Portkey Completions API

openapi: 3.0.0
info:
  title: Portkey Analytics > Graphs Completions 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: Completions
  description: Given a prompt, the model will return one or more predicted completions, and can also return the probabilities of alternative tokens at each position.
paths:
  /completions:
    servers:
    - url: https://api.portkey.ai/v1
      description: Portkey API Public Endpoint
    - url: SELF_HOSTED_GATEWAY_URL
      description: Self-Hosted Gateway URL
    post:
      operationId: createCompletion
      tags:
      - Completions
      summary: Completions
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/CreateCompletionRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/CreateCompletionResponse'
      security:
      - Portkey-Key: []
        Virtual-Key: []
      - Portkey-Key: []
        Provider-Auth: []
        Provider-Name: []
      - Portkey-Key: []
        Config: []
      - Portkey-Key: []
        Provider-Auth: []
        Provider-Name: []
        Custom-Host: []
      x-code-samples:
      - lang: curl
        label: Default
        source: "curl https://api.portkey.ai/v1/completions \\\n  -H \"Content-Type: application/json\" \\\n  -H \"x-portkey-api-key: $PORTKEY_API_KEY\" \\\n  -H \"x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY\" \\\n  -d '{\n    \"model\": \"gpt-3.5-turbo-instruct\",\n    \"prompt\": \"Say this is a test\",\n    \"max_tokens\": 7,\n    \"temperature\": 0\n  }'\n"
      - lang: python
        label: Default
        source: "from portkey_ai import Portkey\n\nportkey = Portkey(\n  api_key = \"PORTKEY_API_KEY\",\n  virtual_key = \"PROVIDER_VIRTUAL_KEY\"\n)\n\nresponse = portkey.completions.create(\n  model=\"gpt-3.5-turbo-instruct\",\n  prompt=\"Say this is a test\",\n  max_tokens=7,\n  temperature=0\n)\n\nprint(response)\n"
      - lang: javascript
        label: Default
        source: "import Portkey from 'portkey-ai';\n\nconst portkey = new Portkey({\n  apiKey: 'PORTKEY_API_KEY',\n  virtualKey: 'PROVIDER_VIRTUAL_KEY'\n});\n\nasync function main() {\n  const response = await portkey.completions.create({\n    model: \"gpt-3.5-turbo-instruct\",\n    prompt: \"Say this is a test.\",\n    max_tokens: 7,\n    temperature: 0,\n  });\n\n  console.log(response);\n}\n\nmain();\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_GATEWAY_URL'\n});\n\nasync function main() {\n  const response = await client.completions.create({\n    model: \"gpt-3.5-turbo-instruct\",\n    prompt: \"Say this is a test.\",\n    max_tokens: 7,\n    temperature: 0,\n  });\n\n  console.log(response);\n}\n\nmain();\n"
      - lang: python
        label: Self-Hosted
        source: "from portkey_ai import Portkey\n\nportkey = Portkey(\n  api_key = \"PORTKEY_API_KEY\",\n  virtual_key = \"PROVIDER_VIRTUAL_KEY\",\n  base_url = \"SELF_HOSTED_GATEWAY_URL\"\n)\n\nresponse = portkey.completions.create(\n  model=\"gpt-3.5-turbo-instruct\",\n  prompt=\"Say this is a test\",\n  max_tokens=7,\n  temperature=0\n)\n\nprint(response)\n"
      - lang: curl
        label: Self-Hosted
        source: "curl https://SELF_HOSTED_GATEWAY_URL/completions \\\n  -H \"Content-Type: application/json\" \\\n  -H \"x-portkey-api-key: $PORTKEY_API_KEY\" \\\n  -H \"x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY\" \\\n  -d '{\n    \"model\": \"gpt-3.5-turbo-instruct\",\n    \"prompt\": \"Say this is a test\",\n    \"max_tokens\": 7,\n    \"temperature\": 0\n  }'\n"
components:
  schemas:
    CompletionUsage:
      type: object
      description: Usage statistics for the completion request.
      properties:
        completion_tokens:
          type: integer
          description: Number of tokens in the generated completion.
        prompt_tokens:
          type: integer
          description: Number of tokens in the prompt.
        total_tokens:
          type: integer
          description: Total number of tokens used in the request (prompt + completion).
        completion_tokens_details:
          type: object
          nullable: true
          description: Breakdown of tokens used in a completion.
          properties:
            reasoning_tokens:
              type: integer
              description: Tokens generated by the model for reasoning.
            accepted_prediction_tokens:
              type: integer
              description: When using Predicted Outputs, the number of tokens in the prediction that appeared in the completion.
            rejected_prediction_tokens:
              type: integer
              description: When using Predicted Outputs, the number of tokens in the prediction that did not appear in the completion.
        prompt_tokens_details:
          type: object
          nullable: true
          description: Breakdown of tokens used in the prompt.
          properties:
            cached_tokens:
              type: integer
              description: Cached tokens present in the prompt.
      required:
      - prompt_tokens
      - completion_tokens
      - total_tokens
    CreateCompletionRequest:
      type: object
      properties:
        model:
          description: 'ID of the model to use. You can use the [List models](https://platform.openai.com/docs/api-reference/models/list) API to see all of your available models, or see our [Model overview](https://platform.openai.com/docs/models/overview) for descriptions of them.

