Update app.py

app.py

@@ -203,223 +203,4 @@ if __name__ == "__main__":
     print("-"*(60 + len(" App Starting ")) + "\n")
 
     print("Launching Gradio Interface for Basic Agent Evaluation...")
-    demo.launch(debug=True, share=False)
-
-
-# import os
-# import gradio as gr
-# import requests
-# import pandas as pd
-# from langchain_core.messages import HumanMessage
-# from agent import build_graph
-
-# # --- Constants ---
-# DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
-
-# class BasicAgent:
-#     """A langgraph agent using OpenAI."""
-#     def __init__(self):
-#         print("=== INITIALIZING OPENAI BASIC AGENT ===")
-#         print(f"Current working directory: {os.getcwd()}")
-#         print(f"Files in directory: {os.listdir('.')}")
-        
-#         # Check environment variables
-#         print("=== ENVIRONMENT VARIABLES ===")
-#         for key in sorted(os.environ.keys()):
-#             if any(term in key.upper() for term in ['OPENAI', 'API_KEY', 'TOKEN', 'TAVILY']):
-#                 value = os.environ[key]
-#                 print(f"{key}: {value[:10] if value else 'None'}...")
-        
-#         # Check specifically for OpenAI API key
-#         openai_key = os.getenv("OPENAI_API_KEY")
-#         if openai_key:
-#             print(f"✓ OpenAI API Key found: {openai_key[:15]}...")
-#         else:
-#             print("✗ OpenAI API Key not found!")
-#             print("Please add OPENAI_API_KEY to your Hugging Face Space secrets")
-        
-#         try:
-#             self.graph = build_graph()
-#             print("✓ Graph built successfully")
-#         except Exception as e:
-#             print(f"✗ Error building graph: {e}")
-#             raise e
-
-#     def __call__(self, question: str) -> str:
-#         print(f"=== AGENT CALL ===")
-#         print(f"Question: {question[:100]}...")
-        
-#         try:
-#             messages = [HumanMessage(content=question)]
-#             print(f"Invoking graph with messages: {len(messages)}")
-            
-#             result = self.graph.invoke({"messages": messages})
-#             print(f"Graph result keys: {result.keys() if isinstance(result, dict) else 'Not a dict'}")
-            
-#             if 'messages' in result and result['messages']:
-#                 answer = result['messages'][-1].content
-#                 print(f"Answer (first 100 chars): {answer[:100]}...")
-#                 return answer
-#             else:
-#                 print("No messages in result")
-#                 return "I apologize, but I couldn't generate a response."
-                
-#         except Exception as e:
-#             print(f"Error in agent call: {e}")
-#             return f"Error: {str(e)}"
-
-# def run_and_submit_all(profile: gr.OAuthProfile | None):
-#     print("=== STARTING RUN AND SUBMIT ===")
-#     space_id = os.getenv("SPACE_ID")
-#     print(f"Space ID: {space_id}")
-    
-#     if not profile:
-#         return "Please Login to Hugging Face with the button.", None
-    
-#     username = profile.username
-#     print(f"Username: {username}")
-    
-#     api_url = DEFAULT_API_URL
-#     questions_url = f"{api_url}/questions"
-#     submit_url = f"{api_url}/submit"
-    
-#     print("=== INITIALIZING AGENT ===")
-#     try:
-#         agent = BasicAgent()
-#         print("✓ Agent initialized successfully")
-#     except Exception as e:
-#         error_msg = f"Error initializing agent: {e}"
-#         print(error_msg)
-#         return error_msg, None
-
-#     agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
-#     print(f"Agent code URL: {agent_code}")
-
-#     print("=== FETCHING QUESTIONS ===")
-#     try:
-#         resp_q = requests.get(questions_url, timeout=15)
-#         resp_q.raise_for_status()
-#         questions = resp_q.json()
-#         print(f"✓ Fetched {len(questions)} questions")
-#     except Exception as e:
-#         error_msg = f"Error fetching questions: {e}"
-#         print(error_msg)
-#         return error_msg, None
-
-#     results_log = []
-#     answers = []
-    
-#     print("=== PROCESSING QUESTIONS ===")
-#     for i, item in enumerate(questions):
-#         task_id = item.get("task_id")
-#         q = item.get("question")
-        
-#         print(f"\n--- Question {i+1}/{len(questions)} ---")
