Update app.py

app.py

@@ -3,7 +3,6 @@ from phi.agent import Agent
 from phi.model.groq import Groq
 from phi.tools.duckduckgo import DuckDuckGo
 from dotenv import load_dotenv
-import time
 
 # Load environment variables
 load_dotenv()
@@ -26,40 +25,27 @@ web_agent = Agent(
     markdown=True  # Format the output in Markdown
 )
 
-# Function to fetch the latest AI news using the correct method
+# Function to fetch the latest AI news
 def fetch_latest_ai_news():
-    # Simulating some processing delay
-    time.sleep(3)
-
     query = "Find the latest news about Artificial Intelligence and summarize it."
-    
-    # Use the correct method on the Agent, likely 'run' or 'execute' instead of 'ask'
-    response = web_agent.execute(query)  # Using 'execute' or any other valid method
-    
-    raw_response = str(response)  # Simulating raw data for terminal-like output
-    processed_response = response.get('response', 'No summary available.')  # Cleaned summary
-    
-    return raw_response, processed_response  # Return raw and processed data for side-by-side display
-
-# Streamlit App Interface
-def create_streamlit_app():
-    st.title("AI News Fetcher")  # Title of the app
-    st.markdown("This app fetches and summarizes the latest AI news using AI models.")
-
-    # Add a button for triggering the process
-    if st.button("Generate AI News"):
-        with st.spinner("Fetching AI news..."):
-            # Get the raw and processed AI news
-            raw_response, processed_response = fetch_latest_ai_news()
-
-            # Display raw response (Terminal-like view)
-            st.subheader("Raw Data")
-            st.text_area("Raw Data", value=raw_response, height=300)
-
-            # Display processed (summarized) response
-            st.subheader("Processed Data")
-            st.markdown(processed_response)
-
-# Running the Streamlit app
-if __name__ == "__main__":
-    create_streamlit_app()
+    response = web_agent.query(query, stream=False)  # Fetch and summarize AI news
+    return response
+
+# Streamlit App
+st.title("AI News Fetcher")
+
+st.markdown("""
+Welcome to the **AI News Fetcher** app! This tool provides the latest summaries of AI-related news from the web.
+
+---
+""")
+
+if st.button("Fetch Latest AI News"):
+    st.info("Fetching the latest AI news. This may take a few seconds...")
+    try:
+        news_summary = fetch_latest_ai_news()
+        st.markdown(news_summary)  # Display the news summary in Markdown format
+    except Exception as e:
+        st.error(f"An error occurred: {str(e)}")
+else:
+    st.write("Click the button above to fetch the latest AI news.")