openapi: 3.0.0
info:
  title: Portkey Analytics > Graphs Logs 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: Logs
  description: Custom Logger to add external logs to Portkey.
paths:
  /logs:
    servers:
    - url: https://api.portkey.ai/v1
      description: Portkey API Public Endpoint
    - url: SELF_HOSTED_GATEWAY_URL
      description: Self-Hosted Gateway URL
    post:
      summary: Insert New logs
      tags:
      - Logs
      description: Submit one or more log entries
      requestBody:
        required: true
        content:
          application/json:
            schema:
              oneOf:
              - $ref: '#/components/schemas/CustomLog'
              - type: array
                items:
                  $ref: '#/components/schemas/CustomLog'
      responses:
        '200':
          description: Successful response
      x-code-samples:
      - lang: python
        label: Default
        source: "from portkey_ai import Portkey\n\nportkey = Portkey(\n  api_key=\"PORTKEY_API_KEY\",\n)\n\nrequest = {\n  \"url\": \"https://api.someprovider.com/model/generate\",\n  \"method\": \"POST\",\n  \"headers\": {\"Content-Type\": \"application/json\"},\n  \"body\": {\"prompt\": \"What is AI?\"},\n}\nresponse = {\n  \"status\": 200,\n  \"headers\": {\"Content-Type\": \"application/json\"},\n  \"body\": {\"response\": \"AI stands for Artificial Intelligence...\"},\n  \"response_time\": 123,\n}\nmetadata = {\n  \"user_id\": \"123\",\n  \"user_name\": \"John Doe\",\n}\n\nresult = portkey.logs.create(request=request, response=response, metadata=metadata)\n\nprint(result)\n"
      - lang: javascript
        label: Default
        source: "import Portkey from \"portkey-ai\";\n\nconst portkey = new Portkey({\n  apiKey:\"PORTKEY_API_KEY\"\n})\n\nasync function main() {\n  const request = {\n    url: \"https://api.someprovider.com/model/generate\",\n    method: \"POST\",\n    headers: { \"Content-Type\": \"application/json\" },\n    body: { prompt: \"What is AI?\" },\n  };\n  const response = {\n    status: 200,\n    headers: { \"Content-Type\": \"application/json\" },\n    body: { response: \"AI stands for Artificial Intelligence...\" },\n    response_time: 123,\n  };\n  const metadata = {\n    user_id: \"123\",\n    user_name: \"John Doe\",\n  };\n  const result = await portkey.logs.create({\n    request: request,\n    response: response,\n    metadata: metadata,\n  });\n  console.log(result);\n}\n\nmain();\n"
      - lang: curl
        label: Default
        source: "curl -X POST \"https://api.portkey.ai/v1/logs\" \\\n-H \"x-portkey-api-key: PORTKEY_API_KEY\" \\\n-H \"Content-Type: application/json\" \\\n-d '{\n  \"request\": {\n    \"url\": \"https://api.someprovider.com/model/generate\",\n    \"method\": \"POST\",\n    \"headers\": { \"Content-Type\": \"application/json\" },\n    \"body\": { \"prompt\": \"What is AI?\" }\n  },\n  \"response\": {\n    \"status\": 200,\n    \"headers\": { \"Content-Type\": \"application/json\" },\n    \"body\": { \"response\": \"AI stands for Artificial Intelligence...\" },\n    \"response_time\": 123\n  },\n  \"metadata\": {\n    \"user_id\": \"123\",\n    \"user_name\": \"John Doe\"\n  }\n}'\n"
      - lang: curl
        label: Self-Hosted
        source: "curl -X POST \"SELF_HOSTED_GATEWAY_URL/logs\" \\\n-H \"x-portkey-api-key: PORTKEY_API_KEY\" \\\n-H \"Content-Type: application/json\" \\\n-d '{\n  \"request\": {\n    \"url\": \"https://api.someprovider.com/model/generate\",\n    \"method\": \"POST\",\n    \"headers\": { \"Content-Type\": \"application/json\" },\n    \"body\": { \"prompt\": \"What is AI?\" }\n  },\n  \"response\": {\n    \"status\": 200,\n    \"headers\": { \"Content-Type\": \"application/json\" },\n    \"body\": { \"response\": \"AI stands for Artificial Intelligence...\" },\n    \"response_time\": 123\n  },\n  \"metadata\": {\n    \"user_id\": \"123\",\n    \"user_name\": \"John Doe\"\n  }\n}'\n"
      - 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_GATEWAY_URL\"\n)\n\nrequest = {\n  \"url\": \"https://api.someprovider.com/model/generate\",\n  \"method\": \"POST\",\n  \"headers\": {\"Content-Type\": \"application/json\"},\n  \"body\": {\"prompt\": \"What is AI?\"},\n}\nresponse = {\n  \"status\": 200,\n  \"headers\": {\"Content-Type\": \"application/json\"},\n  \"body\": {\"response\": \"AI stands for Artificial Intelligence...\"},\n  \"response_time\": 123,\n}\nmetadata = {\n  \"user_id\": \"123\",\n  \"user_name\": \"John Doe\",\n}\n\nresult = portkey.logs.create(request=request, response=response, metadata=metadata)\n\nprint(result)\n"
      - lang: javascript
        label: Self-Hosted
