Update app.py

app.py

@@ -1,9 +1,8 @@
 import streamlit as st
-import wikipedia
 from groq import Groq
 import os
 
-# Step 1: Retrieve API Keys from Hugging Face Secrets
+# Step 1: Retrieve API Key from Hugging Face Secrets
 GROQ_API_KEY = st.secrets["GROQ_API_KEY"]
 
 # Step 2: Initialize Groq Client
@@ -12,46 +11,22 @@ if GROQ_API_KEY is None:
 else:
     groq_client = Groq(api_key=GROQ_API_KEY)
 
-    # Step 3: Wikipedia Query Function
-    def get_wikipedia_response(query):
+    # Step 3: Enhance Suggestions Using Groq
+    def enhance_with_groq(query):
         """
-        Fetch information from Wikipedia based on the query.
+        Enhance the suggestions using Groq.
         """
-        try:
-            # Fetch a summary of the query from Wikipedia
-            result = wikipedia.summary(query, sentences=3)
-            return result
-        except wikipedia.exceptions.DisambiguationError as e:
-            return f"Ambiguous query, please clarify: {e.options}"
-        except wikipedia.exceptions.HTTPTimeoutError:
-            return "Error: Wikipedia request timed out. Please try again."
-        except wikipedia.exceptions.RedirectError:
-            return "Error: Redirect error while fetching Wikipedia data."
-        except Exception as e:
-            return f"An unexpected error occurred: {str(e)}"
-
-    # Step 4: Enhance with Groq (if needed)
-    def enhance_with_groq(query, suggestions=None):
-        """
-        Enhance suggestions using Groq or generate from scratch.
-        """
-        if suggestions is None:
-            # If no suggestions, use Groq to generate an enhancement
-            response_content = query
-        else:
-            response_content = suggestions
-
         try:
             # Perform chat completion using Groq
             chat_completion = groq_client.chat.completions.create(
-                messages=[{"role": "user", "content": response_content}],
+                messages=[{"role": "user", "content": query}],
                 model="llama-3.3-70b-versatile",  # Specify model for Groq
             )
             return chat_completion.choices[0].message.content
         except Exception as e:
             return f"Error with Groq API: {str(e)}"
 
-    # Step 5: Build Streamlit UI
+    # Step 4: Build Streamlit UI
     st.title("Rural Connectivity Advisor")
     st.markdown("""
     Welcome to the **Rural Connectivity Advisor**!  
@@ -69,23 +44,16 @@ else:
     # Fetch and Enhance Suggestions
     if st.sidebar.button("Get Suggestions"):
         if location:
-            # Query Wikipedia first for general information about the location
-            wikipedia_query = f"Internet providers in {location}"
-            wikipedia_response = get_wikipedia_response(wikipedia_query)
-
+            # Formulate the query for Groq based on user inputs
+            query = f"Provide suggestions for {needs} in {location}, especially affordable options and tips."
+            
             st.subheader(f"Suggestions for {needs} in {location}")
-            st.write("Raw Suggestions from Wikipedia:")
-            st.write(wikipedia_response)
+            
+            # Get response from Groq
+            groq_response = enhance_with_groq(query)
 
-            # If Wikipedia response is not enough, use Groq to enhance
-            if wikipedia_response:
-                enhanced_response = enhance_with_groq(wikipedia_query, wikipedia_response)
-                st.subheader("Enhanced Suggestions from Groq:")
-                st.write(enhanced_response)
-            else:
-                # If no meaningful Wikipedia results, fallback to Groq
-                groq_response = enhance_with_groq(wikipedia_query)
-                st.subheader("Generated Response from Groq:")
-                st.write(groq_response)
+            # Display Groq response
+            st.write("Suggestions from Groq:")
+            st.write(groq_response)
         else:
             st.warning("Please enter your location to get recommendations.")