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import discord |
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import logging |
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import os |
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import re |
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import asyncio |
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import subprocess |
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import aiohttp |
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import time |
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from huggingface_hub import InferenceClient |
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from googleapiclient.discovery import build |
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from youtube_transcript_api import YouTubeTranscriptApi, TranscriptsDisabled, NoTranscriptFound |
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from youtube_transcript_api.formatters import TextFormatter |
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from dotenv import load_dotenv |
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from pytube import YouTube |
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import whisper |
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import torch |
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from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq |
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import librosa |
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load_dotenv() |
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logging.basicConfig(level=logging.DEBUG, format='%(asctime)s:%(levelname)s:%(name)s:%(message)s', handlers=[logging.StreamHandler()]) |
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intents = discord.Intents.default() |
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intents.message_content = True |
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intents.messages = True |
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intents.guilds = True |
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intents.guild_messages = True |
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hf_client = InferenceClient("CohereForAI/c4ai-command-r-plus-08-2024", token=os.getenv("HF_TOKEN")) |
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whisper_client = InferenceClient("openai/whisper-large-v3", token=os.getenv("HF_TOKEN")) |
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API_KEY = os.getenv("YOUTUBE_API_KEY") |
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youtube_service = build('youtube', 'v3', developerKey=API_KEY) |
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SPECIFIC_CHANNEL_ID = int(os.getenv("DISCORD_CHANNEL_ID")) |
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MAX_RETRIES = 3 |
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class MyClient(discord.Client): |
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def __init__(self, *args, **kwargs): |
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super().__init__(*args, **kwargs) |
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self.is_processing = False |
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self.session = None |
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async def on_ready(self): |
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logging.info(f'{self.user}λ‘ λ‘κ·ΈμΈλμμ΅λλ€!') |
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subprocess.Popen(["python", "web.py"]) |
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logging.info("Web.py μλ²κ° μμλμμ΅λλ€.") |
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self.session = aiohttp.ClientSession() |
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channel = self.get_channel(SPECIFIC_CHANNEL_ID) |
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if channel: |
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await channel.send("μ νλΈ λΉλμ€ URLμ μ
λ ₯νλ©΄, μλ§κ³Ό λκΈμ κΈ°λ°μΌλ‘ λ΅κΈμ μμ±ν©λλ€.") |
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async def on_message(self, message): |
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if message.author == self.user: |
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return |
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if not self.is_message_in_specific_channel(message): |
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return |
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if self.is_processing: |
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return |
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self.is_processing = True |
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try: |
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video_id = extract_video_id(message.content) |
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if video_id: |
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transcript, language = await get_best_available_transcript(video_id) |
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comments = await get_video_comments(video_id) |
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if comments: |
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if transcript: |
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replies = await generate_replies(comments, transcript) |
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await create_thread_and_send_replies(message, video_id, comments, replies, self.session) |
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else: |
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await message.channel.send("μλ§μ κ°μ Έμ¬ μ μμ΅λλ€. Whisper λͺ¨λΈμ μ¬μ©νμ¬ μλ§μ μμ±ν©λλ€.") |
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transcript = await generate_whisper_transcript(video_id) |
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if transcript: |
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replies = await generate_replies(comments, transcript) |
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await create_thread_and_send_replies(message, video_id, comments, replies, self.session) |
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else: |
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await message.channel.send("Whisper λͺ¨λΈλ‘λ μλ§μ μμ±ν μ μμ΅λλ€. λκΈλ§μ κΈ°λ°μΌλ‘ λ΅λ³μ μμ±ν©λλ€.") |
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replies = await generate_replies(comments, "") |
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await create_thread_and_send_replies(message, video_id, comments, replies, self.session) |
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else: |
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await message.channel.send("λκΈμ κ°μ Έμ¬ μ μμ΅λλ€.") |
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else: |
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await message.channel.send("μ ν¨ν μ νλΈ λΉλμ€ URLμ μ κ³΅ν΄ μ£ΌμΈμ.") |
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finally: |
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self.is_processing = False |
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def is_message_in_specific_channel(self, message): |
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return message.channel.id == SPECIFIC_CHANNEL_ID or ( |
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isinstance(message.channel, discord.Thread) and message.channel.parent_id == SPECIFIC_CHANNEL_ID |
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) |
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async def close(self): |
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if self.session: |
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await self.session.close() |
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await super().close() |
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def extract_video_id(url): |
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video_id = None |
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youtube_regex = ( |
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r'(https?://)?(www\.)?' |
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'(youtube|youtu|youtube-nocookie)\.(com|be)/' |
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'(watch\?v=|embed/|v/|.+\?v=)?([^&=%\?]{11})') |
