> ## Documentation Index
> Fetch the complete documentation index at: https://arize-ax.mintlify.site/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Create an experiment

> Create a new experiment. Empty experiments are not allowed.

Experiments are composed of "runs". Each experiment run (JSON object)
must include an `example_id` field that corresponds to an example in
the dataset, and a `output` field that contains the task's output for
the example (the input).

Payload Requirements
- The `name` must be unique within the target dataset
- Provide at least one run in `experiment_runs`.
- Each run must include:
  - `example_id` -- the ID of an existing example in the dataset/version
  - `output` -- model/task output for that example
  - You may include any additional fields per run that can be used for
  analysis or filtering. For exampple: `model`, `latency_ms`,
  `temperature`, `prompt`, `tool_calls`, etc.

<Note>This endpoint is in beta, read more [here](https://arize.com/docs/ax/rest-reference#api-version-stages).</Note>




## OpenAPI

````yaml https://api.arize.com/v2/spec.yaml post /v2/experiments
openapi: 3.0.3
info:
  title: Arize REST API
  version: 2.0.0
  description: |
    API specification for the backend data server. The API is hosted globally
    at https://api.arize.com/v2 or in your own environment.
  license:
    name: Apache-2.0
    url: https://www.apache.org/licenses/LICENSE-2.0
servers:
  - description: Global
    url: https://api.arize.com
  - description: Regional
    url: https://api.{region}.arize.com
    variables:
      region:
        default: eu-west-1a
        enum:
          - eu-west-1a
          - ca-central-1a
  - description: Custom Host
    url: https://{host}
    variables:
      host:
        default: api.arize.com
security:
  - bearerAuth: []
tags:
  - name: AI Integrations
    description: |
      AI integrations configure access to external LLM providers (e.g. OpenAI,
      Azure OpenAI, AWS Bedrock, Vertex AI). Integrations can be scoped to the
      entire account, a specific organization, or a specific space.
  - name: Annotation Configs
    description: >
      Annotation configs allow you to define consistent annotation schemas that

      can be reused across your workspace, ensuring evaluations are structured
      and

      comparable over time.
  - name: Annotation Queues
    description: >
      Annotation queues help you organize and manage human evaluation workflows.

      Use queues to assign spans or examples to annotators for review and
      labeling.
  - name: API Keys
    description: >
      API keys are used to authenticate requests to the Arize API. List your
      keys

      to view metadata; the raw secret is never returned after creation.
  - name: Datasets
    description: |
      Datasets are structured, version-controlled example collections you use to
      run, evaluate, and track LLM experiments.
  - name: Evaluators
    description: >
      Evaluators are reusable evaluation configurations used to assess the
      quality

      of LLM outputs. They can be template-based (using LLM judges) or
      code-based.
  - name: Experiments
    description: >
      Experiments let you systematically test prompt/model changes using
      datasets,

      tasks, and evaluators.
  - name: Integrations
    description: >
      Integrations configure access to external LLM providers (e.g. OpenAI,

      Azure OpenAI, AWS Bedrock, Vertex AI), notifications services (e.g.
      PagerDuty, Slack), and

      your own agents. Integrations can be scoped to the entire account, a
      specific

      organization, or a specific space.
  - name: Organizations
    description: >
      Organizations are top-level containers within an Arize AX account for
      grouping spaces.
  - name: Projects
    description: |
      Projects represent LLM applications being monitored in Arize where you can
      observe traces and spans.
  - name: Prompts
    description: >
      Prompts are reusable, versioned templates for LLM interactions. Use
      prompts

      to standardize and manage how you interact with LLMs across your
      application.
  - name: Resource Restrictions
    description: |
      Endpoints for restricting and unrestricting resources (projects, models).
  - name: Role Bindings
    description: |
      Role bindings assign a role to a user on a resource. REST currently
      supports space- and project-scoped bindings.
  - name: Roles
    description: >
      Roles define sets of permissions that can be assigned to users within an

      account. Create custom roles to tailor access control to your team's
      needs.
  - name: Spaces
    description: >
      Spaces are containers within an organization for grouping related
      projects,

      datasets, and experiments, enabling collaboration or isolated
      experimentation

      with role-based access control.
  - name: Spans
    description: |
      Spans represent individual operations within a trace. A span captures the
      timing, status, and attributes of a single operation in your application.
  - name: Tasks
    description: |
      Tasks are configurable units of work that tie one or more evaluators to a
      data source (project or dataset). Use tasks to automate evaluation of LLM
      outputs, with support for continuous evaluation and backfill runs.
  - name: Users
    description: >
      Users represent members of an account. The Users endpoints allow creating,

