introduced app.py: a gradio app for interacting with the agent

app.py

@@ -0,0 +1,49 @@
+import gradio as gr
+from src.stock_analysis_agent import StockAnalyst
+
+
+def initialize_agent():
+    print(f'Initializing Stock-Analysis Agent')
+    # Initialize RAG instance
+    try:
+        stock_analyst = StockAnalyst()
+        message = "Stock-Analysis Agent initialized successfully."
+    except Exception as e:
+        stock_analyst = None
+        message = f"Error initializing Stock-Analysis Agent:\n{e}"
+    return message, stock_analyst
+
+def interact_with_agent(agent_instance, ticker):
+    if agent_instance is None:
+        return 'Stock-Analysis Agent is not initialized. Please initialize first.'
+    messages = agent_instance.get_stock_suggestion(ticker)
+    final_message = messages[3].model_dump()['content']
+    return final_message
+
+with gr.Blocks() as demo:
+    gr.Markdown("# Stock Analysis Agent")
+    # State to store the RAG instance
+    message, stock_analyst = initialize_agent()
+    agent_instance = gr.State(None) 
+    init_button = gr.Button("Initialize")
+    init_status = gr.Textbox(label="Initialization Status", interactive=False)
+    # Event handlers
+    init_button.click(
+        initialize_agent,
+        outputs=[init_status, agent_instance]  # Output: status message and the RAG instance
+    )
+    # gr.Text(label='Status', value=message)
+    gr.Markdown("Enter a stock symbol ('ticker') to be analyzed (GOOG, MSFT, etc.)")
+    ticker = gr.Textbox(label="ticker")
+    analyze_button = gr.Button('Analyze Stock')
+    output = gr.Textbox(label="Output Box")
+    analyze_button.click(
+            fn=interact_with_agent,
+            inputs=[agent_instance, ticker],
+            outputs=output, 
+            api_name="analyze_stock")
+
+
+if __name__ == "__main__":
+    demo.launch()
+