> ## Documentation Index > Fetch the complete documentation index at: https://azure-foundry.mintlify.site/llms.txt > Use this file to discover all available pages before exploring further. # Create a vector store file batch. ## OpenAPI ````yaml api-reference/openai-v1.yaml post /vector_stores/{vector_store_id}/file_batches openapi: 3.0.0 info: title: Azure AI Foundry Models Service license: name: MIT url: https://github.com/openai/openai-openapi/blob/master/LICENSE version: v1 servers: - url: '{endpoint}/openai/v1' description: Azure AI Foundry Models APIs variables: endpoint: default: '' description: >- A supported Azure AI Foundry Models APIs endpoint, including protocol and hostname. For example: https://westus.api.cognitive.microsoft.com). security: - ApiKeyAuth: [] - ApiKeyAuth_: [] - OAuth2Auth: - https://cognitiveservices.azure.com/.default tags: - name: Chat - name: Embeddings - name: Evals - name: Files - name: Fine-tuning - name: Models - name: Responses - name: Vector Stores paths: /vector_stores/{vector_store_id}/file_batches: post: tags: - Vector Stores summary: Create a vector store file batch. operationId: createVectorStoreFileBatch parameters: - name: api-version in: query required: false description: >- The explicit Azure AI Foundry Models API version to use for this request. `v1` if not otherwise specified. schema: $ref: '#/components/schemas/AzureAIFoundryModelsApiVersion' default: v1 - name: vector_store_id in: path required: true description: The ID of the vector store for which to create a file batch. schema: type: string requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/OpenAI.CreateVectorStoreFileBatchRequest' responses: '200': description: The request has succeeded. headers: apim-request-id: required: false description: A request ID used for troubleshooting purposes. schema: type: string content: application/json: schema: $ref: '#/components/schemas/OpenAI.VectorStoreFileBatchObject' default: description: An unexpected error response. headers: apim-request-id: required: false description: A request ID used for troubleshooting purposes. schema: type: string content: application/json: schema: $ref: '#/components/schemas/AzureErrorResponse' components: schemas: AzureAIFoundryModelsApiVersion: type: string enum: - v1 - preview OpenAI.CreateVectorStoreFileBatchRequest: type: object required: - file_ids properties: file_ids: type: array items: type: string minItems: 1 maxItems: 500 description: >- A list of [File](/docs/api-reference/files) IDs that the vector store should use. Useful for tools like `file_search` that can access files. chunking_strategy: $ref: '#/components/schemas/OpenAI.ChunkingStrategyRequestParam' attributes: type: object allOf: - $ref: '#/components/schemas/OpenAI.VectorStoreFileAttributes' nullable: true OpenAI.VectorStoreFileBatchObject: type: object required: - id - object - created_at - vector_store_id - status - file_counts properties: id: type: string description: The identifier, which can be referenced in API endpoints. object: type: string enum: - vector_store.files_batch description: The object type, which is always `vector_store.file_batch`. created_at: type: integer format: unixtime description: >- The Unix timestamp (in seconds) for when the vector store files batch was created. vector_store_id: type: string description: >- The ID of the [vector store](/docs/api-reference/vector-stores/object) that the [File](/docs/api-reference/files) is attached to. status: type: string enum: - in_progress - completed - cancelled - failed description: >- The status of the vector store files batch, which can be either `in_progress`, `completed`, `cancelled` or `failed`. file_counts: type: object properties: in_progress: type: integer format: int32 description: The number of files that are currently being processed. completed: type: integer format: int32 description: The number of files that have been processed. failed: type: integer format: int32 description: The number of files that have failed to process. cancelled: type: integer format: int32 description: The number of files that where cancelled. total: type: integer format: int32 description: The total number of files. required: - in_progress - completed - failed - cancelled - total description: A batch of files attached to a vector store. AzureErrorResponse: type: object properties: error: type: object properties: code: type: string description: The distinct, machine-generated identifier for the error. message: type: string description: A human-readable message associated with the error. param: type: string description: >- If applicable, the request input parameter associated with the error type: type: string enum: - error description: The object type, always 'error.' inner_error: {} description: The error details. OpenAI.ChunkingStrategyRequestParam: type: object required: - type properties: type: type: string enum: - auto - static description: The type of chunking strategy. discriminator: propertyName: type mapping: static: '#/components/schemas/OpenAI.StaticChunkingStrategyRequestParam' description: >- The chunking strategy used to chunk the file(s). If not set, will use the `auto` strategy. OpenAI.VectorStoreFileAttributes: type: object additionalProperties: anyOf: - type: string - type: boolean - type: integer format: int32 - type: number format: float description: >- Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format, and querying for objects via API or the dashboard. Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters, booleans, or numbers. x-oaiTypeLabel: map securitySchemes: ApiKeyAuth: type: apiKey in: header name: api-key ApiKeyAuth_: type: apiKey in: header name: authorization OAuth2Auth: type: oauth2 flows: implicit: authorizationUrl: https://login.microsoftonline.com/common/oauth2/v2.0/authorize scopes: https://cognitiveservices.azure.com/.default: '' ````