            '
          anyOf:
          - type: string
          - type: string
            enum:
            - gpt-3.5-turbo-instruct
            - davinci-002
            - babbage-002
          x-oaiTypeLabel: string
        prompt:
          description: 'The prompt(s) to generate completions for, encoded as a string, array of strings, array of tokens, or array of token arrays.


            Note that <|endoftext|> is the document separator that the model sees during training, so if a prompt is not specified the model will generate as if from the beginning of a new document.

            '
          default: <|endoftext|>
          nullable: true
          oneOf:
          - type: string
            default: ''
            example: This is a test.
          - type: array
            items:
              type: string
              default: ''
              example: This is a test.
          - type: array
            minItems: 1
            items:
              type: integer
            example: '[1212, 318, 257, 1332, 13]'
          - type: array
            minItems: 1
            items:
              type: array
              minItems: 1
              items:
                type: integer
            example: '[[1212, 318, 257, 1332, 13]]'
        best_of:
          type: integer
          default: 1
          minimum: 0
          maximum: 20
          nullable: true
          description: 'Generates `best_of` completions server-side and returns the "best" (the one with the highest log probability per token). Results cannot be streamed.


            When used with `n`, `best_of` controls the number of candidate completions and `n` specifies how many to return – `best_of` must be greater than `n`.


            **Note:** Because this parameter generates many completions, it can quickly consume your token quota. Use carefully and ensure that you have reasonable settings for `max_tokens` and `stop`.

            '
        echo:
          type: boolean
          default: false
          nullable: true
          description: 'Echo back the prompt in addition to the completion

            '
        frequency_penalty:
          type: number
          default: 0
          minimum: -2
          maximum: 2
          nullable: true
          description: 'Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model''s likelihood to repeat the same line verbatim.


            [See more information about frequency and presence penalties.](https://platform.openai.com/docs/guides/text-generation/parameter-details)

            '
        logit_bias:
          type: object
          x-oaiTypeLabel: map
          default: null
          nullable: true
          additionalProperties:
            type: integer
          description: 'Modify the likelihood of specified tokens appearing in the completion.


            Accepts a JSON object that maps tokens (specified by their token ID in the GPT tokenizer) to an associated bias value from -100 to 100. You can use this [tokenizer tool](https://platform.openai.com/tokenizer?view=bpe) to convert text to token IDs. Mathematically, the bias is added to the logits generated by the model prior to sampling. The exact effect will vary per model, but values between -1 and 1 should decrease or increase likelihood of selection; values like -100 or 100 should result in a ban or exclusive selection of the relevant token.


            As an example, you can pass `{"50256": -100}` to prevent the <|endoftext|> token from being generated.

            '
        logprobs:
          type: integer
          minimum: 0
          maximum: 5
          default: null
          nullable: true
          description: 'Include the log probabilities on the `logprobs` most likely output tokens, as well the chosen tokens. For example, if `logprobs` is 5, the API will return a list of the 5 most likely tokens. The API will always return the `logprob` of the sampled token, so there may be up to `logprobs+1` elements in the response.


            The maximum value for `logprobs` is 5.

            '
        max_tokens:
          type: integer
          minimum: 0
          default: 16
          example: 16
          nullable: true
          description: 'The maximum number of [tokens](https://platform.openai.com/tokenizer?view=bpe) that can be generated in the completion.


            The token count of your prompt plus `max_tokens` cannot exceed the model''s context length. [Example Python code](https://cookbook.openai.com/examples/how_to_count_tokens_with_tiktoken) for counting tokens.

            '
        n:
          type: integer
          minimum: 1
          maximum: 128
          default: 1
          example: 1
          nullable: true
          description: 'How many completions to generate for each prompt.


            **Note:** Because this parameter generates many completions, it can quickly consume your token quota. Use carefully and ensure that you have reasonable settings for `max_tokens` and `stop`.

            '
        presence_penalty:
          type: number
          default: 0
          minimum: -2
          maximum: 2
          nullable: true
          description: 'Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model''s likelihood to talk about new topics.


            [See more information about frequency and presence penalties.](https://platform.openai.com/docs/guides/text-generation/parameter-details)

            '
        seed:
          type: integer
          minimum: -9223372036854775808
          maximum: 9223372036854775807
          nullable: true
          description: 'If specified, our system will make a best effort to sample deterministically, such that repeated requests with the same `seed` and parameters should return the same result.


