta." } }, "description": "Emitted when there is an additional text delta.", "x-oaiMeta": { "name": "response.output_text.delta", "group": "responses", "example": "{\n \"type\": \"response.output_text.delta\",\n \"item_id\": \"msg_123\",\n \"output_index\": 0,\n \"content_index\": 0,\n \"delta\": \"In\",\n \"sequence_number\": 1\n}\n" } }, "OpenAI.ResponseTextDoneEvent": { "type": "object", "required": [ "type", "item_id", "output_index", "content_index", "text", "sequence_number", "logprobs" ], "properties": { "type": { "type": "string", "enum": [ "response.output_text.done" ], "description": "The type of the event. Always `response.output_text.done`.", "x-stainless-const": true }, "item_id": { "type": "string", "description": "The ID of the output item that the text content is finalized." }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item that the text content is finalized." }, "content_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the content part that the text content is finalized." }, "text": { "type": "string", "description": "The text content that is finalized." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number for this event." }, "logprobs": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.ResponseLogProb" }, "description": "The log probabilities of the tokens in the delta." } }, "description": "Emitted when text content is finalized.", "x-oaiMeta": { "name": "response.output_text.done", "group": "responses", "example": "{\n \"type\": \"response.output_text.done\",\n \"item_id\": \"msg_123\",\n \"output_index\": 0,\n \"content_index\": 0,\n \"text\": \"In a shimmering forest under a sky full of stars, a lonely unicorn named Lila discovered a hidden pond that glowed with moonlight. Every night, she would leave sparkling, magical flowers by the water's edge, hoping to share her beauty with others. One enchanting evening, she woke to find a group of friendly animals gathered around, eager to be friends and share in her magic.\",\n \"sequence_number\": 1\n}\n" } }, "OpenAI.ResponseTextParam": { "type": "object", "properties": { "format": { "$ref": "#/components/schemas/OpenAI.TextResponseFormatConfiguration" }, "verbosity": { "$ref": "#/components/schemas/OpenAI.Verbosity" } }, "description": "Configuration options for a text response from the model. Can be plain\ntext or structured JSON data. Learn more:\n- [Text inputs and outputs](/docs/guides/text)\n- [Structured Outputs](/docs/guides/structured-outputs)" }, "OpenAI.ResponseUsage": { "type": "object", "required": [ "input_tokens", "input_tokens_details", "output_tokens", "output_tokens_details", "total_tokens" ], "properties": { "input_tokens": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The number of input tokens." }, "input_tokens_details": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ResponseUsageInputTokensDetails" } ], "description": "A detailed breakdown of the input tokens." }, "output_tokens": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The number of output tokens." }, "output_tokens_details": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.ResponseUsageOutputTokensDetails" } ], "description": "A detailed breakdown of the output tokens." }, "total_tokens": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The total number of tokens used." } }, "description": "Represents token usage details including input tokens, output tokens,\na breakdown of output tokens, and the total tokens used." }, "OpenAI.ResponseUsageInputTokensDetails": { "type": "object", "required": [ "cached_tokens" ], "properties": { "cached_tokens": { "$ref": "#/components/schemas/OpenAI.integer" } } }, "OpenAI.ResponseUsageOutputTokensDetails": { "type": "object", "required": [ "reasoning_tokens" ], "properties": { "reasoning_tokens": { "$ref": "#/components/schemas/OpenAI.integer" } } }, "OpenAI.ResponseWebSearchCallCompletedEvent": { "type": "object", "required": [ "type", "output_index", "item_id", "sequence_number" ], "properties": { "type": { "type": "string", "enum": [ "response.web_search_call.completed" ], "description": "The type of the event. Always `response.web_search_call.completed`.", "x-stainless-const": true }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item that the web search call is associated with." }, "item_id": { "type": "string", "description": "Unique ID for the output item associated with the web search call." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of the web search call being processed." } }, "description": "Emitted when a web search call is completed.", "x-oaiMeta": { "name": "response.web_search_call.completed", "group": "responses", "example": "{\n \"type\": \"response.web_search_call.completed\",\n \"output_index\": 0,\n \"item_id\": \"ws_123\",\n \"sequence_number\": 0\n}\n" } }, "OpenAI.ResponseWebSearchCallInProgressEvent": { "type": "object", "required": [ "type", "output_index", "item_id", "sequence_number" ], "properties": { "type": { "type": "string", "enum": [ "response.web_search_call.in_progress" ], "description": "The type of the event. Always `response.web_search_call.in_progress`.", "x-stainless-const": true }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item that the web search call is associated with." }, "item_id": { "type": "string", "description": "Unique ID for the output item associated with the web search call." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of the web search call being processed." } }, "description": "Emitted when a web search call is initiated.", "x-oaiMeta": { "name": "response.web_search_call.in_progress", "group": "responses", "example": "{\n \"type\": \"response.web_search_call.in_progress\",\n \"output_index\": 0,\n \"item_id\": \"ws_123\",\n \"sequence_number\": 0\n}\n" } }, "OpenAI.ResponseWebSearchCallSearchingEvent": { "type": "object", "required": [ "type", "output_index", "item_id", "sequence_number" ], "properties": { "type": { "type": "string", "enum": [ "response.web_search_call.searching" ], "description": "The type of the event. Always `response.web_search_call.searching`.", "x-stainless-const": true }, "output_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the output item that the web search call is associated with." }, "item_id": { "type": "string", "description": "Unique ID for the output item associated with the web search call." }, "sequence_number": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The sequence number of the web search call being processed." } }, "description": "Emitted when a web search call is executing.", "x-oaiMeta": { "name": "response.web_search_call.searching", "group": "responses", "example": "{\n \"type\": \"response.web_search_call.searching\",\n \"output_index\": 0,\n \"item_id\": \"ws_123\",\n \"sequence_number\": 0\n}\n" } }, "OpenAI.ScreenshotParam": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "screenshot" ], "description": "Specifies the event type. For a screenshot action, this property is always set to `screenshot`.", "x-stainless-const": true, "default": "screenshot" } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ComputerAction" } ], "description": "A screenshot action.", "title": "Screenshot" }, "OpenAI.ScrollParam": { "type": "object", "required": [ "type", "x", "y", "scroll_x", "scroll_y" ], "properties": { "type": { "type": "string", "enum": [ "scroll" ], "description": "Specifies the event type. For a scroll action, this property is always set to `scroll`.", "x-stainless-const": true, "default": "scroll" }, "x": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The x-coordinate where the scroll occurred." }, "y": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The y-coordinate where the scroll occurred." }, "scroll_x": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The horizontal scroll distance." }, "scroll_y": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The vertical scroll distance." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ComputerAction" } ], "description": "A scroll action.", "title": "Scroll" }, "OpenAI.SearchContextSize": { "type": "string", "enum": [ "low", "medium", "high" ] }, "OpenAI.ServiceTier": { "type": "string", "enum": [ "auto", "default", "flex", "scale", "priority" ], "description": "Specifies the processing type used for serving the request.\n- If set to 'auto', then the request will be processed with the service tier configured in the Project settings. Unless otherwise configured, the Project will use 'default'.\n- If set to 'default', then the request will be processed with the standard pricing and performance for the selected model.\n- If set to '[flex](/docs/guides/flex-processing)' or '[priority](https://openai.com/api-priority-processing/)', then the request will be processed with the corresponding service tier.\n- When not set, the default behavior is 'auto'.\nWhen the `service_tier` parameter is set, the response body will include the `service_tier` value based on the processing mode actually used to serve the request. This response value may be different from the value set in the parameter.", "nullable": true }, "OpenAI.SkillReferenceParam": { "type": "object", "required": [ "type", "skill_id" ], "properties": { "type": { "type": "string", "enum": [ "skill_reference" ], "description": "References a skill created with the /v1/skills endpoint.", "x-stainless-const": true, "default": "skill_reference" }, "skill_id": { "type": "string", "minLength": 1, "maxLength": 64, "description": "The ID of the referenced skill." }, "version": { "type": "string", "description": "Optional skill version. Use a positive integer or 'latest'. Omit for default." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ContainerSkill" } ] }, "OpenAI.SpecificApplyPatchParam": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "apply_patch" ], "description": "The tool to call. Always `apply_patch`.", "x-stainless-const": true, "default": "apply_patch" } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ToolChoiceParam" } ], "description": "Forces the model to call the apply_patch tool when executing a tool call.", "title": "Specific apply patch tool choice" }, "OpenAI.SpecificFunctionShellParam": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "shell" ], "description": "The tool to call. Always `shell`.", "x-stainless-const": true, "default": "shell" } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ToolChoiceParam" } ], "description": "Forces the model to call the shell tool when a tool call is required.", "title": "Specific shell tool choice" }, "OpenAI.SummaryTextContent": { "type": "object", "required": [ "type", "text" ], "properties": { "type": { "type": "string", "enum": [ "summary_text" ], "description": "The type of the object. Always `summary_text`.", "x-stainless-const": true, "default": "summary_text" }, "text": { "type": "string", "description": "A summary of the reasoning output from the model so far." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.MessageContent" } ], "description": "A summary text from the model.", "title": "Summary text" }, "OpenAI.TextContent": { "type": "object", "required": [ "type", "text" ], "properties": { "type": { "type": "string", "enum": [ "text" ], "x-stainless-const": true, "default": "text" }, "text": { "type": "string" } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.MessageContent" } ], "description": "A text content.", "title": "Text Content" }, "OpenAI.TextResponseFormatConfiguration": { "type": "object", "required": [ "type" ], "properties": { "type": { "$ref": "#/components/schemas/OpenAI.TextResponseFormatConfigurationType" } }, "discriminator": { "propertyName": "type", "mapping": { "json_schema": "#/components/schemas/OpenAI.TextResponseFormatJsonSchema", "text": "#/components/schemas/OpenAI.TextResponseFormatConfigurationResponseFormatText", "json_object": "#/components/schemas/OpenAI.TextResponseFormatConfigurationResponseFormatJsonObject" } }, "description": "An object specifying the format that the model must output.\nConfiguring `{ \"type\": \"json_schema\" }` enables Structured Outputs,\nwhich ensures the model will match your supplied JSON schema. Learn more in the\n[Structured Outputs guide](/docs/guides/structured-outputs).\nThe default format is `{ \"type\": \"text\" }` with no additional options.\n*Not recommended for gpt-4o and newer models:**\nSetting to `{ \"type\": \"json_object\" }` enables the older JSON mode, which\nensures the message the model generates is valid JSON. Using `json_schema`\nis preferred for models that support it." }, "OpenAI.TextResponseFormatConfigurationResponseFormatJsonObject": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "json_object" ], "description": "The type of response format being defined. Always `json_object`.", "x-stainless-const": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.TextResponseFormatConfiguration" } ], "description": "JSON object response format. An older method of generating JSON responses.\nUsing `json_schema` is recommended for models that support it. Note that the\nmodel will not generate JSON without a system or user message instructing it\nto do so.", "title": "JSON object" }, "OpenAI.TextResponseFormatConfigurationResponseFormatText": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "text" ], "description": "The type of response format being defined. Always `text`.", "x-stainless-const": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.TextResponseFormatConfiguration" } ], "description": "Default response format. Used to generate text responses.", "title": "Text" }, "OpenAI.TextResponseFormatConfigurationType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "text", "json_schema", "json_object" ] } ] }, "OpenAI.TextResponseFormatJsonSchema": { "type": "object", "required": [ "type", "name", "schema" ], "properties": { "type": { "type": "string", "enum": [ "json_schema" ], "description": "The type of response format being defined. Always `json_schema`.", "x-stainless-const": true }, "description": { "type": "string", "description": "A description of what the response format is for, used by the model to\n determine how to respond in the format." }, "name": { "type": "string", "description": "The name of the response format. Must be a-z, A-Z, 0-9, or contain\n underscores and dashes, with a maximum length of 64." }, "schema": { "$ref": "#/components/schemas/OpenAI.ResponseFormatJsonSchemaSchema" }, "strict": { "type": "boolean", "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.TextResponseFormatConfiguration" } ], "description": "JSON Schema response format. Used to generate structured JSON responses.\nLearn more about [Structured Outputs](/docs/guides/structured-outputs).", "title": "JSON schema" }, "OpenAI.Tool": { "type": "object", "required": [ "type" ], "properties": { "type": { "$ref": "#/components/schemas/OpenAI.ToolType" } }, "discriminator": { "propertyName": "type", "mapping": { "bing_grounding": "#/components/schemas/BingGroundingTool", "fabric_dataagent_preview": "#/components/schemas/MicrosoftFabricPreviewTool", "sharepoint_grounding_preview": "#/components/schemas/SharepointPreviewTool", "azure_ai_search": "#/components/schemas/AzureAISearchTool", "openapi": "#/components/schemas/OpenApiTool", "bing_custom_search_preview": "#/components/schemas/BingCustomSearchPreviewTool", "browser_automation_preview": "#/components/schemas/BrowserAutomationPreviewTool", "azure_function": "#/components/schemas/AzureFunctionTool", "capture_structured_outputs": "#/components/schemas/CaptureStructuredOutputsTool", "a2a_preview": "#/components/schemas/A2APreviewTool", "work_iq_preview": "#/components/schemas/WorkIQPreviewTool", "memory_search_preview": "#/components/schemas/MemorySearchPreviewTool", "code_interpreter": "#/components/schemas/OpenAI.CodeInterpreterTool", "function": "#/components/schemas/OpenAI.FunctionTool", "file_search": "#/components/schemas/OpenAI.FileSearchTool", "computer_use_preview": "#/components/schemas/OpenAI.ComputerUsePreviewTool", "web_search": "#/components/schemas/OpenAI.WebSearchTool", "mcp": "#/components/schemas/OpenAI.MCPTool", "image_generation": "#/components/schemas/OpenAI.ImageGenTool", "local_shell": "#/components/schemas/OpenAI.LocalShellToolParam", "shell": "#/components/schemas/OpenAI.FunctionShellToolParam", "custom": "#/components/schemas/OpenAI.CustomToolParam", "web_search_preview": "#/components/schemas/OpenAI.WebSearchPreviewTool", "apply_patch": "#/components/schemas/OpenAI.ApplyPatchToolParam" } }, "description": "A tool that can be used to generate a response." }, "OpenAI.ToolChoiceAllowed": { "type": "object", "required": [ "type", "mode", "tools" ], "properties": { "type": { "type": "string", "enum": [ "allowed_tools" ], "description": "Allowed tool configuration type. Always `allowed_tools`.", "x-stainless-const": true }, "mode": { "type": "string", "enum": [ "auto", "required" ], "description": "Constrains the tools available to the model to a pre-defined set.