Update app.py

app.py

@@ -3,7 +3,7 @@ import gradio as gr
 import requests
 import pandas as pd
 from smolagents import ToolCallingAgent, tool
-import duckduckgo_search
+from duckduckgo_search import ddg
 import math
 
 # --- Constants ---
@@ -12,11 +12,19 @@ DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 # --- Tools ---
 @tool
 def duck_search(query: str) -> str:
-    """Searches the web using DuckDuckGo and returns a short summary."""
+    """
+    Searches the web using DuckDuckGo and returns a short summary.
+
+    Args:
+        query: The search query string.
+
+    Returns:
+        A string summarizing the top search results.
+    """
     try:
-        results = duckduckgo_search.ddg(query, max_results=3)
+        results = ddg(query, max_results=3)
         if results:
-            return "\n".join([f"{r['title']}: {r['body']}" for r in results])
+            return "\n\n".join([f"{r['title']}: {r['body']}" for r in results])
         else:
             return "No results found."
     except Exception as e:
@@ -24,131 +32,138 @@ def duck_search(query: str) -> str:
 
 @tool
 def calculator(expression: str) -> str:
-    """Safely evaluates basic math expressions."""
+    """
+    Safely evaluates math expressions using Python's math module.
+
+    Args:
+        expression: A valid math expression as a string (e.g., 'sqrt(16) + 10').
+
+    Returns:
+        The result of the evaluated expression or an error message.
+    """
     try:
         result = eval(expression, {"__builtins__": {}}, math.__dict__)
         return str(result)
     except Exception as e:
         return f"Calculation error: {e}"
 
-# --- Agent Definition ---
+# --- Agent Wrapper ---
 class WebSearchAgent:
     def __init__(self):
         self.agent = ToolCallingAgent(
             name="GAIAWebToolAgent",
-            description="An agent that answers questions using reasoning and tools like web search and calculator.",
+            description="Agent that answers questions using web search and calculator tools.",
             tools=[duck_search, calculator],
             step_limit=5,
-            system_prompt="You're a helpful agent tasked with answering general questions using reasoning and external tools if needed. Prioritize factual accuracy, logic, and concise answers."
+            system_prompt=(
+                "You're a helpful reasoning agent. Use available tools like web search "
+                "and calculator to answer the user's question accurately and concisely."
+            ),
         )
-        print("✅ WebSearchAgent initialized.")
+        print("✅ Agent initialized.")
 
     def __call__(self, question: str) -> str:
-        print(f"🔍 Agent received: {question}")
+        print(f"🔍 Question: {question}")
         try:
             return self.agent.run(question)
         except Exception as e:
-            print(f"❌ Error: {e}")
+            print(f"❌ Agent error: {e}")
             return f"Error: {e}"
 
-# --- Main Evaluation Logic ---
+# --- Evaluation and Submission ---
 def run_and_submit_all(profile: gr.OAuthProfile | None):
     space_id = os.getenv("SPACE_ID")
     if profile:
         username = profile.username
-        print(f"User logged in: {username}")
+        print(f"👤 User: {username}")
     else:
-        return "Please login to Hugging Face first.", None
+        return "Please login to Hugging Face.", None
 
     agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
-    api_url = DEFAULT_API_URL
-    questions_url = f"{api_url}/questions"
-    submit_url = f"{api_url}/submit"
+    questions_url = f"{DEFAULT_API_URL}/questions"
+    submit_url = f"{DEFAULT_API_URL}/submit"
 
     try:
         agent = WebSearchAgent()
     except Exception as e:
-        return f"Agent init error: {e}", None
+        return f"Agent initialization error: {e}", None
 
     try:
         print("📥 Fetching questions...")
         response = requests.get(questions_url, timeout=15)
         response.raise_for_status()
-        questions_data = response.json()
-        if not questions_data:
-            return "Fetched questions list is empty or invalid format.", None
-        print(f"✅ Fetched {len(questions_data)} questions.")
+        questions = response.json()
+        if not questions:
+            return "No questions received.", None
+        print(f"✅ Retrieved {len(questions)} questions.")
     except Exception as e:
-        return f"Error fetching questions: {e}", None
+        return f"Failed to fetch questions: {e}", None
 
