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

# List seed datasets

> Get all seed datasets for the user's company



## OpenAPI

````yaml GET /api/dataframer/seed-datasets/
openapi: 3.0.0
info:
  title: DataFramer API
  version: 0.1.0
  description: ''
  termsOfService: https://www.aimon.ai/docs/privacy-policy.pdf
  contact:
    name: DataFramer Support
    email: info@dataframer.ai
  license:
    name: Proprietary
  x-logo:
    url: https://dataframer.ai/logo.png
    altText: DataFramer AI
  x-stainless:
    package-name: aimon-dataframer
    namespace:
      - aimon
      - dataframer
servers:
  - url: https://df-api.dataframer.ai
    description: Production server
security:
  - BearerAuth: []
externalDocs:
  description: Complete API Guide
  url: https://docs.dataframer.ai/dataframer
paths:
  /api/dataframer/seed-datasets/:
    get:
      summary: List seed datasets
      description: Get all seed datasets for your company
      operationId: api_dataframer_datasets_list
      responses:
        '200':
          description: List of datasets
          content:
            application/json:
              schema:
                type: array
                items:
                  $ref: '#/components/schemas/DataframerDatasetList'
              examples:
                datasets_list:
                  value:
                    - id: 550e8400-e29b-41d4-a716-446655440000
                      name: Customer Reviews Dataset
                      description: Product reviews for analysis
                      dataset_type: SINGLE_FILE
                      created_at: '2025-01-15T10:30:00Z'
                      created_by_email: sarah.chen@acme.com
                      folder_count: 0
                      file_count: 1
        '401':
          description: Unauthorized - Invalid or missing authentication token
      x-codeSamples:
        - lang: Python
          source: |-
            import os
            from dataframer import Dataframer

            client = Dataframer(
                api_key=os.environ.get("DATAFRAMER_API_KEY"),  # This is the default and can be omitted
            )
            seed_datasets = client.dataframer.seed_datasets.list()
            print(seed_datasets)
        - lang: cURL
          source: |-
            curl https://df-api.dataframer.ai/api/dataframer/seed-datasets/ \
                -H "Authorization: Bearer $DATAFRAMER_API_KEY"
components:
  schemas:
    DataframerDatasetList:
      type: object
      properties:
        id:
          type: string
          format: uuid
          description: Unique identifier for the dataset
        name:
          type: string
          description: Dataset name
        description:
          type: string
          nullable: true
          description: Optional description of the dataset contents or purpose
        dataset_type:
          type: string
          enum:
            - SINGLE_FILE
            - MULTI_FILE
            - MULTI_FOLDER
          description: >-
            Type of dataset structure. SINGLE_FILE: one CSV/JSON/JSONL file with
            tabular data. MULTI_FILE: multiple individual text files.
            MULTI_FOLDER: files organized into folders where each folder
            represents one sample.
        created_at:
          type: string
          format: date-time
          description: Timestamp when the dataset was created
        created_by_email:
          type: string
          description: Email address of the user who created the dataset
        folder_count:
          type: integer
          description: Total number of folders in the dataset
        file_count:
          type: integer
          description: Total number of files in the dataset
  securitySchemes:
    BearerAuth:
      type: http
      scheme: bearer
      bearerFormat: API Key
      description: 'API Key authentication. Format: "Bearer YOUR_API_KEY"'

````

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