\n `auto` allows the model to pick from among the allowed tools and generate a\n message.\n `required` requires the model to call one or more of the allowed tools." }, "tools": { "type": "array", "items": { "type": "object", "additionalProperties": {} }, "description": "A list of tool definitions that the model should be allowed to call.\n For the Responses API, the list of tool definitions might look like:\n ```json\n [\n { \"type\": \"function\", \"name\": \"get_weather\" },\n { \"type\": \"mcp\", \"server_label\": \"deepwiki\" },\n { \"type\": \"image_generation\" }\n ]\n ```" } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ToolChoiceParam" } ], "description": "Constrains the tools available to the model to a pre-defined set.", "title": "Allowed tools" }, "OpenAI.ToolChoiceCodeInterpreter": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "code_interpreter" ] } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ToolChoiceParam" } ], "description": "Indicates that the model should use a built-in tool to generate a response.\n[Learn more about built-in tools](https://platform.openai.com/docs/guides/tools)." }, "OpenAI.ToolChoiceComputerUsePreview": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "computer_use_preview" ] } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ToolChoiceParam" } ], "description": "Indicates that the model should use a built-in tool to generate a response.\n[Learn more about built-in tools](https://platform.openai.com/docs/guides/tools)." }, "OpenAI.ToolChoiceCustom": { "type": "object", "required": [ "type", "name" ], "properties": { "type": { "type": "string", "enum": [ "custom" ], "description": "For custom tool calling, the type is always `custom`.", "x-stainless-const": true }, "name": { "type": "string", "description": "The name of the custom tool to call." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ToolChoiceParam" } ], "description": "Use this option to force the model to call a specific custom tool.", "title": "Custom tool" }, "OpenAI.ToolChoiceFileSearch": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "file_search" ] } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ToolChoiceParam" } ], "description": "Indicates that the model should use a built-in tool to generate a response.\n[Learn more about built-in tools](https://platform.openai.com/docs/guides/tools)." }, "OpenAI.ToolChoiceFunction": { "type": "object", "required": [ "type", "name" ], "properties": { "type": { "type": "string", "enum": [ "function" ], "description": "For function calling, the type is always `function`.", "x-stainless-const": true }, "name": { "type": "string", "description": "The name of the function to call." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ToolChoiceParam" } ], "description": "Use this option to force the model to call a specific function.", "title": "Function tool" }, "OpenAI.ToolChoiceImageGeneration": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "image_generation" ] } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ToolChoiceParam" } ], "description": "Indicates that the model should use a built-in tool to generate a response.\n[Learn more about built-in tools](https://platform.openai.com/docs/guides/tools)." }, "OpenAI.ToolChoiceMCP": { "type": "object", "required": [ "type", "server_label" ], "properties": { "type": { "type": "string", "enum": [ "mcp" ], "description": "For MCP tools, the type is always `mcp`.", "x-stainless-const": true }, "server_label": { "type": "string", "description": "The label of the MCP server to use." }, "name": { "type": "string", "nullable": true } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ToolChoiceParam" } ], "description": "Use this option to force the model to call a specific tool on a remote MCP server.", "title": "MCP tool" }, "OpenAI.ToolChoiceOptions": { "type": "string", "enum": [ "none", "auto", "required" ], "description": "Controls which (if any) tool is called by the model.\n`none` means the model will not call any tool and instead generates a message.\n`auto` means the model can pick between generating a message or calling one or\nmore tools.\n`required` means the model must call one or more tools.", "title": "Tool choice mode" }, "OpenAI.ToolChoiceParam": { "type": "object", "required": [ "type" ], "properties": { "type": { "$ref": "#/components/schemas/OpenAI.ToolChoiceParamType" } }, "discriminator": { "propertyName": "type", "mapping": { "allowed_tools": "#/components/schemas/OpenAI.ToolChoiceAllowed", "function": "#/components/schemas/OpenAI.ToolChoiceFunction", "mcp": "#/components/schemas/OpenAI.ToolChoiceMCP", "custom": "#/components/schemas/OpenAI.ToolChoiceCustom", "apply_patch": "#/components/schemas/OpenAI.SpecificApplyPatchParam", "shell": "#/components/schemas/OpenAI.SpecificFunctionShellParam", "file_search": "#/components/schemas/OpenAI.ToolChoiceFileSearch", "web_search_preview": "#/components/schemas/OpenAI.ToolChoiceWebSearchPreview", "computer_use_preview": "#/components/schemas/OpenAI.ToolChoiceComputerUsePreview", "web_search_preview_2025_03_11": "#/components/schemas/OpenAI.ToolChoiceWebSearchPreview20250311", "image_generation": "#/components/schemas/OpenAI.ToolChoiceImageGeneration", "code_interpreter": "#/components/schemas/OpenAI.ToolChoiceCodeInterpreter" } }, "description": "How the model should select which tool (or tools) to use when generating\na response. See the `tools` parameter to see how to specify which tools\nthe model can call." }, "OpenAI.ToolChoiceParamType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "allowed_tools", "function", "mcp", "custom", "apply_patch", "shell", "file_search", "web_search_preview", "computer_use_preview", "web_search_preview_2025_03_11", "image_generation", "code_interpreter" ] } ] }, "OpenAI.ToolChoiceWebSearchPreview": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "web_search_preview" ] } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ToolChoiceParam" } ], "description": "Indicates that the model should use a built-in tool to generate a response.\n[Learn more about built-in tools](https://platform.openai.com/docs/guides/tools)." }, "OpenAI.ToolChoiceWebSearchPreview20250311": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "web_search_preview_2025_03_11" ] } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ToolChoiceParam" } ], "description": "Indicates that the model should use a built-in tool to generate a response.\n[Learn more about built-in tools](https://platform.openai.com/docs/guides/tools)." }, "OpenAI.ToolType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "function", "file_search", "computer_use_preview", "web_search", "mcp", "code_interpreter", "image_generation", "local_shell", "shell", "custom", "web_search_preview", "apply_patch", "a2a_preview", "bing_custom_search_preview", "browser_automation_preview", "fabric_dataagent_preview", "sharepoint_grounding_preview", "memory_search_preview", "work_iq_preview", "azure_ai_search", "azure_function", "bing_grounding", "capture_structured_outputs", "openapi" ] } ] }, "OpenAI.ToolsArray": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.Tool" }, "description": "An array of tools the model may call while generating a response. You\ncan specify which tool to use by setting the `tool_choice` parameter.\nWe support the following categories of tools:\n- **Built-in tools**: Tools that are provided by OpenAI that extend the\nmodel's capabilities, like [web search](/docs/guides/tools-web-search)\nor [file search](/docs/guides/tools-file-search). Learn more about\n[built-in tools](/docs/guides/tools).\n- **MCP Tools**: Integrations with third-party systems via custom MCP servers\nor predefined connectors such as Google Drive and SharePoint. Learn more about\n[MCP Tools](/docs/guides/tools-connectors-mcp).\n- **Function calls (custom tools)**: Functions that are defined by you,\nenabling the model to call your own code with strongly typed arguments\nand outputs. Learn more about\n[function calling](/docs/guides/function-calling). You can also use\ncustom tools to call your own code." }, "OpenAI.TopLogProb": { "type": "object", "required": [ "token", "logprob", "bytes" ], "properties": { "token": { "type": "string" }, "logprob": { "$ref": "#/components/schemas/OpenAI.numeric" }, "bytes": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.integer" } } }, "description": "The top log probability of a token.", "title": "Top log probability" }, "OpenAI.TypeParam": { "type": "object", "required": [ "type", "text" ], "properties": { "type": { "type": "string", "enum": [ "type" ], "description": "Specifies the event type. For a type action, this property is always set to `type`.", "x-stainless-const": true, "default": "type" }, "text": { "type": "string", "description": "The text to type." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ComputerAction" } ], "description": "An action to type in text.", "title": "Type" }, "OpenAI.UpdateConversationBody": { "type": "object", "required": [ "metadata" ], "properties": { "metadata": { "type": "object", "allOf": [ { "$ref": "#/components/schemas/OpenAI.Metadata" } ], "nullable": true, "description": "Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format, and querying for objects via API or the dashboard.\n Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters." } } }, "OpenAI.UrlCitationBody": { "type": "object", "required": [ "type", "url", "start_index", "end_index", "title" ], "properties": { "type": { "type": "string", "enum": [ "url_citation" ], "description": "The type of the URL citation. Always `url_citation`.", "x-stainless-const": true, "default": "url_citation" }, "url": { "type": "string", "format": "uri", "description": "The URL of the web resource." }, "start_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the first character of the URL citation in the message." }, "end_index": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.integer" } ], "description": "The index of the last character of the URL citation in the message." }, "title": { "type": "string", "description": "The title of the web resource." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Annotation" } ], "description": "A citation for a web resource used to generate a model response.", "title": "URL citation" }, "OpenAI.VectorStoreFileAttributes": { "type": "object", "additionalProperties": { "anyOf": [ { "type": "string" }, { "$ref": "#/components/schemas/OpenAI.numeric" }, { "type": "boolean" } ] }, "description": "Set of 16 key-value pairs that can be attached to an object. This can be\nuseful for storing additional information about the object in a structured\nformat, and querying for objects via API or the dashboard. Keys are strings\nwith a maximum length of 64 characters. Values are strings with a maximum\nlength of 512 characters, booleans, or numbers.", "x-oaiTypeLabel": "map" }, "OpenAI.Verbosity": { "type": "string", "enum": [ "low", "medium", "high" ], "description": "Constrains the verbosity of the model's response. Lower values will result in\nmore concise responses, while higher values will result in more verbose responses.\nCurrently supported values are `low`, `medium`, and `high`.", "nullable": true }, "OpenAI.WaitParam": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "wait" ], "description": "Specifies the event type. For a wait action, this property is always set to `wait`.", "x-stainless-const": true, "default": "wait" } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.ComputerAction" } ], "description": "A wait action.", "title": "Wait" }, "OpenAI.WebSearchActionFind": { "type": "object", "required": [ "type", "url", "pattern" ], "properties": { "type": { "type": "string", "enum": [ "find_in_page" ], "description": "The action type.", "x-stainless-const": true }, "url": { "type": "string", "format": "uri", "description": "The URL of the page searched for the pattern." }, "pattern": { "type": "string", "description": "The pattern or text to search for within the page." } }, "description": "Action type \"find_in_page\": Searches for a pattern within a loaded page.", "title": "Find action" }, "OpenAI.WebSearchActionOpenPage": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "open_page" ], "description": "The action type.", "x-stainless-const": true }, "url": { "type": "string", "format": "uri", "nullable": true, "description": "The URL opened by the model." } }, "description": "Action type \"open_page\" - Opens a specific URL from search results.", "title": "Open page action" }, "OpenAI.WebSearchActionSearch": { "type": "object", "required": [ "type", "query" ], "properties": { "type": { "type": "string", "enum": [ "search" ], "description": "The action type.", "x-stainless-const": true }, "query": { "type": "string", "description": "[DEPRECATED] The search query.", "deprecated": true }, "queries": { "type": "array", "items": { "type": "string" }, "description": "The search queries.", "title": "Search queries" }, "sources": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.WebSearchActionSearchSources" }, "description": "The sources used in the search.", "title": "Web search sources" } }, "description": "Action type \"search\" - Performs a web search query.", "title": "Search action" }, "OpenAI.WebSearchActionSearchSources": { "type": "object", "required": [ "type", "url" ], "properties": { "type": { "type": "string", "enum": [ "url" ], "x-stainless-const": true }, "url": { "type": "string" } } }, "OpenAI.WebSearchApproximateLocation": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "approximate" ], "description": "The type of location approximation. Always `approximate`.", "x-stainless-const": true, "default": "approximate" }, "country": { "type": "string", "nullable": true }, "region": { "type": "string", "nullable": true }, "city": { "type": "string", "nullable": true }, "timezone": { "type": "string", "nullable": true } }, "description": "The approximate location of the user.", "title": "Web search approximate location" }, "OpenAI.WebSearchPreviewTool": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "web_search_preview" ], "description": "The type of the web search tool. One of `web_search_preview` or `web_search_preview_2025_03_11`.", "x-stainless-const": true, "default": "web_search_preview" }, "user_location": { "type": "object", "allOf": [ { "$ref": "#/components/schemas/OpenAI.ApproximateLocation" } ], "nullable": true }, "search_context_size": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.SearchContextSize" } ], "description": "High level guidance for the amount of context window space to use for the search. One of `low`, `medium`, or `high`. `medium` is the default." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Tool" } ], "description": "This tool searches the web for relevant results to use in a response. Learn more about the [web search tool](https://platform.openai.com/docs/guides/tools-web-search).", "title": "Web search preview" }, "OpenAI.WebSearchTool": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "web_search" ], "description": "The type of the web search tool. One of `web_search` or `web_search_2025_08_26`.", "default": "web_search" }, "filters": { "type": "object", "allOf": [ { "$ref": "#/components/schemas/OpenAI.WebSearchToolFilters" } ], "nullable": true }, "user_location": { "type": "object", "allOf": [ { "$ref": "#/components/schemas/OpenAI.WebSearchApproximateLocation" } ], "nullable": true }, "search_context_size": { "type": "string", "enum": [ "low", "medium", "high" ], "description": "High level guidance for the amount of context window space to use for the search. One of `low`, `medium`, or `high`. `medium` is the default.", "default": "medium" }, "name": { "type": "string", "description": "Optional user-defined name for this tool or configuration." }, "description": { "type": "string", "description": "Optional user-defined description for this tool or configuration." }, "custom_search_configuration": { "allOf": [ { "$ref": "#/components/schemas/WebSearchConfiguration" } ], "description": "The project connections attached to this tool. There can be a maximum of 1 connection\nresource attached to the tool." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Tool" } ], "description": "Search the Internet for sources related to the prompt. Learn more about the\n[web search tool](/docs/guides/tools-web-search).", "title": "Web search" }, "OpenAI.WebSearchToolFilters": { "type": "object", "properties": { "allowed_domains": { "type": "array", "items": { "type": "string" }, "nullable": true } } }, "OpenAI.integer": { "type": "integer", "format": "int64" }, "OpenAI.numeric": { "type": "number", "format": "double" }, "OpenApiAnonymousAuthDetails": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "anonymous" ], "description": "The object type, which is always 'anonymous'." } }, "allOf": [ { "$ref": "#/components/schemas/OpenApiAuthDetails" } ], "description": "Security details for OpenApi anonymous authentication" }, "OpenApiAuthDetails": { "type": "object", "required": [ "type" ], "properties": { "type": { "allOf": [ { "$ref": "#/components/schemas/OpenApiAuthType" } ], "description": "The type of authentication, must be anonymous/project_connection/managed_identity" } }, "discriminator": { "propertyName": "type", "mapping": { "anonymous": "#/components/schemas/OpenApiAnonymousAuthDetails", "project_connection": "#/components/schemas/OpenApiProjectConnectionAuthDetails", "managed_identity": "#/components/schemas/OpenApiManagedAuthDetails" } }, "description": "authentication details for OpenApiFunctionDefinition" }, "OpenApiAuthType": { "anyOf": [ { "type": "string", "enum": [ "anonymous", "project_connection", "managed_identity" ] }, { "type": "string" } ], "description": "Authentication type for OpenApi endpoint. Allowed types are:\n- Anonymous (no authentication required)\n- Project Connection (requires project_connection_id to endpoint, as setup in AI Foundry)\n- Managed_Identity (requires audience for identity based auth)" }, "OpenApiFunctionDefinition": { "type": "object", "required": [ "name", "spec", "auth" ], "properties": { "name": { "type": "string", "description": "The name of the function to be called." }, "description": { "type": "string", "description": "A description of what the function does, used by the model to choose when and how to call the function." }, "spec": { "type": "object", "additionalProperties": {}, "description": "The openapi function shape, described as a JSON Schema object." }, "auth": { "allOf": [ { "$ref": "#/components/schemas/OpenApiAuthDetails" } ], "description": "Open API authentication details" }, "default_params": { "type": "array", "items": { "type": "string" }, "description": "List of OpenAPI spec parameters that will use user-provided defaults" }, "functions": { "type": "array", "items": { "type": "object", "properties": { "name": { "type": "string", "description": "The name of the function to be called." }, "description": { "type": "string", "description": "A description of what the function does, used by the model to choose when and how to call the function." }, "parameters": { "type": "object", "additionalProperties": {}, "description": "The parameters the functions accepts, described as a JSON Schema object." } }, "required": [ "name", "parameters" ] }, "description": "List of function definitions used by OpenApi tool", "readOnly": true } }, "description": "The input definition information for an openapi function." }, "OpenApiManagedAuthDetails": { "type": "object", "required": [ "type", "security_scheme" ], "properties": { "type": { "type": "string", "enum": [ "managed_identity" ], "description": "The object type, which is always 'managed_identity'." }, "security_scheme": { "allOf": [ { "$ref": "#/components/schemas/OpenApiManagedSecurityScheme" } ], "description": "Connection auth security details" } }, "allOf": [ { "$ref": "#/components/schemas/OpenApiAuthDetails" } ], "description": "Security details for OpenApi managed_identity authentication" }, "OpenApiManagedSecurityScheme": { "type": "object", "required": [ "audience" ], "properties": { "audience": { "type": "string", "description": "Authentication scope for managed_identity auth type" } }, "description": "Security scheme for OpenApi managed_identity authentication" }, "OpenApiProjectConnectionAuthDetails": { "type": "object", "required": [ "type", "security_scheme" ], "properties": { "type": { "type": "string", "enum": [ "project_connection" ], "description": "The object type, which is always 'project_connection'." }, "security_scheme": { "allOf": [ { "$ref": "#/components/schemas/OpenApiProjectConnectionSecurityScheme" } ], "description": "Project connection auth security details" } }, "allOf": [ { "$ref": "#/components/schemas/OpenApiAuthDetails" } ], "description": "Security details for OpenApi project connection authentication" }, "OpenApiProjectConnectionSecurityScheme": { "type": "object", "required": [ "project_connection_id" ], "properties": { "project_connection_id": { "type": "string", "description": "Project connection id for Project Connection auth type" } }, "description": "Security scheme for OpenApi managed_identity authentication" }, "OpenApiTool": { "type": "object", "required": [ "type", "openapi" ], "properties": { "type": { "type": "string", "enum": [ "openapi" ], "description": "The object type, which is always 'openapi'." }, "openapi": { "allOf": [ { "$ref": "#/components/schemas/OpenApiFunctionDefinition" } ], "description": "The openapi function definition." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Tool" } ], "description": "The input definition information for an OpenAPI tool as used to configure an agent." }, "OpenApiToolCall": { "type": "object", "required": [ "type", "call_id", "name", "arguments", "status" ], "properties": { "type": { "type": "string", "enum": [ "openapi_call" ] }, "call_id": { "type": "string", "description": "The unique ID of the tool call generated by the model." }, "name": { "type": "string", "description": "The name of the OpenAPI operation being called." }, "arguments": { "type": "string", "description": "A JSON string of the arguments to pass to the tool." }, "status": { "allOf": [ { "$ref": "#/components/schemas/ToolCallStatus" } ], "description": "The status of the tool call." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ], "description": "An OpenAPI tool call." }, "OpenApiToolCallOutput": { "type": "object", "required": [ "type", "call_id", "name", "status" ], "properties": { "type": { "type": "string", "enum": [ "openapi_call_output" ] }, "call_id": { "type": "string", "description": "The unique ID of the tool call generated by the model." }, "name": { "type": "string", "description": "The name of the OpenAPI operation that was called." }, "output": { "allOf": [ { "$ref": "#/components/schemas/ToolCallOutputContent" } ], "description": "The output from the OpenAPI tool call." }, "status": { "allOf": [ { "$ref": "#/components/schemas/ToolCallStatus" } ], "description": "The status of the tool call." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ], "description": "The output of an OpenAPI tool call." }, "OrpoTrainingConfiguration": { "type": "object", "required": [ "algorithm" ], "properties": { "algorithm": { "type": "string", "enum": [ "orpo" ], "description": "Training algorithm, always 'orpo'." }, "lora": { "allOf": [ { "$ref": "#/components/schemas/TrainingLoraConfiguration" } ], "description": "LoRA adapter configuration." }, "eval": { "allOf": [ { "$ref": "#/components/schemas/TrainingEvalConfiguration" } ], "description": "Evaluation configuration." } }, "allOf": [ { "$ref": "#/components/schemas/TrainingConfiguration" } ], "description": "Odds ratio preference optimization training recipe." }, "Output": { "type": "object", "required": [ "job_output_type" ], "properties": { "job_output_type": { "allOf": [ { "$ref": "#/components/schemas/AssetTypes" } ], "description": "Specifies the type of job output." }, "mode": { "allOf": [ { "$ref": "#/components/schemas/InputOutputModes" } ], "description": "Output Asset Delivery Mode." }, "asset_name": { "type": "string", "description": "Name of the output data asset to register." }, "asset_version": { "type": "string", "description": "Version of the output data asset to register." }, "uri": { "type": "string", "description": "Output Asset URI." }, "base_model_id": { "type": "string", "description": "Base model ID. Applies to safetensors_model outputs." }, "description": { "type": "string", "description": "Description for the output." } }, "description": "Job output definition." }, "PageOrder": { "type": "string", "enum": [ "asc", "desc" ] }, "PagedConnection": { "type": "object", "required": [ "value" ], "properties": { "value": { "type": "array", "items": { "$ref": "#/components/schemas/Connection" }, "description": "The Connection items on this page" }, "nextLink": { "type": "string", "format": "uri", "description": "The link to the next page of items" } }, "description": "Paged collection of Connection items" }, "PagedDatasetVersion": { "type": "object", "required": [ "value" ], "properties": { "value": { "type": "array", "items": { "$ref": "#/components/schemas/DatasetVersion" }, "description": "The DatasetVersion items on this page" }, "nextLink": { "type": "string", "format": "uri", "description": "The link to the next page of items" } }, "description": "Paged collection of DatasetVersion items" }, "PagedDeployment": { "type": "object", "required": [ "value" ], "properties": { "value": { "type": "array", "items": { "$ref": "#/components/schemas/Deployment" }, "description": "The Deployment items on this page" }, "nextLink": { "type": "string", "format": "uri", "description": "The link to the next page of items" } }, "description": "Paged collection of Deployment items" }, "PagedEvaluationRule": { "type": "object", "required": [ "value" ], "properties": { "value": { "type": "array", "items": { "$ref": "#/components/schemas/EvaluationRule" }, "description": "The EvaluationRule items on this page" }, "nextLink": { "type": "string", "format": "uri", "description": "The link to the next page of items" } }, "description": "Paged collection of EvaluationRule items" }, "PagedEvaluationTaxonomy": { "type": "object", "required": [ "value" ], "properties": { "value": { "type": "array", "items": { "$ref": "#/components/schemas/EvaluationTaxonomy" }, "description": "The EvaluationTaxonomy items on this page" }, "nextLink": { "type": "string", "format": "uri", "description": "The link to the next page of items" } }, "description": "Paged collection of EvaluationTaxonomy items" }, "PagedEvaluatorVersion": { "type": "object", "required": [ "value" ], "properties": { "value": { "type": "array", "items": { "$ref": "#/components/schemas/EvaluatorVersion" }, "description": "The EvaluatorVersion items on this page" }, "nextLink": { "type": "string", "format": "uri", "description": "The link to the next page of items" } }, "description": "Paged collection of EvaluatorVersion items" }, "PagedIndex": { "type": "object", "required": [ "value" ], "properties": { "value": { "type": "array", "items": { "$ref": "#/components/schemas/Index" }, "description": "The Index items on this page" }, "nextLink": { "type": "string", "format": "uri", "description": "The link to the next page of items" } }, "description": "Paged collection of Index items" }, "PagedInsight": { "type": "object", "required": [ "value" ], "properties": { "value": { "type": "array", "items": { "$ref": "#/components/schemas/Insight" }, "description": "The Insight items on this page" }, "nextLink": { "type": "string", "format": "uri", "description": "The link to the next page of items" } }, "description": "Paged collection of Insight items" }, "PagedRedTeam": { "type": "object", "required": [ "value" ], "properties": { "value": { "type": "array", "items": { "$ref": "#/components/schemas/RedTeam" }, "description": "The RedTeam items on this page" }, "nextLink": { "type": "string", "format": "uri", "description": "The link to the next page of items" } }, "description": "Paged collection of RedTeam items" }, "PagedSchedule": { "type": "object", "required": [ "value" ], "properties": { "value": { "type": "array", "items": { "$ref": "#/components/schemas/Schedule" }, "description": "The Schedule items on this page" }, "nextLink": { "type": "string", "format": "uri", "description": "The link to the next page of items" } }, "description": "Paged collection of Schedule items" }, "PagedScheduleRun": { "type": "object", "required": [ "value" ], "properties": { "value": { "type": "array", "items": { "$ref": "#/components/schemas/ScheduleRun" }, "description": "The ScheduleRun items on this page" }, "nextLink": { "type": "string", "format": "uri", "description": "The link to the next page of items" } }, "description": "Paged collection of ScheduleRun items" }, "PairwisePreferenceColumnMapping": { "type": "object", "required": [ "prompt", "chosen", "rejected" ], "properties": { "prompt": { "type": "string", "description": "Actual dataset column name containing prompts, for example 'prompt' or 'question'." }, "chosen": { "type": "string", "description": "Actual dataset column name containing the preferred response, for example 'chosen', 'accepted_answer', or 'good_response'." }, "rejected": { "type": "string", "description": "Actual dataset column name containing the rejected response, for example 'rejected', 'rejected_answer', or 'bad_response'." } }, "description": "Column mapping for pairwise preference datasets. Keys are logical fields expected by preference training; values are the exact column names in the referenced dataset asset." }, "PairwisePreferenceDatasetConfiguration": { "type": "object", "required": [ "train", "columns" ], "properties": { "train": { "type": "string", "description": "Training dataset asset reference." }, "eval": { "type": "string", "description": "Optional evaluation dataset asset reference." }, "columns": { "allOf": [ { "$ref": "#/components/schemas/PairwisePreferenceColumnMapping" } ], "description": "Mapping from pairwise preference logical fields to actual dataset column names. DPO, ORPO, CPO, and SimPO require 'prompt', 'chosen', and 'rejected'." }, "data_format": { "allOf": [ { "$ref": "#/components/schemas/TrainingDataFormatConfiguration" } ], "description": "Conversational data formatting options." } }, "description": "Dataset configuration for managed pairwise preference training." }, "PairwiseRewardModelTrainingDatasetConfiguration": { "type": "object", "required": [ "kind", "train", "columns" ], "properties": { "kind": { "type": "string", "enum": [ "pairwise" ], "description": "Reward-model