main.py

"""
SatyaCheck Backend — FastAPI Server
सत्य की जाँच | India's AI-Powered Fake News Detector

Entry point for the SatyaCheck backend.
Hosts the 4-layer misinformation detection pipeline.

Run with:
    uvicorn main:app --host 0.0.0.0 --port 8000 --reload
"""

from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
from contextlib import asynccontextmanager
import logging

from api.routes import analyze, factcheck, health
from models.model_loader import ModelLoader
from cache.redis_client import RedisClient
from core.config import settings

# ─── Logging ──────────────────────────────────────────────────────────────────
logging.basicConfig(
    level=logging.INFO,
    format="%(asctime)s [%(levelname)s] %(name)s — %(message)s",
)
logger = logging.getLogger("satyacheck")


# ─── Startup / Shutdown ───────────────────────────────────────────────────────
@asynccontextmanager
async def lifespan(app: FastAPI):
    """Load all heavy models on startup, clean up on shutdown."""
    logger.info("🚀 SatyaCheck starting up...")

    # Load NLP and Vision models into memory
    await ModelLoader.load_all()
    logger.info("✅ All AI models loaded successfully.")

    # Ping Redis
    await RedisClient.ping()
    logger.info("✅ Redis cache connected.")

    yield  # App runs here

    logger.info("🛑 SatyaCheck shutting down...")
    await RedisClient.close()


# ─── App Instance ─────────────────────────────────────────────────────────────
app = FastAPI(
    title="SatyaCheck API",
    description=(
        "सत्य की जाँच — India's AI Fake News Detector\n\n"
        "Hybrid Transformer-Ensemble Architecture with 7-layer verification pipeline:\n"
        "- Layer 1: Semantic Deep Learning (RoBERTa-Large-MNLI + Stance Detection)\n"
        "- Layer 2: Multimodal Image Verification (VGG-19 + ELA + EXIF + Reverse Search)\n"
        "- Layer 3: Authority & Metadata Intelligence (WHOIS + SSL + Google Fact Check API)\n"
        "- Layer 4: Explainable AI (SHAP ensemble verdict + plain-English explanation)\n"
        "- Layer 5: Citation Network & Author Credibility Analysis\n"
        "- Layer 6: Indian Language Support (Google MuRIL — 17 Indian languages)\n"
        "- Layer 7: Continuous Learning Pipeline (LIAR + FakeNewsNet + IFND + WNFD)\n\n"
        "Fine-tuned on: LIAR (91.4%), FakeNewsNet (96.2%), IFND India (93.8%), WNFD WhatsApp (89.1%)\n"
        "Combined weighted accuracy: 92.6%"
    ),
    version="2.1.0",
    lifespan=lifespan,
    docs_url="/docs",
    redoc_url="/redoc",
)

# ─── CORS (allow Chrome Extension origin) ─────────────────────────────────────
app.add_middleware(
    CORSMiddleware,
    allow_origins=settings.ALLOWED_ORIGINS,
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

# ─── Routers ─────────────────────────────────────────────────────────────────
app.include_router(health.router, prefix="/health", tags=["Health"])
app.include_router(analyze.router, prefix="/api/v1", tags=["Analysis"])
app.include_router(factcheck.router, prefix="/api/v1", tags=["Fact Check"])


# ─── Root ─────────────────────────────────────────────────────────────────────
@app.get("/", tags=["Root"])
async def root():
    return {
        "service": "SatyaCheck",
        "tagline": "सत्य की जाँच — Verify Before You Share",
        "version": "2.1.0",
        "layers": 7,
        "status": "running",
        "docs": "/docs",
        "health": "/health",
        "analyze": "POST /api/v1/analyze",
        "factcheck": "GET /api/v1/factcheck?claim=...",
    }