-    answers_payload = []
     results_log = []
-    print("🚀 Running agent on questions...")
-    for item in questions_data:
+    answers_payload = []
+
+    for item in questions:
         task_id = item.get("task_id")
-        question_text = item.get("question")
-        if not task_id or not question_text:
+        question = item.get("question")
+        if not task_id or not question:
             continue
         try:
-            submitted_answer = agent(question_text)
-            answers_payload.append({
-                "task_id": task_id,
-                "submitted_answer": submitted_answer
-            })
+            answer = agent(question)
             results_log.append({
                 "Task ID": task_id,
-                "Question": question_text,
-                "Submitted Answer": submitted_answer
+                "Question": question,
+                "Submitted Answer": answer
+            })
+            answers_payload.append({
+                "task_id": task_id,
+                "submitted_answer": answer
             })
         except Exception as e:
             error_msg = f"Agent error: {e}"
-            print(error_msg)
             results_log.append({
                 "Task ID": task_id,
-                "Question": question_text,
+                "Question": question,
                 "Submitted Answer": error_msg
             })
 
     if not answers_payload:
-        return "No answers to submit.", pd.DataFrame(results_log)
+        return "No answers were generated.", pd.DataFrame(results_log)
 
     print("📤 Submitting answers...")
-    submission_data = {
-        "username": username.strip(),
-        "agent_code": agent_code,
-        "answers": answers_payload
-    }
-
     try:
-        response = requests.post(submit_url, json=submission_data, timeout=60)
+        response = requests.post(submit_url, json={
+            "username": username.strip(),
+            "agent_code": agent_code,
+            "answers": answers_payload
+        }, timeout=60)
         response.raise_for_status()
         result = response.json()
-        final_status = (
+        status = (
             f"✅ Submission Successful!\n"
             f"User: {result.get('username')}\n"
             f"Score: {result.get('score', 'N/A')}% "
             f"({result.get('correct_count', '?')}/{result.get('total_attempted', '?')} correct)\n"
-            f"Message: {result.get('message', 'No message.')}"
+            f"Message: {result.get('message', 'No message')}"
         )
-        return final_status, pd.DataFrame(results_log)
+        return status, pd.DataFrame(results_log)
     except Exception as e:
-        return f"Submission error: {e}", pd.DataFrame(results_log)
+        return f"❌ Submission failed: {e}", pd.DataFrame(results_log)
 
 # --- Gradio UI ---
 with gr.Blocks() as demo:
-    gr.Markdown("# 🧠 GAIA Agent with Web Search & Calculator")
+    gr.Markdown("# 🤖 GAIA Agent with Web Search & Calculator Tools")
     gr.Markdown("""
-    1. Log in to Hugging Face.
-    2. Click **Run Evaluation** to fetch, run, and submit.
-    3. Your agent uses web search (DuckDuckGo) and math tools.
+    - ✅ Log in to your Hugging Face account
+    - 🚀 Click the button to run and submit your agent
+    - 🧠 Agent uses DuckDuckGo search + calculator
     """)
     gr.LoginButton()
-    run_button = gr.Button("🚀 Run Evaluation & Submit All Answers")
-    status_output = gr.Textbox(label="Status", lines=5)
-    results_table = gr.DataFrame(label="Answer Log")
+    run_btn = gr.Button("Run Evaluation & Submit All Answers")
+    status_box = gr.Textbox(label="Status", lines=5)
+    result_table = gr.DataFrame(label="Agent Answers")
 
-    run_button.click(fn=run_and_submit_all, outputs=[status_output, results_table])
+    run_btn.click(fn=run_and_submit_all, outputs=[status_box, result_table])
 
 if __name__ == "__main__":
-    print("🌍 Launching App...")
-    demo.launch(debug=True, share=False)
+    print("🚀 Starting Gradio App...")
+    demo.launch(debug=True, share=False)