Update app.py

app.py

@@ -2,48 +2,40 @@ import os
 import gradio as gr
 import requests
 import pandas as pd
-import spaces
 from smolagents import CodeAgent, DuckDuckGoSearchTool, VisitWebpageTool, InferenceClientModel
 
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
-class GaiaAgent:
-    def __init__(self):
-        print("Initializing GaiaAgent...")
-        self.model = InferenceClientModel(
-            model_id="Qwen/Qwen2.5-Coder-32B-Instruct",
-            token=os.getenv("HF_TOKEN"),
-        )
-        self.agent = CodeAgent(
-            tools=[
-                DuckDuckGoSearchTool(),
-                VisitWebpageTool(),
-            ],
-            model=self.model,
-            max_steps=10,
-            additional_authorized_imports=["math", "datetime", "re", "json"],
-        )
-        print("GaiaAgent ready!")
+def build_agent():
+    model = InferenceClientModel(
+        model_id="Qwen/Qwen2.5-Coder-32B-Instruct",
+        token=os.getenv("HF_TOKEN"),
+    )
+    agent = CodeAgent(
+        tools=[
+            DuckDuckGoSearchTool(),
+            VisitWebpageTool(),
+        ],
+        model=model,
+        max_steps=10,
+        additional_authorized_imports=["math", "datetime", "re", "json"],
+    )
+    return agent
 
-    def __call__(self, question: str) -> str:
-        prompt = f"""Answer the following question.
+def run_agent(agent, question: str) -> str:
+    prompt = f"""Answer the following question.
 Your answer must be as concise as possible — just the final answer, no explanation.
 If the answer is a number, return just the number.
 If the answer is a name, return just the name.
 If the answer is a list, return comma-separated values.
 
 Question: {question}"""
-        try:
-            response = self.agent.run(prompt)
-            return str(response).strip()
-        except Exception as e:
-            print(f"Error: {e}")
-            return "I don't know"
-
-# Funzione con decoratore GPU — obbligatorio per ZeroGPU
-@spaces.GPU
-def run_agent_on_question(agent, question):
-    return agent(question)
+    try:
+        response = agent.run(prompt)
+        return str(response).strip()
+    except Exception as e:
+        print(f"Error: {e}")
+        return "I don't know"
 
 def run_and_submit_all(profile: gr.OAuthProfile | None):
     space_id = os.getenv("SPACE_ID")
@@ -58,7 +50,8 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
     submit_url = f"{api_url}/submit"
 
     try:
-        agent = GaiaAgent()
+        agent = build_agent()
+        print("Agent initialized!")
     except Exception as e:
         return f"Error initializing agent: {e}", None
 
@@ -81,22 +74,22 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
         if not task_id or question_text is None:
             continue
         try:
-            submitted_answer = run_agent_on_question(agent, question_text)
+            submitted_answer = run_agent(agent, question_text)
             answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
             results_log.append({
                 "Task ID": task_id,
                 "Question": question_text[:100],
                 "Submitted Answer": submitted_answer
             })
+            print(f"✅ {task_id}: {submitted_answer[:50]}")
         except Exception as e:
+            print(f"❌ {task_id}: {e}")
             results_log.append({
                 "Task ID": task_id,
                 "Question": question_text[:100],
-                "Submitted Answer": f"ERROR: {e}"
+                "Submitted Answer": "I don't know"
             })
-
-    if not answers_payload:
-        return "Agent did not produce any answers.", pd.DataFrame(results_log)
+            answers_payload.append({"task_id": task_id, "submitted_answer": "I don't know"})
 
     submission_data = {
         "username": username.strip(),