import json
import threading
import requests
import gradio as gr
from agent import build_agent, answer
OWNER='SystemReset'
lock=threading.Lock()
def require_owner(profile):
    if profile is None or profile.username != OWNER:
        raise gr.Error('Sign in as SystemReset to use these controls.')
def respond(message, profile: gr.OAuthProfile | None):
    require_owner(profile)
    return answer(build_agent(use_case=True),message)
def run_challenge(profile: gr.OAuthProfile | None):
    require_owner(profile)
    if not lock.acquire(blocking=False): raise gr.Error('An evaluation is already running.')
    try:
        response=requests.get('https://agents-course-unit4-scoring.hf.space/questions',timeout=60)
        response.raise_for_status()
        questions=response.json()
        agent=build_agent()
        results=[]
        for index,item in enumerate(questions):
            if item.get('file_name') or 'youtube.com/' in item['question']:
                row={'task_id':item['task_id'],'submitted_answer':'','status':'media unsupported'}
            else:
                try:
                    result=answer(agent,item['question'])
                    row={'task_id':item['task_id'],'submitted_answer':result,'status':'generated' if result else 'insufficient evidence'}
                except Exception as exc:
                    row={'task_id':item['task_id'],'submitted_answer':'','status':type(exc).__name__}
            results.append(row)
            with open('challenge_results.json','w') as handle: json.dump(results,handle)
            yield f'Processed {index+1}/{len(questions)} questions',results
    finally:
        lock.release()
def submit_challenge(profile: gr.OAuthProfile | None):
    require_owner(profile)
    if lock.locked(): raise gr.Error('Wait for evaluation to finish.')
    with open('challenge_results.json') as handle: results=json.load(handle)
    if len(results)!=20: raise gr.Error('Complete the evaluation first.')
    payload={'username':OWNER,'agent_code':'https://huggingface.co/spaces/SystemReset/alfred-agents-course/tree/main','answers':[{'task_id':row['task_id'],'submitted_answer':row['submitted_answer']} for row in results]}
    response=requests.post('https://agents-course-unit4-scoring.hf.space/submit',json=payload,timeout=120)
    response.raise_for_status()
    return response.json()
with gr.Blocks() as demo:
    gr.Markdown('# Alfred: Course Research Agent\nSign in as SystemReset. Code is public; model calls and challenge controls are restricted to the owner.')
    gr.LoginButton()
    prompt=gr.Textbox(label='Question')
    reply=gr.Textbox(label='Answer')
    gr.Button('Ask Alfred').click(respond,inputs=[prompt],outputs=[reply])
    gr.Markdown('## Final challenge\nRuns the real agent on benchmark questions. Unsupported media is left unanswered. Submit publishes generated answers and score to the course leaderboard.')
    status=gr.Textbox(label='Progress')
    results=gr.JSON(label='Generated answers')
    gr.Button('Run final challenge').click(run_challenge,outputs=[status,results])
    gr.Button('Submit generated answers').click(submit_challenge,outputs=[results])
if __name__=='__main__': demo.queue().launch()