Update app.py

app.py

@@ -2,36 +2,22 @@ import streamlit as st
 import google.generativeai as genai
 import os
 
-# Configure Gemini API with your key from environment variables
+# Configure Gemini API
 api_key = os.getenv("GEMINI_API_KEY")
 
 if not api_key:
-    st.error("API key is missing! Please set GEMINI_API_KEY in your Hugging Face Spaces secrets.")
+    st.error("API key is missing! Please set GEMINI_API_KEY in your environment variables.")
 else:
     genai.configure(api_key=api_key)
 
-    # Get available models
-    try:
-        available_models = [model.name for model in genai.list_models()]
-        if "gemini-pro" not in available_models:
-            st.warning(f"'gemini-pro' not found. Using 'gemini-pro-latest' instead.")
-            model_name = "gemini-pro-latest"
-        else:
-            model_name = "gemini-pro"
-    except Exception as e:
-        st.error(f"Error fetching available models: {e}")
-        model_name = "gemini-pro-latest"
-
     def gemini_generate(prompt):
-        """Generate content using the Gemini model with error handling."""
-        try:
-            response = genai.GenerativeModel(model_name).generate_content(prompt)
-            return response.text
-        except Exception as e:
-            return f"Error generating response: {e}"
+        """Generate content using the Gemini model."""
+        model = genai.GenerativeModel("gemini-pro-latest")  # Ensure correct model name
+        response = model.generate_content(prompt)
+        return response.text
 
     class GeminiAgent:
-        """A simple agent wrapper that uses the Gemini model for generating responses."""
+        """AI agent that generates responses using the Gemini model."""
         def __init__(self, role, goal, backstory, verbose=True):
             self.role = role
             self.goal = goal
@@ -39,7 +25,7 @@ else:
             self.verbose = verbose
 
         def generate(self, prompt):
-            """Generate a response using Gemini."""
+            """Generate a response using Gemini AI."""
             full_prompt = (
                 f"Role: {self.role}\n"
                 f"Goal: {self.goal}\n"
@@ -51,17 +37,18 @@ else:
             return gemini_generate(full_prompt)
 
     def create_agents(language="English"):
+        """Create AI agents with specific roles."""
         researcher = GeminiAgent(
-            role="Multilingual Research Analyst",
-            goal="Analyze challenges and potential solutions for underserved educational institutions",
-            backstory="Expert in educational data analysis with extensive field experience in underserved regions.",
+            role="Educational Researcher",
+            goal="Analyze challenges and provide solutions for underserved schools, colleges, and universities.",
+            backstory="Expert in education infrastructure and policy for underserved regions.",
             verbose=True
         )
 
         educator = GeminiAgent(
-            role="Bilingual Science Educator",
-            goal=f"Explain the analyzed challenges and solutions in simple terms for {language} speakers",
-            backstory=f"Expert communicator specializing in translating complex educational research into actionable insights in {language}.",
+            role="Education Communicator",
+            goal=f"Explain challenges and solutions in simple terms for {language} speakers.",
+            backstory=f"Skilled at translating research into easy-to-understand insights for {language} learners.",
             verbose=True
         )
 
@@ -72,30 +59,27 @@ else:
     RELEVANT_KEYWORDS = {"school", "college", "university", "education", "students", "infrastructure", "learning"}
 
     def is_relevant_query(user_input):
-        """Check if the user input is relevant based on predefined keywords."""
+        """Check if the query is related to education in underserved regions."""
         return any(keyword in user_input.lower() for keyword in RELEVANT_KEYWORDS)
 
     def get_chatbot_response(user_input):
-        """Process the user's query only if it is relevant."""
-        
+        """Process the query using AI agents."""
         if not is_relevant_query(user_input):
-            return "I'm here to discuss challenges and solutions for schools, colleges, and universities in underserved regions. Please ask a relevant question."
+            return "I'm here to discuss education challenges in underserved regions. Please ask a relevant question."
 
         researcher_prompt = (
-            "Analyze the following query to identify potential challenges and actionable solutions "
-            "for schools, colleges, or universities in underserved regions. Provide detailed insights, "
-            "including possible names of institutions as examples where applicable.\n\n"
+            "Analyze the following query to identify challenges and provide actionable solutions for "
+            "schools, colleges, or universities in underserved regions. Use examples where possible.\n\n"
             f"User Query: {user_input}"
         )
 
         try:
             research_response = researcher_agent.generate(researcher_prompt)
         except Exception as e:
-            return f"Error in research agent: {str(e)}"
+            return f"Error in researcher agent: {str(e)}"
 
         educator_prompt = (
-            "Using the following detailed analysis, explain the challenges and suggested solutions in simple terms. "
-            "Be sure to mention specific institutions if they are provided.\n\n"
+            "Explain the research findings in a simple and easy-to-understand manner.\n\n"
             f"Analysis: {research_response}"
         )
 
@@ -105,24 +89,19 @@ else:
             return f"Error in educator agent: {str(e)}"
 
         combined_response = (
-            "**Detailed Analysis:**\n"
+            "**🔍 Research Findings:**\n"
             f"{research_response}\n\n"
-            "**Simplified Explanation:**\n"
+            "**📖 Simplified Explanation:**\n"
             f"{educator_response}"
         )
         return combined_response
 
-    st.title("EduConnect Underserved Institutions Chatbot")
-    st.write(
-        "Ask any question related to schools, colleges, or universities in underserved regions. "
-        "The chatbot will analyze the challenges, propose actionable solutions, and provide examples of institutions when relevant."
-    )
+    # Streamlit UI
+    st.title("🎓 EduConnect Chatbot")
+    st.write("Ask about schools, colleges, and universities in underserved regions.")
 
     user_input = st.text_input("Enter your question:")
-
+    
     if st.button("Submit"):
-        if user_input.strip():
-            answer = get_chatbot_response(user_input)
-            st.write(answer)
-        else:
-            st.warning("Please enter a question.")
+        response = get_chatbot_response(user_input)
+        st.write(response)