Update app.py

app.py

@@ -2,111 +2,170 @@ import os
 import gradio as gr
 import requests
 import pandas as pd
+
 from smolagents import CodeAgent, DuckDuckGoSearchTool
 from smolagents.models import OpenAIServerModel
 
-# Constants
+# System prompt as per your instructions
+SYSTEM_PROMPT = """You are a general AI assistant. I will ask you a question.
+Report your thoughts, and finish your answer with the following template:
+FINAL ANSWER: [YOUR FINAL ANSWER].
+YOUR FINAL ANSWER should be a number OR as few words as possible OR a comma separated list 
+of numbers and/or strings. If you are asked for a number, don't use comma to write your number neither use units such as $ or percent sign unless specified otherwise. If you are asked for a string, don't use articles, neither abbreviations (e.g. for cities), and write the digits in plain text unless specified otherwise. If you are asked for a comma separated list, apply the above rules depending of whether the element to be put in the list is a number or a string."""
+
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
-# === Define the Smol Agent ===
 class MyAgent:
     def __init__(self):
-        self.model = OpenAIServerModel(model_id="gpt-4")  # or "gpt-3.5-turbo"
+        # Initialize model with system prompt
+        self.model = OpenAIServerModel(
+            model_id="gpt-4",
+            system_message=SYSTEM_PROMPT
+        )
         self.agent = CodeAgent(
             tools=[DuckDuckGoSearchTool()],
-            model=self.model,
-            system_message="""You are a general AI assistant. I will ask you a question.
-Report your thoughts, and finish your answer with the following template:
-FINAL ANSWER: [YOUR FINAL ANSWER].
-YOUR FINAL ANSWER should be a number OR as few words as possible OR a comma separated list 
-of numbers and/or strings. If you are asked for a number, don't use comma to write your number neither use units such as $ or percent sign unless specified otherwise. If you are asked for a string, don't use articles, neither abbreviations (e.g. for cities), and write the digits in plain text unless specified otherwise. If you are asked for a comma separated list, apply the above rules depending of whether the element to be put in the list is a number or a string."""
+            model=self.model
         )
 
     def __call__(self, question: str) -> str:
+        # Run agent on the question
         return self.agent.run(question)
 
-# === Submission Logic ===
 def run_and_submit_all(profile: gr.OAuthProfile | None):
+    """
+    Fetches questions, runs the agent, submits answers, returns status and results table.
+    """
     space_id = os.getenv("SPACE_ID")
+
     if profile:
         username = profile.username
         print(f"User logged in: {username}")
     else:
+        print("User not logged in.")
         return "Please Login to Hugging Face with the button.", None
 
-    agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
-    questions_url = f"{DEFAULT_API_URL}/questions"
-    submit_url = f"{DEFAULT_API_URL}/submit"
+    api_url = DEFAULT_API_URL
+    questions_url = f"{api_url}/questions"
+    submit_url = f"{api_url}/submit"
 
     try:
         agent = MyAgent()
     except Exception as e:
+        print(f"Error initializing agent: {e}")
         return f"Error initializing agent: {e}", None
 
-    # Fetch Questions
+    agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
+    print(f"Agent code URL: {agent_code}")
+
+    print(f"Fetching questions from: {questions_url}")
     try:
-        res = requests.get(questions_url, timeout=15)
-        res.raise_for_status()
-        questions_data = res.json()
+        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 Exception as e:
-        return f"Failed to fetch questions: {e}", None
+        print(f"Error fetching questions: {e}")
+        return f"Error fetching questions: {e}", None
 
     results_log = []
     answers_payload = []
-
+    print(f"Running agent on {len(questions_data)} questions...")
     for item in questions_data:
         task_id = item.get("task_id")
-        question = item.get("question")
-        if not task_id or question is None:
+        question_text = item.get("question")
+        if not task_id or question_text is None:
+            print(f"Skipping invalid item: {item}")
             continue
         try:
-            answer = agent(question)
-            results_log.append({"Task ID": task_id, "Question": question, "Submitted Answer": answer})
-            answers_payload.append({"task_id": task_id, "submitted_answer": answer})
+            submitted_answer = agent(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})
         except Exception as e:
-            results_log.append({"Task ID": task_id, "Question": question, "Submitted Answer": f"ERROR: {e}"})
+            print(f"Error running agent on task {task_id}: {e}")
+            results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": f"AGENT ERROR: {e}"})
 
     if not answers_payload:
-        return "No answers generated.", pd.DataFrame(results_log)
-
-    submission_data = {
-        "username": username,
-        "agent_code": agent_code,
-        "answers": answers_payload
-    }
+        print("Agent did not produce any answers to submit.")
+        return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
 
