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v5

latestOpenAPI 3.1.02026-08-025631,1012.8 MB
Documents

Get a document by ID (namespace-scoped).

Get a document by ID without specifying a collection.

Searches across all collections in the namespace. Use the collection-scoped GET /v1/collections/{collection_id}/documents/{document_id} when you know the collection for a faster lookup.

get/v1/documents/{document_id}

Path parameters

document_idstring required

The ID of the document to retrieve.

The ID of the document to retrieve.

Query parameters

return_presigned_urlsboolean

Generate fresh presigned download URLs for all blobs with S3 storage

Generate fresh presigned download URLs for all blobs with S3 storage

return_vectorsboolean nullable
return_vector_namesboolean

Include a '_vectors' field listing available vector names

Include a '_vectors' field listing available vector names

expandstring nullable

Comma-separated fields containing document IDs to resolve inline. Referenced documents are fetched and attached under an '_expanded' key. Supports dot-notation for nested fields (e.g., 'items.product_id'). Max 50 unique references per request.

Comma-separated fields containing document IDs to resolve inline. Referenced documents are fetched and attached under an '_expanded' key. Supports dot-notation for nested fields (e.g., 'items.product_id'). Max 50 unique references per request.

Response

Successful Response

document_idstring required

REQUIRED. Unique identifier for the document. Format: 'doc_' prefix + alphanumeric characters. Use for: API queries, references, filtering.

collection_idstring required

REQUIRED. ID of the collection this document belongs to. Format: 'col_' prefix + alphanumeric characters. Use for: Collection-scoped queries, filtering.

Example response

{
  "_internal": {
    "collection_id": "col_articles",
    "created_at": "2025-10-31T10:00:00Z",
    "document_id": "doc_f8966ff29c18e20c6b45e053",
    "internal_id": "org_abc123",
    "lineage": {
      "chain": [
        {
          "collection_id": "col_articles",
          "feature_extractor_id": "text_extractor_v1",
          "timestamp": "2025-10-31T10:00:00Z"
        }
      ],
      "path": "bkt_content/col_articles",
      "root_bucket_id": "bkt_content",
      "root_object_id": "obj_article_001",
      "source_object_id": "obj_article_001",
      "source_type": "bucket"
    },
    "metadata": {
      "ingestion_status": "COMPLETED"
    },
    "modality": "text",
    "namespace_id": "ns_xyz789",
    "source_blobs": [
      {
        "blob_id": "blob_text_001",
        "blob_property": "content",
        "blob_type": "text"
      }
    ],
    "updated_at": "2025-10-31T10:00:00Z"
  },
  "author": "Dr. Smith",
  "collection_id": "col_articles",
  "description": "Text document with _internal structure",
  "document_id": "doc_f8966ff29c18e20c6b45e053",
  "title": "AI in Healthcare"
}