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import os
import gradio as gr
import requests
import pandas as pd
from tools import FinalAnswerTool
from smolagents import CodeAgent, OpenAIServerModel
# --- Constants ---
DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
class BasicAgent:
def __init__(self):
# Use GPT-4o; ensure your API key has access
model = OpenAIServerModel(model_id="gpt-4o")
final_tool = FinalAnswerTool()
self.agent = CodeAgent(
model=model,
tools=[final_tool],
max_steps=3,
verbosity_level=1
)
def __call__(self, question: str) -> str:
return self.agent.run(question)
def run_and_submit_all(profile):
# Extract username
username = None
if profile:
if isinstance(profile, dict):
username = profile.get('username') or profile.get('name') or profile.get('login') or profile.get('id')
else:
username = getattr(profile, 'username', None) or getattr(profile, 'name', None)
if not username:
return "Please login to Hugging Face with the login button.", None
# Fetch questions
try:
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
# Run agent
agent = BasicAgent()
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(text)
except Exception as e:
ans = f"ERROR: {e}"
results.append({'Task ID': tid, 'Question': text, 'Answer': ans})
payload.append({'task_id': tid, 'submitted_answer': ans})
if not payload:
return "Agent returned no answers.", pd.DataFrame(results)
# Submit
submission = {
'username': username,
'agent_code': f"https://huggingface.co/spaces/{os.getenv('SPACE_ID')}/tree/main",
'answers': payload
}
try:
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.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:
status = f"Submission Failed: {e}"
return status, pd.DataFrame(results)
def test_random_question(profile):
username = None
if profile:
if isinstance(profile, dict):
username = profile.get('username') or profile.get('name')
else:
username = getattr(profile, 'username', None) or getattr(profile, 'name', None)
if not username:
return "Please login to Hugging Face with the login button.", ""
try:
q = requests.get(f"{DEFAULT_API_URL}/random-question", timeout=15).json()
ans = BasicAgent()(q.get('question', ''))
return q.get('question', ''), ans
except Exception as e:
return f"Error during test: {e}", ""
# --- Gradio UI ---
with gr.Blocks() as demo:
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 Hugging Face account.
3. Use **Run Evaluation & Submit All Answers** or **Test Random Question**.
"""
)
login = gr.LoginButton()
run_btn = gr.Button("Run Evaluation & Submit All Answers")
test_btn = gr.Button("Test Random Question")
status_out = gr.Textbox(label="Status / Result", lines=5, interactive=False)
table_out = gr.DataFrame(label="Full Results Table", wrap=True)
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])
if __name__ == "__main__":
demo.launch(debug=True, share=False)
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