Update app.py

app.py

@@ -3,36 +3,52 @@ import gradio as gr
 import requests
 import pandas as pd
 
-from agent import create_agent, fetch_random_question
+from smolagents import CodeAgent, OpenAIServerModel
+from tools import FinalAnswerTool
 
+# --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
+class BasicAgent:
+    def __init__(self):
+    
+        model = OpenAIServerModel(model_id="gpt-4o")
+        final_tool = FinalAnswerTool()
+        self.agent = CodeAgent(
+            model=model,
+            tools=[final_tool],
+            # opzioni aggiuntive, se vuoi:
+            max_steps=3,
+            verbosity_level=1
+        )
+
+    def __call__(self, question: str) -> str:
+  
+        return self.agent.run(question)
+
 def run_and_submit_all(profile):
+    space_id = os.getenv("SPACE_ID")
     if not profile:
         return "Please login to Hugging Face with the login button.", None
     username = getattr(profile, "username", None) or getattr(profile, "name", None)
     if not username:
         return "Login error: username not found.", None
 
-    # Fetch questions
+    # 1) Fetch questions
     try:
-        qs = requests.get(f"{DEFAULT_API_URL}/questions", timeout=15)
-        qs.raise_for_status()
-        questions = qs.json()
+        resp = requests.get(f"{DEFAULT_API_URL}/questions", timeout=15)
+        resp.raise_for_status()
+        questions = resp.json()
     except Exception as e:
         return f"Error fetching questions: {e}", None
 
-    # Instantiate agent
-    agent = create_agent()
-
-    # Run and collect answers
+    # 2) Run agent
+    agent = BasicAgent()
     results, payload = [], []
     for q in questions:
-        tid, text = q.get("task_id"), q.get("question")
-        if not (tid and text):
-            continue
+        tid, text = q["task_id"], q["question"]
         try:
-            ans = agent.run(text)   # <-- positional!
+            ans = agent(text)
         except Exception as e:
             ans = f"ERROR: {e}"
         results.append({"Task ID": tid, "Question": text, "Answer": ans})
@@ -41,20 +57,21 @@ def run_and_submit_all(profile):
     if not payload:
         return "Agent returned no answers.", pd.DataFrame(results)
 
-    # Submit
+    # 3) Submit
     submission = {
         "username": username,
-        "agent_code": f"https://huggingface.co/spaces/{os.getenv('SPACE_ID')}/tree/main",
+        "agent_code": f"https://huggingface.co/spaces/{space_id}/tree/main",
         "answers": payload
     }
     try:
-        resp = requests.post(f"{DEFAULT_API_URL}/submit", json=submission, timeout=60)
-        resp.raise_for_status()
-        data = resp.json()
+        sub_resp = requests.post(f"{DEFAULT_API_URL}/submit", json=submission, timeout=60)
+        sub_resp.raise_for_status()
+        data = sub_resp.json()
         status = (
             f"Submission Successful!\n"
             f"User: {data['username']}\n"
-            f"Score: {data['score']}% ({data['correct_count']}/{data['total_attempted']})\n"
+            f"Score: {data['score']}% "
+            f"({data['correct_count']}/{data['total_attempted']})\n"
             f"Message: {data['message']}"
         )
     except Exception as e:
@@ -62,27 +79,25 @@ def run_and_submit_all(profile):
 
     return status, pd.DataFrame(results)
 
-
 def test_random_question(profile):
     if not profile:
         return "Please login to Hugging Face with the login button.", ""
-    q = fetch_random_question()
-    agent = create_agent()
-    # Positional call again
-    answer = agent.run(q["question"])
-    return q["question"], answer
-
+    try:
+        q = requests.get(f"{DEFAULT_API_URL}/random-question", timeout=15).json()
+        ans = BasicAgent()(q["question"])
+        return q["question"], ans
+    except Exception as e:
+        return f"Error during test: {e}", ""
 
+# --- Gradio UI ---
 with gr.Blocks() as demo:
-    gr.Markdown("# SmolAgent Evaluation Runner")
-    gr.Markdown(
-        """
-        **Instructions:**
-        1. Clone this space and define your agent logic in `agent.py`.
-        2. Log in with your Hugging Face account using the login button below.
-        3. Use **Run Evaluation & Submit All Answers** or **Test Random Question**.
-        """
-    )
+    gr.Markdown("# Basic Agent Evaluation Runner")
+    gr.Markdown("""
+**Instructions:**
+1. Clone this space and define your agent in `tools.py`.
+2. Log in with your HF account.
+3. Use **Run Evaluation & Submit All Answers** or **Test Random Question**.
+""")
 
     login = gr.LoginButton()
     run_btn = gr.Button("Run Evaluation & Submit All Answers")
@@ -93,8 +108,8 @@ with gr.Blocks() as demo:
     question_out = gr.Textbox(label="Random Question", lines=3, interactive=False)
     answer_out = gr.Textbox(label="Agent Answer", lines=3, interactive=False)
 
-    run_btn.click(fn=run_and_submit_all, inputs=[login], outputs=[status_out, table_out])
-    test_btn.click(fn=test_random_question, inputs=[login], outputs=[question_out, answer_out])
+    run_btn.click(run_and_submit_all, inputs=[login], outputs=[status_out, table_out])
+    test_btn.click(test_random_question, inputs=[login], outputs=[question_out, answer_out])
 
 if __name__ == "__main__":
     demo.launch(debug=True, share=False)