> ## Documentation Index
> Fetch the complete documentation index at: https://docs.mka1.com/llms.txt
> Use this file to discover all available pages before exploring further.

# List files in a batch

> Retrieves a paginated list of all files within a specific batch operation.



## OpenAPI

````yaml https://apigw.mka1.com/speakeasy.json get /api/v1/llm/vector_stores/{vector_store_id}/file_batches/{batch_id}/files
openapi: 3.1.1
info:
  title: MKA1 API
  version: 1.1.0
  description: >-
    The MKA1 API is a RESTful API that provides access to the MKA1 platform.
    Learn how to get started with the API and the TypeScript SDK
    [here](https://mka1.apidocumentation.com/guides/getting-started).
  license:
    name: Proprietary
servers:
  - url: https://apigw.mka1.com
    description: MKA1 API Gateway
  - url: /
    description: Relative server URL (configurable via SDK constructor)
security: []
tags:
  - name: Resource Authorization
    description: >-
      Manage permissions for LLM resources. Create resources, grant/revoke
      permissions, and delete resources. Only resource owners can grant, revoke,
      or delete permissions.
    x-displayName: Resource Authorization
  - name: Embeddings
    description: >-
      Text embedding API endpoints for generating vector representations of
      text. Create semantic embeddings for search, clustering, and similarity
      matching using various embedding models.
    x-displayName: Embeddings
  - name: Feedback
    description: >-
      User feedback API for rating and commenting on chat completions. Collect
      thumbs up/down ratings and detailed feedback to improve model responses
      and track user satisfaction.
    x-displayName: Feedback
  - name: Images
    description: >-
      Image generation API endpoints for creating images from text descriptions.
      Generate images with control over size, quality, and style.
    x-displayName: Images
  - name: MCP Vault
    description: >-
      MCP vault API for storing user-owned MCP server configurations and
      encrypted credentials. Agents reference vault IDs so secrets are resolved
      only at tool execution time.
    x-displayName: MCP Vault
  - name: Speech
    description: >-
      Speech API endpoints for audio processing. Convert text to
      natural-sounding speech (TTS) or transcribe speech to text (STT) in
      different languages.
    x-displayName: Speech
  - name: Usage
    description: >-
      Usage tracking and analytics API for monitoring token consumption, request
      counts, and cost analysis. View detailed statistics per user, model, and
      time period.
    x-displayName: Usage
  - name: Extract
    description: >-
      Structured data extraction API for extracting information from files.
      Define JSON schemas to extract structured data from images, PDFs, and
      documents. Supports reusable schema templates.
    x-displayName: Extract
  - name: Text Classification
    description: >-
      Text classification API for categorizing text into predefined labels. Use
      AI models to classify text content for sentiment analysis, topic
      categorization, and content moderation.
    x-displayName: Text Classification
  - name: Responses
    description: >-
      Agent-powered responses API for creating AI agents with autonomous tool
      usage. Build conversational assistants that can use web search, file
      operations, image generation, code execution, computer use simulation, and
      MCP integrations. Supports background processing, streaming, and real-time
      status tracking.
    x-displayName: Responses
  - name: Files
    description: >-
      File management API for uploading, storing, and managing files with
      automatic expiration and S3 integration. Upload files that can be used
      with Assistants, Vector Stores, and other features. Files are stored in S3
      with metadata tracked in PostgreSQL. Supports automatic cleanup of expired
      files.
    x-displayName: Files
  - name: Vector Stores
    description: >-
      Vector store API for storing and searching documents using embeddings.
      Create vector stores, upload files with automatic chunking and embedding
      generation, and perform semantic search. Files are processed
      asynchronously using Temporal workflows for durability. Supports automatic
      cleanup of expired stores and LanceDB for efficient vector storage.
    x-displayName: Vector Stores
  - name: Conversations
    description: >-
      Conversation management API for storing and retrieving conversation state
      across Response API calls. Create conversations, add items (user messages,
      assistant messages, system messages), and maintain conversation history.