+    submission_data = {"username": username.strip(), "agent_code": agent_code, "answers": answers_payload}
+    print(f"Submitting {len(answers_payload)} answers to: {submit_url}")
     try:
-        res = requests.post(submit_url, json=submission_data, timeout=60)
-        res.raise_for_status()
-        result_data = res.json()
-        summary = (
+        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"Score: {result_data.get('score', '?')}% "
-            f"({result_data.get('correct_count', '?')}/{result_data.get('total_attempted', '?')})\n"
-            f"Message: {result_data.get('message', '')}"
+            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.')}"
         )
-        return summary, pd.DataFrame(results_log)
+        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 Exception:
+            error_detail += f" Response: {e.response.text[:500]}"
+        status_message = f"Submission Failed: {error_detail}"
+        print(status_message)
+        return status_message, pd.DataFrame(results_log)
+    except requests.exceptions.Timeout:
+        status_message = "Submission Failed: The request timed out."
+        print(status_message)
+        return status_message, pd.DataFrame(results_log)
     except Exception as e:
-        return f"Submission failed: {e}", pd.DataFrame(results_log)
+        status_message = f"An unexpected error occurred during submission: {e}"
+        print(status_message)
+        return status_message, pd.DataFrame(results_log)
 
-# === Gradio UI ===
 with gr.Blocks() as demo:
-    gr.Markdown("# Agent Evaluation Runner (SmolAgents)")
-    gr.Markdown("""
-**Instructions:**
-1. Clone this space and customize your agent.
-2. Log in with Hugging Face.
-3. Click 'Run Evaluation' to answer and submit.
-""")
+    gr.Markdown("# Basic Agent Evaluation Runner")
+    gr.Markdown(
+        """
+        **Instructions:**
+        1. Clone this space, modify code to define your agent's logic, tools, and packages.
+        2. Log in to your Hugging Face account using the button below.
+        3. Click 'Run Evaluation & Submit All Answers' to fetch questions, run your agent, submit answers, and see your score.
+        
+        **Note:** Submitting can take some time.
+        """
+    )
 
     gr.LoginButton()
     run_button = gr.Button("Run Evaluation & Submit All Answers")
-    status_output = gr.Textbox(label="Status", lines=4, interactive=False)
-    results_table = gr.DataFrame(label="Results", wrap=True)
+
+    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.click(fn=run_and_submit_all, outputs=[status_output, results_table])
 
 if __name__ == "__main__":
-    print("Launching...")
-    demo.launch(debug=True)
+    print("\n" + "-"*30 + " App Starting " + "-"*30)
+    space_host = os.getenv("SPACE_HOST")
+    space_id = os.getenv("SPACE_ID")
+
+    if space_host:
+        print(f"✅ SPACE_HOST found: {space_host}")
+        print(f"   Runtime URL should be: https://{space_host}.hf.space")
+    else:
+        print("ℹ️  SPACE_HOST environment variable not found (running locally?).")
+
+    if space_id:
+        print(f"✅ SPACE_ID found: {space_id}")
+        print(f"   Repo URL: https://huggingface.co/spaces/{space_id}")
+        print(f"   Repo Tree URL: https://huggingface.co/spaces/{space_id}/tree/main")
+    else:
+        print("ℹ️  SPACE_ID environment variable not found (running locally?).")
+
+    print("-"*(60 + len(" App Starting ")) + "\n")
+
+    print("Launching Gradio Interface for Basic Agent Evaluation...")
+    demo.launch(debug=True, share=False)