Update app.py

app.py

@@ -1,15 +1,21 @@
 import streamlit as st
+import os
+import requests
 from tavily import TavilyClient
+from groq import Groq
 
-# Step 1: Retrieve Tavily API Key from Hugging Face Secrets
-TAVILY_API_KEY = st.secrets["TAVILY_API_KEY"]  # Access the API key securely from Hugging Face Secrets
-if TAVILY_API_KEY is None:
-    st.error("API key is missing. Please add the TAVILY_API_KEY in Hugging Face Secrets.")
+# Step 1: Retrieve API Keys from Hugging Face Secrets
+TAVILY_API_KEY = st.secrets["TAVILY_API_KEY"]
+GROQ_API_KEY = st.secrets["GROQ_API_KEY"]
+
+if TAVILY_API_KEY is None or GROQ_API_KEY is None:
+    st.error("API key(s) are missing. Please add the API keys in Hugging Face Secrets.")
 else:
-    # Initialize Tavily Client with the API key
+    # Step 2: Initialize Clients for Tavily and Groq
     tavily_client = TavilyClient(api_key=TAVILY_API_KEY)
+    groq_client = Groq(api_key=GROQ_API_KEY)
 
-    # Step 2: Fetch Suggestions Using Tavily
+    # Step 3: Fetch Suggestions Using Tavily
     def fetch_tavily_suggestions(location, need):
         """
         Use Tavily API to fetch real-time suggestions based on location and need.
@@ -19,18 +25,29 @@ else:
         try:
             # Execute the query using TavilyClient
             response = tavily_client.search(query)
-            st.write(f"Raw API Response: {response}")  # Debug: print the raw response for inspection
-
-            # Check if the 'text' key exists in the response and return it
-            if "text" in response:
-                return response["text"]
-            else:
-                return "No suggestions available in the response."
-
+            return response.get("text", "No suggestions available.")
         except Exception as e:
             return f"Error: {str(e)}"
 
-    # Step 3: Build Streamlit UI
+    # Step 4: Enhance Suggestions Using Groq
+    def enhance_with_groq(suggestions):
+        """
+        Use the Groq model to enhance and organize the suggestions.
+        """
+        groq_client = Groq(api_key=GROQ_API_KEY)
+        
+        try:
+            # Perform chat completion using Groq for better formatting and response enhancement
+            chat_completion = groq_client.chat.completions.create(
+                messages=[{"role": "user", "content": suggestions}],
+                model="llama-3.3-70b-versatile",  # Specify model for Groq
+            )
+            # Extract and return the enhanced message
+            return chat_completion.choices[0].message.content
+        except Exception as e:
+            return f"Error with Groq API: {str(e)}"
+
+    # Step 5: Build Streamlit UI
     st.title("Rural Connectivity Advisor")
     st.markdown("""
     Welcome to the **Rural Connectivity Advisor**!  
@@ -45,11 +62,17 @@ else:
     location = st.sidebar.text_input("Enter Your Location (e.g., City, District)")
     needs = st.sidebar.selectbox("What do you need?", ["Internet Provider", "Signal Boosting Tips", "Offline Tools"])
 
-    # Fetch and Display Suggestions
+    # Fetch and Enhance Suggestions
     if st.sidebar.button("Get Suggestions"):
         if location:
             st.subheader(f"Suggestions for {needs} in {location}")
-            suggestions = fetch_tavily_suggestions(location, needs)
-            st.write(suggestions)
+            tavily_suggestions = fetch_tavily_suggestions(location, needs)
+            st.write("Raw Suggestions from Tavily:")
+            st.write(tavily_suggestions)
+
+            # Enhance the response using Groq
+            enhanced_suggestions = enhance_with_groq(tavily_suggestions)
+            st.subheader("Enhanced Suggestions:")
+            st.write(enhanced_suggestions)
         else:
             st.warning("Please enter your location to get recommendations.")