> ## Documentation Index > Fetch the complete documentation index at: https://docs.mielto.com/llms.txt > Use this file to discover all available pages before exploring further. # Get Content Chunks > Get all chunks/vectors for a specific content in a collection. Returns all the chunks (text segments with embeddings) that were created when processing this content in the specified collection. This is useful for: - Debugging vector search results - Analyzing how content was chunked - Inspecting chunk metadata - Retrieving embeddings for analysis **Important:** The same content can have different chunks in different collections (due to different chunking strategies, embedding models, etc.), so `collection_id` is required to ensure you get the correct set of chunks. Args: content_id: The unique identifier for the content collection_id: The collection ID (ensures correct chunks are retrieved) include_embeddings: Whether to include embedding vectors (default: false to save bandwidth) Returns: ContentChunksResponse with list of chunks and metadata Example: GET /contents/con_abc123/chunks?collection_id=col_xyz789&include_embeddings=false Response: { "content_id": "con_abc123", "collection_id": "col_xyz789", "chunks": [ { "id": "vec_chunk1", "content_id": "con_abc123", "content": "First chunk text...", "embedding": null, // or array if include_embeddings=true "meta_data": {"page": 1, "section": "intro"}, "collection_id": "col_xyz789", "workspace_id": "wsp_123" }, ... ], "total_chunks": 42, "includes_embeddings": false } Raises: 404: If content not found or collection not accessible 500: If error retrieving chunks ## OpenAPI ````yaml api-reference/openapi.json get /api/v1/contents/{content_id}/chunks openapi: 3.1.0 info: title: FastAPI app version: 0.1.0 servers: [] security: [] paths: /api/v1/contents/{content_id}/chunks: get: tags: - Contents summary: Get Content Chunks description: >- Get all chunks/vectors for a specific content in a collection. Returns all the chunks (text segments with embeddings) that were created when processing this content in the specified collection. This is useful for: - Debugging vector search results - Analyzing how content was chunked - Inspecting chunk metadata - Retrieving embeddings for analysis **Important:** The same content can have different chunks in different collections (due to different chunking strategies, embedding models, etc.), so `collection_id` is required to ensure you get the correct set of chunks. Args: content_id: The unique identifier for the content collection_id: The collection ID (ensures correct chunks are retrieved) include_embeddings: Whether to include embedding vectors (default: false to save bandwidth) Returns: ContentChunksResponse with list of chunks and metadata Example: GET /contents/con_abc123/chunks?collection_id=col_xyz789&include_embeddings=false Response: { "content_id": "con_abc123", "collection_id": "col_xyz789", "chunks": [ { "id": "vec_chunk1", "content_id": "con_abc123", "content": "First chunk text...", "embedding": null, // or array if include_embeddings=true "meta_data": {"page": 1, "section": "intro"}, "collection_id": "col_xyz789", "workspace_id": "wsp_123" }, ... ], "total_chunks": 42, "includes_embeddings": false } Raises: 404: If content not found or collection not accessible 500: If error retrieving chunks operationId: get_content_chunks_api_v1_contents__content_id__chunks_get parameters: - name: content_id in: path required: true schema: type: string title: Content Id - name: collection_id in: query required: true schema: type: string description: Collection ID (required to ensure correct chunks) title: Collection Id description: Collection ID (required to ensure correct chunks) - name: include_embeddings in: query required: false schema: type: boolean description: Include embedding vectors (can be large) default: false title: Include Embeddings description: Include embedding vectors (can be large) - name: X-Workspace-Id in: header required: false schema: anyOf: - type: string - type: 'null' description: The workspace ID title: X-Workspace-Id description: The workspace ID responses: '200': description: Successful Response content: application/json: schema: $ref: '#/components/schemas/ContentChunksResponse' '422': description: Validation Error content: application/json: schema: $ref: '#/components/schemas/HTTPValidationError' security: - DualAuthScheme: [] components: schemas: ContentChunksResponse: properties: content_id: type: string title: Content Id description: Content ID collection_id: type: string title: Collection Id description: Collection ID chunks: items: $ref: '#/components/schemas/ContentChunk' type: array title: Chunks description: List of chunks total_chunks: type: integer title: Total Chunks description: Total number of chunks includes_embeddings: type: boolean title: Includes Embeddings description: Whether embeddings are included type: object required: - content_id - collection_id - chunks - total_chunks - includes_embeddings title: ContentChunksResponse description: Schema for content chunks response. HTTPValidationError: properties: detail: items: $ref: '#/components/schemas/ValidationError' type: array title: Detail type: object title: HTTPValidationError ContentChunk: properties: id: type: string title: Id description: Chunk/vector ID content_id: type: string title: Content Id description: Parent content ID content: type: string title: Content description: Chunk text content embedding: anyOf: - items: type: number type: array - type: 'null' title: Embedding description: Embedding vector (optional, can be large) meta_data: additionalProperties: true type: object title: Meta Data description: Chunk metadata collection_id: anyOf: - type: string - type: 'null' title: Collection Id description: Collection ID workspace_id: anyOf: - type: string - type: 'null' title: Workspace Id description: Workspace ID name: anyOf: - type: string - type: 'null' title: Name description: Chunk name (standard PgVector only) filters: anyOf: - additionalProperties: true type: object - type: 'null' title: Filters description: Filters (standard PgVector only) created_at: anyOf: - {} - type: 'null' title: Created At description: Creation timestamp (standard PgVector only) type: object required: - id - content_id - content title: ContentChunk description: Schema for a content chunk/vector. ValidationError: properties: loc: items: anyOf: - type: string - type: integer type: array title: Location msg: type: string title: Message type: type: string title: Error Type type: object required: - loc - msg - type title: ValidationError securitySchemes: DualAuthScheme: type: http scheme: bearer ````