Create app.py

app.py

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+import streamlit as st
+from phi.agent import Agent
+from phi.model.groq import Groq
+from phi.tools.duckduckgo import DuckDuckGo
+from phi.tools.yfinance import YFinanceTools
+import os
+
+# Streamlit App Configuration
+st.set_page_config(
+    page_title="Financial Analysis AI Agent",
+    page_icon="💹",
+    layout="wide"
+)
+
+# Web Search Agent
+def create_web_search_agent():
+    return Agent(
+        name="Web Search Agent",
+        role="Search the web for information",
+        model=Groq(id="llama-3.2-3b-preview"),
+        tools=[DuckDuckGo()],
+        instructions=["Always include sources"],
+        show_tools_call=True,
+        markdown=True,
+    )
+
+# Financial Agent
+def create_financial_agent():
+    return Agent(
+        name="Finance AI Agent",
+        role="Analyze financial data and provide insights",
+        model=Groq(id="llama-3.2-3b-preview"),
+        tools=[
+            YFinanceTools(
+                stock_price=True, 
+                analyst_recommendations=True, 
+                stock_fundamentals=True,
+                company_news=True
+            )
+        ],
+        instructions=["Use tables to display the data"],
+        show_tools_call=True,
+        markdown=True,
+    )
+
+# Create Multi-Agent
+multi_ai_agent = Agent(
+    team=[create_web_search_agent(), create_financial_agent()],
+    instructions=[
+        "Always include sources", 
+        "Use tables to display the data"
+    ],
+    show_tools_call=True,
+    markdown=True,
+)
+
+# Streamlit App
+def main():
+    st.title("🤖 Financial Analysis AI Agent")
+    st.write("Get comprehensive financial insights using AI-powered web search and analysis!")
+
+    # Sidebar for configuration
+    st.sidebar.header("🔧 Query Configuration")
+    
+    # Stock Symbol Input
+    stock_symbol = st.sidebar.text_input(
+        "Enter Stock Symbol", 
+        value="NVDA", 
+        help="Enter a valid stock ticker symbol"
+    )
+
+    # Query Type Selection
+    query_type = st.sidebar.selectbox(
+        "Select Analysis Type",
+        [
+            "Analyst Recommendations",
+            "Latest Company News",
+            "Stock Fundamentals",
+            "Comprehensive Financial Overview"
+        ]
+    )
+
+    # Generate Query
+    if query_type == "Analyst Recommendations":
+        query = f"Summarize analyst recommendations for {stock_symbol}"
+    elif query_type == "Latest Company News":
+        query = f"Provide the latest news for {stock_symbol}"
+    elif query_type == "Stock Fundamentals":
+        query = f"Analyze stock fundamentals for {stock_symbol}"
+    else:
+        query = f"Provide a comprehensive financial overview for {stock_symbol}"
+
+    # Submit Button
+    if st.sidebar.button("Generate Analysis"):
+        with st.spinner("Analyzing financial data..."):
+            # Capture the response
+            response_container = st.container()
+            with response_container:
+                try:
+                    # Stream the response
+                    full_response = ""
+                    response_placeholder = st.empty()
+                    for chunk in multi_ai_agent.respond(query, stream=True):
+                        full_response += chunk
+                        response_placeholder.markdown(full_response)
+                    
+                    # Final display
+                    st.success("Analysis Complete!")
+                except Exception as e:
+                    st.error(f"An error occurred: {e}")
+
+    # Footer
+    st.sidebar.markdown("---")
+    st.sidebar.info(
+        "💡 Tip: Use this tool to get quick financial insights. "
+        "Always verify important financial decisions independently."
+    )
+
+# Run the Streamlit app
+if __name__ == "__main__":
+    main()