openapi: 3.0.0 info: title: Portkey Analytics > Graphs Feedback API description: The Portkey REST API. Please see https://portkey.ai/docs/api-reference for more details. version: 2.0.0 termsOfService: https://portkey.ai/terms contact: name: Portkey Developer Forum url: https://portkey.wiki/community license: name: MIT url: https://github.com/Portkey-AI/portkey-openapi/blob/master/LICENSE servers: - url: https://api.portkey.ai/v1 description: Portkey API Public Endpoint security: - Portkey-Key: [] tags: - name: Feedback description: Send and Update any feedback. paths: /feedback: servers: - url: https://api.portkey.ai/v1 description: Portkey API Public Endpoint - url: SELF_HOSTED_CONTROL_PLANE_URL description: Self-Hosted Control Plane URL post: summary: Create new feedback description: This endpoint allows users to submit feedback for a particular interaction or response. operationId: createFeedback tags: - Feedback requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/FeedbackRequest' responses: '200': description: Feedback successfully saved content: application/json: schema: $ref: '#/components/schemas/FeedbackResponse' x-code-samples: - lang: python label: Default source: "from portkey_ai import Portkey\n\nportkey = Portkey(api_key=\"PORTKEY_API_KEY\")\n\nfeedback = portkey.feedback.create(\n trace_id=\"REQUEST_TRACE_ID\",\n value=1\n)\n\nprint(feedback)\n" - lang: javascript label: Default source: "import { Portkey } from \"portkey-ai\";\n\nconst portkey = new Portkey({\n apiKey: \"PORTKEY_API_KEY\"\n});\n\nconst feedback = await portkey.feedback.create({\n trace_id: \"REQUEST_TRACE_ID\",\n value: 1\n});\n\nconsole.log(feedback);\n" - lang: curl label: Default source: 'curl -X POST https://api.portkey.ai/v1/feedback \ -H "x-portkey-api-key: PORTKEY_API_KEY" \ -H "Content-Type: application/json" \ -d ''{"trace_id":"REQUEST_TRACE_ID","value":1}'' ' - lang: python label: Self-Hosted source: "from portkey_ai import Portkey\n\nportkey = Portkey(\n api_key=\"PORTKEY_API_KEY\",\n base_url=\"SELF_HOSTED_CONTROL_PLANE_URL\"\n)\n\nfeedback = portkey.feedback.create(\n trace_id=\"REQUEST_TRACE_ID\",\n value=1\n)\n\nprint(feedback)\n" - lang: javascript label: Self-Hosted source: "import { Portkey } from \"portkey-ai\";\n\nconst portkey = new Portkey({\n apiKey: \"PORTKEY_API_KEY\",\n virtualKey: \"PROVIDER_VIRTUAL_KEY\",\n baseUrl: \"SELF_HOSTED_CONTROL_PLANE_URL\"\n});\n\nasync function main() {\n const feedback = await portkey.feedback.create({\n trace_id: \"REQUEST_TRACE_ID\",\n value: 1\n });\n console.log(feedback);\n}\n\nmain();\n" - lang: curl label: Self-Hosted source: 'curl -X POST SELF_HOSTED_CONTROL_PLANE_URL/feedback \ -H "x-portkey-api-key: PORTKEY_API_KEY" \ -H "Content-Type: application/json" \ -d ''{"trace_id":"REQUEST_TRACE_ID","value":1}'' ' /feedback/{id}: servers: - url: https://api.portkey.ai/v1 description: Portkey API Public Endpoint - url: SELF_HOSTED_CONTROL_PLANE_URL description: Self-Hosted Control Plane URL put: summary: Updates existing feedback description: This endpoint allows users to update existing feedback. operationId: updateFeedback parameters: - name: id in: path description: Feedback ID required: true schema: type: string format: uuid tags: - Feedback requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/FeedbackUpdateRequest' responses: '200': description: Feedback successfully updated content: application/json: schema: $ref: '#/components/schemas/FeedbackResponse' x-code-samples: - lang: python label: Default source: "from portkey_ai import Portkey\n\nportkey = Portkey(api_key=\"PORTKEY_API_KEY\")\n\nfeedback = portkey.feedback.update(\n feedback_id=\"FEEDBACK_ID\",\n value=1\n)\n\nprint(feedback)\n" - lang: javascript label: Default source: "import { Portkey } from \"portkey-ai\";\n\nconst portkey = new Portkey({\n apiKey: \"PORTKEY_API_KEY\"\n});\n\nconst feedback = await portkey.feedback.update({\n feedbackId: \"FEEDBACK_ID\",\n value: 1\n});\n\nconsole.log(feedback);\n" - lang: curl label: Default source: 'curl -X POST https://api.portkey.ai/v1/feedback/{id} \ -H "x-portkey-api-key: PORTKEY_API_KEY" \ -H "Content-Type: application/json" \ -d ''{"value":1}'' ' - lang: python label: Self-Hosted source: "from portkey_ai import Portkey\n\nportkey = Portkey(\n api_key=\"PORTKEY_API_KEY\",\n base_url=\"SELF_HOSTED_CONTROL_PLANE_URL\"\n)\n\nfeedback = portkey.feedback.update(\n feedback_id=\"FEEDBACK_ID\",\n value=1\n)\n\nprint(feedback)\n" - lang: javascript label: Self-Hosted source: "import { Portkey } from \"portkey-ai\";\n\nconst portkey = new Portkey({\n apiKey: \"PORTKEY_API_KEY\",\n virtualKey: \"PROVIDER_VIRTUAL_KEY\",\n baseUrl: \"SELF_HOSTED_CONTROL_PLANE_URL\"\n});\n\nasync function main() {\n const feedback = await