        source: "import Portkey from \"portkey-ai\";\n\nconst portkey = new Portkey({\n  apiKey:\"PORTKEY_API_KEY\",\n  baseUrl: \"SELF_HOSTED_GATEWAY_URL\"\n})\n\nasync function main() {\n  const request = {\n    url: \"https://api.someprovider.com/model/generate\",\n    method: \"POST\",\n    headers: { \"Content-Type\": \"application/json\" },\n    body: { prompt: \"What is AI?\" },\n  };\n  const response = {\n    status: 200,\n    headers: { \"Content-Type\": \"application/json\" },\n    body: { response: \"AI stands for Artificial Intelligence...\" },\n    response_time: 123,\n  };\n  const metadata = {\n    user_id: \"123\",\n    user_name: \"John Doe\",\n  };\n  const result = await portkey.logs.create({\n    request: request,\n    response: response,\n    metadata: metadata,\n  });\n  console.log(result);\n}\n\nmain();\n"
  /logs/{logId}:
    servers:
    - url: https://api.portkey.ai/v1
      description: Portkey API Public Endpoint
    - url: SELF_HOSTED_GATEWAY_URL
      description: Self-Hosted Gateway URL
    get:
      tags:
      - Logs
      summary: Get a specific log
      parameters:
      - name: logId
        in: path
        required: true
        schema:
          type: string
      responses:
        '200':
          description: Successful response
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/LogObject'
components:
  schemas:
    AnalyticsMetrics:
      type: object
      description: Analytics metrics extracted from the log entry
      properties:
        id:
          type: string
          format: uuid
          description: Unique identifier for the log entry
          example: 550e8400-e29b-41d4-a716-446655440000
        organisation_id:
          type: string
          description: Organization identifier
          example: org-123
        organisation_name:
          type: string
          description: Organization name
          example: Acme Corp
        prompt_id:
          type: string
          description: Prompt identifier
          example: prompt-789
        prompt_version_id:
          type: string
          description: Prompt version identifier
          example: prompt-v1
        config_id:
          type: string
          description: Configuration identifier
          example: config-123
        created_at:
          type: string
          format: date-time
          description: Timestamp when the log was created
          example: '2024-01-15T10:30:00.000'
        is_success:
          type: boolean
          description: Whether the request was successful (status code 200-299)
          example: true
        ai_org:
          type: string
          description: AI provider organization (e.g., openai, anthropic)
          example: openai
        ai_model:
          type: string
          description: AI model used
          example: gpt-4o
        req_units:
          type: number
          format: float
          description: Request token units
          example: 100
        res_units:
          type: number
          format: float
          description: Response token units
          example: 50
        total_units:
          type: number
          format: float
          description: Total token units (req_units + res_units)
          example: 150
        cost:
          type: number
          format: float
          description: Cost in the specified currency
          example: 0.002
        cost_currency:
          type: string
          description: Currency code for the cost
          default: USD
          example: USD
        request_url:
          type: string
          format: uri
          description: Sanitized request URL
          example: https://api.openai.com/v1/chat/completions
        request_method:
          type: string
          description: HTTP method
          example: POST
        response_status_code:
          type: integer
          format: int32
          description: HTTP response status code
          example: 200
        response_time:
          type: integer
          format: int64
          description: Response time in milliseconds
          example: 1234
        is_proxy_call:
          type: boolean
          description: Whether this was a proxy call
          example: true
        cache_status:
          type: string
          nullable: true
          description: Cache status (e.g., HIT, MISS, DISABLED, SEMANTIC HIT)
          example: MISS
        cache_type:
          type: string
          nullable: true
          description: Type of cache used
          example: semantic
        stream_mode:
          type: integer
          nullable: true
          description: Whether streaming was enabled (1) or not (0)
          example: 1
        retry_success_count:
          type: integer
          description: Number of successful retries
