Upload 3 files

agent.py

@@ -134,8 +134,5 @@ def get_tools() -> List[BaseTool]:
         web_tool
     ]
 
-# REMOVED circular import from app.py
-# This file now just defines tools and doesn't attempt to build the agent
-
 if __name__ == "__main__":
     print("This module defines tools for the agent. Run app.py or standalone_debug.py to test the agent.") 

app.py

@@ -284,72 +284,37 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
         results_df = pd.DataFrame(results_log)
         return status_message, results_df
 
-# Try to load Gradio components, handling potential OAuth errors
-try:
-    # --- Build Gradio Interface using Blocks ---
-    with gr.Blocks() as demo:
-        gr.Markdown("# Basic Agent Evaluation Runner")
-        gr.Markdown(
-            """
-            **Instructions:**
 
-            1.  Please clone this space, then modify the code to define your agent's logic, the tools, the necessary packages, etc ...
-            2.  Log in to your Hugging Face account using the button below. This uses your HF username for submission.
-            3.  Click 'Run Evaluation & Submit All Answers' to fetch questions, run your agent, submit answers, and see the score.
+# --- Build Gradio Interface using Blocks ---
+with gr.Blocks() as demo:
+    gr.Markdown("# Basic Agent Evaluation Runner")
+    gr.Markdown(
+        """
+        **Instructions:**
 
-            ---
-            **Disclaimers:**
-            Once clicking on the "submit button, it can take quite some time ( this is the time for the agent to go through all the questions).
-            This space provides a basic setup and is intentionally sub-optimal to encourage you to develop your own, more robust solution. For instance for the delay process of the submit button, a solution could be to cache the answers and submit in a seperate action or even to answer the questions in async.
-            """
-        )
+        1.  Please clone this space, then modify the code to define your agent's logic, the tools, the necessary packages, etc ...
+        2.  Log in to your Hugging Face account using the button below. This uses your HF username for submission.
+        3.  Click 'Run Evaluation & Submit All Answers' to fetch questions, run your agent, submit answers, and see the score.
 
-        gr.LoginButton()
+        ---
+        **Disclaimers:**
+        Once clicking on the "submit button, it can take quite some time ( this is the time for the agent to go through all the questions).
+        This space provides a basic setup and is intentionally sub-optimal to encourage you to develop your own, more robust solution. For instance for the delay process of the submit button, a solution could be to cache the answers and submit in a seperate action or even to answer the questions in async.
+        """
+    )
 
-        run_button = gr.Button("Run Evaluation & Submit All Answers")
+    gr.LoginButton()
 
-        status_output = gr.Textbox(label="Run Status / Submission Result", lines=5, interactive=False)
-        results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True)
+    run_button = gr.Button("Run Evaluation & Submit All Answers")
 
-        run_button.click(
-            fn=run_and_submit_all,
-            outputs=[status_output, results_table]
-        )
-except ImportError as e:
-    print(f"Error initializing Gradio OAuth components: {e}")
-    print("This error is expected when running locally without OAuth dependencies.")
-    print("You can test the agent using standalone_debug.py or mini_test.py instead.")
-    # Create a minimal demo without OAuth if running locally
-    try:
-        import gradio as gr
-        with gr.Blocks() as demo:
-            gr.Markdown("# Agent Test Environment (Local Mode)")
-            gr.Markdown("OAuth dependencies not found. Running in local test mode.")
-            
-            with gr.Row():
-                with gr.Column():
-                    question_input = gr.Textbox(label="Enter your question", lines=2)
-                    test_button = gr.Button("Test Agent")
-                
-                with gr.Column():
-                    answer_output = gr.Textbox(label="Agent Answer", lines=10)
-            
-            def test_agent_locally(question):
-                try:
-                    agent = BasicAgent()
-                    result = agent(question)
-                    return result
-                except Exception as e:
-                    return f"Error: {str(e)}\n\n{traceback.format_exc()}"
-            
-            test_button.click(
-                fn=test_agent_locally,
-                inputs=[question_input],
-                outputs=[answer_output]
-            )
-    except Exception as e:
-        print(f"Failed to create even minimal Gradio interface: {e}")
-        demo = None
+    status_output = gr.Textbox(label="Run Status / Submission Result", lines=5, interactive=False)
+    # Removed max_rows=10 from DataFrame constructor
+    results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True)
+
+    run_button.click(
+        fn=run_and_submit_all,
+        outputs=[status_output, results_table]
+    )
 
 if __name__ == "__main__":
     print("\n" + "-"*30 + " App Starting " + "-"*30)
@@ -373,3 +338,4 @@ if __name__ == "__main__":
     print("-"*(60 + len(" App Starting ")) + "\n")
 
     print("Launching Gradio Interface for Basic Agent Evaluation...")
+    demo.launch(debug=True, share=False)