Update app.py

app.py

@@ -1,232 +1,33 @@
-import os
+"""
+Simple Gradio demo to interact with the baseline agent locally.
+
+Run with:
+```powershell
+python app.py
+```
+Then open the printed local URL or the Gradio link.
+"""
 import gradio as gr
-import requests
-import inspect
-import pandas as pd
-from smoleagents_agent import OptimizedSmolagentsGAIAgent as SmolagentsGAIAgent
+from code_agent import run_agent
 
-# --- Constants ---
 
-DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
-
-def run_and_submit_all(profile: gr.OAuthProfile | None):
-    """
-    Fetches all questions, runs the Enhanced DirectToolAgent on them, submits all answers,
-    and displays the results.
-    """
-    # --- Determine HF Space Runtime URL and Repo URL ---
-    space_id = os.getenv("SPACE_ID")
-
-    if profile:
-        username = f"{profile.username}"
-        print(f"User logged in: {username}")
-    else:
-        print("User not logged in.")
-        return "Please Login to Hugging Face with the button.", None
-
-    api_url = DEFAULT_API_URL
-    questions_url = f"{api_url}/questions"
-    submit_url = f"{api_url}/submit"
-
-    # 1. Instantiate Enhanced Direct Tool Agent
-    try:
-        agent = SmolagentsGAIAgent()
-        print("Enhanced Direct Tool Agent initialized successfully!")
-    except Exception as e:
-        print(f"Error instantiating enhanced direct tool agent: {e}")
-        return f"Error initializing enhanced direct tool agent: {e}", None
-    
-    agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
-    print(f"Agent code link: {agent_code}")
-
-    # 2. Fetch Questions
-    print(f"Fetching questions from: {questions_url}")
+def respond(prompt: str):
+    # Run the real smolagents CodeAgent (or raise if not available)
     try:
-        response = requests.get(questions_url, timeout=15)
-        response.raise_for_status()
-        questions_data = response.json()
-        if not questions_data:
-             print("Fetched questions list is empty.")
-             return "Fetched questions list is empty or invalid format.", None
-        print(f"Fetched {len(questions_data)} questions.")
-    except requests.exceptions.RequestException as e:
-        print(f"Error fetching questions: {e}")
-        return f"Error fetching questions: {e}", None
-    except requests.exceptions.JSONDecodeError as e:
-         print(f"Error decoding JSON response from questions endpoint: {e}")
-         print(f"Response text: {response.text[:500]}")
-         return f"Error decoding server response for questions: {e}", None
+        ans = run_agent(prompt)
+        return ans
     except Exception as e:
-        print(f"An unexpected error occurred fetching questions: {e}")
-        return f"An unexpected error occurred fetching questions: {e}", None
-
-    # 3. Run Enhanced DirectToolAgent
-    results_log = []
-    answers_payload = []
-    print(f"Running enhanced direct tool agent on {len(questions_data)} questions...")
-    
-    for i, item in enumerate(questions_data):
-        task_id = item.get("task_id")
-        question_text = item.get("question")
-        
-        if not task_id or question_text is None:
-            print(f"Skipping item with missing task_id or question: {item}")
-            continue
-            
-        try:
-            print(f"\n--- Processing Question {i+1}/{len(questions_data)} ---")
-            print(f"Task ID: {task_id}")
-            print(f"Question: {question_text[:100]}...")
-            
-            # Run the enhanced smolagents agent
-            submitted_answer = agent.process_question(question_text)
-            
-            answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
-            results_log.append({
-                "Task ID": task_id, 
-                "Question": question_text, 
-                "Submitted Answer": submitted_answer
-            })
-            
-            print(f"Answer: {submitted_answer[:100]}...")
-            
-        except Exception as e:
-             print(f"Error running agent on task {task_id}: {e}")
-             error_answer = f"AGENT ERROR: {str(e)[:100]}"
-             answers_payload.append({"task_id": task_id, "submitted_answer": error_answer})
-             results_log.append({
-                 "Task ID": task_id, 
-                 "Question": question_text, 
-                 "Submitted Answer": error_answer
-             })
-
-    if not answers_payload:
-        print("Enhanced DirectToolAgent did not produce any answers to submit.")
-        return "Enhanced DirectToolAgent did not produce any answers to submit.", pd.DataFrame(results_log)
-
-    # 4. Prepare Submission 
-    submission_data = {
-        "username": username.strip(), 
-        "agent_code": agent_code, 
-        "answers": answers_payload
-    }
-    
-    status_update = f"Enhanced DirectToolAgent finished. Submitting {len(answers_payload)} answers for user '{username}'..."
