import gradio as gr
import requests
import re
import os
import json
import time
import threading
from googleapiclient.discovery import build
from huggingface_hub import InferenceClient
from pytube import YouTube
import whisper
import logging

# 로그 설정
logging.basicConfig(level=logging.INFO)

# Whisper 모델 로드
model = whisper.load_model("base")

# YouTube API 키
API_KEY = 'AIzaSyDUz3wkGal0ewRtPlzeMit88bV4hS4ZIVY'

# YouTube API 서비스 빌드
youtube = build('youtube', 'v3', developerKey=API_KEY)

# Hugging Face API 설정
client = InferenceClient(model="meta-llama/Meta-Llama-3-70B-Instruct", token=os.getenv("HF_TOKEN"))

WEBHOOK_URL = "https://connect.pabbly.com/workflow/sendwebhookdata/IjU3NjUwNTZhMDYzMDA0MzA1MjZhNTUzMzUxM2Ii_pc"
COMMENTS_FILE = 'comments.json'

DEFAULT_SYSTEM_PROMPT = "대화시 반드시 나의 이름 'GPTube'를 밝히며 한글로 인사를하라. 반드시 '한글'(한국어)로 250 토큰 이내로 답변을 생성하고 출력하라. Respond to the following YouTube comment in a friendly and helpful manner:"

stop_event = threading.Event()  # 스레드 중지를 위한 이벤트

def load_existing_comments():
    if os.path.exists(COMMENTS_FILE):
        with open(COMMENTS_FILE, 'r') as file:
            return json.load(file)
    return []

def save_comments(comments):
    with open(COMMENTS_FILE, 'w') as file:
        json.dump(comments, file)

def download_audio(video_url):
    yt = YouTube(video_url)
    audio = yt.streams.filter(only_audio=True).first()
    audio_path = audio.download(output_path=".")
    
    file_stats = os.stat(audio_path)
    logging.info(f'Size of audio file in Bytes: {file_stats.st_size}')
    
    if file_stats.st_size <= 30000000:  # Check the file size limit
        base, ext = os.path.splitext(audio_path)
        new_file = base + '.mp3'
        os.rename(audio_path, new_file)
        return new_file
    else:
        logging.error('Videos for transcription on this space are limited to about 1.5 hours. Please contact support for more information.')
        return None

def generate_transcript(audio_path):
    try:
        if not audio_path or not os.path.exists(audio_path):
            raise ValueError("유효한 오디오 파일 경로가 아닙니다.")
        
        result = model.transcribe(audio_path)
        return result['text'].strip()
    except Exception as e:
        logging.error(f"Exception during transcription: {str(e)}")
        return f"전사 중 오류가 발생했습니다: {str(e)}"

def generate_reply(comment_text, system_prompt):
    prompt = f"{system_prompt}\n\nComment: {comment_text}\n\nReply:"
    response = client.text_generation(
        prompt=prompt,
        max_new_tokens=250,
        temperature=0.7,
        top_p=0.9
    )
    if isinstance(response, dict) and 'generated_text' in response:
        return response['generated_text']
    return response

def send_webhook(data):
    response = requests.post(WEBHOOK_URL, json=data)
    return response.status_code, response.text

def get_video_comments(video_id):
    try:
        comments = []
        request = youtube.commentThreads().list(
            part='snippet',
            videoId=video_id,
            maxResults=100,   #댓글 읽어들이는 수 정의
            textFormat='plainText'
        )
        response = request.execute()
        while request is not None:
            for item in response['items']:
                snippet = item['snippet']['topLevelComment']['snippet']
                comment = {
                    'comment_id': item['snippet']['topLevelComment']['id'],
                    'author': snippet['authorDisplayName'],
                    'published_at': snippet['publishedAt'],
                    'text': snippet['textDisplay'],
                    'reply_count': item['snippet']['totalReplyCount']
                }
                comments.append(comment)
            if 'nextPageToken' in response:
                request = youtube.commentThreads().list(
                    part='snippet',
                    videoId=video_id,
                    pageToken=response['nextPageToken'],
                    maxResults=100,  #댓글 읽어들이는 수 정의
                    textFormat='plainText'
                )
                response = request.execute()
            else:
                break
        return comments
    except Exception as e:
        return [{'error': str(e)}]

