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| import os | |
| import asyncio | |
| import argparse | |
| import gradio as gr | |
| import requests | |
| import pandas as pd | |
| from agno.agent import RunResponse | |
| from agent import agent | |
| DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space" | |
| async def _async_answer(answer_text: str) -> str: | |
| response: RunResponse = await agent.arun(answer_text) | |
| return response.content | |
| class BasicAgent: | |
| def __init__(self): | |
| pass | |
| def __call__(self, task_id: str, question: str) -> str: | |
| print("[INFO] Answering question: >>>", question) | |
| return asyncio.run(_async_answer(f"{task_id}: {question}")) | |
| def run_agent(profile: gr.OAuthProfile | None, task_id: str | None = None, submit: bool = True): | |
| space_id = os.getenv("SPACE_ID") | |
| if profile: | |
| username = f"{profile.username}" | |
| else: | |
| return "Please log in to Hugging Face.", None | |
| api_url = DEFAULT_API_URL | |
| questions_url = f"{api_url}/questions" | |
| submit_url = f"{api_url}/submit" | |
| files_url = f"{api_url}/files/{task_id}" | |
| try: | |
| agent_instance = BasicAgent() | |
| 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 | |
| if task_id: | |
| questions_data = [q for q in questions_data if str(q.get("task_id")) == str(task_id)] | |
| if not questions_data: | |
| return f"Task {task_id} not found.", None | |
| results_log = [] | |
| answers_payload = [] | |
| for item in questions_data: | |
| tid = item.get("task_id") | |
| qtext = item.get("question") | |
| if not tid or qtext is None: | |
| continue | |
| try: | |
| submitted_answer = agent_instance(task_id, qtext) | |
| answers_payload.append({"task_id": tid, "submitted_answer": submitted_answer}) | |
| results_log.append({"Task ID": tid, "Question": qtext, "Submitted Answer": submitted_answer}) | |
| except Exception as e: | |
| results_log.append({"Task ID": tid, "Question": qtext, "Submitted Answer": f"AGENT ERROR: {e}"}) | |
| if not answers_payload: | |
| return "No answers produced.", pd.DataFrame(results_log) | |
| if not submit: | |
| return "Test mode: nothing submitted.", 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"Score: {result_data.get('score', 'N/A')}% " | |
| f"({result_data.get('correct_count', '?')}/{result_data.get('total_attempted', '?')})\n" | |
| f"Message: {result_data.get('message', '')}" | |
| ) | |
| return final_status, pd.DataFrame(results_log) | |
| except Exception as e: | |
| return f"Submission failed: {e}", pd.DataFrame(results_log) | |
| def run_agent_single(profile: gr.OAuthProfile | None, task_id: str): | |
| return run_agent(profile, task_id or None, submit=False) | |
| def run_agent_all(profile: gr.OAuthProfile | None, task_id: str): | |
| return run_agent(profile, task_id or None, submit=True) | |
| with gr.Blocks() as demo: | |
| gr.Markdown("# Basic Agent Evaluation Runner") | |
| gr.LoginButton() | |
| task_id_input = gr.Textbox(label="Task ID (optional)", placeholder="e.g. 2023060607") | |
| run_test_button = gr.Button("Test Single Task (no submit)") | |
| run_all_button = gr.Button("Run & Submit All") | |
| status_output = gr.Textbox(label="Status", lines=5, interactive=False) | |
| results_table = gr.DataFrame(label="Results", wrap=True) | |
| run_test_button.click( | |
| fn=run_agent_single, | |
| inputs=[task_id_input], | |
| outputs=[status_output, results_table], | |
| ) | |
| run_all_button.click( | |
| fn=run_agent_all, | |
| inputs=[task_id_input], | |
| outputs=[status_output, results_table], | |
| ) | |
| gr.Markdown( | |
| "Running all tasks may take time. Use the single‑task button to debug quickly." | |
| ) | |
| if __name__ == "__main__": | |
| space_host = os.getenv("SPACE_HOST") | |
| space_id = os.getenv("SPACE_ID") | |
| if space_host: | |
| print(f"SPACE_HOST: {space_host}") | |
| if space_id: | |
| print(f"SPACE_ID: {space_id}") | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument("--task-id", help="Run a single task locally without submission") | |
| args, _ = parser.parse_known_args() | |
| if args.task_id: | |
| status, table = run_agent(profile=None, task_id=args.task_id, submit=False) | |
| print(status) | |
| if table is not None: | |
| print(table) | |
| else: | |
| demo.launch(debug=True, share=False) | |