          example: 0
        trace_id:
          type: string
          description: Distributed tracing trace ID
          example: trace-123
        span_id:
          type: string
          description: Distributed tracing span ID
          example: span-456
        span_name:
          type: string
          description: Name of the span
          example: llm
        parent_span_id:
          type: string
          description: Parent span ID in distributed tracing
          example: span-789
        mode:
          type: string
          description: Request mode (e.g., single, loadbalance, fallback)
          example: single
        virtual_key:
          type: string
          description: Virtual key identifier
          example: vk-123
        source:
          type: string
          description: Source of the request (e.g., rubeus, proxy)
          example: rubeus
        runtime:
          type: string
          description: Runtime environment
          example: node
        runtime_version:
          type: string
          description: Runtime version
          example: 18.0.0
        sdk_version:
          type: string
          description: SDK version
          example: 1.0.0
        config:
          type: string
          description: Configuration slug or ID
          example: pc-config-123
        internal_trace_id:
          type: string
          description: Internal trace ID for gateway tracking
          example: internal-trace-123
        last_used_option_index:
          type: integer
          description: Index of the last used option in the config
          example: 0
        config_version_id:
          type: string
          description: Configuration version identifier
          example: config-v1
        prompt_slug:
          type: string
          description: Prompt slug
          example: my-prompt
        workspace_slug:
          type: string
          nullable: true
          description: Workspace slug
          example: my-workspace
        log_store_file_path_format:
          type: string
          description: Path format version for log storage
          example: v1
        metadata.key:
          type: array
          items:
            type: string
            nullable: true
          description: Array of metadata keys
          example:
          - key1
          - key2
        metadata.value:
          type: array
          items:
            type: string
            nullable: true
          description: Array of metadata values
          example:
          - value1
          - value2
        api_key_id:
          type: string
          description: API key identifier
          example: api-key-123
        request_parsing_time:
          type: integer
          format: int64
          description: Time taken to parse the request in milliseconds
          example: 5
        pre_processing_time:
          type: integer
          format: int64
          description: Time taken for pre-processing in milliseconds
          example: 10
        cache_processing_time:
          type: integer
          format: int64
          description: Time taken for cache processing in milliseconds
          example: 2
        response_parsing_time:
          type: integer
          format: int64
          description: Time taken to parse the response in milliseconds
          example: 8
        gateway_processing_time:
          type: integer
          format: int64
          description: Total gateway processing time in milliseconds
          example: 50
        upstream_response_time:
          type: integer
          format: int64
          description: Upstream provider response time in milliseconds
          example: 1200
    LogRequest:
      type: object
      required:
      - url
      - method
      - portkeyHeaders
      properties:
        url:
          type: string
          format: uri
          description: Sanitized request URL
          example: https://api.openai.com/v1/chat/completions
        method:
          type: string
          description: HTTP method
          enum:
          - GET
          - POST
          - PUT
          - DELETE
          - PATCH
          - OPTIONS
          - HEAD
          example: POST
        headers:
          type: object
          additionalProperties:
            type: string
          description: Request headers (only present when debug logging is enabled)
          example:
            Content-Type: application/json
            Authorization: Bearer hashed_value
        body:
          type: object
          additionalProperties: true
          description: Request body (only present when debug logging is enabled)
        portkeyHeaders:
