Query
Endpoints
Query
Query the knowledge base with natural language
POST
Query
Query the Vrin knowledge base. Returns an AI-generated answer backed by knowledge graph facts and vector search results.
Bearer token. Example:
Bearer vrin_live_abc123Natural-language question to answer.
If
true, the response is delivered as Server-Sent Events (SSE). Each event contains a JSON object with type and data fields.Answer depth:
"chat" (concise), "thinking" (reasoning chains), "research" (exhaustive multi-hop).Override retrieval depth:
"basic", "thinking", "research".LLM model override (e.g.
"gpt-4o").Conversation session ID to continue.
If
true, maintain conversation context. A session_id will be returned in the response.If
true, include AI-generated summary. Set to false for raw fact retrieval only.Enable web search augmentation.
Upload IDs to include as additional context.
Non-streaming response
Streaming response (SSE)
Whenstream: true, the response is text/event-stream:
SSE event types
| Type | Data fields | Description |
|---|---|---|
metadata | session_id, total_facts, total_chunks, entities, model | Retrieval metadata, sent first |
content | delta | Text token |
reasoning | chains or steps | Reasoning chain steps |
sources | sources | Source document references |
done | error?, insufficient_coverage? | Stream complete |
error | message | Fatal error |
Insufficient coverage
When the knowledge base has no relevant facts, the response includesinsufficient_coverage: true and skips LLM generation.