openapi: 3.0.0
info:
  title: 'OpenAI fine tuning'
  description: Needs description.
  version: 2.0.0
  termsOfService: https://openai.com/policies/terms-of-use
  contact:
    name: OpenAI Support
    url: https://help.openai.com/
  license:
    name: MIT
    url: https://github.com/openai/openai-openapi/blob/master/LICENSE
servers:
  - url: https://api.openai.com/v1
tags:
  - name: Fine Tuning
paths:
  /fine_tuning/jobs:
    post:
      operationId: createFineTuningJob
      tags:
        - Fine Tuning
      summary: >-
        OpenAI Creates a fine-tuning job which begins the process of creating a new model from a given dataset.


        Response includes details of the enqueued job including job status and the name of the fine-tuned models once complete.


        [Learn more about fine-tuning](/docs/guides/fine-tuning)
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/CreateFineTuningJobRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/FineTuningJob'
      x-oaiMeta:
        name: Create fine-tuning job
        group: fine-tuning
        returns: A [fine-tuning.job](/docs/api-reference/fine-tuning/object) object.
        examples:
          - title: Default
            request:
              curl: |
                curl https://api.openai.com/v1/fine_tuning/jobs \
                  -H "Content-Type: application/json" \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -d '{
                    "training_file": "file-BK7bzQj3FfZFXr7DbL6xJwfo",
                    "model": "gpt-3.5-turbo"
                  }'
              python: |
                from openai import OpenAI
                client = OpenAI()

                client.fine_tuning.jobs.create(
                  training_file="file-abc123",
                  model="gpt-3.5-turbo"
                )
              node.js: |
                import OpenAI from "openai";

                const openai = new OpenAI();

                async function main() {
                  const fineTune = await openai.fineTuning.jobs.create({
                    training_file: "file-abc123"
                  });

                  console.log(fineTune);
                }

                main();
            response: |
              {
                "object": "fine_tuning.job",
                "id": "ftjob-abc123",
                "model": "gpt-3.5-turbo-0613",
                "created_at": 1614807352,
                "fine_tuned_model": null,
                "organization_id": "org-123",
                "result_files": [],
                "status": "queued",
                "validation_file": null,
                "training_file": "file-abc123",
              }
          - title: Epochs
            request:
              curl: |
                curl https://api.openai.com/v1/fine_tuning/jobs \
                  -H "Content-Type: application/json" \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -d '{
                    "training_file": "file-abc123",
                    "model": "gpt-3.5-turbo",
                    "hyperparameters": {
                      "n_epochs": 2
                    }
                  }'
              python: |
                from openai import OpenAI
                client = OpenAI()

                client.fine_tuning.jobs.create(
                  training_file="file-abc123",
                  model="gpt-3.5-turbo",
                  hyperparameters={
                    "n_epochs":2
                  }
                )
              node.js: |
                import OpenAI from "openai";

                const openai = new OpenAI();

                async function main() {
                  const fineTune = await openai.fineTuning.jobs.create({
                    training_file: "file-abc123",
                    model: "gpt-3.5-turbo",
                    hyperparameters: { n_epochs: 2 }
                  });

                  console.log(fineTune);
                }

                main();
            response: |
              {
                "object": "fine_tuning.job",
                "id": "ftjob-abc123",
                "model": "gpt-3.5-turbo-0613",
                "created_at": 1614807352,
                "fine_tuned_model": null,
                "organization_id": "org-123",
                "result_files": [],
                "status": "queued",
                "validation_file": null,
                "training_file": "file-abc123",
                "hyperparameters": {"n_epochs": 2},
              }
          - title: Validation file
            request:
              curl: |
                curl https://api.openai.com/v1/fine_tuning/jobs \
                  -H "Content-Type: application/json" \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -d '{
                    "training_file": "file-abc123",
                    "validation_file": "file-abc123",
                    "model": "gpt-3.5-turbo"
                  }'
              python: |
                from openai import OpenAI
                client = OpenAI()

                client.fine_tuning.jobs.create(
                  training_file="file-abc123",
                  validation_file="file-def456",
                  model="gpt-3.5-turbo"
                )
              node.js: |
                import OpenAI from "openai";

                const openai = new OpenAI();

                async function main() {
                  const fineTune = await openai.fineTuning.jobs.create({
                    training_file: "file-abc123",
                    validation_file: "file-abc123"
                  });