      listing, updating (display name), and removing users from the account
      programmatically.
paths:
  /v2/experiments:
    post:
      tags:
        - Experiments
      summary: Create an experiment
      description: >
        Create a new experiment. Empty experiments are not allowed.


        Experiments are composed of "runs". Each experiment run (JSON object)

        must include an `example_id` field that corresponds to an example in

        the dataset, and a `output` field that contains the task's output for

        the example (the input).


        Payload Requirements

        - The `name` must be unique within the target dataset

        - Provide at least one run in `experiment_runs`.

        - Each run must include:
          - `example_id` -- the ID of an existing example in the dataset/version
          - `output` -- model/task output for that example
          - You may include any additional fields per run that can be used for
          analysis or filtering. For exampple: `model`, `latency_ms`,
          `temperature`, `prompt`, `tool_calls`, etc.

        <Note>This endpoint is in beta, read more
        [here](https://arize.com/docs/ax/rest-reference#api-version-stages).</Note>
      operationId: experiments_create
      requestBody:
        $ref: '#/components/requestBodies/CreateExperimentRequestBody'
      responses:
        '201':
          $ref: '#/components/responses/Experiment'
        '400':
          $ref: '#/components/responses/BadRequest'
        '401':
          $ref: '#/components/responses/Unauthorized'
        '403':
          $ref: '#/components/responses/Forbidden'
        '404':
          $ref: '#/components/responses/NotFound'
        '409':
          $ref: '#/components/responses/Conflict'
        '422':
          $ref: '#/components/responses/UnprocessableEntity'
        '429':
          $ref: '#/components/responses/RateLimitExceeded'
components:
  requestBodies:
    CreateExperimentRequestBody:
      description: Body containing experiment creation parameters
      required: true
      content:
        application/json:
          schema:
            required:
              - name
              - dataset_id
              - experiment_runs
            type: object
            properties:
              name:
                type: string
                description: Name of the experiment
              dataset_id:
                type: string
                description: ID of the dataset to create the experiment for
              experiment_runs:
                type: array
                description: Array of experiment run data
                items:
                  $ref: '#/components/schemas/ExperimentRunCreate'
          example:
            name: My Experiment Name
            dataset_id: dataset_12345
            experiment_runs:
              - example_id: example_001
                output: '4'
                model: gpt-4o-mini
                temperature: 0.2
                latency_ms: 118
                prompt: Answer the math question briefly.
              - example_id: example_002
                output: '4'
                model: gpt-4o-mini
                temperature: 0.2
                latency_ms: 132
              - example_id: example_003
                output: '4'
                model: gpt-4o-mini
                temperature: 0.2
                latency_ms: 125
  responses:
    Experiment:
      description: An experiment object
      content:
        application/json:
          schema:
            $ref: '#/components/schemas/Experiment'
          example:
            id: RXhwZXJpbWVudDoxOmFCY0Q=
            name: Experiment 1
            dataset_id: RGF0YXNldDoxOmFCY0Q=
            dataset_version_id: RGF0YXNldFZlcnNpb246MTphQmNE
            created_at: '2024-01-01T12:00:00Z'
            updated_at: '2024-01-02T12:00:00Z'
    BadRequest:
      description: Invalid request
      content:
        application/problem+json:
          schema:
            $ref: '#/components/schemas/Problem'
          example:
            status: 400
            title: Invalid request parameters
            detail: The 'name' field is required and must be a non-empty string.
            instance: /resource
            type: https://arize.com/docs/ax/rest-reference/errors#invalid-request
    Unauthorized:
      description: Authentication is required
      content:
        application/problem+json:
          schema:
            $ref: '#/components/schemas/Problem'
          example:
            status: 401
            title: Authentication required
            detail: You must be authenticated to access this resource.
            instance: /resource
            type: >-
              https://arize.com/docs/ax/rest-reference/errors#authentication-required
    Forbidden:
      description: Insufficient permissions to access this resource
      content:
        application/problem+json:
          schema:
            $ref: '#/components/schemas/Problem'
          example:
            status: 403
            title: Access forbidden
            detail: You do not have permission to access this resource.
            instance: /resource/12345
            type: https://arize.com/docs/ax/rest-reference/errors#access-forbidden
    NotFound:
      description: Not found
      content:
        application/problem+json:
          schema:
            $ref: '#/components/schemas/Problem'
          example:
            status: 404
