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app.py

@@ -16,24 +16,40 @@ from chatbot import agent
 
 
 # Chat history to maintain conversation context
-def chatbot(message, history):
-    # Get response from agent
+def relavant_info(message, history):
+    """
+    Relevant information for the user
+    Args:
+        message (str): The input text to search through
+        letter (str): The letter to search for
+
+    Returns:
+       str: The relevant information extracted from the message
+    """
     response = agent.run(message)
     return response
 
 # Create Gradio interface
-demo = gr.ChatInterface(
-    fn=chatbot,
-    title="Smol-Agent Chatbot",
-    description="Ask me anything!",
-    examples=[
-        "What is machine learning?",
-        "How does a transformer model work?",
-        "Explain quantum computing in simple terms"
-    ],
-    theme=gr.themes.Soft()
-)
+# demo = gr.ChatInterface(
+#     fn=relavant_info,
+#     title="Smol-Agent Chatbot",
+#     description="Ask me anything!",
+#     examples=[
+#         "What is machine learning?",
+#         "How does a transformer model work?",
+#         "Explain quantum computing in simple terms"
+#     ],
+#     theme=gr.themes.Soft()
+# )
+with gr.Blocks(theme=gr.themes.Default(primary_hue="sky")) as ui:
+    gr.Markdown("# Deep Research")
+    query_textbox = gr.Textbox(label="What topic would you like to research?")
+    run_button = gr.Button("Run", variant="primary")
+    report = gr.Markdown(label="Report")
+    
+    run_button.click(fn=relavant_info, inputs=query_textbox, outputs=report)
+    query_textbox.submit(fn=relavant_info, inputs=query_textbox, outputs=report)
 
 # Launch the app
 if __name__ == "__main__":
-    demo.launch(mcp_server=True)
+    ui.launch(mcp_server=True)