                  console.log(fineTune);
                }

                main();
            response: |
              {
                "object": "fine_tuning.job",
                "id": "ftjob-abc123",
                "model": "gpt-3.5-turbo-0613",
                "created_at": 1614807352,
                "fine_tuned_model": null,
                "organization_id": "org-123",
                "result_files": [],
                "status": "queued",
                "validation_file": "file-abc123",
                "training_file": "file-abc123",
              }
    get:
      operationId: listPaginatedFineTuningJobs
      tags:
        - Fine Tuning
      summary: |-
        OpenAI List your organization's fine-tuning jobs
      parameters:
        - name: after
          in: query
          description: Identifier for the last job from the previous pagination request.
          required: false
          schema:
            type: string
        - name: limit
          in: query
          description: Number of fine-tuning jobs to retrieve.
          required: false
          schema:
            type: integer
            default: 20
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ListPaginatedFineTuningJobsResponse'
      x-oaiMeta:
        name: List fine-tuning jobs
        group: fine-tuning
        returns: >-
          A list of paginated [fine-tuning
          job](/docs/api-reference/fine-tuning/object) objects.
        examples:
          request:
            curl: |
              curl https://api.openai.com/v1/fine_tuning/jobs?limit=2 \
                -H "Authorization: Bearer $OPENAI_API_KEY"
            python: |
              from openai import OpenAI
              client = OpenAI()

              client.fine_tuning.jobs.list()
            node.js: |-
              import OpenAI from "openai";

              const openai = new OpenAI();

              async function main() {
                const list = await openai.fineTuning.jobs.list();

                for await (const fineTune of list) {
                  console.log(fineTune);
                }
              }

              main();
          response: |
            {
              "object": "list",
              "data": [
                {
                  "object": "fine_tuning.job.event",
                  "id": "ft-event-TjX0lMfOniCZX64t9PUQT5hn",
                  "created_at": 1689813489,
                  "level": "warn",
                  "message": "Fine tuning process stopping due to job cancellation",
                  "data": null,
                  "type": "message"
                },
                { ... },
                { ... }
              ], "has_more": true
            }
  /fine_tuning/jobs/{fine_tuning_job_id}:
    get:
      operationId: retrieveFineTuningJob
      tags:
        - Fine Tuning
      summary: |-
        OpenAI Get info about a fine-tuning job.

        [Learn more about fine-tuning](/docs/guides/fine-tuning)
      parameters:
        - in: path
          name: fine_tuning_job_id
          required: true
          schema:
            type: string
            example: ft-AF1WoRqd3aJAHsqc9NY7iL8F
          description: |
            The ID of the fine-tuning job.
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/FineTuningJob'
      x-oaiMeta:
        name: Retrieve fine-tuning job
        group: fine-tuning
        returns: >-
          The [fine-tuning](/docs/api-reference/fine-tuning/object) object with
          the given ID.
        examples:
          request:
            curl: >
              curl
              https://api.openai.com/v1/fine_tuning/jobs/ft-AF1WoRqd3aJAHsqc9NY7iL8F
              \
                -H "Authorization: Bearer $OPENAI_API_KEY"
            python: |
              from openai import OpenAI
              client = OpenAI()

              client.fine_tuning.jobs.retrieve("ftjob-abc123")
            node.js: |
              import OpenAI from "openai";

              const openai = new OpenAI();

              async function main() {
                const fineTune = await openai.fineTuning.jobs.retrieve("ftjob-abc123");

