Spaces:
Sleeping
Sleeping
import os | |
import gradio as gr | |
import requests | |
import pandas as pd | |
from smolagents import CodeAgent, DuckDuckGoSearchTool, OpenAIServerModel | |
# --- Constants --- | |
DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space" | |
# --- Enhanced Agent Definition --- | |
class GAIAAgent: | |
def __init__(self): | |
print("GAIAAgent initialized.") | |
model = OpenAIServerModel(model_id="gpt-4o") | |
search_tool = DuckDuckGoSearchTool() | |
self.agent = CodeAgent(model=model, tools=[search_tool]) | |
def format_prompt(self, question: str, file_content: str = None) -> str: | |
prompt = ( | |
"You are a helpful AI agent solving a question from the GAIA benchmark. " | |
"Respond only with the final answer." | |
) | |
if file_content: | |
prompt += f"\nAttached File Content:\n{file_content}\n" | |
prompt += f"\nQuestion: {question}\nAnswer:" | |
return prompt | |
def read_file(self, filename: str) -> str: | |
filepath = os.path.join("./", filename) | |
if filename.endswith(".txt") and os.path.exists(filepath): | |
with open(filepath, "r") as file: | |
return file.read()[:1000] # limit to 1000 chars | |
return "" | |
def __call__(self, question: str, file_name: str = None) -> str: | |
file_content = self.read_file(file_name) if file_name else None | |
prompt = self.format_prompt(question, file_content) | |
result = self.agent.run(prompt) | |
return result.strip() | |
def run_and_submit_all(profile: gr.OAuthProfile | None): | |
space_id = os.getenv("SPACE_ID") | |
if profile: | |
username = f"{profile.username}" | |
print(f"User logged in: {username}") | |
else: | |
print("User not logged in.") | |
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 = GAIAAgent() | |
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") | |
file_name = item.get("file_name") | |
if not task_id or question_text is None: | |
continue | |
try: | |
submitted_answer = agent(question_text, file_name) | |
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}"}) | |
if not answers_payload: | |
return "Agent did not produce any answers to submit.", pd.DataFrame(results_log) | |
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"Overall Score: {result_data.get('score', 'N/A')}% " | |
f"({result_data.get('correct_count', '?')}/{result_data.get('total_attempted', '?')} correct)\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("# GAIA Agent Evaluation Runner") | |
gr.Markdown(""" | |
**Instructions:** | |
1. Log in to your Hugging Face account. | |
2. Click the button to run the agent and submit answers. | |
3. Your score will be printed below. | |
""") | |
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", wrap=True) | |
run_button.click( | |
fn=run_and_submit_all, | |
outputs=[status_output, results_table] | |
) | |
if __name__ == "__main__": | |
print("Launching GAIA agent app...") | |
demo.launch(debug=True, share=False) | |