Query Document Content

Search within a specific document using semantic search. Performs vector similarity search on the document's embedded chunks to find relevant content. Useful for: - Finding specific information in large documents - Testing embedding quality - Building document Q&A features - Extracting key passages Returns ranked chunks with relevance scores.

Authentication

AuthorizationBearer

API key or access token, sent as Authorization: Bearer <token>. The simplest option: create an API key in your dashboard under Settings, then paste it here.

OR
AuthorizationBearer

API key or access token, sent as Authorization: Bearer <token>. The simplest option: create an API key in your dashboard under Settings, then paste it here.

Path parameters

document_idstringRequiredformat: "uuid"
The UUID of the document
org_idstringRequiredformat: "uuid"
The unique identifier of the organization.
project_idstringRequiredformat: "uuid"
The unique identifier of the project.

Query parameters

querystringRequired
Search query

Response

Ranked chunks matching the query
chat_document_idstringformat: "uuid"
textstring
scoredouble

Errors

400
Bad Request Error
403
Forbidden Error
404
Not Found Error
422
Unprocessable Entity Error