                console.log(fineTune);
              }

              main();
          response: |
            {
              "object": "fine_tuning.job",
              "id": "ftjob-abc123",
              "model": "davinci-002",
              "created_at": 1692661014,
              "finished_at": 1692661190,
              "fine_tuned_model": "ft:davinci-002:my-org:custom_suffix:7q8mpxmy",
              "organization_id": "org-123",
              "result_files": [
                  "file-abc123"
              ],
              "status": "succeeded",
              "validation_file": null,
              "training_file": "file-abc123",
              "hyperparameters": {
                  "n_epochs": 4,
              },
              "trained_tokens": 5768
            }
  /fine_tuning/jobs/{fine_tuning_job_id}/events:
    get:
      operationId: listFineTuningEvents
      tags:
        - Fine Tuning
      summary: |-
        OpenAI Get status updates for a fine-tuning job.
      parameters:
        - in: path
          name: fine_tuning_job_id
          required: true
          schema:
            type: string
            example: ft-AF1WoRqd3aJAHsqc9NY7iL8F
          description: |
            The ID of the fine-tuning job to get events for.
        - name: after
          in: query
          description: Identifier for the last event from the previous pagination request.
          required: false
          schema:
            type: string
        - name: limit
          in: query
          description: Number of events to retrieve.
          required: false
          schema:
            type: integer
            default: 20
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ListFineTuningJobEventsResponse'
      x-oaiMeta:
        name: List fine-tuning events
        group: fine-tuning
        returns: A list of fine-tuning event objects.
        examples:
          request:
            curl: >
              curl
              https://api.openai.com/v1/fine_tuning/jobs/ftjob-abc123/events \
                -H "Authorization: Bearer $OPENAI_API_KEY"
            python: |
              from openai import OpenAI
              client = OpenAI()

              client.fine_tuning.jobs.list_events(
                fine_tuning_job_id="ftjob-abc123",
                limit=2
              )
            node.js: |-
              import OpenAI from "openai";

              const openai = new OpenAI();

              async function main() {
                const list = await openai.fineTuning.list_events(id="ftjob-abc123", limit=2);

                for await (const fineTune of list) {
                  console.log(fineTune);
                }
              }

              main();
          response: |
            {
              "object": "list",
              "data": [
                {
                  "object": "fine_tuning.job.event",
                  "id": "ft-event-ddTJfwuMVpfLXseO0Am0Gqjm",
                  "created_at": 1692407401,
                  "level": "info",
                  "message": "Fine tuning job successfully completed",
                  "data": null,
                  "type": "message"
                },
                {
                  "object": "fine_tuning.job.event",
                  "id": "ft-event-tyiGuB72evQncpH87xe505Sv",
                  "created_at": 1692407400,
                  "level": "info",
                  "message": "New fine-tuned model created: ft:gpt-3.5-turbo:openai::7p4lURel",
                  "data": null,
                  "type": "message"
                }
              ],
              "has_more": true
            }
  /fine_tuning/jobs/{fine_tuning_job_id}/cancel:
    post:
      operationId: cancelFineTuningJob
      tags:
        - Fine Tuning
      summary: |-
        OpenAI Immediately cancel a fine-tune job.
      parameters:
        - in: path
          name: fine_tuning_job_id
          required: true
          schema:
            type: string
            example: ft-AF1WoRqd3aJAHsqc9NY7iL8F
          description: |
            The ID of the fine-tuning job to cancel.
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/FineTuningJob'
      x-oaiMeta:
        name: Cancel fine-tuning
        group: fine-tuning
        returns: >-
          The cancelled [fine-tuning](/docs/api-reference/fine-tuning/object)
          object.
        examples:
          request:
            curl: >
              curl -X POST
              https://api.openai.com/v1/fine_tuning/jobs/ftjob-abc123/cancel \
                -H "Authorization: Bearer $OPENAI_API_KEY"
            python: |
              from openai import OpenAI
              client = OpenAI()

              client.fine_tuning.jobs.cancel("ftjob-abc123")
            node.js: |-
              import OpenAI from "openai";

              const openai = new OpenAI();

              async function main() {
                const fineTune = await openai.fineTuning.jobs.cancel("ftjob-abc123");

