Update app.py

app.py

@@ -1,27 +1,42 @@
+
 import streamlit as st
 from langchain_google_genai import ChatGoogleGenerativeAI  
-from google.ai.generativelanguage_v1beta.types import Tool as GenAITool
+from langchain.tools import Tool
+from langchain_community.tools.google_search import GoogleSearchResults
 import json
 
+# Get API key for Gemini
+GEMINI_API_KEY = userdata.get("gemini_api")
+
 # Configure LangChain LLM with Gemini 2.0
-llm = ChatGoogleGenerativeAI(model="gemini-2.0-flash", google_api_key=os.getenv("gemini_api"))
+llm = ChatGoogleGenerativeAI(model="gemini-2.0-flash-exp", google_api_key=os.getenv("gemini_api"))
+
+# Google Search Tool (does not require API key)
+google_search = GoogleSearchResults()
+search_tool = Tool(
+    name="Google Search",
+    func=google_search.run,
+    description="Search the web for information.",
+)
 
 def azure_cert_bot(cert_name):
     query = f"Microsoft Azure {cert_name} certification curriculum site:microsoft.com"
     
-    # Use Gemini's built-in Google Search tool
-    resp = llm.invoke(
-        f"Find the Microsoft documentation for {cert_name} and generate key Q&A based on the curriculum.",
-        tools=[GenAITool(google_search={})],
+    # Perform Google Search
+    search_results = search_tool.run(query)
+    
+    # Generate Q&A using Gemini
+    prompt = (
+        f"Based on the following curriculum details, generate key questions and answers in markdown format for the {cert_name} certification exam:\n\n{search_results}"
     )
+    response = llm.invoke(prompt)
     
     try:
-        response_text = resp.get("content", "No response generated.") if isinstance(resp, dict) else resp
-        response_text = "\n".join([line for line in response_text.split("\n") if not line.lower().startswith("content=") and "metadata" not in line.lower()])
+        response_text = response.get("content", "No response generated.") if isinstance(response, dict) else response
     except Exception as e:
         response_text = f"Error processing response: {str(e)}"
     
-    return query, response_text
+    return search_results, response_text
 
 # Streamlit UI Enhancements
 st.set_page_config(page_title="Azure Certification Prep Assistant", layout="wide")
@@ -60,10 +75,10 @@ st.markdown("<div class='title'>Azure Certification Prep Assistant</div>", unsaf
 cert_name = st.text_input("Enter Azure Certification Name (e.g., AZ-900)", "")
 if st.button("Get Certification Details"):
     if cert_name:
-        search_query, qa_content = azure_cert_bot(cert_name)
+        links, qa_content = azure_cert_bot(cert_name)
         
-        st.markdown("<div class='subheader'>Certification Search Query</div>", unsafe_allow_html=True)
-        st.markdown(f"<div class='markdown-text-container'>🔍 {search_query}</div>", unsafe_allow_html=True)
+        st.markdown("<div class='subheader'>Certification Links & Curriculum</div>", unsafe_allow_html=True)
+        st.markdown(f"<div class='markdown-text-container'>{links}</div>", unsafe_allow_html=True)
         
         st.markdown("<div class='subheader'>Exam Questions & Answers</div>", unsafe_allow_html=True)
         st.markdown(f"<div class='markdown-text-container'>{qa_content}</div>", unsafe_allow_html=True)