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_id
The UUID of the document
org_id
The unique identifier of the organization.
project_id
The unique identifier of the project.
Query parameters
query
Search query
Response
Ranked chunks matching the query
chat_document_id
text
score
Errors
400
Bad Request Error
403
Forbidden Error
404
Not Found Error
422
Unprocessable Entity Error