            title: Resource not found
            detail: The requested resource with ID '12345' was not found.
            instance: /resource/12345
            type: https://arize.com/docs/ax/rest-reference/errors#resource-not-found
    Conflict:
      description: Resource conflict
      content:
        application/problem+json:
          schema:
            $ref: '#/components/schemas/Problem'
          example:
            status: 409
            title: Resource conflict
            detail: A resource with the given identifier already exists.
            instance: /resource
            type: https://arize.com/docs/ax/rest-reference/errors#resource-conflict
    UnprocessableEntity:
      description: Unprocessable entity
      content:
        application/problem+json:
          schema:
            $ref: '#/components/schemas/Problem'
          example:
            status: 422
            title: Unprocessable Entity
            detail: One or more fields failed validation.
            instance: /resource/12345
            type: >-
              https://arize.com/docs/ax/rest-reference/errors#unprocessable-entity
    RateLimitExceeded:
      description: Rate limit exceeded
      headers:
        Retry-After:
          description: |
            When throttled (429), how long to wait before retrying. Value is
            either a delta-seconds integer.
          schema:
            type: integer
            minimum: 0
          example: 42
      content:
        application/problem+json:
          schema:
            $ref: '#/components/schemas/Problem'
          example:
            status: 429
            title: Rate limit exceeded
            detail: >-
              You have exceeded the allowed number of requests. Please try again
              later.
            instance: /resource
            type: >-
              https://arize.com/docs/ax/rest-reference/errors#rate-limit-exceeded
  schemas:
    ExperimentRunCreate:
      type: object
      description: >-
        An experiment run with experiment data including outputs, evaluations,
        and trace metadata
      properties:
        example_id:
          type: string
          description: ID of the dataset example associated with this experiment run
        output:
          type: string
          description: output of the task for the matching example
      required:
        - example_id
        - output
      additionalProperties: true
    Experiment:
      required:
        - id
        - name
        - dataset_id
        - dataset_version_id
        - created_at
        - updated_at
      type: object
      properties:
        id:
          type: string
          description: Unique identifier for the experiment
        name:
          type: string
          description: Name of the experiment
        dataset_id:
          type: string
          description: Unique identifier for the dataset this experiment belongs to
        dataset_version_id:
          type: string
          description: Unique identifier for the dataset version this experiment belongs to
        created_at:
          type: string
          description: Timestamp for when the experiment was created
          format: date-time
        updated_at:
          type: string
          description: Timestamp for the last update of the experiment
          format: date-time
        experiment_traces_project_id:
          type: string
          description: >-
            Unique identifier for the experiment traces project this experiment
            belongs to (if it exists)
      description: >
        Experiments combine a dataset (example inputs/expected outputs), a task

        (the function that produces model outputs), and one or more evaluators

        (code or LLM judges) to measure performance. Each run is stored
        independently

        so you can compare runs, track progress, and validate improvements over
        time.

        See the full definition on the Experiments page.


        Use an experiment to run tasks on a dataset, attach evaluators to score
        outputs,

        and compare runs to confirm improvements.
      additionalProperties: false
    Problem:
      type: object
      description: RFC 9457 Problem Details
      properties:
        title:
          type: string
          description: A short, human-readable summary of the problem type
        status:
          type: integer
          description: >-
            The HTTP status code generated by the origin server for this
            occurrence of the problem
        type:
          type: string
          format: uri-reference
          description: A URI reference that identifies the problem type
        detail:
          type: string
          description: >-
            A human-readable explanation specific to this occurrence of the
            problem
        instance:
          type: string
          format: uri-reference
          description: >-
            A URI reference that identifies the specific occurrence of the
            problem
      required:
        - title
        - status
      additionalProperties: false
  securitySchemes:
    bearerAuth:
      type: http
      scheme: bearer
      bearerFormat: <api-key>
      description: >
        Most Arize AI endpoints require authentication. For those endpoints that
        require authentication, include your API key in the request header using
        the format

        ``` Authorization: Bearer <api-key>

        ```

````