Update app.py

app.py

@@ -2,23 +2,18 @@ import os
 import gradio as gr
 import requests
 import pandas as pd
+import spaces
 from smolagents import CodeAgent, DuckDuckGoSearchTool, VisitWebpageTool, InferenceClientModel
 
-# --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
-# --- Agent Definition ---
 class GaiaAgent:
     def __init__(self):
         print("Initializing GaiaAgent...")
-        
-        # Modello HF via API
         self.model = InferenceClientModel(
             model_id="Qwen/Qwen2.5-Coder-32B-Instruct",
             token=os.getenv("HF_TOKEN"),
         )
-        
-        # Tool
         self.agent = CodeAgent(
             tools=[
                 DuckDuckGoSearchTool(),
@@ -31,33 +26,30 @@ class GaiaAgent:
         print("GaiaAgent ready!")
 
     def __call__(self, question: str) -> str:
-        print(f"Question: {question[:100]}...")
-        
-        # Prompt che forza risposta pulita — fondamentale per exact match
-        prompt = f"""Answer the following question. 
-Your answer must be as concise as possible — just the final answer, no explanation, no punctuation unless required.
+        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)
-            answer = str(response).strip()
-            print(f"Answer: {answer}")
-            return answer
+            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)
 
 def run_and_submit_all(profile: gr.OAuthProfile | None):
     space_id = os.getenv("SPACE_ID")
 
     if profile:
         username = f"{profile.username}"
-        print(f"User logged in: {username}")
     else:
         return "Please Login to Hugging Face with the button.", None
 
@@ -65,7 +57,6 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
     questions_url = f"{api_url}/questions"
     submit_url = f"{api_url}/submit"
 
-    # 1. Inizializza agente
     try:
         agent = GaiaAgent()
     except Exception as e:
@@ -73,7 +64,6 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
 
     agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
 
-    # 2. Fetch domande
     try:
         response = requests.get(questions_url, timeout=15)
         response.raise_for_status()
@@ -82,7 +72,6 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
     except Exception as e:
         return f"Error fetching questions: {e}", None
 
-    # 3. Esegui agente su ogni domanda
     results_log = []
     answers_payload = []
 
@@ -92,7 +81,7 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
         if not task_id or question_text is None:
             continue
         try:
-            submitted_answer = agent(question_text)
+            submitted_answer = run_agent_on_question(agent, question_text)
             answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
             results_log.append({
                 "Task ID": task_id,
@@ -109,7 +98,6 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
     if not answers_payload:
         return "Agent did not produce any answers.", pd.DataFrame(results_log)
 
-    # 4. Submit
     submission_data = {
         "username": username.strip(),
         "agent_code": agent_code,
@@ -132,14 +120,12 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
         return f"Submission Failed: {e}", pd.DataFrame(results_log)
 
 
-# --- Gradio Interface ---
 with gr.Blocks() as demo:
     gr.Markdown("# 🎩 GAIA Agent — sofials")
     gr.Markdown("""
     **Instructions:**
     1. Log in with your Hugging Face account
     2. Click 'Run Evaluation & Submit All Answers'
-    3. Wait for the agent to answer all questions (may take several minutes)
     """)
 
     gr.LoginButton()