dataset kind, always 'pairwise'." }, "train": { "type": "string", "description": "Training dataset asset reference." }, "eval": { "type": "string", "description": "Optional evaluation dataset asset reference." }, "columns": { "allOf": [ { "$ref": "#/components/schemas/PairwisePreferenceColumnMapping" } ], "description": "Mapping from pairwise reward-model logical fields to actual dataset column names. Pairwise reward-model training requires 'prompt', 'chosen', and 'rejected'." }, "data_format": { "allOf": [ { "$ref": "#/components/schemas/TrainingDataFormatConfiguration" } ], "description": "Conversational data formatting options." } }, "allOf": [ { "$ref": "#/components/schemas/RewardModelTrainingDatasetConfiguration" } ], "description": "Pairwise preference dataset for managed reward-model training." }, "PendingUploadRequest": { "type": "object", "required": [ "pendingUploadType" ], "properties": { "pendingUploadId": { "type": "string", "description": "If PendingUploadId is not provided, a random GUID will be used." }, "connectionName": { "type": "string", "description": "Azure Storage Account connection name to use for generating temporary SAS token" }, "pendingUploadType": { "type": "string", "enum": [ "BlobReference" ], "description": "BlobReference is the only supported type." } }, "description": "Represents a request for a pending upload." }, "PendingUploadResponse": { "type": "object", "required": [ "blobReference", "pendingUploadId", "pendingUploadType" ], "properties": { "blobReference": { "allOf": [ { "$ref": "#/components/schemas/BlobReference" } ], "description": "Container-level read, write, list SAS." }, "pendingUploadId": { "type": "string", "description": "ID for this upload request." }, "version": { "type": "string", "description": "Version of asset to be created if user did not specify version when initially creating upload" }, "pendingUploadType": { "type": "string", "enum": [ "BlobReference" ], "description": "BlobReference is the only supported type" } }, "description": "Represents the response for a pending upload request" }, "PolicyGradientTrainingAlgorithm": { "type": "string", "enum": [ "rloo", "reinforce_pp" ], "description": "Policy-gradient algorithm used by managed online reinforcement training." }, "PolicyGradientTrainingJob": { "type": "object", "required": [ "type", "algorithm", "dataset", "runtime" ], "properties": { "type": { "type": "string", "enum": [ "policy_gradient" ], "description": "Managed training job type, always 'policy_gradient'." }, "algorithm": { "allOf": [ { "$ref": "#/components/schemas/PolicyGradientTrainingAlgorithm" } ], "description": "Policy-gradient algorithm to run." }, "dataset": { "allOf": [ { "$ref": "#/components/schemas/GrpoTrainingDatasetConfiguration" } ], "description": "Training and optional evaluation datasets." }, "runtime": { "allOf": [ { "$ref": "#/components/schemas/PolicyGradientTrainingRuntimeConfiguration" } ], "description": "Runtime options for managed online policy-gradient training." } }, "allOf": [ { "$ref": "#/components/schemas/ModelTrainingJobCreate" } ], "description": "Request body for creating a managed online policy-gradient training job from a base model." }, "PolicyGradientTrainingRuntimeConfiguration": { "type": "object", "required": [ "judge", "rollout" ], "properties": { "framework": { "allOf": [ { "$ref": "#/components/schemas/TrainingFramework" } ], "description": "Training framework implementation. If omitted, the service selects a compatible framework." }, "hyperparameters": { "type": "object", "additionalProperties": {}, "description": "Algorithm-specific hyperparameters passed through to the selected framework." }, "judge": { "allOf": [ { "$ref": "#/components/schemas/TrainingRewardConfiguration" } ], "description": "Judge used to score generated completions during online policy-gradient training. Required for RLOO and REINFORCE++." }, "reference": { "allOf": [ { "$ref": "#/components/schemas/ModelTrainingReferenceConfiguration" } ], "description": "Reference policy used for KL anchoring." }, "lora": { "allOf": [ { "$ref": "#/components/schemas/TrainingLoraConfiguration" } ], "description": "LoRA adapter configuration." }, "rollout": { "allOf": [ { "$ref": "#/components/schemas/TrainingRolloutConfiguration" } ], "description": "Rollout generation configuration. Required for RLOO and REINFORCE++." }, "eval": { "allOf": [ { "$ref": "#/components/schemas/TrainingEvalConfiguration" } ], "description": "Evaluation configuration." }, "packaging": { "allOf": [ { "$ref": "#/components/schemas/ModelTrainingPackagingConfiguration" } ], "description": "Model artifact packaging options." } }, "description": "Runtime options for managed online policy-gradient training." }, "PpoCriticConfiguration": { "type": "object", "properties": { "model": { "type": "string", "description": "Optional critic model asset reference. If omitted, the service initializes the critic from the policy model." }, "value_loss_coefficient": { "type": "number", "format": "double", "description": "Value loss coefficient." }, "gamma": { "type": "number", "format": "double", "description": "GAE discount factor." }, "lambda": { "type": "number", "format": "double", "description": "GAE lambda." } }, "description": "Critic or value model configuration for managed PPO training." }, "PpoTrainingConfiguration": { "type": "object", "required": [ "algorithm", "reward" ], "properties": { "algorithm": { "type": "string", "enum": [ "ppo" ], "description": "Training algorithm, always 'ppo'." }, "reward": { "allOf": [ { "$ref": "#/components/schemas/TrainingRewardConfiguration" } ], "description": "Reward signal configuration." }, "lora": { "allOf": [ { "$ref": "#/components/schemas/TrainingLoraConfiguration" } ], "description": "LoRA adapter configuration." }, "rollout": { "allOf": [ { "$ref": "#/components/schemas/TrainingRolloutConfiguration" } ], "description": "Rollout generation configuration." }, "eval": { "allOf": [ { "$ref": "#/components/schemas/TrainingEvalConfiguration" } ], "description": "Evaluation configuration." } }, "allOf": [ { "$ref": "#/components/schemas/TrainingConfiguration" } ], "description": "Proximal policy optimization training recipe." }, "PpoTrainingJob": { "type": "object", "required": [ "type", "dataset", "runtime" ], "properties": { "type": { "type": "string", "enum": [ "ppo" ], "description": "Managed training job type, always 'ppo'." }, "dataset": { "allOf": [ { "$ref": "#/components/schemas/GrpoTrainingDatasetConfiguration" } ], "description": "Training and optional evaluation datasets." }, "runtime": { "allOf": [ { "$ref": "#/components/schemas/PpoTrainingRuntimeConfiguration" } ], "description": "Runtime options for managed PPO." } }, "allOf": [ { "$ref": "#/components/schemas/ModelTrainingJobCreate" } ], "description": "Request body for creating a managed PPO training job from a base model." }, "PpoTrainingRuntimeConfiguration": { "type": "object", "required": [ "judge", "rollout" ], "properties": { "framework": { "allOf": [ { "$ref": "#/components/schemas/TrainingFramework" } ], "description": "Training framework implementation. If omitted, the service selects a compatible framework." }, "hyperparameters": { "type": "object", "additionalProperties": {}, "description": "Algorithm-specific hyperparameters passed through to the selected framework." }, "judge": { "allOf": [ { "$ref": "#/components/schemas/TrainingRewardConfiguration" } ], "description": "Judge used to score generated completions during PPO training. Required for PPO." }, "reference": { "allOf": [ { "$ref": "#/components/schemas/ModelTrainingReferenceConfiguration" } ], "description": "Reference policy used for KL anchoring." }, "critic": { "allOf": [ { "$ref": "#/components/schemas/PpoCriticConfiguration" } ], "description": "Critic or value model configuration." }, "lora": { "allOf": [ { "$ref": "#/components/schemas/TrainingLoraConfiguration" } ], "description": "LoRA adapter configuration." }, "rollout": { "allOf": [ { "$ref": "#/components/schemas/TrainingRolloutConfiguration" } ], "description": "Rollout generation configuration. Required for PPO." }, "eval": { "allOf": [ { "$ref": "#/components/schemas/TrainingEvalConfiguration" } ], "description": "Evaluation configuration." }, "packaging": { "allOf": [ { "$ref": "#/components/schemas/ModelTrainingPackagingConfiguration" } ], "description": "Model artifact packaging options." } }, "description": "Runtime options for managed PPO training." }, "PreferenceTrainingAlgorithm": { "type": "string", "enum": [ "dpo", "orpo", "cpo", "simpo" ], "description": "Preference optimization algorithm used by managed pairwise preference training." }, "PreferenceTrainingJob": { "type": "object", "required": [ "type", "algorithm", "dataset" ], "properties": { "type": { "type": "string", "enum": [ "preference" ], "description": "Managed training job type, always 'preference'." }, "algorithm": { "allOf": [ { "$ref": "#/components/schemas/PreferenceTrainingAlgorithm" } ], "description": "Preference optimization algorithm to run." }, "dataset": { "allOf": [ { "$ref": "#/components/schemas/PairwisePreferenceDatasetConfiguration" } ], "description": "Training and optional evaluation datasets." }, "runtime": { "allOf": [ { "$ref": "#/components/schemas/PreferenceTrainingRuntimeConfiguration" } ], "description": "Runtime options for managed pairwise preference training." } }, "allOf": [ { "$ref": "#/components/schemas/ModelTrainingJobCreate" } ], "description": "Request body for creating a managed pairwise preference training job from a base model." }, "PreferenceTrainingRuntimeConfiguration": { "type": "object", "properties": { "framework": { "allOf": [ { "$ref": "#/components/schemas/TrainingFramework" } ], "description": "Training framework implementation. If omitted, the service selects a compatible framework." }, "hyperparameters": { "type": "object", "additionalProperties": {}, "description": "Algorithm-specific hyperparameters passed through to the selected framework." }, "reference": { "allOf": [ { "$ref": "#/components/schemas/ModelTrainingReferenceConfiguration" } ], "description": "Reference policy used by algorithms that require KL anchoring or a reference model." }, "lora": { "allOf": [ { "$ref": "#/components/schemas/TrainingLoraConfiguration" } ], "description": "LoRA adapter configuration." }, "eval": { "allOf": [ { "$ref": "#/components/schemas/TrainingEvalConfiguration" } ], "description": "Evaluation configuration." }, "packaging": { "allOf": [ { "$ref": "#/components/schemas/ModelTrainingPackagingConfiguration" } ], "description": "Model artifact packaging options." } }, "description": "Runtime options for managed pairwise preference training." }, "PromptAgentDefinition": { "type": "object", "required": [ "kind", "model" ], "properties": { "kind": { "type": "string", "enum": [ "prompt" ] }, "model": { "type": "string", "description": "The model deployment to use for this agent." }, "instructions": { "type": "string", "nullable": true, "description": "A system (or developer) message inserted into the model's context." }, "temperature": { "type": "number", "format": "float", "nullable": true, "minimum": 0, "maximum": 2, "description": "What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.\nWe generally recommend altering this or `top_p` but not both.", "default": 1 }, "top_p": { "type": "number", "format": "float", "nullable": true, "minimum": 0, "maximum": 1, "description": "An alternative to sampling with temperature, called nucleus sampling,\nwhere the model considers the results of the tokens with top_p probability\nmass. So 0.1 means only the tokens comprising the top 10% probability mass\nare considered.\n\nWe generally recommend altering this or `temperature` but not both.", "default": 1 }, "reasoning": { "type": "object", "allOf": [ { "$ref": "#/components/schemas/OpenAI.Reasoning" } ], "nullable": true }, "tools": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.Tool" }, "description": "An array of tools the model may call while generating a response. You\ncan specify which tool to use by setting the `tool_choice` parameter." }, "tool_choice": { "anyOf": [ { "type": "string" }, { "$ref": "#/components/schemas/OpenAI.ToolChoiceParam" } ], "description": "How the model should select which tool (or tools) to use when generating a response.\nSee the `tools` parameter to see how to specify which tools the model can call." }, "text": { "allOf": [ { "$ref": "#/components/schemas/PromptAgentDefinitionTextOptions" } ], "description": "Configuration options for a text response from the model. Can be plain text or structured JSON data." }, "structured_inputs": { "type": "object", "additionalProperties": { "$ref": "#/components/schemas/StructuredInputDefinition" }, "description": "Set of structured inputs that can participate in prompt template substitution or tool argument bindings." } }, "allOf": [ { "$ref": "#/components/schemas/AgentDefinition" } ], "description": "The prompt agent definition" }, "PromptAgentDefinitionTextOptions": { "type": "object", "properties": { "format": { "$ref": "#/components/schemas/OpenAI.TextResponseFormatConfiguration" } }, "description": "Configuration options for a text response from the model. Can be plain text or structured JSON data." }, "PromptBasedEvaluatorDefinition": { "type": "object", "required": [ "type", "prompt_text" ], "properties": { "type": { "type": "string", "enum": [ "prompt" ] }, "prompt_text": { "type": "string", "description": "The prompt text used for evaluation" } }, "allOf": [ { "$ref": "#/components/schemas/EvaluatorDefinition" } ], "description": "Prompt-based evaluator" }, "ProtocolVersionRecord": { "type": "object", "required": [ "protocol", "version" ], "properties": { "protocol": { "allOf": [ { "$ref": "#/components/schemas/AgentProtocol" } ], "description": "The protocol type." }, "version": { "type": "string", "description": "The version string for the protocol, e.g. 