def fetch_comments(video_url, system_prompt):
    log_entries = []
    video_id_match = re.search(r'(?:v=|\/)([0-9A-Za-z_-]{11}).*', video_url)
    if video_id_match:
        video_id = video_id_match.group(1)
        audio_path = download_audio(video_url)
        if not audio_path:
            return "오디오를 다운로드할 수 없습니다."
        
        transcript = generate_transcript(audio_path)
        
        existing_comments = load_existing_comments()
        new_comments = get_video_comments(video_id)
        
        if not new_comments or 'error' in new_comments[0]:
            return "댓글을 찾을 수 없거나 오류가 발생했습니다."
        
        recent_new_comments = [c for c in new_comments if c['comment_id'] not in {c['comment_id'] for c in existing_comments} and c['reply_count'] == 0]
        
        if recent_new_comments:
            for most_recent_comment in recent_new_comments:
                combined_prompt = f"{transcript}\n\n{system_prompt}"
                reply_text = generate_reply(most_recent_comment['text'], combined_prompt)
                webhook_data = {
                    "comment_id": most_recent_comment['comment_id'],
                    "author": most_recent_comment['author'],
                    "published_at": most_recent_comment['published_at'],
                    "text": most_recent_comment['text'],
                    "reply_text": reply_text
                }
                webhook_status, webhook_response = send_webhook(webhook_data)
                log_entries.append(f"최근 댓글: {most_recent_comment['text']}\n\n답변 생성: {reply_text}\n\n웹훅 응답: {webhook_status} - {webhook_response}")
                existing_comments.append(most_recent_comment)
            save_comments(existing_comments)
        else:
            log_entries.append("새로운 댓글이 없습니다.")
    else:
        log_entries.append("유효하지 않은 YouTube URL입니다.")
    return "\n\n".join(log_entries)

def background_fetch_comments():
    while not stop_event.is_set():
        result = fetch_comments("https://www.youtube.com/watch?v=dQw4w9WgXcQ", DEFAULT_SYSTEM_PROMPT)  # URL과 프롬프트 실제 사용 예시
        print(result)
        time.sleep(10)

def start_background_fetch():
    threading.Thread(target=background_fetch_comments).start()

def stop_background_fetch():
    stop_event.set()

def get_text(video_url):
    audio_path = download_audio(video_url)
    if not audio_path:
        return "오디오를 다운로드할 수 없습니다."
    
    transcript = generate_transcript(audio_path)
    return transcript

# Gradio 인터페이스 정의
demo = gr.Blocks()

with demo:
    gr.Markdown("<h1><center>GPTube</center></h1>")
   
    with gr.Row():
        input_text_url = gr.Textbox(placeholder='YouTube video URL', label='YouTube URL')
        input_text_prompt = gr.Textbox(placeholder='시스템 프롬프트', label='시스템 프롬프트', value=DEFAULT_SYSTEM_PROMPT, lines=5)
    
    with gr.Row():
        result_button_transcribe = gr.Button('Transcribe')
        result_button_comments = gr.Button('Fetch Comments and Generate Reply')
    
    with gr.Row():
        output_text_transcribe = gr.Textbox(placeholder='Transcript of the YouTube video.', label='Transcript', lines=20)
        output_text_prompt = gr.Textbox(placeholder='응답 텍스트', label='응답 텍스트', lines=20)
    
    result_button_transcribe.click(get_text, inputs=input_text_url, outputs=output_text_transcribe, api_name="transcribe_api")
    result_button_comments.click(fetch_comments, inputs=[input_text_url, input_text_prompt], outputs=output_text_prompt, api_name="fetch_comments_api")

# 인터페이스 실행
demo.launch()