9b86f9a694
RAG Service Implementation: - Create rag-service/ with full structure (config, document_store, embedding, pipelines) - Document Store: PostgreSQL + pgvector via Haystack - Embedding: BAAI/bge-m3 (multilingual, 1024 dim) - Ingest Pipeline: Convert ParsedDocument to Haystack Documents, embed, index - Query Pipeline: Retrieve documents, generate answers via DAGI Router - FastAPI endpoints: /ingest, /query, /health Tests: - Unit tests for ingest and query pipelines - E2E test with example parsed JSON - Test fixtures with real PARSER output example Router Integration: - Add mode='rag_query' routing rule in router-config.yml - Priority 7, uses local_qwen3_8b for RAG queries Docker: - Add rag-service to docker-compose.yml - Configure dependencies (router, city-db) - Add model cache volume Documentation: - Complete README with API examples - Integration guides for PARSER and Router
106 lines
2.6 KiB
Python
106 lines
2.6 KiB
Python
"""
|
|
RAG Service - FastAPI application
|
|
Retrieval-Augmented Generation for MicroDAO
|
|
"""
|
|
|
|
import logging
|
|
from fastapi import FastAPI, HTTPException
|
|
from fastapi.middleware.cors import CORSMiddleware
|
|
|
|
from app.models import IngestRequest, IngestResponse, QueryRequest, QueryResponse
|
|
from app.ingest_pipeline import ingest_parsed_document
|
|
from app.query_pipeline import answer_query
|
|
|
|
logger = logging.getLogger(__name__)
|
|
|
|
# FastAPI app
|
|
app = FastAPI(
|
|
title="RAG Service",
|
|
description="Retrieval-Augmented Generation service for MicroDAO",
|
|
version="1.0.0"
|
|
)
|
|
|
|
# CORS middleware
|
|
app.add_middleware(
|
|
CORSMiddleware,
|
|
allow_origins=["*"],
|
|
allow_credentials=True,
|
|
allow_methods=["*"],
|
|
allow_headers=["*"],
|
|
)
|
|
|
|
|
|
@app.get("/health")
|
|
async def health():
|
|
"""Health check endpoint"""
|
|
return {
|
|
"status": "healthy",
|
|
"service": "rag-service",
|
|
"version": "1.0.0"
|
|
}
|
|
|
|
|
|
@app.post("/ingest", response_model=IngestResponse)
|
|
async def ingest_endpoint(request: IngestRequest):
|
|
"""
|
|
Ingest parsed document from PARSER service into RAG
|
|
|
|
Body:
|
|
- dao_id: DAO identifier
|
|
- doc_id: Document identifier
|
|
- parsed_json: ParsedDocument JSON from PARSER service
|
|
- user_id: Optional user identifier
|
|
"""
|
|
try:
|
|
result = ingest_parsed_document(
|
|
dao_id=request.dao_id,
|
|
doc_id=request.doc_id,
|
|
parsed_json=request.parsed_json,
|
|
user_id=request.user_id
|
|
)
|
|
|
|
return IngestResponse(**result)
|
|
|
|
except Exception as e:
|
|
logger.error(f"Ingest endpoint error: {e}", exc_info=True)
|
|
raise HTTPException(status_code=500, detail=str(e))
|
|
|
|
|
|
@app.post("/query", response_model=QueryResponse)
|
|
async def query_endpoint(request: QueryRequest):
|
|
"""
|
|
Answer query using RAG pipeline
|
|
|
|
Body:
|
|
- dao_id: DAO identifier
|
|
- question: User question
|
|
- top_k: Optional number of documents to retrieve
|
|
- user_id: Optional user identifier
|
|
"""
|
|
try:
|
|
result = await answer_query(
|
|
dao_id=request.dao_id,
|
|
question=request.question,
|
|
top_k=request.top_k,
|
|
user_id=request.user_id
|
|
)
|
|
|
|
return QueryResponse(**result)
|
|
|
|
except Exception as e:
|
|
logger.error(f"Query endpoint error: {e}", exc_info=True)
|
|
raise HTTPException(status_code=500, detail=str(e))
|
|
|
|
|
|
if __name__ == "__main__":
|
|
import uvicorn
|
|
from app.core.config import settings
|
|
|
|
uvicorn.run(
|
|
"app.main:app",
|
|
host=settings.API_HOST,
|
|
port=settings.API_PORT,
|
|
reload=True
|
|
)
|
|
|