      Supports metadata tracking and multi-turn dialogue state management.
    x-displayName: Conversations
  - name: Guardrails
    description: >-
      AI safety guardrails API for configuring content moderation and security
      policies. Set up ban word lists, prompt injection detection, and system
      prompt leakage prevention. Guardrails apply to all requests from an
      account and can be tested before deployment.
    x-displayName: Guardrails
  - name: Models
    description: >-
      Model listing API for discovering available models. Returns model IDs,
      ownership, and metadata for all registered models in the gateway.
    x-displayName: Models
  - name: Skills
    description: >-
      Skills API for managing versioned bundles of instructions and files
      following the Agent Skills standard. Create, version, and download
      reusable skill packages that include SKILL.md manifests for agent
      environments.
    x-displayName: Skills
  - name: Chat Completions
    description: >-
      **Deprecated: Use the Responses API (`/api/v1/llm/responses`) instead.**
      Chat completion endpoints with support for streaming, tool calls, and
      multiple providers.
    x-deprecated: true
    x-displayName: Chat Completions
  - name: Batches
    x-displayName: Batches
  - name: Evals
    x-displayName: Evals
  - name: Fine-Tuning
    x-displayName: Fine-Tuning
  - name: Memory Stores
    x-displayName: Memory Stores
  - name: Prompts
    x-displayName: Prompts
  - name: API Key
    x-displayName: API Key
  - name: Organization
    x-displayName: Organization
  - name: Cluster Admin
    x-displayName: Cluster Admin
  - name: Sessions
    description: Create, inspect, access, and terminate sandbox sessions.
    x-displayName: Sessions
  - name: Browser
    description: >-
      Connect to browser sessions through the gateway port proxy. Browser
      sessions expose a Chrome DevTools Protocol endpoint on port 9222.
    x-displayName: Browser
  - name: Execution
    description: Run shell commands and code inside an existing sandbox session.
    x-displayName: Execution
  - name: Workspace
    description: >-
      Inspect the workspace manifest, transfer files or archives, and download
      generated artifacts.
    x-displayName: Workspace
  - name: Sandbox Usage
    description: >-
      Aggregate sandbox usage statistics across sessions, execution, and
      workspace operations.
    x-displayName: Sandbox Usage
  - name: Sandbox Pricing
    description: >-
      Cluster-admin management of the sandbox compute rate card used for
      budgeted spend.
    x-displayName: Sandbox Pricing
  - name: Agents
    description: Create and manage reusable agent definitions.
    x-displayName: Agents
  - name: Agent Versions
    description: Inspect an agent's configuration history and roll back to a prior version.
    x-displayName: Agent Versions
  - name: Agent Runs
    description: Execute saved agents and inspect persisted run results.
    x-displayName: Agent Runs
  - name: Agent Connectors
    description: >-
      Connect saved agents to external messaging channels such as Telegram,
      including text, photo, and supported document exchange.
    x-displayName: Agent Connectors
  - name: Agent Schedules
    description: Create and manage scheduled or recurring saved agent runs.
    x-displayName: Agent Schedules
  - name: schema-4_other
    x-displayName: other
  - name: Budgets
    x-displayName: Budgets
  - name: Settings
    x-displayName: Settings
  - name: Deployments
    description: Long-lived inference servers.
    x-displayName: Deployments
  - name: Fine-Tune Jobs
    description: Submit, monitor, and cancel fine-tune jobs.
    x-displayName: Fine-Tune Jobs
  - name: Container Images
    description: Custom container images for deployments and jobs.
    x-displayName: Container Images
  - name: Serving Models
    description: Models registered for deployment and fine-tuning.
    x-displayName: Serving Models
  - name: Volumes
    description: Persistent storage for weights and checkpoints.
    x-displayName: Volumes
  - name: Secrets
    description: Credentials injected into your workloads.
    x-displayName: Secrets
  - name: Accelerators
    description: Available accelerator types (GPU, NPU, TPU).
    x-displayName: Accelerators
paths:
  /api/v1/llm/vector_stores/{vector_store_id}/file_batches/{batch_id}/files:
    get:
      tags:
        - Vector Stores
      summary: List files in a batch
      description: >-
        Retrieves a paginated list of all files within a specific batch
        operation.
      operationId: listVectorStoreFilesInBatch
      parameters:
        - name: vector_store_id
          in: path
          required: true
          schema:
            type: string
            description: The ID of the vector store that the files belong to.
          example: vs_abc123
        - name: batch_id
          in: path
          required: true
          schema:
            type: string
            description: The ID of the file batch that the files belong to.