'v0.1.1'." } }, "description": "A record mapping for a single protocol and its version." }, "PyTorchDistribution": { "type": "object", "required": [ "distribution_type" ], "properties": { "distribution_type": { "type": "string", "enum": [ "pytorch" ], "description": "Specifies the type of distribution framework." }, "process_count_per_instance": { "type": "integer", "format": "int32", "description": "Number of processes per node." } }, "allOf": [ { "$ref": "#/components/schemas/DistributionConfiguration" } ], "description": "PyTorch distribution configuration." }, "QueueSettings": { "type": "object", "properties": { "job_tier": { "type": "string", "description": "Controls the compute job tier." } }, "description": "Queue settings for the job." }, "RaiConfig": { "type": "object", "required": [ "rai_policy_name" ], "properties": { "rai_policy_name": { "type": "string", "description": "The name of the RAI policy to apply." } }, "description": "Configuration for Responsible AI (RAI) content filtering and safety features." }, "RayDistribution": { "type": "object", "required": [ "distribution_type" ], "properties": { "distribution_type": { "type": "string", "enum": [ "ray" ], "description": "Specifies the type of distribution framework." }, "port": { "type": "integer", "format": "int32", "description": "The port of the head Ray process." }, "address": { "type": "string", "description": "The address of the Ray head node." }, "include_dashboard": { "type": "boolean", "description": "Whether to start the Ray dashboard GUI." }, "dashboard_port": { "type": "integer", "format": "int32", "description": "The port to bind the dashboard server to." }, "head_node_additional_args": { "type": "string", "description": "Additional arguments passed to ray start on the head node." }, "worker_node_additional_args": { "type": "string", "description": "Additional arguments passed to ray start on worker nodes." }, "enable_remote_access_client_server": { "type": "boolean", "description": "Whether to expose the Ray Client server port through the AML proxy for remote access. When true, the Ray Client port is registered as an interactive endpoint, enabling remote ray.init() connections via the WebSocket-TCP bridge. When false or omitted, the Ray Client port is not accessible externally." }, "client_server_port": { "type": "integer", "format": "int32", "description": "The port for the Ray Client server. Defaults to 10001. Only relevant when enable_remote_access_client_server is true." } }, "allOf": [ { "$ref": "#/components/schemas/DistributionConfiguration" } ], "description": "Ray distribution configuration." }, "RecurrenceSchedule": { "type": "object", "required": [ "type" ], "properties": { "type": { "allOf": [ { "$ref": "#/components/schemas/RecurrenceType" } ], "description": "Recurrence type for the recurrence schedule." } }, "discriminator": { "propertyName": "type", "mapping": { "Hourly": "#/components/schemas/HourlyRecurrenceSchedule", "Daily": "#/components/schemas/DailyRecurrenceSchedule", "Weekly": "#/components/schemas/WeeklyRecurrenceSchedule", "Monthly": "#/components/schemas/MonthlyRecurrenceSchedule" } }, "description": "Recurrence schedule model." }, "RecurrenceTrigger": { "type": "object", "required": [ "type", "interval", "schedule" ], "properties": { "type": { "type": "string", "enum": [ "Recurrence" ], "description": "Type of the trigger." }, "startTime": { "type": "string", "description": "Start time for the recurrence schedule in ISO 8601 format." }, "endTime": { "type": "string", "description": "End time for the recurrence schedule in ISO 8601 format." }, "timeZone": { "type": "string", "description": "Time zone for the recurrence schedule.", "default": "UTC" }, "interval": { "type": "integer", "format": "int32", "description": "Interval for the recurrence schedule." }, "schedule": { "allOf": [ { "$ref": "#/components/schemas/RecurrenceSchedule" } ], "description": "Recurrence schedule for the recurrence trigger." } }, "allOf": [ { "$ref": "#/components/schemas/Trigger" } ], "description": "Recurrence based trigger." }, "RecurrenceType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "Hourly", "Daily", "Weekly", "Monthly" ] } ], "description": "Recurrence type." }, "RedTeam": { "type": "object", "required": [ "id", "target" ], "properties": { "id": { "type": "string", "description": "Identifier of the red team run.", "readOnly": true }, "displayName": { "type": "string", "description": "Name of the red-team run." }, "numTurns": { "type": "integer", "format": "int32", "description": "Number of simulation rounds." }, "attackStrategies": { "type": "array", "items": { "$ref": "#/components/schemas/AttackStrategy" }, "description": "List of attack strategies or nested lists of attack strategies." }, "simulationOnly": { "type": "boolean", "description": "Simulation-only or Simulation + Evaluation. Default false, if true the scan outputs conversation not evaluation result.", "default": false }, "riskCategories": { "type": "array", "items": { "$ref": "#/components/schemas/RiskCategory" }, "description": "List of risk categories to generate attack objectives for." }, "applicationScenario": { "type": "string", "description": "Application scenario for the red team operation, to generate scenario specific attacks." }, "tags": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Red team's tags. Unlike properties, tags are fully mutable." }, "properties": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Red team's properties. Unlike tags, properties are add-only. Once added, a property cannot be removed." }, "status": { "type": "string", "description": "Status of the red-team. It is set by service and is read-only.", "readOnly": true }, "target": { "allOf": [ { "$ref": "#/components/schemas/TargetConfig" } ], "description": "Target configuration for the red-team run." } }, "description": "Red team details." }, "RedTeamEvalRunDataSource": { "type": "object", "required": [ "type", "item_generation_params", "target" ], "properties": { "type": { "type": "string", "enum": [ "azure_ai_red_team" ], "description": "The type of data source. Always `azure_ai_red_team`." }, "item_generation_params": { "allOf": [ { "$ref": "#/components/schemas/ItemGenerationParams" } ], "description": "The parameters for item generation." }, "target": { "allOf": [ { "$ref": "#/components/schemas/Target" } ], "description": "The target configuration for the evaluation." } }, "allOf": [ { "$ref": "#/components/schemas/EvalRunDataSource" } ] }, "RedTeamItemGenerationParams": { "type": "object", "required": [ "type", "attack_strategies", "num_turns" ], "properties": { "type": { "type": "string", "enum": [ "red_team" ], "description": "The type of item generation parameters." }, "attack_strategies": { "type": "array", "items": { "$ref": "#/components/schemas/AttackStrategy" }, "description": "The collection of attack strategies to be used." }, "num_turns": { "type": "integer", "format": "int32", "description": "The number of turns allowed in the game.", "default": 20 } }, "allOf": [ { "$ref": "#/components/schemas/ItemGenerationParams" } ] }, "RedTeamSeedPromptsItemGenerationParams": { "type": "object", "required": [ "type", "attack_strategies", "num_turns", "source" ], "properties": { "type": { "type": "string", "enum": [ "red_team_seed_prompts" ], "description": "The type of item generation parameters, always `red_team_seed_prompts`." }, "attack_strategies": { "type": "array", "items": { "$ref": "#/components/schemas/AttackStrategy" }, "description": "The collection of attack strategies to be used." }, "num_turns": { "type": "integer", "format": "int32", "description": "The number of turns allowed in the game.", "default": 20 }, "source": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.EvalJsonlFileContentSource" } ], "description": "The source of JSONL content to be processed." } }, "allOf": [ { "$ref": "#/components/schemas/ItemGenerationParams" } ], "description": "Represents the parameters for red team seed prompts item generation." }, "RedTeamTaxonomyItemGenerationParams": { "type": "object", "required": [ "type", "attack_strategies", "num_turns", "source" ], "properties": { "type": { "type": "string", "enum": [ "red_team_taxonomy" ], "description": "The type of item generation parameters, always `red_team_taxonomy`." }, "attack_strategies": { "type": "array", "items": { "$ref": "#/components/schemas/AttackStrategy" }, "description": "The collection of attack strategies to be used." }, "num_turns": { "type": "integer", "format": "int32", "description": "The number of turns allowed in the game.", "default": 20 }, "source": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.EvalJsonlFileContentSource" } ], "description": "The source from which JSONL content is read." } }, "allOf": [ { "$ref": "#/components/schemas/ItemGenerationParams" } ], "description": "Represents the parameters for red team taxonomy item generation." }, "ReinforcePpTrainingConfiguration": { "type": "object", "required": [ "algorithm", "reward" ], "properties": { "algorithm": { "type": "string", "enum": [ "reinforce_pp" ], "description": "Training algorithm, always 'reinforce_pp'." }, "reward": { "allOf": [ { "$ref": "#/components/schemas/TrainingRewardConfiguration" } ], "description": "Reward signal configuration." }, "lora": { "allOf": [ { "$ref": "#/components/schemas/TrainingLoraConfiguration" } ], "description": "LoRA adapter configuration." }, "rollout": { "allOf": [ { "$ref": "#/components/schemas/TrainingRolloutConfiguration" } ], "description": "Rollout generation configuration." }, "eval": { "allOf": [ { "$ref": "#/components/schemas/TrainingEvalConfiguration" } ], "description": "Evaluation configuration." } }, "allOf": [ { "$ref": "#/components/schemas/TrainingConfiguration" } ], "description": "REINFORCE++ training recipe." }, "ResponseRetrievalItemGenerationParams": { "type": "object", "required": [ "type", "max_num_turns", "data_mapping", "source" ], "properties": { "type": { "type": "string", "enum": [ "response_retrieval" ], "description": "The type of item generation parameters, always `response_retrieval`." }, "max_num_turns": { "type": "integer", "format": "int32", "description": "The maximum number of turns of chat history to evaluate." }, "data_mapping": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Mapping from source fields to response_id field, required for retrieving chat history." }, "source": { "anyOf": [ { "$ref": "#/components/schemas/OpenAI.EvalJsonlFileContentSource" }, { "$ref": "#/components/schemas/OpenAI.EvalJsonlFileIdSource" } ], "description": "The source from which JSONL content is read." } }, "allOf": [ { "$ref": "#/components/schemas/ItemGenerationParams" } ], "description": "Represents the parameters for response retrieval item generation." }, "RewardModelTrainingConfiguration": { "type": "object", "required": [ "algorithm" ], "properties": { "algorithm": { "type": "string", "enum": [ "reward_model" ], "description": "Training algorithm, always 'reward_model'." }, "lora": { "allOf": [ { "$ref": "#/components/schemas/TrainingLoraConfiguration" } ], "description": "LoRA adapter configuration." }, "eval": { "allOf": [ { "$ref": "#/components/schemas/TrainingEvalConfiguration" } ], "description": "Evaluation configuration." } }, "allOf": [ { "$ref": "#/components/schemas/TrainingConfiguration" } ], "description": "Reward model training recipe." }, "RewardModelTrainingDatasetConfiguration": { "type": "object", "required": [ "kind" ], "properties": { "kind": { "type": "string", "description": "Reward-model dataset kind." } }, "discriminator": { "propertyName": "kind", "mapping": { "pairwise": "#/components/schemas/PairwiseRewardModelTrainingDatasetConfiguration", "scored": "#/components/schemas/ScoredRewardModelTrainingDatasetConfiguration" } }, "description": "Dataset configuration for managed reward-model training." }, "RewardModelTrainingJob": { "type": "object", "required": [ "type", "dataset" ], "properties": { "type": { "type": "string", "enum": [ "reward_model" ], "description": "Managed training job type, always 'reward_model'." }, "dataset": { "allOf": [ { "$ref": "#/components/schemas/RewardModelTrainingDatasetConfiguration" } ], "description": "Training and optional evaluation datasets." }, "runtime": { "allOf": [ { "$ref": "#/components/schemas/RewardModelTrainingRuntimeConfiguration" } ], "description": "Runtime options for managed reward-model training." } }, "allOf": [ { "$ref": "#/components/schemas/ModelTrainingJobCreate" } ], "description": "Request body for creating a managed reward-model training job from a base model." }, "RewardModelTrainingLoss": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "bradley_terry", "regression" ] } ], "description": "Loss function used for reward-model training." }, "RewardModelTrainingRuntimeConfiguration": { "type": "object", "properties": { "framework": { "allOf": [ { "$ref": "#/components/schemas/TrainingFramework" } ], "description": "Training framework implementation. If omitted, the service selects a compatible framework." }, "hyperparameters": { "type": "object", "additionalProperties": {}, "description": "Algorithm-specific hyperparameters passed through to the selected framework." }, "loss": { "allOf": [ { "$ref": "#/components/schemas/RewardModelTrainingLoss" } ], "description": "Loss function used for reward-model training." }, "lora": { "allOf": [ { "$ref": "#/components/schemas/TrainingLoraConfiguration" } ], "description": "LoRA adapter configuration." }, "eval": { "allOf": [ { "$ref": "#/components/schemas/TrainingEvalConfiguration" } ], "description": "Evaluation configuration." }, "packaging": { "allOf": [ { "$ref": "#/components/schemas/ModelTrainingPackagingConfiguration" } ], "description": "Model artifact packaging options." } }, "description": "Runtime options for managed reward-model training." }, "RiskCategory": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "HateUnfairness", "Violence", "Sexual", "SelfHarm", "ProtectedMaterial", "CodeVulnerability", "UngroundedAttributes", "ProhibitedActions", "SensitiveDataLeakage", "TaskAdherence" ] } ], "description": "Risk category for the attack objective." }, "RlooTrainingConfiguration": { "type": "object", "required": [ "algorithm", "reward" ], "properties": { "algorithm": { "type": "string", "enum": [ "rloo" ], "description": "Training algorithm, always 'rloo'." }, "reward": { "allOf": [ { "$ref": "#/components/schemas/TrainingRewardConfiguration" } ], "description": "Reward signal configuration." }, "lora": { "allOf": [ { "$ref": "#/components/schemas/TrainingLoraConfiguration" } ], "description": "LoRA adapter configuration." }, "rollout": { "allOf": [ { "$ref": "#/components/schemas/TrainingRolloutConfiguration" } ], "description": "Rollout generation configuration." }, "eval": { "allOf": [ { "$ref": "#/components/schemas/TrainingEvalConfiguration" } ], "description": "Evaluation configuration." } }, "allOf": [ { "$ref": "#/components/schemas/TrainingConfiguration" } ], "description": "REINFORCE leave-one-out training recipe." }, "SASCredentials": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "SAS" ], "description": "The credential type", "readOnly": true }, "SAS": { "type": "string", "description": "SAS token", "readOnly": true } }, "allOf": [ { "$ref": "#/components/schemas/BaseCredentials" } ], "description": "Shared Access Signature (SAS) credential definition" }, "SampleType": { "anyOf": [ { "type": "string", "enum": [ "EvaluationResultSample" ] }, { "type": "string" } ], "description": "The type of sample used in the analysis." }, "SasCredential": { "type": "object", "required": [ "sasUri", "type" ], "properties": { "sasUri": { "type": "string", "description": "SAS uri", "readOnly": true }, "type": { "type": "string", "enum": [ "SAS" ], "description": "Type of credential", "readOnly": true } }, "description": "SAS Credential definition" }, "Schedule": { "type": "object", "required": [ "id", "enabled", "trigger", "task", "systemData" ], "properties": { "id": { "type": "string", "description": "Identifier of the schedule.", "readOnly": true }, "displayName": { "type": "string", "description": "Name of the schedule." }, "description": { "type": "string", "description": "Description of the schedule." }, "enabled": { "type": "boolean", "description": "Enabled status of the schedule." }, "provisioningStatus": { "allOf": [ { "$ref": "#/components/schemas/ScheduleProvisioningStatus" } ], "description": "Provisioning status of the schedule.", "readOnly": true }, "trigger": { "allOf": [ { "$ref": "#/components/schemas/Trigger" } ], "description": "Trigger for the schedule." }, "task": { "allOf": [ { "$ref": "#/components/schemas/ScheduleTask" } ], "description": "Task for the schedule." }, "tags": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Schedule's tags. Unlike properties, tags are fully mutable." }, "properties": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Schedule's properties. Unlike tags, properties are add-only. Once added, a property cannot be removed." }, "systemData": { "type": "object", "additionalProperties": { "type": "string" }, "description": "System metadata for the resource.", "readOnly": true } }, "description": "Schedule model." }, "ScheduleProvisioningStatus": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "Creating", "Updating", "Deleting", "Succeeded", "Failed" ] } ], "description": "Schedule provisioning status." }, "ScheduleRun": { "type": "object", "required": [ "id", "scheduleId", "success", "properties" ], "properties": { "id": { "type": "string", "description": "Identifier of the schedule run.", "readOnly": true }, "scheduleId": { "type": "string", "description": "Identifier of the schedule." }, "success": { "type": "boolean", "description": "Trigger success