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

# Create a dataset



## OpenAPI

````yaml post /datasets
openapi: 3.0.3
info:
  title: HoneyHive API
  version: 1.0.1
servers:
  - url: https://api.honeyhive.ai
security:
  - BearerAuth: []
paths:
  /datasets:
    post:
      tags:
        - Datasets
      summary: Create a dataset
      operationId: createDataset
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/CreateDatasetRequest'
      responses:
        '200':
          description: Successful creation
          content:
            application/json:
              schema:
                type: object
                properties:
                  inserted:
                    type: boolean
                  result:
                    type: object
                    properties:
                      insertedId:
                        type: string
                        description: UUID for the created dataset
      x-codeSamples:
        - lang: python
          label: createDataset
          source: >-
            import honeyhive

            from honeyhive.models import components


            s = honeyhive.HoneyHive(
                bearer_auth="<YOUR_BEARER_TOKEN_HERE>",
            )



            res =
            s.datasets.create_dataset(request=components.CreateDatasetRequest(
                project='New Project',
                name='test-dataset',
                description='A test dataset',
                type=components.CreateDatasetRequestType.EVALUATION,
                datapoints=[
                    '66369748b5773befbdc661e2',
                ],
                linked_evals=[
                    '<value>',
                ],
                saved=False,
                pipeline_type=components.CreateDatasetRequestPipelineType.EVENT,
                metadata={
                    'source': 'dev',
                },
            ))


            if res.object is not None:
                # handle response
                pass
        - lang: typescript
          label: createDataset
          source: >-
            import { HoneyHive } from "honeyhive";

            import { CreateDatasetRequestPipelineType, CreateDatasetRequestType
            } from "honeyhive/dist/models/components";


            async function run() {
              const sdk = new HoneyHive({
                bearerAuth: "<YOUR_BEARER_TOKEN_HERE>",
              });

              const res = await sdk.datasets.createDataset({
                project: "New Project",
                name: "test-dataset",
                description: "A test dataset",
                type: CreateDatasetRequestType.Evaluation,
                datapoints: [
                  "66369748b5773befbdc661e2",
                ],
                linkedEvals: [
                  "<value>",
                ],
                saved: false,
                pipelineType: CreateDatasetRequestPipelineType.Event,
                metadata: {
                  "source": "dev",
                },
              });

              if (res.statusCode == 200) {
                // handle response
              }
            }


            run();
components:
  schemas:
    CreateDatasetRequest:
      type: object
      properties:
        project:
          type: string
          description: Name of the project associated with this dataset like `New Project`
        name:
          type: string
          description: Name of the dataset
        description:
          type: string
          description: A description for the dataset
        type:
          type: string
          enum:
            - evaluation
            - fine-tuning
          description: >-
            What the dataset is to be used for - "evaluation" (default) or
            "fine-tuning"
        datapoints:
          type: array
          items:
            type: string
          description: List of unique datapoint ids to be included in this dataset
        linked_evals:
          type: array
          items:
            type: string
          description: List of unique evaluation run ids to be associated with this dataset
        saved:
          type: boolean
        pipeline_type:
          type: string
          enum:
            - event
            - session
          description: >-
            The type of data included in the dataset - "event" (default) or
            "session"
        metadata:
          type: object
          additionalProperties: true
          description: Any helpful metadata to track for the dataset
      required:
        - project
        - name
      example:
        project: New Project
        name: test-dataset
        description: A test dataset
        type: evaluation
        datapoints:
          - 66369748b5773befbdc661e2
        linked_evals: []
        saved: false
        pipeline_type: event
        metadata:
          source: dev
  securitySchemes:
    BearerAuth:
      type: http
      scheme: bearer

````