-    print(status_update)
-
-    # 5. Submit
-    print(f"Submitting {len(answers_payload)} answers to: {submit_url}")
-    try:
-        response = requests.post(submit_url, json=submission_data, timeout=60)
-        response.raise_for_status()
-        result_data = response.json()
-        
-        final_status = (
-            f"Submission Successful!\n"
-            f"User: {result_data.get('username')}\n"
-            f"Overall Score: {result_data.get('score', 'N/A')}% "
-            f"({result_data.get('correct_count', '?')}/{result_data.get('total_attempted', '?')} correct)\n"
-            f"Message: {result_data.get('message', 'No message received.')}"
-        )
-        
-        print("Submission successful!")
-        results_df = pd.DataFrame(results_log)
-        return final_status, results_df
-        
-    except requests.exceptions.HTTPError as e:
-        error_detail = f"Server responded with status {e.response.status_code}."
-        try:
-            error_json = e.response.json()
-            error_detail += f" Detail: {error_json.get('detail', e.response.text)}"
-        except requests.exceptions.JSONDecodeError:
-            error_detail += f" Response: {e.response.text[:500]}"
-        
-        status_message = f"Submission Failed: {error_detail}"
-        print(status_message)
-        results_df = pd.DataFrame(results_log)
-        return status_message, results_df
-        
-    except requests.exceptions.Timeout:
-        status_message = "Submission Failed: The request timed out."
-        print(status_message)
-        results_df = pd.DataFrame(results_log)
-        return status_message, results_df
-
-    except requests.exceptions.RequestException as e:
-        status_message = f"Submission Failed: Network error - {e}"
-        print(status_message)
-        results_df = pd.DataFrame(results_log)
-        return status_message, results_df
-
-    except Exception as e:
-        status_message = f"An unexpected error occurred during submission: {e}"
-        print(status_message)
-        results_df = pd.DataFrame(results_log)
-        return status_message, results_df
-
-
-# --- Build Gradio Interface using Blocks ---
-with gr.Blocks(title="Enhanced Smolagents GAIA Agent") as demo:
-    gr.Markdown("# Enhanced Smolagents GAIA Agent Evaluation")
-    gr.Markdown(
-        """
-        ## Instructions:
-        1. **Login** to Hugging Face using the button below
-        2. **Click** 'Run Enhanced Evaluation & Submit All Answers'
-        3. **Wait** for your enhanced smolagents agent to process all questions
-        4. **View** your score and detailed results
-
-        ## How the Enhanced Agent Works:
-        - **Smart Capability Detection**: Automatically detects available tools
-        - **Fallback Strategy**: Uses basic responses when advanced features unavailable
-        - **Enhanced Responses**: Leverages Wikipedia, web search, and data tools when possible
-        - **Zero-Error Operation**: Guaranteed to complete all questions regardless of available features
-
-        **Note**: This enhanced version maximizes capabilities while maintaining complete reliability.
-        """
-    )
-
-    gr.LoginButton()
-
-    run_button = gr.Button("Run Enhanced Smolagents GAIA Evaluation & Submit All Answers", variant="primary")
-
-    status_output = gr.Textbox(
-        label="📊 Run Status / Submission Result", 
-        lines=10, 
-        interactive=False
-    )
-    
-    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__ == "__app__":
-    print("\n" + "="*60 + " Enhanced Smolagents GAIA Agent Starting " + "="*60)
-
-    # Check environment variables
-    space_host_startup = os.getenv("SPACE_HOST")
-    space_id_startup = os.getenv("SPACE_ID")
+        return f"(agent error) {e}"
 
-    if space_host_startup:
-        print(f"[OK] SPACE_HOST found: {space_host_startup}")
-        print(f"   Runtime URL: https://{space_host_startup}.hf.space")
-    else:
-        print("[INFO] SPACE_HOST not found (running locally)")
 
-    if space_id_startup:
-        print(f"[OK] SPACE_ID found: {space_id_startup}")
-        print(f"   Repo URL: https://huggingface.co/spaces/{space_id_startup}")
-        print(f"   Code URL: https://huggingface.co/spaces/{space_id_startup}/tree/main")
-    else:
-        print("[INFO] SPACE_ID not found (running locally)")
+demo = gr.Interface(
+    fn=respond,
+    inputs=gr.Textbox(lines=5, label="User Prompt"),
+    outputs=gr.Textbox(lines=10, label="Agent Response"),
+    title="Agents Course — Final Agent Demo",
+    description="smolagents CodeAgent demo for the course final project.",
+)
 
-    print("="*(120 + len(" Enhanced Smolagents GAIA Agent Starting ")) + "\n")
 
-    print("Launching Enhanced Smolagents GAIA Agent Evaluation Interface...")
-    demo.launch(debug=True, share=False)
+if __name__ == "__main__":
+    demo.launch()