                console.log(fineTune);
              }
              main();
          response: |
            {
              "object": "fine_tuning.job",
              "id": "ftjob-abc123",
              "model": "gpt-3.5-turbo-0613",
              "created_at": 1689376978,
              "fine_tuned_model": null,
              "organization_id": "org-123",
              "result_files": [],
              "hyperparameters": {
                "n_epochs":  "auto"
              },
              "status": "cancelled",
              "validation_file": "file-abc123",
              "training_file": "file-abc123"
            }
components:
  securitySchemes:
    ApiKeyAuth:
      type: http
      scheme: bearer
  schemas:
    FineTuningJob:
      type: object
      title: FineTuningJob
      description: >
        The `fine_tuning.job` object represents a fine-tuning job that has been
        created through the API.
      properties:
        id:
          type: string
          description: The object identifier, which can be referenced in the API endpoints.
        created_at:
          type: integer
          description: >-
            The Unix timestamp (in seconds) for when the fine-tuning job was
            created.
        error:
          type: object
          nullable: true
          description: >-
            For fine-tuning jobs that have `failed`, this will contain more
            information on the cause of the failure.
          properties:
            code:
              type: string
              description: A machine-readable error code.
            message:
              type: string
              description: A human-readable error message.
            param:
              type: string
              description: >-
                The parameter that was invalid, usually `training_file` or
                `validation_file`. This field will be null if the failure was
                not parameter-specific.
              nullable: true
          required:
            - code
            - message
            - param
        fine_tuned_model:
          type: string
          nullable: true
          description: >-
            The name of the fine-tuned model that is being created. The value
            will be null if the fine-tuning job is still running.
        finished_at:
          type: integer
          nullable: true
          description: >-
            The Unix timestamp (in seconds) for when the fine-tuning job was
            finished. The value will be null if the fine-tuning job is still
            running.
        hyperparameters:
          type: object
          description: >-
            The hyperparameters used for the fine-tuning job. See the
            [fine-tuning guide](/docs/guides/fine-tuning) for more details.
          properties:
            n_epochs:
              oneOf:
                - type: string
                  enum:
                    - auto
                - type: integer
                  minimum: 1
                  maximum: 50
              default: auto
              description: >-
                The number of epochs to train the model for. An epoch refers to
                one full cycle through the training dataset.

                "auto" decides the optimal number of epochs based on the size of
                the dataset. If setting the number manually, we support any
                number between 1 and 50 epochs.
          required:
            - n_epochs
        model:
          type: string
          description: The base model that is being fine-tuned.
        object:
          type: string
          description: The object type, which is always "fine_tuning.job".
          enum:
            - fine_tuning.job
        organization_id:
          type: string
          description: The organization that owns the fine-tuning job.
        result_files:
          type: array
          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).
          items:
            type: string
            example: file-abc123
        status:
          type: string
          description: >-
            The current status of the fine-tuning job, which can be either
            `validating_files`, `queued`, `running`, `succeeded`, `failed`, or
            `cancelled`.
          enum:
            - validating_files
            - queued
            - running
            - succeeded
            - failed
            - cancelled
        trained_tokens:
          type: integer
          nullable: true
          description: >-
            The total number of billable tokens processed by this fine-tuning
            job. The value will be null if the fine-tuning job is still running.
        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
          description: >-
            The file ID used for validation. You can retrieve the validation
            results with the [Files
            API](/docs/api-reference/files/retrieve-contents).
      required:
        - created_at
        - error
        - finished_at
        - fine_tuned_model
        - hyperparameters
        - id
        - model
        - object
        - organization_id
        - result_files
        - status
        - trained_tokens
        - training_file
        - validation_file
      x-oaiMeta:
        name: The fine-tuning job object
        example: |
          {
            "object": "fine_tuning.job",
            "id": "ftjob-abc123",
            "model": "davinci-002",
            "created_at": 1692661014,
            "finished_at": 1692661190,
            "fine_tuned_model": "ft:davinci-002:my-org:custom_suffix:7q8mpxmy",
            "organization_id": "org-123",
            "result_files": [
                "file-abc123"
            ],
            "status": "succeeded",
            "validation_file": null,
            "training_file": "file-abc123",
            "hyperparameters": {
                "n_epochs": 4,
            },
            "trained_tokens": 5768
          }
    ListPaginatedFineTuningJobsResponse:
      type: object
      properties:
        data:
          type: array
          items:
            $ref: '#/components/schemas/FineTuningJob'
        has_more:
          type: boolean
        object:
          type: string
          enum:
            - list
      required:
        - object
        - data
        - has_more
    ListFineTuningJobEventsResponse:
      type: object
      properties:
        data:
          type: array
          items:
            $ref: '#/components/schemas/FineTuningJobEvent'
        object:
          type: string
          enum:
            - list
      required:
        - object
        - data
security:
  - ApiKeyAuth: []
x-oaiMeta:
  groups:
    - id: audio
      title: Audio
      description: |
        Learn how to turn audio into text or text into audio.

        Related guide: [Speech to text](/docs/guides/speech-to-text)
      sections:
        - type: endpoint
          key: createSpeech
          path: createSpeech
        - type: endpoint
          key: createTranscription
          path: createTranscription
        - type: endpoint
          key: createTranslation
          path: createTranslation
    - id: chat
      title: Chat
      description: >
        Given a list of messages comprising a conversation, the model will
        return a response.