          type: object
          additionalProperties:
            type: string
          description: Portkey-specific headers
          example:
            x-portkey-trace-id: trace-123
            x-portkey-span-id: span-456
            x-portkey-metadata: '{"key":"value"}'
    CustomLog:
      type: object
      properties:
        request:
          type: object
          properties:
            url:
              type: string
            method:
              type: string
            headers:
              type: object
              additionalProperties:
                type: string
            body:
              type: object
          required:
          - url
          - body
        response:
          type: object
          properties:
            status:
              type: integer
            headers:
              type: object
              additionalProperties:
                type: string
            body:
              type: object
            response_time:
              type: integer
          required:
          - body
        metadata:
          type: object
          properties:
            trace_id:
              type: string
            span_id:
              type: string
            span_name:
              type: string
            additionalProperties:
              type: string
      required:
      - request
      - response
    LogResponse:
      type: object
      required:
      - status
      - responseTime
      - lastUsedOptionJsonPath
      properties:
        status:
          type: integer
          format: int32
          description: HTTP response status code
          example: 200
        headers:
          type: object
          additionalProperties:
            type: string
          description: Response headers (only present when debug logging is enabled or request failed)
          example:
            Content-Type: application/json
        body:
          type: object
          additionalProperties: true
          description: Response body (only present when debug logging is enabled or request failed). May be redacted for certain embedding models.
          example:
            id: chatcmpl-123
            object: chat.completion
            created: 1677652288
        responseTime:
          type: integer
          format: int64
          description: Response time in milliseconds
          example: 1234
        lastUsedOptionJsonPath:
          type: string
          description: JSON path to the last used option in the config
          example: $.config.options[0]
    RequestResponseObject:
      type: object
      properties:
        body:
          type: object
          additionalProperties: true
          description: The body content
        headers:
          type: object
          additionalProperties:
            type: string
          description: Headers if present
        url:
          type: string
          format: uri
          description: URL if present
        method:
          type: string
          description: HTTP method if present
    LogObject:
      type: object
      required:
      - _id
      - request
      - response
      - organisation_id
      - created_at
      properties:
        _id:
          type: string
          format: uuid
          description: Unique identifier for the log entry
          nullable: true
          example: 550e8400-e29b-41d4-a716-446655440000
        request:
          $ref: '#/components/schemas/LogRequest'
        response:
          $ref: '#/components/schemas/LogResponse'
        organisation_id:
          type: string
          description: Organization identifier
          nullable: true
          example: org-123
        created_at:
          type: string
          format: date-time
          description: Timestamp when the log was created
          nullable: true
          example: '2024-01-15T10:30:00.000Z'
        metrics:
          $ref: '#/components/schemas/AnalyticsMetrics'
          description: Analytics metrics object containing detailed metrics about the request
        finalUntransformedRequest:
          $ref: '#/components/schemas/RequestResponseObject'
          description: The original request before any transformations (only present when debug logging is enabled)
        originalResponse:
          $ref: '#/components/schemas/RequestResponseObject'
          description: The original response from the provider (only present when debug logging is enabled or request failed)
        transformedRequest:
          $ref: '#/components/schemas/RequestResponseObject'
          description: The request after transformations (only present when debug logging is enabled)
  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