portkey.feedback.update({\n feedbackId: \"FEEDBACK_ID\",\n value: 1\n });\n console.log(feedback);\n}\n\nmain();\n" - lang: curl label: Self-Hosted source: 'curl -X POST SELF_HOSTED_CONTROL_PLANE_URL/feedback/{id} \ -H "x-portkey-api-key: PORTKEY_API_KEY" \ -H "Content-Type: application/json" \ -d ''{"value":1}'' ' components: schemas: FeedbackResponse: type: object properties: status: type: string description: success or failure message: type: string description: Confirmation message indicating successful feedback submission. feedback_ids: type: array description: Ids of Feedbacks created returned in the same order as input items: type: string FeedbackUpdateRequest: type: object required: - value properties: value: type: integer description: Feedback value, an integer between -10 and 10. minimum: -10 maximum: 10 weight: type: number format: float description: Weight of the feedback, a float between 0 and 1. Default is 1.0. minimum: 0 maximum: 1 default: 1.0 metadata: type: object additionalProperties: true description: Additional metadata for the feedback. FeedbackRequest: type: object required: - trace_id - value properties: trace_id: type: string description: Unique identifier for the request trace. value: type: integer description: Feedback value, an integer between -10 and 10. minimum: -10 maximum: 10 weight: type: number format: float description: Weight of the feedback, a float between 0 and 1. Default is 1.0. minimum: 0 maximum: 1 default: 1.0 metadata: type: object additionalProperties: true description: Additional metadata for the feedback. securitySchemes: Portkey-Key: type: apiKey in: header name: x-portkey-api-key Virtual-Key: type: apiKey in: header name: x-portkey-virtual-key Provider-Auth: type: http scheme: bearer Provider-Name: type: apiKey in: header name: x-portkey-provider Config: type: apiKey in: header name: x-portkey-config Custom-Host: type: apiKey in: header name: x-portkey-custom-host x-server-groups: ControlPlaneServers: - url: https://api.portkey.ai/v1 description: Portkey API Public Endpoint - url: SELF_HOSTED_CONTROL_PLANE_URL description: Self-Hosted Control Plane URL DataPlaneServers: - url: https://api.portkey.ai/v1 description: Portkey API Public Endpoint - url: SELF_HOSTED_GATEWAY_URL description: Self-Hosted Gateway URL PublicServers: - url: https://api.portkey.ai description: Portkey Public API (no auth required) x-mint: mcp: enabled: true name: Portkey MCP description: Official MCP Server for Portkey Docs & APIs x-code-samples: navigationGroups: - id: endpoints title: Endpoints - id: assistants title: Assistants - id: legacy title: Legacy groups: - id: audio title: Audio description: 'Learn how to turn audio into text or text into audio. Related guide: [Speech to text](https://platform.openai.com/docs/guides/speech-to-text) ' navigationGroup: endpoints sections: - type: endpoint key: createSpeech path: createSpeech - type: endpoint key: createTranscription path: createTranscription - type: endpoint key: createTranslation path: createTranslation - type: object key: CreateTranscriptionResponseJson path: json-object - type: object key: CreateTranscriptionResponseVerboseJson path: verbose-json-object - id: chat title: Chat description: 'Given a list of messages comprising a conversation, the model will return a response. Related guide: [Chat Completions](https://platform.openai.com/docs/guides/text-generation) ' navigationGroup: endpoints sections: - type: endpoint key: createChatCompletion path: create - type: object key: CreateChatCompletionResponse path: object - type: object key: CreateChatCompletionStreamResponse path: streaming - id: realtime title: Realtime description: 'WebSocket proxy for provider Realtime APIs (`GET` upgrade). Use `wss://` with the same `/v1` data-plane base as other gateway routes. Related guide: [OpenAI Realtime API](https://platform.openai.com/docs/guides/realtime) ' navigationGroup: endpoints sections: - type: endpoint key: connectRealtime path: connect - id: embeddings title: Embeddings description: 'Get a vector representation of a given input that can be easily consumed by machine learning models and algorithms. Related guide: [Embeddings](https://platform.openai.com/docs/guides/embeddings) ' navigationGroup: endpoints sections: - type: endpoint key: createEmbedding path: create - type: object key: Embedding path: object - id: rerank title: Rerank description: 'Rerank a list of documents based on their relevance to a query. Reranking improves search results by scoring documents based on semantic relevance rather than keyword matching. Supported providers: Cohere, Voyage, Jina, Pinecone, Bedrock, Azure AI. ' navigationGroup: endpoints sections: - type: endpoint key: createRerank path: create - type: object key: CreateRerankResponse path: object - id: fine-tuning title: Fine-tuning description: 'Manage fine-tuning jobs to tailor a model to your specific training data. Related guide: [Fine-tune models](https://platform.openai.com/docs/guides/fine-tuning) ' navigationGroup: endpoints sections: - type: endpoint key: createFineTuningJob path: create - type: endpoint key: listPaginatedFineTuningJobs path: list - type: endpoint key: listFineTuningEvents path: list-events - type: endpoint key: listFineTuningJobCheckpoints path: list-checkpoints - type: endpoint key: retrieveFineTuningJob path: retrieve - type: endpoint key: cancelFineTuningJob path: cancel - type: object key: FinetuneChatRequestInput path: chat-input - type: object key: FinetuneCompletionRequestInput path: completions-input - type: object key: FineTuningJob path: object - type: object key: FineTuningJobEvent path: event-object - type: object key: FineTuningJobCheckpoint path: checkpoint-object - id: batch title: Batch description: 'Create large batches of API requests for asynchronous processing. The Batch API returns completions within 24 hours for a 50% discount. Related guide: [Batch](https://platform.openai.com/docs/guides/batch) ' navigationGroup: endpoints sections: - type: endpoint key: createBatch path: create - type: endpoint key: retrieveBatch path: retrieve - type: endpoint key: cancelBatch path: cancel - type: endpoint key: listBatches path: list - type: object key: Batch path: object - type: object key: BatchRequestInput path: request-input - type: object key: BatchRequestOutput path: request-output - id: files title: Files description: 'Files are used to upload documents that can be used with features like [Assistants](https://platform.openai.com/docs/api-reference/assistants), [Fine-tuning](https://platform.openai.com/docs/api-reference/fine-tuning), and [Batch API](https://platform.openai.com/docs/guides/batch). ' navigationGroup: endpoints sections: - type: endpoint key: createFile path: create - type: endpoint key: listFiles path: list - type: endpoint key: retrieveFile path: retrieve - type: endpoint key: deleteFile path: delete - type: endpoint key: downloadFile path: retrieve-contents - type: object key: OpenAIFile path: object - id: images title: Images description: 'Given a prompt and/or an input image, the model will generate a new image. Related guide: [Image generation](https://platform.openai.com/docs/guides/images) ' navigationGroup: endpoints sections: - type: endpoint key: createImage path: create - type: endpoint key: createImageEdit path: createEdit - type: endpoint key: createImageVariation path: createVariation - type: object key: Image path: object - id: models title: Models description: 'List and describe the various models available in the API. You can refer to the [Models](https://platform.openai.com/docs/models) documentation to understand what models are available and the differences between them. ' navigationGroup: endpoints sections: - type: endpoint key: listModels path: list - type: endpoint key: retrieveModel path: retrieve - type: endpoint key: deleteModel path: delete - type: object key: Model path: object - id: moderations title: Moderations description: 'Given some input text, outputs if the model classifies it as potentially harmful across several categories. Related guide: [Moderations](https://platform.openai.com/docs/guides/moderation) ' navigationGroup: endpoints sections: - type: endpoint key: createModeration path: create - type: object key: CreateModerationResponse path: object - id: assistants title: Assistants beta: true description: 'Build assistants that can call models and use tools to perform tasks. [Get started with the Assistants API](https://platform.openai.com/docs/assistants) ' navigationGroup: assistants sections: - type: endpoint key: createAssistant path: createAssistant - type: endpoint key: listAssistants path: listAssistants - type: endpoint key: getAssistant path: getAssistant - type: endpoint key: modifyAssistant path: modifyAssistant - type: endpoint key: deleteAssistant path: deleteAssistant - type: object key: AssistantObject path: object - id: threads title: Threads beta: true description: 'Create threads that assistants can interact with. Related guide: [Assistants](https://platform.openai.com/docs/assistants/overview) ' navigationGroup: assistants sections: - type: endpoint key: createThread path: createThread - type: endpoint key: getThread path: getThread - type: endpoint key: modifyThread path: modifyThread - type: endpoint key: deleteThread path: deleteThread - type: object key: ThreadObject path: object - id: messages title: Messages beta: true description: 'Create messages within threads Related guide: [Assistants](https://platform.openai.com/docs/assistants/overview) ' navigationGroup: assistants sections: - type: endpoint key: createMessage path: createMessage - type: endpoint key: listMessages path: listMessages - type: endpoint key: getMessage path: getMessage - type: endpoint key: modifyMessage path: modifyMessage - type: endpoint key: deleteMessage path: deleteMessage - type: object key: MessageObject path: object - id: runs title: Runs beta: true description: 'Represents an execution run on a thread. Related guide: [Assistants](https://platform.openai.com/docs/assistants/overview) ' navigationGroup: assistants sections: - type: endpoint key: createRun path: createRun - type: endpoint key: createThreadAndRun path: createThreadAndRun - type: endpoint key: listRuns path: listRuns - type: endpoint key: getRun path: getRun - type: endpoint key: modifyRun path: modifyRun - type: endpoint key: submitToolOuputsToRun path: submitToolOutputs - type: endpoint key: cancelRun path: cancelRun - type: object key: RunObject path: object - id: run-steps title: Run Steps beta: true description: 'Represents the steps (model and tool calls) taken during the run. Related guide: [Assistants](https://platform.openai.com/docs/assistants/overview) ' navigationGroup: assistants sections: - type: endpoint key: listRunSteps path: listRunSteps - type: endpoint key: getRunStep path: getRunStep - type: object key: RunStepObject path: step-object - id: vector-stores title: Vector Stores beta: true description: 'Vector stores are used to store files for use by the `file_search` tool. Related guide: [File Search](https://platform.openai.com/docs/assistants/tools/file-search) ' navigationGroup: assistants sections: - type: endpoint key: createVectorStore path: create - type: endpoint key: listVectorStores path: list - type: endpoint key: getVectorStore path: retrieve - type: endpoint key: modifyVectorStore path: modify - type: endpoint key: deleteVectorStore path: delete - type: object key: VectorStoreObject path: object - id: vector-stores-files title: Vector Store Files beta: true description: 'Vector store files represent files inside a vector store. Related guide: [File Search](https://platform.openai.com/docs/assistants/tools/file-search) ' navigationGroup: assistants sections: - type: endpoint key: createVectorStoreFile path: createFile - type: endpoint key: listVectorStoreFiles path: listFiles - type: endpoint key: getVectorStoreFile path: getFile - type: endpoint key: deleteVectorStoreFile path: deleteFile - type: object key: VectorStoreFileObject path: file-object - id: vector-stores-file-batches title: Vector Store File Batches beta: true description: 'Vector store file batches represent operations to add multiple files to a vector store. Related guide: [File Search](https://platform.openai.com/docs/assistants/tools/file-search) ' navigationGroup: assistants sections: - type: endpoint key: createVectorStoreFileBatch path: createBatch - type: endpoint key: getVectorStoreFileBatch path: getBatch - type: endpoint key: cancelVectorStoreFileBatch path: cancelBatch - type: endpoint key: listFilesInVectorStoreBatch path: listBatchFiles - type: object key: VectorStoreFileBatchObject path: batch-object - id: assistants-streaming title: Streaming beta: true description: 'Stream the result of executing a Run or resuming a Run after submitting tool outputs. You can stream events from the [Create Thread and Run](https://platform.openai.com/docs/api-reference/runs/createThreadAndRun), [Create Run](https://platform.openai.com/docs/api-reference/runs/createRun), and [Submit Tool Outputs](https://platform.openai.com/docs/api-reference/runs/submitToolOutputs) endpoints by passing `"stream": true`. The response will be a [Server-Sent events](https://html.spec.whatwg.org/multipage/server-sent-events.html#server-sent-events) stream. Our Node and Python SDKs provide helpful utilities to make streaming easy. Reference the [Assistants API quickstart](https://platform.openai.com/docs/assistants/overview) to learn more. ' navigationGroup: assistants sections: - type: object key: MessageDeltaObject path: message-delta-object - type: object key: RunStepDeltaObject path: run-step-delta-object - type: object key: AssistantStreamEvent path: events - id: completions title: Completions legacy: true navigationGroup: legacy description: 'Given a prompt, the model will return one or more predicted completions along with the probabilities of alternative tokens at each position. Most developer should use our [Chat Completions API](https://platform.openai.com/docs/guides/text-generation/text-generation-models) to leverage our best and newest models. ' sections: - type: endpoint key: createCompletion path: create - type: object key: CreateCompletionResponse path: object