Update app.py

app.py

@@ -1,5 +1,4 @@
 """ Basic Agent Evaluation Runner – invia sempre tutte le risposte """
-
 import os
 import requests
 import gradio as gr
@@ -7,18 +6,16 @@ import pandas as pd
 from langchain_core.messages import HumanMessage
 from agent import build_graph
 
-
 # --- Constants ------------------------------------------------------------ #
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
-
 # --- Agent wrapper -------------------------------------------------------- #
 class BasicAgent:
     """LangGraph agent ready for evaluation."""
     def __init__(self):
         print("BasicAgent initialized (provider=groq).")
         self.graph = build_graph(provider="groq")
-
+    
     def __call__(self, question: str) -> str:
         print(f"Agent received question (first 50 chars): {question[:50]}...")
         msgs = [HumanMessage(content=question)]
@@ -27,7 +24,6 @@ class BasicAgent:
         # rimuove la parte "FINAL ANSWER: "
         return answer[14:]
 
-
 # --- Main evaluation logic ------------------------------------------------ #
 def run_and_submit_all(profile: gr.OAuthProfile | None):
     # 0. Check login
@@ -35,13 +31,13 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
         return "Please Login to Hugging Face with the button.", None
     username = profile.username
     print(f"User logged in: {username}")
-
+    
     # 1. Instantiate agent
     try:
         agent = BasicAgent()
     except Exception as e:
         return f"Error initializing agent: {e}", None
-
+    
     # 2. Fetch questions
     try:
         resp = requests.get(f"{DEFAULT_API_URL}/questions", timeout=15)
@@ -51,21 +47,20 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
             return "Fetched questions list is empty.", None
     except Exception as e:
         return f"Error fetching questions: {e}", None
-
+    
     # 3. Run agent and build payload
     answers_payload = []
     results_log = []
-
     for item in questions_data:
         task_id = item.get("task_id")
         q_text = item.get("question")
-
         submitted_answer = "errore"  # default in caso di failure
+        
         try:
             submitted_answer = agent(q_text)
         except Exception as e:
             print(f"Error running agent on task {task_id}: {e}")
-
+        
         # in ogni caso inseriamo la risposta (successo o errore)
         answers_payload.append(
             {"task_id": task_id, "submitted_answer": submitted_answer}
@@ -77,14 +72,14 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
                 "Submitted Answer": submitted_answer,
             }
         )
-
+    
     # 4. Submit answers
     submission = {
         "username": username,
         "agent_code": f"https://huggingface.co/spaces/{os.getenv('SPACE_ID', '')}/tree/main",
         "answers": answers_payload,
     }
-
+    
     try:
         resp = requests.post(f"{DEFAULT_API_URL}/submit", json=submission, timeout=60)
         resp.raise_for_status()
@@ -97,10 +92,9 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
         )
     except Exception as e:
         status_msg = f"Submission Failed: {e}"
-
+    
     return status_msg, pd.DataFrame(results_log)
 
-
 # --- Gradio UI ------------------------------------------------------------ #
 with gr.Blocks() as demo:
     gr.Markdown("# Basic Agent Evaluation Runner (retry & error-safe)")
@@ -108,7 +102,8 @@ with gr.Blocks() as demo:
     run_btn = gr.Button("Run Evaluation & Submit All Answers")
     status_box = gr.Textbox(lines=5, label="Run Status / Submission Result")
     results_tbl = gr.DataFrame(label="Questions and Agent Answers", wrap=True)
+    
     run_btn.click(fn=run_and_submit_all, outputs=[status_box, results_tbl])
 
 if __name__ == "__main__":
-    demo.launch(debug=True, share=False)
+    demo.launch(debug=True, share=False)