          example: vsfb_abc123
        - name: limit
          in: query
          schema:
            type: integer
            minimum: 1
            maximum: 100
            default: 20
            description: >-
              A limit on the number of objects to be returned. Limit can range
              between 1 and 100, and the default is 20.
          allowEmptyValue: true
          example: 20
        - name: order
          in: query
          schema:
            enum:
              - asc
              - desc
            type: string
            default: desc
            description: >-
              Sort order by the created_at timestamp of the objects. 'asc' for
              ascending order and 'desc' for descending order.
          allowEmptyValue: true
          example: desc
        - name: after
          in: query
          schema:
            type: string
            description: >-
              A cursor for use in pagination. An object ID that defines your
              place in the list for fetching the next page.
          allowEmptyValue: true
          example: file-abc123
        - name: before
          in: query
          schema:
            type: string
            description: >-
              A cursor for use in pagination. An object ID that defines your
              place in the list for fetching the previous page.
          allowEmptyValue: true
        - name: filter
          in: query
          schema:
            enum:
              - in_progress
              - completed
              - failed
              - cancelled
            type: string
            description: >-
              Filter by file status. One of in_progress, completed, failed,
              cancelled.
          allowEmptyValue: true
          example: completed
        - name: X-On-Behalf-Of
          in: header
          required: false
          schema:
            type: string
          description: Optional external end-user identifier forwarded by the API gateway.
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/VectorStoreFileList'
              example:
                object: list
                data:
                  - id: file-abc123
                    object: vector_store.file
                    usage_bytes: 256000
                    created_at: 1704067200
                    vector_store_id: vs_abc123
                    filename: product-manual.pdf
                    status: completed
                    last_error: null
                    chunking_strategy:
                      type: auto
                    attributes:
                      category: manual
                      version: '2.0'
                first_id: file-abc123
                last_id: file-abc123
                has_more: false
      security:
        - bearerAuth: []
      x-codeSamples:
        - lang: python
          label: Python (SDK)
          source: |-
            from meetkai_mka1 import SDK


            with SDK(
                bearer_auth="<YOUR_BEARER_TOKEN_HERE>",
            ) as sdk:

                res = sdk.llm.vector_stores.list_files_in_batch(vector_store_id="vs_abc123", batch_id="vsfb_abc123", limit=20, order="desc", after="file-abc123", filter_="completed")

                # Handle response
                print(res)
        - lang: typescript
          label: Typescript (SDK)
          source: |-
            import { SDK } from "@meetkai/mka1";

            const sdk = new SDK({
              bearerAuth: "<YOUR_BEARER_TOKEN_HERE>",
            });

            async function run() {
              const result = await sdk.llm.vectorStores.listFilesInBatch({
                vectorStoreId: "vs_abc123",
                batchId: "vsfb_abc123",
                after: "file-abc123",
                filter: "completed",
              });

              console.log(result);
            }

            run();
        - lang: csharp
          label: CSharp (SDK)
          source: >-
            using MeetKai.MKA1;

            using MeetKai.MKA1.Types.Components;

            using MeetKai.MKA1.Types.Requests;


            var sdk = new SDK(bearerAuth: "<YOUR_BEARER_TOKEN_HERE>");


            ListVectorStoreFilesInBatchRequest req = new
            ListVectorStoreFilesInBatchRequest() {
                VectorStoreId = "vs_abc123",
                BatchId = "vsfb_abc123",
                After = "file-abc123",
                Filter = ListVectorStoreFilesInBatchFilter.Completed,
            };


            var res = await sdk.Llm.VectorStores.ListFilesInBatchAsync(req);


            // handle response
components:
  schemas:
    VectorStoreFileList:
      type: object
      properties:
        object:
          const: list
          description: The object type, which is always 'list'.
        data:
          type: array
          items:
            $ref: '#/components/schemas/VectorStoreFile'
          description: Array of vector store file objects.
        first_id:
          type: string
          description: The ID of the first object in the list.
        last_id:
          type: string
          description: The ID of the last object in the list.
        has_more:
          type: boolean
          description: Whether there are more objects available.
      required:
        - object
        - data
        - first_id
        - last_id
        - has_more
      description: A list of vector store files.
