> ## Documentation Index > Fetch the complete documentation index at: https://docs.dataframer.ai/llms.txt > Use this file to discover all available pages before exploring further. # Create seed dataset from ZIP > Create a seed dataset by uploading a ZIP file The system automatically detects the dataset type based on ZIP structure: * **SINGLE\_FILE**: ZIP contains exactly one file containing all the samples * **MULTI\_FILE**: ZIP contains multiple files at root level, where each file is a separate sample * **MULTI\_FOLDER**: ZIP contains multiple folders, where each folder is a separate sample and only contains files with no nested folders ## File constraints by dataset type | Type | Allowed formats | Size limit | Count limit | | ------------- | ------------------------------ | -------------------- | -------------------------------------- | | SINGLE\_FILE | CSV, JSON, JSONL | 50MB | 1 file, min 2 rows | | MULTI\_FILE | TXT, MD, JSON, CSV, JSONL, PDF | 1MB/file, 50MB total | 2-1000 files | | MULTI\_FOLDER | TXT, MD, JSON, CSV, JSONL, PDF | 1MB/file, 50MB total | 2-1000 files, 20/folder, min 2 folders | ## OpenAPI ````yaml POST /api/dataframer/seed-datasets/create-from-zip/ 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: [] tags: - name: Seed Datasets description: Manage seed datasets for generation - name: Specs description: Data specifications for sample generation - name: Runs description: Generation runs and results - name: Evaluations description: Evaluate generated sample quality - name: Red Teaming description: Security testing and adversarial prompts - name: Spec Creation description: Create specs from datasets or from scratch (seedless) - name: Generation description: Synthetic data generation - name: API Keys description: API key management and rotation - name: Health description: Health check endpoints - name: Models description: Available AI models externalDocs: description: Complete API Guide url: https://docs.dataframer.ai/dataframer paths: /api/dataframer/seed-datasets/create-from-zip/: post: tags: - Seed Datasets summary: Create seed dataset from ZIP description: >- Create a seed dataset by uploading a ZIP file. The system automatically detects the dataset type based on ZIP structure: - **SINGLE_FILE**: ZIP contains exactly one file containing all the samples - **MULTI_FILE**: ZIP contains multiple files at root level, where each file is a separate sample - **MULTI_FOLDER**: ZIP contains multiple folders, where each folder is a separate sample and only contains files with no nested folders ## File constraints by dataset type | Type | Allowed formats | Size limit | Count limit | |------|----------------|------------|-------------| | SINGLE_FILE | CSV, JSON, JSONL | 50MB | 1 file, min 2 rows | | MULTI_FILE | TXT, MD, JSON, CSV, JSONL, PDF | 1MB/file, 50MB total | 2-1000 files | | MULTI_FOLDER | TXT, MD, JSON, CSV, JSONL, PDF | 1MB/file, 50MB total | 2-1000 files, 20/folder, min 2 folders | operationId: api_dataframer_datasets_create_from_zip requestBody: required: true content: multipart/form-data: schema: type: object required: - name - zip_file properties: name: type: string description: Dataset name (unique within company) description: type: string description: Optional dataset description zip_file: type: string format: binary description: >- ZIP file containing dataset files. For MULTI_FOLDER datasets, the order files appear in the ZIP determines their order within each folder — earlier files should be the ones that later files may depend on. encoding: zip_file: contentType: application/zip responses: '201': description: Seed dataset created successfully content: application/json: schema: $ref: '#/components/schemas/DataframerDataset' examples: dataset_from_zip: value: id: 550e8400-e29b-41d4-a716-446655440000 name: Support Ticket Conversations description: Customer support chat logs organized by ticket dataset_type: MULTI_FOLDER file_count: 10 folder_count: 2 created_at: '2025-01-15T10:30:00Z' updated_at: '2025-01-15T10:30:00Z' created_by_email: sarah.chen@acme.com '400': description: Bad Request - Invalid ZIP structure or file validation errors '401': description: Unauthorized x-codeSamples: - lang: JavaScript source: >- import fs from 'fs'; import Dataframer from 'dataframer'; const client = new Dataframer({ apiKey: process.env['DATAFRAMER_API_KEY'], // This is the default and can be omitted }); const response = await client.dataframer.seedDatasets.createFromZip({ name: 'name', zip_file: fs.createReadStream('path/to/file'), }); console.log(response.id); - 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 ) response = client.dataframer.seed_datasets.create_from_zip( name="name", zip_file=b"Example data", ) print(response.id) components: schemas: DataframerDataset: type: object properties: id: type: string format: uuid readOnly: true 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 readOnly: true description: Timestamp when the dataset was created updated_at: type: string format: date-time readOnly: true description: Timestamp when the dataset was last modified created_by_email: type: string readOnly: true description: Email address of the user who created the dataset files: type: array items: $ref: '#/components/schemas/File' readOnly: true description: List of all files in the dataset folder_count: type: integer readOnly: true description: Total number of folders in the dataset file_count: type: integer readOnly: true description: Total number of files in the dataset sample_count: type: integer nullable: true readOnly: true description: >- Number of data samples in the dataset. Only populated for SINGLE_FILE datasets (e.g. number of rows in a CSV). File: type: object properties: id: type: string format: uuid readOnly: true description: Unique identifier for the file file_type: type: string enum: - json - jsonl - csv - md - txt - pdf description: >- File format. json: single JSON object or array. jsonl: newline-delimited JSON records. csv: comma-separated values. md: Markdown text. txt: plain text. pdf: PDF document. size_bytes: type: integer nullable: true description: File size in bytes sha256: type: string nullable: true description: SHA-256 hash of the file contents for integrity verification path: type: string readOnly: true description: >- Full path of the file. For files in folders, includes folder name (e.g., 'folder_name/file.txt'). For files at root level, just the filename. securitySchemes: BearerAuth: type: http scheme: bearer bearerFormat: API Key description: 'API Key authentication. Format: "Bearer YOUR_API_KEY"' ````