            Determinism is not guaranteed, and you should refer to the `system_fingerprint` response parameter to monitor changes in the backend.

            '
        stop:
          description: 'Up to 4 sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence.

            '
          default: null
          nullable: true
          oneOf:
          - type: string
            default: <|endoftext|>
            example: '

              '
            nullable: true
          - type: array
            minItems: 1
            maxItems: 4
            items:
              type: string
              example: '["\n"]'
        stream:
          description: 'Whether to stream back partial progress. If set, tokens will be sent as data-only [server-sent events](https://developer.mozilla.org/en-UShttps://platform.openai.com/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format) as they become available, with the stream terminated by a `data: [DONE]` message. [Example Python code](https://cookbook.openai.com/examples/how_to_stream_completions).

            '
          type: boolean
          nullable: true
          default: false
        stream_options:
          $ref: '#/components/schemas/ChatCompletionStreamOptions'
        suffix:
          description: 'The suffix that comes after a completion of inserted text.


            This parameter is only supported for `gpt-3.5-turbo-instruct`.

            '
          default: null
          nullable: true
          type: string
          example: test.
        temperature:
          type: number
          minimum: 0
          maximum: 2
          default: 1
          example: 1
          nullable: true
          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.


            We generally recommend altering this or `top_p` but not both.

            '
        top_p:
          type: number
          minimum: 0
          maximum: 1
          default: 1
          example: 1
          nullable: true
          description: 'An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.


            We generally recommend altering this or `temperature` but not both.

            '
        user:
          type: string
          example: user-1234
          description: 'A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. [Learn more](https://platform.openai.com/docs/guides/safety-best-practices/end-user-ids).

            '
      required:
      - model
      - prompt
    ChatCompletionStreamOptions:
      description: 'Options for streaming response. Only set this when you set `stream: true`.

        '
      type: object
      nullable: true
      default: null
      properties:
        include_usage:
          type: boolean
          description: 'If set, an additional chunk will be streamed before the `data: [DONE]` message. The `usage` field on this chunk shows the token usage statistics for the entire request, and the `choices` field will always be an empty array. All other chunks will also include a `usage` field, but with a null value.

            '
    CreateCompletionResponse:
      type: object
      description: 'Represents a completion response from the API. Note: both the streamed and non-streamed response objects share the same shape (unlike the chat endpoint).

        '
      properties:
        id:
          type: string
          description: A unique identifier for the completion.
        choices:
          type: array
          description: The list of completion choices the model generated for the input prompt.
          items:
            type: object
            required:
            - finish_reason
            - index
            - logprobs
            - text
            properties:
              finish_reason:
                type: string
                description: 'The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence,

                  `length` if the maximum number of tokens specified in the request was reached,

                  or `content_filter` if content was omitted due to a flag from our content filters.

                  '
                enum:
                - stop
                - length
                - content_filter
              index:
                type: integer
              logprobs:
                type: object
                nullable: true
                properties:
                  text_offset:
                    type: array
                    items:
                      type: integer
                  token_logprobs:
                    type: array
                    items:
                      type: number
                  tokens:
                    type: array
                    items:
                      type: string
                  top_logprobs:
                    type: array
                    items:
                      type: object
                      additionalProperties:
                        type: number
              text:
                type: string
        created:
          type: integer
          description: The Unix timestamp (in seconds) of when the completion was created.
        model:
          type: string
          description: The model used for completion.
        system_fingerprint:
          type: string
          description: 'This fingerprint represents the backend configuration that the model runs with.


            Can be used in conjunction with the `seed` request parameter to understand when backend changes have been made that might impact determinism.

            '
        object:
          type: string
          description: The object type, which is always "text_completion"
          enum:
          - text_completion
        usage:
          $ref: '#/components/schemas/CompletionUsage'
      required:
      - id
      - object
      - created
      - model
      - choices
      x-code-samples:
        name: The completion object
        legacy: true
        example: "{\n  \"id\": \"cmpl-uqkvlQyYK7bGYrRHQ0eXlWi7\",\n  \"object\": \"text_completion\",\n  \"created\": 1589478378,\n  \"model\": \"gpt-4-turbo\",\n  \"choices\": [\n    {\n      \"text\": \"\\n\\nThis is indeed a test\",\n      \"index\": 0,\n      \"logprobs\": null,\n      \"finish_reason\": \"length\"\n    }\n  ],\n  \"usage\": {\n    \"prompt_tokens\": 5,\n    \"completion_tokens\": 7,\n    \"total_tokens\": 12\n  }\n}\n"
  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.o

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# Full source: https://raw.githubusercontent.com/api-evangelist/portkey/refs/heads/main/openapi/portkey-completions-api-openapi.yml