        Related guide: [Chat Completions](/docs/guides/text-generation)
      sections:
        - type: endpoint
          key: createChatCompletion
          path: create
        - type: object
          key: CreateChatCompletionResponse
          path: object
        - type: object
          key: CreateChatCompletionStreamResponse
          path: streaming
    - 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](/docs/guides/embeddings)
      sections:
        - type: endpoint
          key: createEmbedding
          path: create
        - type: object
          key: Embedding
          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](/docs/guides/fine-tuning)
      sections:
        - type: endpoint
          key: createFineTuningJob
          path: create
        - type: endpoint
          key: listPaginatedFineTuningJobs
          path: list
        - type: endpoint
          key: listFineTuningEvents
          path: list-events
        - type: endpoint
          key: retrieveFineTuningJob
          path: retrieve
        - type: endpoint
          key: cancelFineTuningJob
          path: cancel
        - type: object
          key: FineTuningJob
          path: object
        - type: object
          key: FineTuningJobEvent
          path: event-object
    - id: files
      title: Files
      description: >
        Files are used to upload documents that can be used with features like
        [Assistants](/docs/api-reference/assistants) and
        [Fine-tuning](/docs/api-reference/fine-tuning).
      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](/docs/guides/images)
      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](/docs/models) documentation to understand what models
        are available and the differences between them.
      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 a input text, outputs if the model classifies it as violating
        OpenAI's content policy.


        Related guide: [Moderations](/docs/guides/moderation)
      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](/docs/assistants)
      sections:
        - type: endpoint
          key: createAssistant
          path: createAssistant
        - type: endpoint
          key: createAssistantFile
          path: createAssistantFile
        - type: endpoint
          key: listAssistants
          path: listAssistants
        - type: endpoint
          key: listAssistantFiles
          path: listAssistantFiles
        - type: endpoint
          key: getAssistant
          path: getAssistant
        - type: endpoint
          key: getAssistantFile
          path: getAssistantFile
        - type: endpoint
          key: modifyAssistant
          path: modifyAssistant
        - type: endpoint
          key: deleteAssistant
          path: deleteAssistant
        - type: endpoint
          key: deleteAssistantFile
          path: deleteAssistantFile
        - type: object
          key: AssistantObject
          path: object
        - type: object
          key: AssistantFileObject
          path: file-object
    - id: threads
      title: Threads
      beta: true
      description: |
        Create threads that assistants can interact with.

        Related guide: [Assistants](/docs/assistants/overview)
      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](/docs/assistants/overview)
      sections:
        - type: endpoint
          key: createMessage
          path: createMessage
        - type: endpoint
          key: listMessages
          path: listMessages
        - type: endpoint
          key: listMessageFiles
          path: listMessageFiles
        - type: endpoint
          key: getMessage
          path: getMessage
        - type: endpoint
          key: getMessageFile
          path: getMessageFile
        - type: endpoint
          key: modifyMessage
          path: modifyMessage
        - type: object
          key: MessageObject
          path: object
        - type: object
          key: MessageFileObject
          path: file-object
    - id: runs
      title: Runs
      beta: true
      description: |
        Represents an execution run on a thread.

        Related guide: [Assistants](/docs/assistants/overview)
      sections:
        - type: endpoint
          key: createRun
          path: createRun
        - type: endpoint
          key: createThreadAndRun
          path: createThreadAndRun
        - type: endpoint
          key: listRuns
          path: listRuns
        - type: endpoint
          key: listRunSteps
          path: listRunSteps
        - type: endpoint
          key: getRun
          path: getRun
        - type: endpoint
          key: getRunStep
          path: getRunStep
        - type: endpoint
          key: modifyRun
          path: modifyRun
        - type: endpoint
          key: submitToolOuputsToRun
          path: submitToolOutputs
        - type: endpoint
          key: cancelRun
          path: cancelRun
        - type: object
          key: RunObject
          path: object
        - type: object
          key: RunStepObject
          path: step-object
    - id: completions
      title: Completions
      legacy: true
      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](/docs/guides/text-generation/text-generation-models) to leverage
        our best and newest models. Most models that support the legacy
        Completions endpoint [will be shut off on January 4th,
        2024](/docs/deprecations/2023-07-06-gpt-and-embeddings).
      sections:
        - type: endpoint
          key: createCompletion
          path: create
        - type: object
          key: CreateCompletionResponse
          path: object