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main.py — FastAPI application entry point for the NEET Biology Q&A system
Run:
uvicorn Backend.main:app --reload --port 8000
Docs:
http://localhost:8000/docs (Swagger UI)
http://localhost:8000/redoc (ReDoc)
"""
import time
from contextlib import asynccontextmanager
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
from Backend.schemas import HealthResponse
from Backend.routers.qa import router as qa_router
# ==============================
# STARTUP / SHUTDOWN
# ==============================
@asynccontextmanager
async def lifespan(app: FastAPI):
"""
Pre-load heavy models at startup so the first request is fast.
"""
print("\n🚀 Starting NEET Biology Q&A Backend...")
start = time.time()
# Pre-load BERT classifier (singleton)
from Classification.classify_and_extract import get_predictor
get_predictor()
# Pre-load embedding model (singleton)
from rag.retriever import get_embedding_model
get_embedding_model()
elapsed = time.time() - start
print(f"✅ All models loaded in {elapsed:.1f}s — server ready!\n")
yield # App runs here
print("\n🛑 Shutting down NEET Biology Q&A Backend.")
# ==============================
# APP INSTANCE
# ==============================
app = FastAPI(
title="NEET Biology Q&A API",
description=(
"AI-powered Question Answering system for NEET Biology. "
"Uses BERT classification for chapter detection and a "
"RAG pipeline with NCERT textbook context for accurate answers."
),
version="1.0.0",
lifespan=lifespan,
)
# ==============================
# CORS — Allow frontend access
# ==============================
app.add_middleware(
CORSMiddleware,
allow_origins=[
"http://localhost:3000", # React/Next.js dev
"http://localhost:5173", # Vite dev
"http://localhost:5500", # Live Server
"http://127.0.0.1:5500",
"*", # Allow all for development
],
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
# ==============================
# ROUTES
# ==============================
app.include_router(qa_router)
@app.get(
"/health",
response_model=HealthResponse,
tags=["System"],
summary="Health check",
)
async def health_check():
"""Check if the server and all components are running."""
from Classification.classify_and_extract import _predictor
from rag.retriever import _embedding_model, _supabase_client
return HealthResponse(
status="ok",
version="1.0.0",
components={
"bert_classifier": "loaded" if _predictor is not None else "not loaded",
"embedding_model": "loaded" if _embedding_model is not None else "not loaded",
"supabase": "connected" if _supabase_client is not None else "not connected",
},
)
@app.get("/", tags=["System"])
async def root():
"""API root — welcome message."""
return {
"message": "NEET Biology Q&A API",
"version": "1.0.0",
"docs": "/docs",
"endpoints": {
"POST /api/qa": "Full Q&A pipeline (classify + answer + verify)",
"POST /api/classify": "Chapter classification + topic extraction only",
"GET /health": "Health check",
},
}
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