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import os
import gradio as gr
import requests
import pandas as pd
from agent import create_agent, fetch_random_question
# --- Constants ---
DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
def run_and_submit_all(profile: gr.OAuthProfile | None):
"""
Fetch all questions, run the SmolAgent on them, submit all answers,
and display the results.
"""
space_id = os.getenv("SPACE_ID")
if profile:
username = profile.username
print(f"User logged in: {username}")
else:
print("User not logged in.")
return "Please login to Hugging Face with the button.", None
questions_url = f"{DEFAULT_API_URL}/questions"
submit_url = f"{DEFAULT_API_URL}/submit"
try:
agent = create_agent()
print("SmolAgent initialized.")
except Exception as e:
print(f"Error instantiating agent: {e}")
return f"Error initializing agent: {e}", None
agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
print(f"Agent code URL: {agent_code}")
try:
response = requests.get(questions_url, timeout=15)
response.raise_for_status()
questions = response.json()
if not questions:
return "No questions fetched.", None
print(f"Fetched {len(questions)} questions.")
except Exception as e:
print(f"Error fetching questions: {e}")
return f"Error fetching questions: {e}", None
results = []
payload = []
for q in questions:
tid = q.get("task_id")
text = q.get("question")
if not tid or not text:
continue
try:
ans = agent.run(question=text)
except Exception as e:
ans = f"ERROR: {e}"
payload.append({"task_id": tid, "submitted_answer": ans})
results.append({"Task ID": tid, "Question": text, "Answer": ans})
if not payload:
return "Agent returned no answers.", pd.DataFrame(results)
submission = {"username": username, "agent_code": agent_code, "answers": payload}
try:
resp = requests.post(submit_url, json=submission, timeout=60)
resp.raise_for_status()
data = resp.json()
status = (
f"Submission Successful!\n"
f"User: {data.get('username')}\n"
f"Score: {data.get('score')}% ({data.get('correct_count')}/{data.get('total_attempted')})\n"
f"Message: {data.get('message')}"
)
except Exception as e:
print(f"Submission error: {e}")
status = f"Submission Failed: {e}"
return status, pd.DataFrame(results)
def test_random_question(profile: gr.OAuthProfile | None):
"""
Fetch a random GAIA question and return the agent's answer.
"""
if not profile:
return "Please login to test.", ""
try:
q = fetch_random_question()
agent = create_agent()
ans = agent.run(question=q.get("question", ""))
return q.get("question", ""), ans
except Exception as e:
print(f"Test error: {e}")
return f"Error: {e}", ""
# --- Gradio Interface ---
with gr.Blocks() as demo:
gr.Markdown("# SmolAgent Evaluation Runner")
gr.Markdown(
"""
**Istruzioni:**
1. Clone questo space e definisci la logica in agent.py.
2. Effettua il login con il tuo account Hugging Face.
3. Usa 'Run Evaluation & Submit All Answers' o 'Test Random Question'.
"""
)
login = gr.LoginButton()
run_all = gr.Button("Run Evaluation & Submit All Answers")
test = gr.Button("Test Random Question")
status = gr.Textbox(label="Status / Risultato", lines=5, interactive=False)
table = gr.DataFrame(label="Risultati Completi", wrap=True)
qbox = gr.Textbox(label="Domanda Casuale", lines=3, interactive=False)
abox = gr.Textbox(label="Risposta Agente", lines=3, interactive=False)
run_all.click(fn=run_and_submit_all, inputs=[login], outputs=[status, table])
test.click(fn=test_random_question, inputs=[login], outputs=[qbox, abox])
if __name__ == "__main__":
demo.launch(debug=True, share=False)
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