-#         print(f"Task ID: {task_id}")
-#         print(f"Question: {q[:100]}...")
-        
-#         if not task_id or q is None:
-#             print("Skipping - missing task_id or question")
-#             continue
-            
-#         try:
-#             print("Calling agent...")
-#             ans = agent(q)
-#             print(f"Answer: {ans[:100]}...")
-            
-#             answers.append({"task_id": task_id, "submitted_answer": ans})
-#             results_log.append({"Task ID": task_id, "Question": q, "Submitted Answer": ans})
-#             print("✓ Question processed successfully")
-            
-#         except Exception as e:
-#             error_msg = f"ERROR: {e}"
-#             print(f"✗ Error processing question: {error_msg}")
-#             results_log.append({"Task ID": task_id, "Question": q, "Submitted Answer": error_msg})
-
-#     if not answers:
-#         return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
-
-#     print(f"=== SUBMITTING {len(answers)} ANSWERS ===")
-#     payload = {"username": username.strip(), "agent_code": agent_code, "answers": answers}
-    
-#     try:
-#         resp_s = requests.post(submit_url, json=payload, timeout=60)
-#         resp_s.raise_for_status()
-#         data = resp_s.json()
-        
-#         status = (
-#             f"Submission Successful!\n"
-#             f"User: {data.get('username')}\n"
-#             f"Score: {data.get('score', 'N/A')}% "
-#             f"({data.get('correct_count', '?')}/{data.get('total_attempted', '?')})\n"
-#             f"{data.get('message', '')}"
-#         )
-#         print("✓ Submission successful")
-#         print(status)
-#         return status, pd.DataFrame(results_log)
-        
-#     except Exception as e:
-#         error_msg = f"Submission Failed: {e}"
-#         print(error_msg)
-#         return error_msg, pd.DataFrame(results_log)
-
-# # Simple test function for debugging
-# def test_agent():
-#     """Test function to verify agent works"""
-#     print("=== TESTING AGENT ===")
-#     try:
-#         agent = BasicAgent()
-#         test_questions = [
-#             "What is 2 + 3?",
-#             "What is 10 * 5?",
-#             "Search for information about Python programming"
-#         ]
-        
-#         for q in test_questions:
-#             print(f"\nTesting: {q}")
-#             answer = agent(q)
-#             print(f"Answer: {answer}")
-            
-#     except Exception as e:
-#         print(f"Test failed: {e}")
-
-# with gr.Blocks() as demo:
-#     gr.Markdown("# OpenAI-Powered Agent Evaluation Runner")
-#     gr.Markdown("""
-#     This agent uses OpenAI's GPT models instead of Hugging Face.
-    
-#     ## Setup Instructions:
-#     1. Get an OpenAI API key from https://platform.openai.com/api-keys
-#     2. Add it as `OPENAI_API_KEY` in your Hugging Face Space secrets
-#     3. (Optional) Add `TAVILY_API_KEY` for web search functionality
-#     4. Log in with the button below
-#     5. Click **Run Evaluation & Submit All Answers**
-    
-#     ## Current Configuration:
-#     - Model: GPT-3.5-turbo (change to GPT-4 in agent.py if you have access)
-#     - Tools: Math operations, Wikipedia search, Arxiv search, Web search (if Tavily configured)
-#     """)
-    
-#     with gr.Row():
-#         gr.LoginButton()
-#         test_btn = gr.Button("Test Agent", variant="secondary")
-    
-#     run_btn = gr.Button("Run Evaluation & Submit All Answers", variant="primary")
-#     status_out = gr.Textbox(label="Run Status / Submission Result", lines=5)
-#     results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True)
-    
-#     # Button actions
-#     run_btn.click(fn=run_and_submit_all, outputs=[status_out, results_table])
-#     test_btn.click(fn=test_agent, outputs=[])
-
-# if __name__ == "__main__":
-#     print("=== STARTING OPENAI GRADIO APP ===")
-    
-#     # Quick environment check
-#     openai_key = os.getenv("OPENAI_API_KEY")
-#     if openai_key:
-#         print(f"✓ OpenAI API Key configured: {openai_key[:15]}...")
-#     else:
-#         print("⚠️  OpenAI API Key not found - please add OPENAI_API_KEY to your Space secrets")
-    
-#     demo.launch(debug=True, share=False)
+    demo.launch(debug=True, share=False)