Update app.py

app.py

@@ -4,270 +4,148 @@ import requests
 import pandas as pd
 from smolagents import CodeAgent, DuckDuckGoSearchTool, LiteLLMModel
 
-# --- Constants ---
+# API URL for submission
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
-# --- Agent Definition ---
+# My agent class
 class BasicAgent:
     def __init__(self):
-        print("Initializing smolagents CodeAgent...")
-        try:
-            # Create model - using FREE Llama model
-            self.model = LiteLLMModel(
-                model_id="huggingface/meta-llama/Llama-3.2-3B-Instruct"
-            )
-            
-            # Create search tool
-            self.search_tool = DuckDuckGoSearchTool()
-            
-            # Create agent with tools
-            self.agent = CodeAgent(
-                tools=[self.search_tool],
-                model=self.model,
-                additional_authorized_imports=[
-                    "requests", 
-                    "pandas", 
-                    "numpy", 
-                    "openpyxl", 
-                    "xlrd"
-                ]
-            )
-            print("✅ Agent initialized successfully!")
-        except Exception as e:
-            print(f"❌ Error initializing agent: {e}")
-            raise e
+        print("Starting agent...")
+        
+        # Get my HF token
+        token = os.getenv("hf_token")  # ← Changed to lowercase!
+        
+        if not token:
+            raise Exception("Token not found! Check secrets.")
+        
+        # Create the model
+        self.model = LiteLLMModel(
+            model_id="huggingface/meta-llama/Llama-3.2-3B-Instruct",
+            api_key=token
+        )
+        
+        # Add web search
+        self.search_tool = DuckDuckGoSearchTool()
+        
+        # Create agent
+        self.agent = CodeAgent(
+            tools=[self.search_tool],
+            model=self.model,
+            additional_authorized_imports=["requests", "pandas", "numpy", "openpyxl", "xlrd"]
+        )
+        
+        print("Agent ready!")
     
     def __call__(self, question: str) -> str:
-        """Run agent on a question and return the answer"""
-        print(f"📝 Question: {question[:80]}...")
+        print(f"Question: {question[:50]}...")
         try:
-            # Run the agent
             answer = self.agent.run(question)
-            answer_str = str(answer)
-            print(f"✅ Answer: {answer_str[:80]}...")
-            return answer_str
+            return str(answer)
         except Exception as e:
-            error_msg = f"Error: {str(e)}"
-            print(f"❌ {error_msg}")
-            return error_msg
+            return f"Error: {str(e)}"
 
 
 def run_and_submit_all(profile: gr.OAuthProfile | None):
-    """
-    Fetches questions, runs agent, submits answers, returns results.
-    """
-    # Get Space ID
+    """Main function to run the evaluation"""
+    
     space_id = os.getenv("SPACE_ID")
-
-    # Check if user is logged in
+    
+    # Check if logged in
     if profile:
-        username = f"{profile.username}"
-        print(f"👤 User logged in: {username}")
+        username = profile.username
+        print(f"Logged in as: {username}")
     else:
-        print("⚠️ User not logged in")
-        return "Please Login to Hugging Face with the button above.", None
-
-    # API endpoints
-    api_url = DEFAULT_API_URL
-    questions_url = f"{api_url}/questions"
-    submit_url = f"{api_url}/submit"
-
-    # 1. Initialize Agent
-    print("\n" + "="*60)
-    print("🤖 INITIALIZING AGENT")
-    print("="*60)
+        return "Please login first!", None
+    
+    # URLs
+    questions_url = f"{DEFAULT_API_URL}/questions"
+    submit_url = f"{DEFAULT_API_URL}/submit"
+    
+    # Initialize agent
+    print("Creating agent...")
     try:
         agent = BasicAgent()
     except Exception as e:
-        error_msg = f"Error initializing agent: {e}"
-        print(f"❌ {error_msg}")
-        return error_msg, None
+        return f"Error creating agent: {e}", None
     
-    # Code URL for submission
     agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
-    print(f"📂 Code URL: {agent_code}")
-
-    # 2. Fetch Questions
-    print("\n" + "="*60)
-    print("📥 FETCHING QUESTIONS")
-    print("="*60)
-    print(f"URL: {questions_url}")
+    
+    # Get questions
+    print("Getting questions...")
     try:
         response = requests.get(questions_url, timeout=15)
         response.raise_for_status()
-        questions_data = response.json()
-        
-        if not questions_data:
-            return "No questions received from server.", None
-            
-        print(f"✅ Fetched {len(questions_data)} questions")
+        questions = response.json()
+        print(f"Got {len(questions)} questions")
     except Exception as e:
-        error_msg = f"Error fetching questions: {e}"
-        print(f"❌ {error_msg}")
-        return error_msg, None
-
-    # 3. Run Agent on Questions
-    print("\n" + "="*60)
-    print("🚀 RUNNING AGENT ON QUESTIONS")
-    print("="*60)
+        return f"Error getting questions: {e}", None
     
-    results_log = []
-    answers_payload = []
+    # Answer questions
+    print("Answering questions...")
+    results = []
+    answers = []
     
-    for idx, item in enumerate(questions_data, 1):
+    for i, item in enumerate(questions):
         task_id = item.get("task_id")
-        question_text = item.get("question")
+        question = item.get("question")
         
-        if not task_id or question_text is None:
-            print(f"⚠️ Skipping invalid question")
+        if not task_id or not question:
             continue
         