status of the schedule run.", "readOnly": true }, "triggerTime": { "type": "string", "description": "Trigger time of the schedule run." }, "error": { "type": "string", "description": "Error information for the schedule run.", "readOnly": true }, "properties": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Properties of the schedule run.", "readOnly": true } }, "description": "Schedule run model." }, "ScheduleTask": { "type": "object", "required": [ "type" ], "properties": { "type": { "allOf": [ { "$ref": "#/components/schemas/ScheduleTaskType" } ], "description": "Type of the task." }, "configuration": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Configuration for the task." } }, "discriminator": { "propertyName": "type", "mapping": { "Evaluation": "#/components/schemas/EvaluationScheduleTask", "Insight": "#/components/schemas/InsightScheduleTask" } }, "description": "Schedule task model." }, "ScheduleTaskType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "Evaluation", "Insight" ] } ], "description": "Type of the task." }, "ScoredRewardModelColumnMapping": { "type": "object", "required": [ "prompt", "response", "score" ], "properties": { "prompt": { "type": "string", "description": "Actual dataset column name containing prompts, for example 'prompt' or 'question'." }, "response": { "type": "string", "description": "Actual dataset column name containing responses, for example 'response' or 'completion'." }, "score": { "type": "string", "description": "Actual dataset column name containing numeric reward scores, for example 'score' or 'reward'." } }, "description": "Column mapping for scored reward-model datasets. Keys are logical fields expected by scored reward-model training; values are the exact column names in the referenced dataset asset." }, "ScoredRewardModelTrainingDatasetConfiguration": { "type": "object", "required": [ "kind", "train", "columns" ], "properties": { "kind": { "type": "string", "enum": [ "scored" ], "description": "Reward-model dataset kind, always 'scored'." }, "train": { "type": "string", "description": "Training dataset asset reference." }, "eval": { "type": "string", "description": "Optional evaluation dataset asset reference." }, "columns": { "allOf": [ { "$ref": "#/components/schemas/ScoredRewardModelColumnMapping" } ], "description": "Mapping from scored reward-model logical fields to actual dataset column names. Scored reward-model training requires 'prompt', 'response', and 'score'." }, "data_format": { "allOf": [ { "$ref": "#/components/schemas/TrainingDataFormatConfiguration" } ], "description": "Conversational data formatting options." } }, "allOf": [ { "$ref": "#/components/schemas/RewardModelTrainingDatasetConfiguration" } ], "description": "Scored response dataset for managed reward-model training." }, "SftTrainingColumnMapping": { "type": "object", "required": [ "messages" ], "properties": { "messages": { "type": "string", "description": "Actual dataset column name containing chat messages used for supervised fine tuning, for example 'messages' or 'conversation_json'." } }, "description": "Column mapping for managed SFT datasets. Keys are logical fields expected by SFT; values are the exact column names in the referenced dataset asset. The training dataset must contain chat messages for each training example." }, "SftTrainingConfiguration": { "type": "object", "required": [ "algorithm" ], "properties": { "algorithm": { "type": "string", "enum": [ "sft" ], "description": "Training algorithm, always 'sft'." }, "lora": { "allOf": [ { "$ref": "#/components/schemas/TrainingLoraConfiguration" } ], "description": "LoRA adapter configuration." }, "eval": { "allOf": [ { "$ref": "#/components/schemas/TrainingEvalConfiguration" } ], "description": "Evaluation configuration." } }, "allOf": [ { "$ref": "#/components/schemas/TrainingConfiguration" } ], "description": "Supervised fine-tuning recipe." }, "SftTrainingDatasetConfiguration": { "type": "object", "required": [ "train", "columns" ], "properties": { "train": { "type": "string", "description": "Training dataset asset reference." }, "eval": { "type": "string", "description": "Optional evaluation dataset asset reference." }, "columns": { "allOf": [ { "$ref": "#/components/schemas/SftTrainingColumnMapping" } ], "description": "Mapping from SFT logical fields to actual dataset column names. SFT requires the 'messages' logical field." }, "data_format": { "allOf": [ { "$ref": "#/components/schemas/TrainingDataFormatConfiguration" } ], "description": "Conversational data formatting options." } }, "description": "Dataset configuration for managed supervised fine tuning." }, "SftTrainingJob": { "type": "object", "required": [ "type", "dataset" ], "properties": { "type": { "type": "string", "enum": [ "sft" ], "description": "Managed training job type, always 'sft'." }, "dataset": { "allOf": [ { "$ref": "#/components/schemas/SftTrainingDatasetConfiguration" } ], "description": "Training and optional evaluation datasets." }, "runtime": { "allOf": [ { "$ref": "#/components/schemas/SftTrainingRuntimeConfiguration" } ], "description": "Runtime options for managed SFT." } }, "allOf": [ { "$ref": "#/components/schemas/ModelTrainingJobCreate" } ], "description": "Request body for creating a managed SFT training job from a base model." }, "SftTrainingRuntimeConfiguration": { "type": "object", "properties": { "framework": { "allOf": [ { "$ref": "#/components/schemas/TrainingFramework" } ], "description": "Training framework implementation. If omitted, the service selects a compatible framework." }, "hyperparameters": { "type": "object", "additionalProperties": {}, "description": "Algorithm-specific hyperparameters passed through to the selected framework." }, "lora": { "allOf": [ { "$ref": "#/components/schemas/TrainingLoraConfiguration" } ], "description": "LoRA adapter configuration." }, "eval": { "allOf": [ { "$ref": "#/components/schemas/TrainingEvalConfiguration" } ], "description": "Evaluation configuration." }, "packaging": { "allOf": [ { "$ref": "#/components/schemas/ModelTrainingPackagingConfiguration" } ], "description": "Model artifact packaging options." } }, "description": "Runtime options for managed supervised fine tuning." }, "SharepointGroundingToolCall": { "type": "object", "required": [ "type", "call_id", "arguments", "status" ], "properties": { "type": { "type": "string", "enum": [ "sharepoint_grounding_preview_call" ] }, "call_id": { "type": "string", "description": "The unique ID of the tool call generated by the model." }, "arguments": { "type": "string", "description": "A JSON string of the arguments to pass to the tool." }, "status": { "allOf": [ { "$ref": "#/components/schemas/ToolCallStatus" } ], "description": "The status of the tool call." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ], "description": "A SharePoint grounding tool call." }, "SharepointGroundingToolCallOutput": { "type": "object", "required": [ "type", "call_id", "status" ], "properties": { "type": { "type": "string", "enum": [ "sharepoint_grounding_preview_call_output" ] }, "call_id": { "type": "string", "description": "The unique ID of the tool call generated by the model." }, "output": { "allOf": [ { "$ref": "#/components/schemas/ToolCallOutputContent" } ], "description": "The output from the SharePoint grounding tool call." }, "status": { "allOf": [ { "$ref": "#/components/schemas/ToolCallStatus" } ], "description": "The status of the tool call." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ], "description": "The output of a SharePoint grounding tool call." }, "SharepointGroundingToolParameters": { "type": "object", "properties": { "name": { "type": "string", "description": "Optional user-defined name for this tool or configuration." }, "description": { "type": "string", "description": "Optional user-defined description for this tool or configuration." }, "project_connections": { "type": "array", "items": { "$ref": "#/components/schemas/ToolProjectConnection" }, "maxItems": 1, "description": "The project connections attached to this tool. There can be a maximum of 1 connection\nresource attached to the tool." } }, "description": "The sharepoint grounding tool parameters." }, "SharepointPreviewTool": { "type": "object", "required": [ "type", "sharepoint_grounding_preview" ], "properties": { "type": { "type": "string", "enum": [ "sharepoint_grounding_preview" ], "description": "The object type, which is always 'sharepoint_grounding_preview'." }, "name": { "type": "string", "description": "Optional user-defined name for this tool or configuration." }, "description": { "type": "string", "description": "Optional user-defined description for this tool or configuration." }, "sharepoint_grounding_preview": { "allOf": [ { "$ref": "#/components/schemas/SharepointGroundingToolParameters" } ], "description": "The sharepoint grounding tool parameters." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Tool" } ], "description": "The input definition information for a sharepoint tool as used to configure an agent." }, "SimPoTrainingConfiguration": { "type": "object", "required": [ "algorithm" ], "properties": { "algorithm": { "type": "string", "enum": [ "simpo" ], "description": "Training algorithm, always 'simpo'." }, "lora": { "allOf": [ { "$ref": "#/components/schemas/TrainingLoraConfiguration" } ], "description": "LoRA adapter configuration." }, "eval": { "allOf": [ { "$ref": "#/components/schemas/TrainingEvalConfiguration" } ], "description": "Evaluation configuration." } }, "allOf": [ { "$ref": "#/components/schemas/TrainingConfiguration" } ], "description": "Simple preference optimization training recipe." }, "SkillObject": { "type": "object", "required": [ "object", "skill_id", "has_blob", "name" ], "properties": { "object": { "allOf": [ { "$ref": "#/components/schemas/SkillObjectType" } ], "description": "The object type, which is always 'skill'.", "default": "skill" }, "skill_id": { "type": "string", "description": "The unique identifier of the skill." }, "has_blob": { "type": "boolean", "description": "Whether the skill was created from a GZip blob package." }, "name": { "type": "string", "maxLength": 63, "description": "The unique name of the skill." }, "description": { "type": "string", "maxLength": 1024, "description": "A human-readable description of the skill." }, "metadata": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Set of key-value pairs associated with the skill." } }, "description": "A skill object." }, "SkillObjectType": { "type": "string", "enum": [ "skill", "skill.deleted" ], "description": "The object type of a skill resource." }, "Sku": { "type": "object", "required": [ "capacity", "family", "name", "size", "tier" ], "properties": { "capacity": { "type": "integer", "format": "int64", "description": "Sku capacity" }, "family": { "type": "string", "description": "Sku family" }, "name": { "type": "string", "description": "Sku name" }, "size": { "type": "string", "description": "Sku size" }, "tier": { "type": "string", "description": "Sku tier" } }, "description": "Sku information" }, "StructuredInputDefinition": { "type": "object", "properties": { "description": { "type": "string", "description": "A human-readable description of the input." }, "default_value": { "description": "The default value for the input if no run-time value is provided." }, "schema": { "type": "object", "additionalProperties": {}, "description": "The JSON schema for the structured input (optional)." }, "required": { "type": "boolean", "description": "Whether the input property is required when the agent is invoked.", "default": false } }, "description": "An structured input that can participate in prompt template substitutions and tool argument binding." }, "StructuredOutputDefinition": { "type": "object", "required": [ "name", "description", "schema", "strict" ], "properties": { "name": { "type": "string", "description": "The name of the structured output." }, "description": { "type": "string", "description": "A description of the output to emit. Used by the model to determine when to emit the output." }, "schema": { "type": "object", "additionalProperties": {}, "description": "The JSON schema for the structured output." }, "strict": { "type": "boolean", "nullable": true, "description": "Whether to enforce strict validation. Default `true`." } }, "description": "A structured output that can be produced by the agent." }, "StructuredOutputsOutputItem": { "type": "object", "required": [ "type", "output" ], "properties": { "type": { "type": "string", "enum": [ "structured_outputs" ] }, "output": { "description": "The structured output captured during the response." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ] }, "SyntheticDataGenerationPreviewEvalRunDataSource": { "type": "object", "required": [ "type", "item_generation_params", "target" ], "properties": { "type": { "type": "string", "enum": [ "azure_ai_synthetic_data_gen_preview" ], "description": "The type of data source, always `azure_ai_synthetic_data_gen_preview`." }, "item_generation_params": { "allOf": [ { "$ref": "#/components/schemas/SyntheticDataGenerationPreviewItemGenerationParams" } ], "description": "The parameters for item generation." }, "target": { "allOf": [ { "$ref": "#/components/schemas/Target" } ], "description": "The target configuration for the evaluation." }, "input_messages": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.CreateEvalResponsesRunDataSourceInputMessagesTemplate" } ], "description": "Input messages template configuration applicable only if target is of type 'azure_ai_model'" } }, "allOf": [ { "$ref": "#/components/schemas/EvalRunDataSource" } ], "description": "Represents a data source for evaluation runs that evaluates based on generated synthetic data for testing purposes." }, "SyntheticDataGenerationPreviewItemGenerationParams": { "type": "object", "required": [ "type", "samples_count", "model_deployment_name", "sources" ], "properties": { "type": { "type": "string", "enum": [ "synthetic_data_gen_preview" ], "description": "The type of item generation parameters." }, "samples_count": { "type": "integer", "format": "int32", "description": "The maximum number of data samples to generate." }, "prompt": { "type": "string", "description": "The prompt used for generating synthetic data. This is option if target is of type 'azure_ai_agent' with instructions configured in agent." }, "model_deployment_name": { "type": "string", "description": "The name of the model deployment to use for generating synthetic data." }, "output_dataset_name": { "type": "string", "description": "The name of the output dataset where generated synthetic data will be stored. If not provided, service generates dataset name automatically." }, "output_dataset_id": { "type": "string", "description": "The identifier of the output dataset where generated synthetic data is stored. The generated data is a jsonl file with columns id, query and test_description.", "readOnly": true }, "sources": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.EvalJsonlFileIdSource" }, "description": "The optional seed data content source files for data generation." } }, "allOf": [ { "$ref": "#/components/schemas/ItemGenerationParams" } ] }, "SystemData": { "type": "object", "properties": { "created_by": { "type": "string", "description": "The identity that created the resource.", "readOnly": true }, "created_by_type": { "type": "string", "description": "The type of identity that created the resource.", "readOnly": true }, "created_at": { "allOf": [ { "$ref": "#/components/schemas/FoundryTimestamp" } ], "description": "The timestamp of resource creation (UTC).", "readOnly": true }, "last_modified_by": { "type": "string", "description": "The identity that last modified the resource.", "readOnly": true }, "last_modified_by_type": { "type": "string", "description": "The type of identity that last