Sprint 13: Add WhatsApp webhook router and dependencies

api.py

@@ -15,6 +15,7 @@ from slowapi.util import get_remote_address
 from slowapi.errors import RateLimitExceeded
 from bhashini import translate_text, LANGUAGE_CODES
 from eligibility.engine import check_eligibility
+from whatsapp.webhook import router as whatsapp_router
 
 # --- SECURE KEYS ---
 SUPABASE_URL = os.environ.get("SUPABASE_URL")
@@ -26,6 +27,7 @@ supabase: Client = create_client(SUPABASE_URL, SUPABASE_KEY)
 groq_client = Groq(api_key=GROQ_API_KEY)
 
 app = FastAPI()
+app.include_router(whatsapp_router)
 
 # --- RATE LIMITER CONFIG ---
 limiter = Limiter(key_func=get_remote_address)

whatsapp/webhook.py

@@ -0,0 +1,142 @@
+import hmac
+import hashlib
+import os
+import httpx
+import datetime
+from fastapi import APIRouter, Request, HTTPException, BackgroundTasks
+from fastapi.responses import PlainTextResponse
+from supabase import create_client
+
+router = APIRouter()
+
+VERIFY_TOKEN = os.environ.get("WHATSAPP_VERIFY_TOKEN")
+WA_TOKEN = os.environ.get("WHATSAPP_TOKEN")
+PHONE_NUMBER_ID = os.environ.get("WHATSAPP_PHONE_NUMBER_ID")
+APP_SECRET = os.environ.get("WHATSAPP_APP_SECRET")  # Fixed signature secret
+
+SUPABASE_URL = os.environ.get("SUPABASE_URL")
+SUPABASE_KEY = os.environ.get("SUPABASE_KEY")
+supabase = create_client(SUPABASE_URL, SUPABASE_KEY)
+
+WA_API_URL = f"https://graph.facebook.com/v19.0/{PHONE_NUMBER_ID}/messages"
+
+# ── Webhook Verification (GET) ────────────────────────────────────────────────
+@router.get("/webhook/whatsapp")
+async def verify_webhook(request: Request):
+    params = request.query_params
+    if params.get("hub.mode") == "subscribe" and params.get("hub.verify_token") == VERIFY_TOKEN:
+        print("✅ WhatsApp webhook verified")
+        return PlainTextResponse(content=params.get("hub.challenge"))
+    raise HTTPException(status_code=403, detail="Verification failed")
+
+# ── Incoming Message Handler (POST) ──────────────────────────────────────────
+@router.post("/webhook/whatsapp")
+async def receive_message(request: Request, background_tasks: BackgroundTasks):
+    # Verify HMAC signature using APP_SECRET
+    signature = request.headers.get("X-Hub-Signature-256", "")
+    body = await request.body()
+    
+    expected = "sha256=" + hmac.new(APP_SECRET.encode(), body, hashlib.sha256).hexdigest()
+    if not hmac.compare_digest(signature, expected):
+        raise HTTPException(status_code=403, detail="Invalid signature")
+
+    data = await request.json()
+    try:
+        entry = data["entry"][0]["changes"][0]["value"]
+        if "messages" not in entry:
+            return {"status": "ok"} # Ignore status updates (read receipts, etc.)
+            
+        message = entry["messages"][0]
+        from_number = message["from"]
+        msg_type = message["type"]
+        
+        if msg_type == "text":
+            query_text = message["text"]["body"]
+            background_tasks.add_task(process_and_reply, from_number, query_text, "english")
+        elif msg_type == "audio":
+            audio_id = message["audio"]["id"]
+            background_tasks.add_task(process_voice_and_reply, from_number, audio_id)
+            
+    except (KeyError, IndexError) as e:
+        print(f"Webhook parsing error: {e}")
+        
+    return {"status": "ok"}
+
+async def send_whatsapp_message(to: str, text: str):
+    """Send a text reply via WhatsApp Cloud API."""
+    if len(text) > 4096:
+        text = text[:4000] + "\n\n_[Reply truncated. Visit govbridge.in for full answer]_"
+        
+    payload = {
+        "messaging_product": "whatsapp",
+        "to": to,
+        "type": "text",
+        "text": {"body": text}
+    }
+    async with httpx.AsyncClient() as client:
+        await client.post(
+            WA_API_URL, json=payload, headers={"Authorization": f"Bearer {WA_TOKEN}"}
+        )
+
+def check_and_increment_quota() -> bool:
+    """Returns True if within quota, False if limit reached."""
+    current_month = datetime.datetime.utcnow().strftime("%Y-%m")
+    
+    # Supabase atomic upsert via RPC or standard select/update
+    res = supabase.table("whatsapp_quota").select("conversation_count").eq("month", current_month).execute()
+    
+    if res.data:
+        count = res.data[0]["conversation_count"]
+        if count >= 950:
+            return False
+        supabase.table("whatsapp_quota").update({"conversation_count": count + 1}).eq("month", current_month).execute()
+    else:
+        supabase.table("whatsapp_quota").insert({"month": current_month, "conversation_count": 1}).execute()
+        
+    return True
+
+async def process_and_reply(from_number: str, query: str, language: str):
+    """Full RAG pipeline for WhatsApp."""
+    if not check_and_increment_quota():
+        await send_whatsapp_message(from_number, "⚠️ Our WhatsApp service has reached its monthly limit. Please visit govbridge.in for full access.")
+        return
+
+    # TODO: Import your actual run_rag_pipeline function here once refactored
+    # from api import run_rag_pipeline  
+    # answer, sources = await run_rag_pipeline(query, language)
+    
+    # Mocking response until Step 4 refactor is complete
+    answer = f"Echoing your RAG query: {query}" 
+    sources = ["Source 1", "Source 2"]
+
+    sources_text = ""
+    if sources:
+        sources_text = "\n\n📄 *Sources:*\n" + "\n".join([f"• {s}" for s in sources[:3]])
+        
+    reply = f"🏛️ *GovBridge India*\n\n{answer}{sources_text}"
+    await send_whatsapp_message(from_number, reply)
+
+async def process_voice_and_reply(from_number: str, audio_id: str):
+    """Download voice message and transcribe via Whisper."""
+    async with httpx.AsyncClient() as client:
+        meta_resp = await client.get(
+            f"https://graph.facebook.com/v19.0/{audio_id}",
+            headers={"Authorization": f"Bearer {WA_TOKEN}"}
+        )
+        audio_url = meta_resp.json()["url"]
+        
+        audio_resp = await client.get(audio_url, headers={"Authorization": f"Bearer {WA_TOKEN}"})
+        audio_bytes = audio_resp.content
+
+        transcription_resp = await client.post(
+            "https://api.groq.com/openai/v1/audio/transcriptions",
+            headers={"Authorization": f"Bearer {os.environ['GROQ_API_KEY']}"},
+            files={"file": ("audio.ogg", audio_bytes, "audio/ogg")},
+            data={"model": "whisper-large-v3-turbo", "language": "hi"}
+        )
+        transcript = transcription_resp.json().get("text", "")
+        
+    if transcript:
+        await process_and_reply(from_number, transcript, "hindi")
+    else:
+        await send_whatsapp_message(from_number, "🙏 Sorry, I couldn't understand the voice message. Please type your question.")