add files

README.md

@@ -1,10 +1 @@
----
-title: Customer Service
-emoji: 🐢
-colorFrom: yellow
-colorTo: green
-sdk: docker
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# customer_service

app.py

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+import os
+from fastapi import FastAPI, Request
+from pinecone import Pinecone
+from groq import Groq
+import httpx # For sending messages back to Telegram
+
+# 1. Configuration & Clients
+# Use Hugging Face Secrets for these!
+PINECONE_API_KEY = os.environ.get("PINECONE_API_KEY")
+GROQ_API_KEY = os.environ.get("GROQ_API_KEY")
+TELEGRAM_TOKEN = os.environ.get("TELEGRAM_TOKEN")
+TELEGRAM_URL = f"https://api.telegram.org/bot{TELEGRAM_TOKEN}/sendMessage"
+
+pc = Pinecone(api_key=PINECONE_API_KEY)
+index = pc.Index("customerserviceindex")
+groq_client = Groq(api_key=GROQ_API_KEY)
+
+app = FastAPI()
+
+# 2. The Core AI Logic
+async def get_ai_response(user_query: str):
+    # Vectorize query using Pinecone Inference
+    query_embedding = pc.inference.embed(
+        model_id="multilingual-e5-large",
+        inputs=[user_query],
+        parameters={"input_type": "query"}
+    )
+
+    # Search Pinecone for Bank Context
+    search_results = index.query(
+        vector=query_embedding[0].values,
+        top_k=3,
+        include_metadata=True
+    )
+    
+    context_text = "\n".join([res.metadata['original_text'] for res in search_results.matches])
+
+    # Construct the System Prompt
+    # We use facts from the profile: Islamic banking, based in Mukalla [cite: 15, 6]
+    prompt = f"""
+    You are the official AI assistant for Hadhramout Bank (بنك حضرموت).
+    Your tone is professional, helpful, and culturally respectful to the Yemeni community.
+    Use ONLY the provided context to answer. If the information isn't there, 
+    kindly ask the customer to visit the main branch in Al Mukalla.
+    
+    Context:
+    {context_text}
+    
+    Customer Question: {user_query}
+    """
+
+    completion = groq_client.chat.completions.create(
+        messages=[{"role": "user", "content": prompt}],
+        model="llama3-8b-8192",
+    )
+    return completion.choices[0].message.content
+
+# 3. The Webhook Endpoint
+@app.post("/webhook")
+async def telegram_webhook(request: Request):
+    data = await request.json()
+    
+    if "message" in data:
+        chat_id = data["message"]["chat"]["id"]
+        user_text = data["message"].get("text", "")
+
+        if user_text:
+            # Get the intelligent response
+            ai_answer = await get_ai_response(user_text)
+            
+            # Send back to Telegram
+            async with httpx.AsyncClient() as client:
+                await client.post(TELEGRAM_URL, json={
+                    "chat_id": chat_id,
+                    "text": ai_answer
+                })
+                
+    return {"status": "ok"}
+
+@app.get("/")
+async def root():
+    return {"message": "Hadhramout Bank AI Backend is Live"}

requirements.txt

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+fastapi==0.104.1
+uvicorn==0.24.0
+pinecone==2.2.4
+groq==0.4.1
+httpx==0.25.2
+python-dotenv==1.0.0