modified the resource.", "readOnly": true }, "last_modified_at": { "allOf": [ { "$ref": "#/components/schemas/FoundryTimestamp" } ], "description": "The timestamp of resource last modification (UTC).", "readOnly": true } }, "description": "Metadata pertaining to creation and last modification of the resource." }, "Target": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "description": "The type of target." } }, "discriminator": { "propertyName": "type", "mapping": { "azure_ai_model": "#/components/schemas/AzureAIModelTarget", "azure_ai_agent": "#/components/schemas/AzureAIAgentTarget" } }, "description": "Base class for targets with discriminator support." }, "TargetCompletionEvalRunDataSource": { "type": "object", "required": [ "type", "source", "target" ], "properties": { "type": { "type": "string", "enum": [ "azure_ai_target_completions" ], "description": "The type of data source, always `azure_ai_target_completions`." }, "input_messages": { "allOf": [ { "$ref": "#/components/schemas/OpenAI.CreateEvalCompletionsRunDataSourceInputMessagesItemReference" } ], "description": "Input messages configuration." }, "source": { "anyOf": [ { "$ref": "#/components/schemas/OpenAI.EvalJsonlFileContentSource" }, { "$ref": "#/components/schemas/OpenAI.EvalJsonlFileIdSource" } ], "description": "The source configuration for inline or file data." }, "target": { "allOf": [ { "$ref": "#/components/schemas/Target" } ], "description": "The target configuration for the evaluation." } }, "allOf": [ { "$ref": "#/components/schemas/EvalRunDataSource" } ], "description": "Represents a data source for target-based completion evaluation configuration." }, "TargetConfig": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "description": "Type of the model configuration." } }, "discriminator": { "propertyName": "type", "mapping": { "AzureOpenAIModel": "#/components/schemas/AzureOpenAIModelConfiguration" } }, "description": "Abstract class for target configuration." }, "TargetUpdate": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "description": "The type of target." } }, "discriminator": { "propertyName": "type", "mapping": { "azure_ai_model": "#/components/schemas/AzureAIModelTargetUpdate", "azure_ai_agent": "#/components/schemas/AzureAIAgentTargetUpdate" } }, "description": "Base class for targets with discriminator support." }, "TaxonomyCategory": { "type": "object", "required": [ "id", "name", "riskCategory", "subCategories" ], "properties": { "id": { "type": "string", "description": "Unique identifier of the taxonomy category." }, "name": { "type": "string", "description": "Name of the taxonomy category." }, "description": { "type": "string", "description": "Description of the taxonomy category." }, "riskCategory": { "allOf": [ { "$ref": "#/components/schemas/RiskCategory" } ], "description": "Risk category associated with this taxonomy category." }, "subCategories": { "type": "array", "items": { "$ref": "#/components/schemas/TaxonomySubCategory" }, "description": "List of taxonomy sub categories." }, "properties": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Additional properties for the taxonomy category." } }, "description": "Taxonomy category definition." }, "TaxonomySubCategory": { "type": "object", "required": [ "id", "name", "enabled" ], "properties": { "id": { "type": "string", "description": "Unique identifier of the taxonomy sub-category." }, "name": { "type": "string", "description": "Name of the taxonomy sub-category." }, "description": { "type": "string", "description": "Description of the taxonomy sub-category." }, "enabled": { "type": "boolean", "description": "List of taxonomy items under this sub-category." }, "properties": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Additional properties for the taxonomy sub-category." } }, "description": "Taxonomy sub-category definition." }, "TensorFlowDistribution": { "type": "object", "required": [ "distribution_type" ], "properties": { "distribution_type": { "type": "string", "enum": [ "tensorflow" ], "description": "Specifies the type of distribution framework." }, "worker_count": { "type": "integer", "format": "int32", "description": "Number of workers. If not specified, will default to the instance count." }, "parameter_server_count": { "type": "integer", "format": "int32", "description": "Number of parameter server tasks." } }, "allOf": [ { "$ref": "#/components/schemas/DistributionConfiguration" } ], "description": "TensorFlow distribution configuration." }, "ToolCallOutputContent": { "anyOf": [ { "type": "object", "additionalProperties": {} }, { "type": "string" }, { "type": "array", "items": {} } ], "description": "The output content from a tool call, which can be a dictionary, string, or array." }, "ToolCallStatus": { "type": "string", "enum": [ "in_progress", "completed", "incomplete", "failed" ], "description": "The status of a tool call." }, "ToolDescription": { "type": "object", "properties": { "name": { "type": "string", "description": "The name of the tool." }, "description": { "type": "string", "description": "A brief description of the tool's purpose." } }, "description": "Description of a tool that can be used by an agent." }, "ToolProjectConnection": { "type": "object", "required": [ "project_connection_id" ], "properties": { "name": { "type": "string", "description": "Optional user-defined name for this tool or configuration." }, "description": { "type": "string", "description": "Optional user-defined description for this tool or configuration." }, "project_connection_id": { "type": "string", "description": "A project connection in a ToolProjectConnectionList attached to this tool." } }, "description": "A project connection resource." }, "ToolsetObject": { "type": "object", "required": [ "object", "id", "created_at", "updated_at", "name", "tools" ], "properties": { "object": { "type": "string", "enum": [ "toolset" ], "description": "The object type, which is always 'toolset'." }, "id": { "type": "string", "description": "The unique identifier of the toolset." }, "created_at": { "type": "integer", "format": "unixtime", "description": "The Unix timestamp (seconds) when the toolset was created." }, "updated_at": { "type": "integer", "format": "unixtime", "description": "The Unix timestamp (seconds) when the toolset was last updated." }, "name": { "type": "string", "maxLength": 256, "description": "The name of the toolset." }, "description": { "type": "string", "maxLength": 512, "description": "A human-readable description of the toolset." }, "metadata": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Arbitrary key-value metadata to associate with the toolset." }, "tools": { "type": "array", "items": { "$ref": "#/components/schemas/OpenAI.Tool" }, "description": "The list of tools contained in this toolset." } }, "description": "A toolset that stores reusable tool definitions for agents." }, "TracesPreviewEvalRunDataSource": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "enum": [ "azure_ai_traces_preview" ], "description": "The type of data source, always `azure_ai_traces_preview`." }, "trace_ids": { "type": "array", "items": { "type": "string" }, "description": "Collection of Agent trace identifiers that should be evaluated." }, "agent_id": { "type": "string", "description": "The agent ID used to filter traces for evaluation." }, "agent_name": { "type": "string", "description": "The agent name used to filter traces for evaluation." }, "lookback_hours": { "type": "integer", "format": "int32", "description": "Lookback window (in hours) applied when retrieving traces from Application Insights.\n For scheduled evaluations this is inferred from the recurrence interval.", "default": 168 }, "end_time": { "type": "integer", "format": "unixtime", "description": "Unix timestamp (in seconds) marking the end of the trace query window. Defaults to the current time." }, "max_traces": { "type": "integer", "format": "int32", "description": "Sampling limit applied to traces retrieved for evaluation.", "default": 1000 }, "ingestion_delay_seconds": { "type": "integer", "format": "int32", "description": "The delay to apply for ingestion when querying traces.", "default": 300 } }, "allOf": [ { "$ref": "#/components/schemas/EvalRunDataSource" } ], "description": "Represents a data source for evaluation runs that operate over Agent traces stored in Application Insights." }, "TrainingAlgorithm": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "sft", "dpo", "kto", "orpo", "cpo", "simpo", "grpo", "ppo", "rloo", "reinforce_pp", "reward_model" ] } ], "description": "Training algorithm used by a declarative training job." }, "TrainingBuiltinRewardConfiguration": { "type": "object", "required": [ "kind", "type" ], "properties": { "kind": { "type": "string", "enum": [ "builtin" ], "description": "Reward or judge signal kind, always 'builtin'." }, "type": { "allOf": [ { "$ref": "#/components/schemas/TrainingBuiltinRewardType" } ], "description": "Built-in reward or verifier type." }, "configuration": { "type": "object", "additionalProperties": {}, "description": "Optional verifier configuration." } }, "allOf": [ { "$ref": "#/components/schemas/TrainingRewardConfiguration" } ], "description": "Built-in reward or verifier used as a judge." }, "TrainingBuiltinRewardType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "exact_match", "regex", "math_equivalence", "unit_tests" ] } ], "description": "Built-in reward or verifier type." }, "TrainingColumnMapping": { "type": "object", "properties": { "prompt": { "type": "string", "description": "Column containing prompts." }, "chosen": { "type": "string", "description": "Column containing chosen responses for preference training." }, "rejected": { "type": "string", "description": "Column containing rejected responses for preference training." }, "reference": { "type": "string", "description": "Column containing reference answers or reward context." }, "messages": { "type": "string", "description": "Column containing chat messages." }, "response": { "type": "string", "description": "Column containing responses for KTO or scored reward-model training." }, "label": { "type": "string", "description": "Column containing binary desirability labels for KTO training." }, "score": { "type": "string", "description": "Column containing numeric reward scores for scored reward-model training." } }, "description": "Mapping from logical training fields to columns in the dataset." }, "TrainingCompositeRewardConfiguration": { "type": "object", "required": [ "kind", "rewards" ], "properties": { "kind": { "type": "string", "enum": [ "composite" ], "description": "Reward or judge signal kind, always 'composite'." }, "rewards": { "type": "array", "items": { "$ref": "#/components/schemas/TrainingWeightedRewardConfiguration" }, "description": "Weighted reward signals to combine." } }, "allOf": [ { "$ref": "#/components/schemas/TrainingRewardConfiguration" } ], "description": "Composite reward or judge made from multiple weighted reward signals." }, "TrainingConfiguration": { "type": "object", "required": [ "algorithm", "model", "dataset" ], "properties": { "algorithm": { "allOf": [ { "$ref": "#/components/schemas/TrainingAlgorithm" } ], "description": "Training algorithm." }, "framework": { "allOf": [ { "$ref": "#/components/schemas/TrainingFramework" } ], "description": "Training framework implementation. If omitted, the service selects a compatible framework for the algorithm and records the resolved framework on the job." }, "resolved_framework": { "allOf": [ { "$ref": "#/components/schemas/TrainingFramework" } ], "description": "Training framework resolved by the service.", "readOnly": true }, "framework_version": { "type": "string", "description": "Version of the resolved training framework used by the service.", "readOnly": true }, "model": { "type": "string", "description": "Base model asset reference." }, "dataset": { "allOf": [ { "$ref": "#/components/schemas/TrainingDatasetConfiguration" } ], "description": "Training and optional evaluation datasets." }, "hyperparameters": { "type": "object", "additionalProperties": {}, "description": "Algorithm-specific hyperparameters. Strongly typed SDK helpers may project common hyperparameters into richer language-specific types." } }, "discriminator": { "propertyName": "algorithm", "mapping": { "sft": "#/components/schemas/SftTrainingConfiguration", "dpo": "#/components/schemas/DpoTrainingConfiguration", "kto": "#/components/schemas/KtoTrainingConfiguration", "orpo": "#/components/schemas/OrpoTrainingConfiguration", "cpo": "#/components/schemas/CpoTrainingConfiguration", "simpo": "#/components/schemas/SimPoTrainingConfiguration", "grpo": "#/components/schemas/GrpoTrainingConfiguration", "ppo": "#/components/schemas/PpoTrainingConfiguration", "rloo": "#/components/schemas/RlooTrainingConfiguration", "reinforce_pp": "#/components/schemas/ReinforcePpTrainingConfiguration", "reward_model": "#/components/schemas/RewardModelTrainingConfiguration" } }, "description": "Declarative training recipe. When specified, command must be omitted and environment_image_reference is optional." }, "TrainingDataFormatConfiguration": { "type": "object", "properties": { "chat_template": { "allOf": [ { "$ref": "#/components/schemas/ChatTemplate" } ], "description": "Built-in chat template to apply to the dataset." }, "chat_template_path": { "type": "string", "description": "Path to a custom chat template relative to the job's code directory." } }, "description": "Formatting options for conversational training data." }, "TrainingDatasetConfiguration": { "type": "object", "required": [ "train" ], "properties": { "train": { "type": "string", "description": "Training dataset asset reference." }, "eval": { "type": "string", "description": "Optional evaluation dataset asset reference." }, "columns": { "allOf": [ { "$ref": "#/components/schemas/TrainingColumnMapping" } ], "description": "Mapping from training fields to dataset columns." }, "data_format": { "allOf": [ { "$ref": "#/components/schemas/TrainingDataFormatConfiguration" } ], "description": "Conversational data formatting options." } }, "description": "Dataset configuration for a declarative training job." }, "TrainingDeploymentRewardConfiguration": { "type": "object", "required": [ "kind", "deployment" ], "properties": { "kind": { "type": "string", "enum": [ "deployment" ], "description": "Reward or judge signal kind, always 'deployment'." }, "deployment": { "type": "string", "description": "Model deployment name or resource reference used as the judge." }, "rubric": { "type": "string", "description": "Rubric or scoring instruction for the judge deployment." } }, "allOf": [ { "$ref": "#/components/schemas/TrainingRewardConfiguration" } ], "description": "Model deployment used as an LLM judge." }, "TrainingEntryPointReference": { "type": "object", "required": [ "entry_point" ], "properties": { "entry_point": { "type": "string", "description": "Path to the Python callable in module/file.py:function format." } }, "description": "Reference to a Python callable relative to the job's code directory." }, "TrainingEvalBenchmark": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "gsm8k", "mmlu", "humaneval", "mbpp", "arc", "hellaswag" ] } ], "description": "Built-in evaluation benchmark." }, "TrainingEvalConfiguration": { "type": "object", "properties": { "benchmark": { "allOf": [ { "$ref": "#/components/schemas/TrainingEvalBenchmark" } ], "description": "Named built-in benchmark. Mutually exclusive with dataset." }, "dataset": { "type": "string", "description": "Custom evaluation dataset asset reference. Mutually exclusive with benchmark." }, "every_n_steps": { "type": "integer", "format": "int32", "description": "Evaluation frequency in training steps. Omit for end-of-training only." } }, "description": "Evaluation configuration for a declarative training