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import os | |
import gradio as gr | |
import pandas as pd | |
import traceback | |
from graph_builder import build_graph | |
from api_client import fetch_questions, submit_answers | |
class GaiaAgent: | |
def __init__(self): | |
self.graph = build_graph() | |
self.executor = self.graph.compile() | |
def __call__(self, question): | |
# Explicitly pass the state dictionary | |
result_state = self.executor.invoke({"question": question}) | |
return result_state.get("final_answer", "No answer generated.") | |
def run_and_submit_all(profile): | |
try: | |
space_id = os.getenv("SPACE_ID") | |
username = profile if profile else None | |
if not username: | |
return "β Please log in to Hugging Face.", None | |
agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main" | |
agent = GaiaAgent() | |
questions_data = fetch_questions() | |
if not questions_data: | |
return "β No questions retrieved from GAIA API.", None | |
answers_payload = [] | |
results_log = [] | |
for item in questions_data: | |
task_id = item["task_id"] | |
question = item["question"] | |
answer = agent(question) | |
answers_payload.append({"task_id": task_id, "submitted_answer": answer}) | |
results_log.append({ | |
"Task ID": task_id, | |
"Question": question, | |
"Submitted Answer": answer | |
}) | |
result = submit_answers(username, agent_code, answers_payload) | |
final_status = ( | |
f"β Submission Successful!\n" | |
f"User: {result.get('username')}\n" | |
f"Score: {result.get('score')}%\n" | |
f"Correct: {result.get('correct_count')}/{result.get('total_attempted')}\n" | |
f"Message: {result.get('message', '')}" | |
) | |
return final_status, pd.DataFrame(results_log) | |
except Exception as e: | |
error_message = ( | |
f"β An error occurred:\n{str(e)}\n\n" | |
f"Traceback:\n{traceback.format_exc()}" | |
) | |
return error_message, None | |
with gr.Blocks() as demo: | |
gr.Markdown("# π€ GAIA LangGraph Agent") | |
gr.Markdown("Log in and run your agent to evaluate on the GAIA benchmark.") | |
login_button = gr.LoginButton() | |
run_button = gr.Button("π Run Evaluation & Submit All Answers") | |
status_output = gr.Textbox(label="Run Status", lines=10) | |
results_table = gr.DataFrame(label="Results") | |
run_button.click( | |
fn=run_and_submit_all, | |
inputs=[login_button], | |
outputs=[status_output, results_table] | |
) | |
if __name__ == "__main__": | |
demo.launch() | |