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import os
import gradio as gr
import requests
import pandas as pd
from transformers.tools import HfAgent
DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
class SmartAgent:
def __init__(self):
self.agent = HfAgent("https://api-inference.huggingface.co/chat/agent")
print("SmartAgent initialized with Hugging Face tools.")
def __call__(self, question: str) -> str:
print(f"[SmartAgent] Received question: {question[:100]}")
try:
result = self.agent.run(question)
print(f"[SmartAgent] Agent result: {result}")
return str(result)
except Exception as e:
print(f"[SmartAgent] Error: {e}")
return f"Agent error: {e}"
def run_and_submit_all(profile: gr.OAuthProfile | None):
space_id = os.getenv("SPACE_ID")
if profile:
username = f"{profile.username}"
else:
return "Please Login to Hugging Face with the button.", None
api_url = DEFAULT_API_URL
questions_url = f"{api_url}/questions"
submit_url = f"{api_url}/submit"
try:
agent = SmartAgent()
except Exception as e:
return f"Error initializing agent: {e}", None
agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
try:
response = requests.get(questions_url, timeout=15)
response.raise_for_status()
questions_data = response.json()
except Exception as e:
return f"Error fetching questions: {e}", None
results_log = []
answers_payload = []
for item in questions_data:
task_id = item.get("task_id")
question_text = item.get("question")
if not task_id or question_text is None:
continue
try:
submitted_answer = agent(question_text)
answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": submitted_answer})
except Exception as e:
results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": f"AGENT ERROR: {e}"})
submission_data = {
"username": username.strip(),
"agent_code": agent_code,
"answers": answers_payload
}
try:
response = requests.post(submit_url, json=submission_data, timeout=60)
response.raise_for_status()
result_data = response.json()
final_status = (
f"Submission Successful!\n"
f"User: {result_data.get('username')}\n"
f"Score: {result_data.get('score', 'N/A')}%\n"
f"Correct: {result_data.get('correct_count', '?')}/{result_data.get('total_attempted', '?')}\n"
f"Message: {result_data.get('message', 'No message received.')}"
)
return final_status, pd.DataFrame(results_log)
except Exception as e:
return f"Submission failed: {e}", pd.DataFrame(results_log)
with gr.Blocks() as demo:
gr.Markdown("# Smart AI Agent (Web, Image, Video, and QA Support)")
gr.Markdown("""
This agent can:
- Answer complex questions
- Perform web searches
- Explain images or videos from URLs
Please login and run the evaluation to test the agent.
""")
gr.LoginButton()
run_button = gr.Button("Run Evaluation & Submit All Answers")
status_output = gr.Textbox(label="Run Status / Submission Result", lines=5, interactive=False)
results_table = gr.DataFrame(label="Questions and Agent Answers")
run_button.click(fn=run_and_submit_all, outputs=[status_output, results_table])
if __name__ == "__main__":
demo.launch(debug=True, share=False)
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