job." }, "TrainingEvaluatorRewardConfiguration": { "type": "object", "required": [ "kind", "evaluator" ], "properties": { "kind": { "type": "string", "enum": [ "evaluator" ], "description": "Reward or judge signal kind, always 'evaluator'." }, "evaluator": { "type": "string", "description": "Evaluator asset reference." }, "input_mapping": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Optional evaluator input mapping." } }, "allOf": [ { "$ref": "#/components/schemas/TrainingRewardConfiguration" } ], "description": "Foundry evaluator used as a judge." }, "TrainingFramework": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "trl", "verl", "open_rlhf", "nemo_rl", "slime", "torch_forge" ] } ], "description": "Training framework used to lower a declarative training job into an execution command." }, "TrainingFunctionRewardConfiguration": { "type": "object", "required": [ "kind", "function" ], "properties": { "kind": { "type": "string", "enum": [ "function" ], "description": "Reward or judge signal kind, always 'function'." }, "function": { "allOf": [ { "$ref": "#/components/schemas/TrainingEntryPointReference" } ], "description": "Python callable used to compute reward scores." } }, "allOf": [ { "$ref": "#/components/schemas/TrainingRewardConfiguration" } ], "description": "Python callable used as a judge." }, "TrainingInlineFunctionConfiguration": { "type": "object", "required": [ "def" ], "properties": { "def": { "type": "string", "description": "Python function definition." }, "runtime": { "allOf": [ { "$ref": "#/components/schemas/TrainingInlineFunctionRuntime" } ], "description": "Runtime dependencies for the inline function." } }, "description": "Inline Python function definition for custom training logic." }, "TrainingInlineFunctionRewardConfiguration": { "type": "object", "required": [ "kind", "inline_function" ], "properties": { "kind": { "type": "string", "enum": [ "inline_function" ], "description": "Reward or judge signal kind, always 'inline_function'." }, "inline_function": { "allOf": [ { "$ref": "#/components/schemas/TrainingInlineFunctionConfiguration" } ], "description": "Inline Python function used to compute reward scores." } }, "allOf": [ { "$ref": "#/components/schemas/TrainingRewardConfiguration" } ], "description": "Inline Python function used as a judge." }, "TrainingInlineFunctionRuntime": { "type": "object", "properties": { "pip": { "type": "array", "items": { "type": "string" }, "description": "Pip packages to install before invoking the inline function." } }, "description": "Python runtime dependencies for an inline function." }, "TrainingJobService": { "type": "object", "properties": { "type": { "allOf": [ { "$ref": "#/components/schemas/JobServiceType" } ], "description": "Service type.", "readOnly": true }, "port": { "type": "integer", "format": "int32", "description": "Service port.", "readOnly": true }, "status": { "type": "string", "description": "Service status.", "readOnly": true }, "error": { "type": "object", "additionalProperties": {}, "description": "Terminal error for the service, if any.", "readOnly": true }, "endpoint": { "type": "string", "format": "uri", "description": "Service endpoint URI.", "readOnly": true }, "properties": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Additional service properties.", "readOnly": true } }, "description": "Service endpoint details for a training job." }, "TrainingJobServiceCollection": { "type": "object", "required": [ "services" ], "properties": { "services": { "type": "object", "additionalProperties": { "$ref": "#/components/schemas/TrainingJobService" }, "description": "Services keyed by service name.", "readOnly": true } }, "description": "Services exposed by a training job." }, "TrainingLoraConfiguration": { "type": "object", "required": [ "rank" ], "properties": { "rank": { "type": "integer", "format": "int32", "description": "Low-rank dimension." }, "alpha": { "type": "integer", "format": "int32", "description": "LoRA scaling factor.", "default": 16 }, "dropout": { "type": "number", "format": "double", "description": "Dropout applied to adapter inputs.", "default": 0.05 }, "target_modules": { "type": "string", "description": "Linear layers that receive adapters. Use 'auto' to let the framework choose defaults.", "default": "auto" }, "quantize": { "type": "boolean", "description": "Whether to enable QLoRA 4-bit base weight loading.", "default": false } }, "description": "LoRA adapter configuration for parameter-efficient fine tuning." }, "TrainingModelRewardConfiguration": { "type": "object", "required": [ "kind", "model" ], "properties": { "kind": { "type": "string", "enum": [ "model" ], "description": "Reward or judge signal kind, always 'model'." }, "model": { "type": "string", "description": "Reward model asset reference used to compute scores." } }, "allOf": [ { "$ref": "#/components/schemas/TrainingRewardConfiguration" } ], "description": "Learned reward model used as a judge." }, "TrainingRewardConfiguration": { "type": "object", "required": [ "kind" ], "properties": { "kind": { "allOf": [ { "$ref": "#/components/schemas/TrainingRewardKind" } ], "description": "Reward or judge signal kind." } }, "discriminator": { "propertyName": "kind", "mapping": { "model": "#/components/schemas/TrainingModelRewardConfiguration", "function": "#/components/schemas/TrainingFunctionRewardConfiguration", "inline_function": "#/components/schemas/TrainingInlineFunctionRewardConfiguration", "builtin": "#/components/schemas/TrainingBuiltinRewardConfiguration", "evaluator": "#/components/schemas/TrainingEvaluatorRewardConfiguration", "deployment": "#/components/schemas/TrainingDeploymentRewardConfiguration", "composite": "#/components/schemas/TrainingCompositeRewardConfiguration" } }, "description": "Reward or judge signal configuration for reinforcement or reward model training." }, "TrainingRewardKind": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "model", "function", "inline_function", "builtin", "evaluator", "deployment", "composite" ] } ], "description": "Reward or judge signal kind." }, "TrainingRolloutConfiguration": { "type": "object", "required": [ "engine" ], "properties": { "engine": { "allOf": [ { "$ref": "#/components/schemas/TrainingRolloutEngine" } ], "description": "Rollout inference engine." }, "num_generations": { "type": "integer", "format": "int32", "description": "Number of completions to generate for each prompt." }, "max_prompt_length": { "type": "integer", "format": "int32", "description": "Maximum prompt length in tokens." }, "max_completion_length": { "type": "integer", "format": "int32", "description": "Maximum completion length in tokens." }, "temperature": { "type": "number", "format": "double", "description": "Sampling temperature for rollout generation." }, "top_p": { "type": "number", "format": "double", "description": "Nucleus sampling probability for rollout generation." }, "stop": { "type": "array", "items": { "type": "string" }, "description": "Stop sequences for rollout generation." }, "batch_size": { "type": "integer", "format": "int32", "description": "Rollout batch size." }, "seed": { "type": "integer", "format": "int32", "description": "Random seed for rollout generation." }, "tensor_parallel_size": { "type": "integer", "format": "int32", "description": "Tensor parallel size used by the rollout engine.", "default": 1 }, "gpu_memory_utilization": { "type": "number", "format": "double", "description": "GPU memory utilization target for the rollout engine, between 0.0 and 1.0." } }, "description": "Rollout generation configuration for online reinforcement learning." }, "TrainingRolloutEngine": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "vllm", "sglang", "hf", "megatron_inference" ] } ], "description": "Inference engine used for rollout generation during online reinforcement learning." }, "TrainingWeightedRewardConfiguration": { "type": "object", "required": [ "reward" ], "properties": { "reward": { "allOf": [ { "$ref": "#/components/schemas/TrainingRewardConfiguration" } ], "description": "Reward signal." }, "weight": { "type": "number", "format": "double", "description": "Weight applied to this reward signal.", "default": 1 } }, "description": "Weighted reward signal used in a composite judge." }, "TreatmentEffectType": { "anyOf": [ { "type": "string", "enum": [ "TooFewSamples", "Inconclusive", "Changed", "Improved", "Degraded" ] }, { "type": "string" } ], "description": "Treatment Effect Type." }, "Trigger": { "type": "object", "required": [ "type" ], "properties": { "type": { "allOf": [ { "$ref": "#/components/schemas/TriggerType" } ], "description": "Type of the trigger." } }, "discriminator": { "propertyName": "type", "mapping": { "Cron": "#/components/schemas/CronTrigger", "Recurrence": "#/components/schemas/RecurrenceTrigger", "OneTime": "#/components/schemas/OneTimeTrigger" } }, "description": "Base model for Trigger of the schedule." }, "TriggerType": { "anyOf": [ { "type": "string" }, { "type": "string", "enum": [ "Cron", "Recurrence", "OneTime" ] } ], "description": "Type of the trigger." }, "UpdateAgentFromManifestRequest": { "type": "object", "required": [ "manifest_id", "parameter_values" ], "properties": { "metadata": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Set of 16 key-value pairs that can be attached to an object. This can be\nuseful for storing additional information about the object in a structured\nformat, and querying for objects via API or the dashboard.\n\nKeys are strings with a maximum length of 64 characters. Values are strings\nwith a maximum length of 512 characters.", "x-oaiTypeLabel": "map" }, "description": { "type": "string", "maxLength": 512, "description": "A human-readable description of the agent." }, "manifest_id": { "type": "string", "description": "The manifest ID to import the agent version from." }, "parameter_values": { "type": "object", "additionalProperties": {}, "description": "The inputs to the manifest that will result in a fully materialized Agent." } } }, "UpdateAgentRequest": { "type": "object", "required": [ "definition" ], "properties": { "metadata": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Set of 16 key-value pairs that can be attached to an object. This can be\nuseful for storing additional information about the object in a structured\nformat, and querying for objects via API or the dashboard.\n\nKeys are strings with a maximum length of 64 characters. Values are strings\nwith a maximum length of 512 characters.", "x-oaiTypeLabel": "map" }, "description": { "type": "string", "maxLength": 512, "description": "A human-readable description of the agent." }, "definition": { "allOf": [ { "$ref": "#/components/schemas/AgentDefinition" } ], "description": "The agent definition. This can be a workflow, hosted agent, or a simple agent definition.", "x-ms-foundry-meta": { "conditional_previews": [ "HostedAgents=V1Preview", "ContainerAgents=V1Preview", "WorkflowAgents=V1Preview" ] } } } }, "UpdateEvalParametersBody": { "type": "object", "properties": { "name": { "type": "string" }, "metadata": { "type": "object", "allOf": [ { "$ref": "#/components/schemas/OpenAI.Metadata" } ], "nullable": true }, "properties": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Set of immutable 16 key-value pairs that can be attached to an object for storing additional information.\n Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters." } } }, "UserProfileMemoryItem": { "type": "object", "required": [ "kind" ], "properties": { "kind": { "type": "string", "enum": [ "user_profile" ], "description": "The kind of the memory item." } }, "allOf": [ { "$ref": "#/components/schemas/MemoryItem" } ], "description": "A memory item specifically containing user profile information extracted from conversations, such as preferences, interests, and personal details.", "x-ms-foundry-meta": { "conditional_previews": [ "MemoryStores=V1Preview" ] } }, "WebSearchConfiguration": { "type": "object", "required": [ "project_connection_id", "instance_name" ], "properties": { "name": { "type": "string", "description": "Optional user-defined name for this tool or configuration." }, "description": { "type": "string", "description": "Optional user-defined description for this tool or configuration." }, "project_connection_id": { "type": "string", "description": "Project connection id for grounding with bing custom search" }, "instance_name": { "type": "string", "description": "Name of the custom configuration instance given to config." } }, "description": "A web search configuration for bing custom search" }, "WeeklyRecurrenceSchedule": { "type": "object", "required": [ "type", "daysOfWeek" ], "properties": { "type": { "type": "string", "enum": [ "Weekly" ], "description": "Weekly recurrence type." }, "daysOfWeek": { "type": "array", "items": { "$ref": "#/components/schemas/DayOfWeek" }, "description": "Days of the week for the recurrence schedule." } }, "allOf": [ { "$ref": "#/components/schemas/RecurrenceSchedule" } ], "description": "Weekly recurrence schedule." }, "WorkIQPreviewTool": { "type": "object", "required": [ "type", "work_iq_preview" ], "properties": { "type": { "type": "string", "enum": [ "work_iq_preview" ], "description": "The object type, which is always 'work_iq_preview'." }, "work_iq_preview": { "allOf": [ { "$ref": "#/components/schemas/WorkIQPreviewToolParameters" } ], "description": "The WorkIQ tool parameters." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.Tool" } ], "description": "A WorkIQ server-side tool." }, "WorkIQPreviewToolParameters": { "type": "object", "required": [ "project_connection_id" ], "properties": { "project_connection_id": { "type": "string", "description": "The ID of the WorkIQ project connection." } }, "description": "The WorkIQ tool parameters." }, "WorkflowActionOutputItem": { "type": "object", "required": [ "type", "kind", "action_id", "status" ], "properties": { "type": { "type": "string", "enum": [ "workflow_action" ] }, "kind": { "type": "string", "description": "The kind of CSDL action (e.g., 'SetVariable', 'InvokeAzureAgent')." }, "action_id": { "type": "string", "description": "Unique identifier for the action." }, "parent_action_id": { "type": "string", "description": "ID of the parent action if this is a nested action." }, "previous_action_id": { "type": "string", "description": "ID of the previous action if this action follows another." }, "status": { "type": "string", "enum": [ "completed", "failed", "in_progress", "cancelled" ], "description": "Status of the action (e.g., 'in_progress', 'completed', 'failed', 'cancelled')." } }, "allOf": [ { "$ref": "#/components/schemas/OpenAI.OutputItem" } ] }, "WorkflowAgentDefinition": { "type": "object", "required": [ "kind" ], "properties": { "kind": { "type": "string", "enum": [ "workflow" ] }, "workflow": { "type": "string", "description": "The CSDL YAML definition of the workflow." } }, "allOf": [ { "$ref": "#/components/schemas/AgentDefinition" } ], "description": "The workflow agent definition.", "x-ms-foundry-meta": { "required_previews": [ "WorkflowAgents=V1Preview" ] } }, "integer": { "type": "integer", "format": "int64" } }, "securitySchemes": { "ApiKeyAuth": { "type": "apiKey", "in": "header", "name": "api-key" }, "OAuth2Auth": { "type": "oauth2", "flows": { "implicit": { "authorizationUrl": "https://login.microsoftonline.com/common/oauth2/v2.0/authorize", "scopes": { "https://ai.azure.com/.default": "" } } } } } }, "servers": [ { "url": "{endpoint}", "description": "Microsoft Foundry", "variables": { "endpoint": { "default": "", "description": "Foundry Project endpoint in the form\n\"https://{ai-services-account-name}.services.ai.azure.com/api/projects/{project-name}\".\nIf you only have one Project in your Foundry Hub, or to target the default Project\nin your Hub, use the form\n\"https://{ai-services-account-name}.services.ai.azure.com/api/projects/_project\"" } } } ] }