    VectorStoreFile:
      type: object
      properties:
        id:
          type: string
          description: The identifier, which can be referenced in API endpoints.
        object:
          const: vector_store.file
          description: The object type, which is always 'vector_store.file'.
        usage_bytes:
          type: integer
          minimum: -9007199254740991
          maximum: 9007199254740991
          description: >-
            The total vector store usage in bytes. Note that this may be
            different from the original file size.
        created_at:
          type: integer
          minimum: -9007199254740991
          maximum: 9007199254740991
          description: >-
            The Unix timestamp (in seconds) for when the vector store file was
            created.
        vector_store_id:
          type: string
          description: The ID of the vector store that the File is attached to.
        filename:
          type: string
          description: >-
            The name of the underlying file. Extension field not present in the
            OpenAI API; omitted on create responses.
        status:
          enum:
            - in_progress
            - completed
            - cancelled
            - failed
          type: string
          description: >-
            The status of the vector store file. 'in_progress' means currently
            processing, 'completed' indicates the file is ready for use,
            'cancelled' means processing was cancelled, 'failed' means an error
            occurred.
        last_error:
          anyOf:
            - $ref: '#/components/schemas/VectorStoreFileError'
            - type: 'null'
          description: >-
            The last error associated with this vector store file. Will be null
            if there are no errors.
        chunking_strategy:
          $ref: '#/components/schemas/ChunkingStrategy'
          description: The strategy used to chunk the file.
        attributes:
          type: object
          propertyNames:
            type: string
            maxLength: 64
          additionalProperties:
            anyOf:
              - type: string
                maxLength: 512
              - type: boolean
              - type: number
          description: >-
            Set of 16 key-value pairs that can be attached to an object. Keys
            are strings with a maximum length of 64 characters. Values are
            strings with a maximum length of 512 characters, booleans, or
            numbers.
      required:
        - id
        - object
        - usage_bytes
        - created_at
        - vector_store_id
        - status
        - last_error
      description: A list of files attached to a vector store.
    VectorStoreFileError:
      type: object
      properties:
        code:
          enum:
            - server_error
            - unsupported_file
            - invalid_file
          type: string
          description: One of server_error, unsupported_file, or invalid_file.
        message:
          type: string
          description: A human-readable description of the error.
      required:
        - code
        - message
      description: >-
        The last error associated with this vector store file. Will be null if
        there are no errors.
    ChunkingStrategy:
      anyOf:
        - $ref: '#/components/schemas/AutoChunkingStrategy'
        - $ref: '#/components/schemas/StaticChunkingStrategy'
        - $ref: '#/components/schemas/OtherChunkingStrategy'
    AutoChunkingStrategy:
      type: object
      properties:
        type:
          const: auto
          description: Always 'auto'. The default chunking strategy.
      required:
        - type
      description: >-
        The default chunking strategy. This strategy currently uses a
        max_chunk_size_tokens of 800 and chunk_overlap_tokens of 400.
    StaticChunkingStrategy:
      type: object
      properties:
        type:
          const: static
          description: Always 'static'.
        static:
          type: object
          properties:
            chunk_overlap_tokens:
              type: integer
              minimum: -9007199254740991
              maximum: 9007199254740991
              description: >-
                The number of tokens that overlap between chunks. The default
                value is 400. Must not exceed half of max_chunk_size_tokens.
            max_chunk_size_tokens:
              type: integer
              minimum: 100
              maximum: 4096
              description: >-
                The maximum number of tokens in each chunk. The default value is
                800. The minimum value is 100 and the maximum value is 4096.
          required:
            - chunk_overlap_tokens
            - max_chunk_size_tokens
      required:
        - type
        - static
      description: >-
        Customize your own chunking strategy by setting chunk size and chunk
        overlap.
    OtherChunkingStrategy:
      type: object
      properties:
        type:
          const: other
          description: Always 'other'.
      required:
        - type
      description: >-
        This is returned when the chunking strategy is unknown. Typically, this
        is because the file was indexed before the chunking_strategy concept was
        introduced in the API.
  securitySchemes:
    bearerAuth:
      type: http
      scheme: bearer
      bearerFormat: API Key
      description: >-
        Gateway auth: send `Authorization: Bearer <mka1-api-key>`. For
        multi-user server-side integrations, you can also send `X-On-Behalf-Of:
        <external-user-id>`.

````