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| import os | |
| import gradio as gr | |
| import requests | |
| import pandas as pd | |
| from agent import run_agent_on_question # your real agent logic | |
| DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space" | |
| class WrappedAgent: | |
| def __init__(self): | |
| print("Custom Agent loaded.") | |
| def __call__(self, question: str) -> str: | |
| # question comes with context already | |
| parts = question.split("|||", 1) | |
| raw_question = parts[-1] | |
| print(f"Calling run_agent_on_question on: {raw_question[:60]}...") | |
| return run_agent_on_question({"question": raw_question, "task_id": "N/A"}) | |
| def run_and_submit_all(profile: gr.OAuthProfile | None): | |
| space_id = os.getenv("SPACE_ID") | |
| if not profile: | |
| return "Please login to Hugging Face via the login button.", None | |
| username = profile.username | |
| questions_url = f"{DEFAULT_API_URL}/questions" | |
| submit_url = f"{DEFAULT_API_URL}/submit" | |
| agent = WrappedAgent() | |
| agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main" | |
| try: | |
| resp = requests.get(questions_url, timeout=15) | |
| resp.raise_for_status() | |
| questions = resp.json() | |
| except Exception as e: | |
| return f"Error fetching questions: {e}", None | |
| results = [] | |
| answers = [] | |
| for q in questions: | |
| task_id = q.get("task_id") | |
| question = q.get("question", "") | |
| # optionally fetch file: requests.get(BASE_URL + f"/files/{task_id}") | |
| full_input = f"{task_id}|||{question}" | |
| submitted = agent(full_input) | |
| answers.append({"task_id": task_id, "submitted_answer": submitted}) | |
| results.append({"Task ID": task_id, "Question": question, "Submitted Answer": submitted}) | |
| submission = { | |
| "username": username, | |
| "agent_code": agent_code, | |
| "answers": answers | |
| } | |
| try: | |
| sub_resp = requests.post(submit_url, 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', 'N/A')}% " | |
| f"({data.get('correct_count','?')}/{data.get('total_attempted','?')})\n" | |
| f"{data.get('message')}" | |
| ) | |
| return status, pd.DataFrame(results) | |
| except Exception as e: | |
| return f"Submission failed: {e}", pd.DataFrame(results) | |
| with gr.Blocks() as demo: | |
| gr.Markdown("# Custom GAIA Evaluation Runner") | |
| gr.Markdown("Log in, click the button, and your agent runs through all GAIA questions.") | |
| gr.LoginButton() | |
| run_btn = gr.Button("Run Evaluation & Submit All Answers") | |
| out_txt = gr.Textbox(label="Run Status / Submission Result", interactive=False, lines=5) | |
| out_tbl = gr.DataFrame(label="Questions & Submitted Answer") | |
| run_btn.click(fn=run_and_submit_all, outputs=[out_txt, out_tbl]) | |
| if __name__ == "__main__": | |
| demo.launch(debug=True, share=False) | |