1.8 KiB
TrustGraph Document RAG API
This presents a prompt to the Document RAG service and retrieves the answer. This makes use of a number of the other APIs behind the scenes: Embeddings, Document Embeddings, Prompt, TextCompletion, Triples Query.
Request/response
Request
The request contains the following fields:
query: The question to answer
Response
The response contains the following fields:
response: LLM response
REST service
The REST service accepts a request object containing the query field.
The response is a JSON object containing the response field.
e.g.
Request:
{
"query": "What does NASA stand for?"
}
Response:
{
"response": "National Aeronautics and Space Administration"
}
Websocket
Requests have a request object containing the query field.
Responses have a response object containing response field.
e.g.
Request:
{
"id": "blrqotfefnmnh7de-14",
"service": "document-rag",
"flow": "default",
"request": {
"query": "What does NASA stand for?"
}
}
Response:
{
"id": "blrqotfefnmnh7de-14",
"response": {
"response": "National Aeronautics and Space Administration"
},
"complete": true
}
Pulsar
The Pulsar schema for the Document RAG API is defined in Python code here:
Default request queue:
non-persistent://tg/request/document-rag
Default response queue:
non-persistent://tg/response/document-rag
Request schema:
trustgraph.schema.DocumentRagQuery
Response schema:
trustgraph.schema.DocumentRagResponse
Pulsar Python client
The client class is
trustgraph.clients.DocumentRagClient