-        print(f"\n[{idx}/{len(questions_data)}] Task ID: {task_id}")
+        print(f"Question {i+1}/{len(questions)}")
         
         try:
-            # Run agent
-            submitted_answer = agent(question_text)
-            
-            # Store answer
-            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
-            })
-            
+            answer = agent(question)
+            answers.append({"task_id": task_id, "submitted_answer": answer})
+            results.append({"Task ID": task_id, "Question": question, "Submitted Answer": answer})
         except Exception as e:
-            error_answer = f"AGENT ERROR: {e}"
-            print(f"❌ Error: {e}")
-            
-            results_log.append({
-                "Task ID": task_id,
-                "Question": question_text,
-                "Submitted Answer": error_answer
-            })
-
-    if not answers_payload:
-        return "Agent did not produce any answers.", pd.DataFrame(results_log)
-
-    # 4. Submit Answers
-    print("\n" + "="*60)
-    print("📤 SUBMITTING ANSWERS")
-    print("="*60)
-    print(f"Submitting {len(answers_payload)} answers for user: {username}")
+            print(f"Error on question {i+1}: {e}")
+            results.append({"Task ID": task_id, "Question": question, "Submitted Answer": f"Error: {e}"})
     
-    submission_data = {
-        "username": username.strip(),
+    if not answers:
+        return "No answers generated", pd.DataFrame(results)
+    
+    # Submit
+    print(f"Submitting {len(answers)} answers...")
+    submission = {
+        "username": username,
         "agent_code": agent_code,
-        "answers": answers_payload
+        "answers": answers
     }
     
     try:
-        response = requests.post(submit_url, json=submission_data, timeout=60)
+        response = requests.post(submit_url, json=submission, timeout=60)
         response.raise_for_status()
-        result_data = response.json()
+        result = response.json()
         
-        # Format success message
-        final_status = (
-            f"✅ Submission Successful!\n\n"
-            f"User: {result_data.get('username')}\n"
-            f"Score: {result_data.get('score', 'N/A')}%\n"
-            f"Correct: {result_data.get('correct_count', '?')}/{result_data.get('total_attempted', '?')}\n"
-            f"Message: {result_data.get('message', 'No message')}"
+        status = (
+            f"Submission successful!\n"
+            f"User: {result.get('username')}\n"
+            f"Score: {result.get('score')}%\n"
+            f"Correct: {result.get('correct_count')}/{result.get('total_attempted')}\n"
+            f"Message: {result.get('message')}"
         )
         
-        print("="*60)
-        print(final_status)
-        print("="*60)
-        
-        results_df = pd.DataFrame(results_log)
-        return final_status, results_df
-        
+        return status, pd.DataFrame(results)
+    
     except Exception as e:
-        error_msg = f"❌ Submission Failed: {e}"
-        print(error_msg)
-        results_df = pd.DataFrame(results_log)
-        return error_msg, results_df
-
+        return f"Submission failed: {e}", pd.DataFrame(results)
 
-# --- Gradio Interface ---
-with gr.Blocks(theme=gr.themes.Soft()) as demo:
-    gr.Markdown("# 🤖 smolagents Exam Runner")
-    gr.Markdown(
-        """
-        ### Instructions:
-        1. **Log in** with your Hugging Face account (button below)
-        2. **Click** "Run Evaluation & Submit All Answers"
-        3. **Wait** - This takes several minutes as the agent answers each question
-        4. **View** your score and answers
-        
-        ---
-        
-        ⚠️ **Note:** The agent uses web search and code execution to answer questions.
-        This may take 5-10 minutes to complete all questions.
-        """
-    )
 
+# Gradio UI
+with gr.Blocks() as demo:
+    gr.Markdown("# My Agent Evaluation")
+    gr.Markdown("Login and click the button to run the evaluation.")
+    
     gr.LoginButton()
-
-    run_button = gr.Button(
-        "🚀 Run Evaluation & Submit All Answers",
-        variant="primary",
-        size="lg"
-    )
-
-    status_output = gr.Textbox(
-        label="📊 Status & Results",
-        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]
-    )
-
-    gr.Markdown(
-        """
-        ---
-        **Tips:**
-        - The agent searches the web for answers
-        - Some questions require data analysis or file processing
-        - Answers are submitted automatically after completion
-        """
-    )
-
-
-if __name__ == "__main__":
-    print("\n" + "="*70)
-    print(" " * 20 + "🚀 SMOLAGENTS EXAM RUNNER")
-    print("="*70)
+    run_btn = gr.Button("Run Evaluation & Submit")
     
-    # Check environment variables
-    space_host = os.getenv("SPACE_HOST")
-    space_id = os.getenv("SPACE_ID")
-
-    if space_host:
-        print(f"✅ SPACE_HOST: {space_host}")
-        print(f"   Runtime URL: https://{space_host}.hf.space")
-    else:
-        print("ℹ️  SPACE_HOST not found (running locally?)")
-
-    if space_id:
-        print(f"✅ SPACE_ID: {space_id}")
-        print(f"   Repo: https://huggingface.co/spaces/{space_id}")
-    else:
-        print("ℹ️  SPACE_ID not found (running locally?)")
-
-    print("="*70 + "\n")
-    print("🎬 Launching Gradio Interface...\n")
+    status = gr.Textbox(label="Status", lines=5)
+    table = gr.DataFrame(label="Results", wrap=True)
     
-    demo.launch(debug=True, share=False)
+    run_btn.click(fn=run_and_submit_all, outputs=[status, table])
+
+if __name__ == "__main__":
+    print("Starting app...")
+    demo.launch()