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match = re.match(youtube_regex, url) |
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if match: |
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video_id = match.group(6) |
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logging.debug(f'μΆμΆλ λΉλμ€ ID: {video_id}') |
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return video_id |
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async def get_best_available_transcript(video_id, max_retries=5, delay=10): |
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async def fetch_transcript(language): |
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try: |
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transcript = await asyncio.to_thread(YouTubeTranscriptApi.get_transcript, video_id, languages=[language]) |
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return transcript, language |
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except (NoTranscriptFound, TranscriptsDisabled): |
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logging.warning(f'{language} μλ§μ΄ μ 곡λμ§ μμ.') |
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return None, None |
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except Exception as e: |
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logging.warning(f'{language} μλ§ κ°μ Έμ€κΈ° μ€λ₯: {e}') |
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return None, None |
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for attempt in range(max_retries): |
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ko_transcript, ko_lang = await fetch_transcript('ko') |
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if ko_transcript: |
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return ko_transcript, ko_lang |
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en_transcript, en_lang = await fetch_transcript('en') |
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if en_transcript: |
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return en_transcript, en_lang |
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try: |
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transcripts = await asyncio.to_thread(YouTubeTranscriptApi.list_transcripts, video_id) |
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manual_transcript = transcripts.find_manually_created_transcript(['ko', 'en']) |
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transcript = await asyncio.to_thread(manual_transcript.fetch) |
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return transcript, manual_transcript.language_code |
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except (NoTranscriptFound, TranscriptsDisabled) as e: |
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logging.warning(f'μλ μλ§μ μ°Ύμ μ μμ: {e}') |
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except Exception as e: |
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if attempt < max_retries - 1: |
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logging.error(f'μλ§ κ°μ Έμ€κΈ° μ€ν¨ (μλ {attempt + 1}/{max_retries}): {e}') |
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await asyncio.sleep(delay) |
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else: |
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logging.error(f'μ΅μ’
μλ§ κ°μ Έμ€κΈ° μ€ν¨: {e}') |
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return None, None |
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return None, None |
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async def generate_whisper_transcript(video_id): |
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try: |
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yt = YouTube(f'https://www.youtube.com/watch?v={video_id}') |
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audio_stream = yt.streams.filter(only_audio=True).first() |
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audio_file = audio_stream.download(output_path='temp', filename=f'{video_id}.mp3') |
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audio, sr = librosa.load(audio_file, sr=16000) |
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device = "cuda" if torch.cuda.is_available() else "cpu" |
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processor = AutoProcessor.from_pretrained("openai/whisper-large-v3") |
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model = AutoModelForSpeechSeq2Seq.from_pretrained("openai/whisper-large-v3").to(device) |
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input_features = processor(audio, sampling_rate=sr, return_tensors="pt").input_features.to(device) |
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predicted_ids = model.generate(input_features) |
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transcription = processor.batch_decode(predicted_ids, skip_special_tokens=True) |
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os.remove(audio_file) |
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return transcription[0] |
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except Exception as e: |
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logging.error(f'Whisper μλ§ μμ± μ€ν¨: {e}') |
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return None |
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async def get_video_comments(video_id): |
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comments = [] |
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response = youtube_service.commentThreads().list( |
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part='snippet', |
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videoId=video_id, |
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maxResults=100 |
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).execute() |
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for item in response.get('items', []): |
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comment = item['snippet']['topLevelComment']['snippet']['textOriginal'] |
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comment_id = item['snippet']['topLevelComment']['id'] |
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comments.append((comment, comment_id)) |
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logging.debug(f'κ°μ Έμ¨ λκΈ: {comments}') |
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return comments |
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async def generate_replies(comments, transcript): |
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replies = [] |
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for comment, _ in comments: |
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messages = [ |
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{"role": "system", "content": f"""λμ μ΄λ¦μ OpenFreeAIμ΄λ€. λ΅κΈ μμ±ν κ°μ₯ λ§μ§λ§μ λμ μ΄λ¦μ λ°νκ³ κ³΅μνκ² μΈμ¬νλΌ. λΉλμ€ μλ§: {transcript}"""}, |
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{"role": "user", "content": comment} |
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] |
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loop = asyncio.get_event_loop() |
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response = await loop.run_in_executor(None, lambda: hf_client.chat_completion( |
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messages, max_tokens=250, temperature=0.7, top_p=0.85)) |
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if response.choices and response.choices[0].message: |
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reply = response.choices[0].message['content'].strip() |
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else: |
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reply = "λ΅κΈμ μμ±ν μ μμ΅λλ€." |
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replies.append(reply) |
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logging.debug(f'μμ±λ λ΅κΈ: {replies}') |
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return replies |
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async def create_thread_and_send_replies(message, video_id, comments, replies, session): |
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thread = await message.channel.create_thread(name=f"{message.author.name}μ λκΈ λ΅κΈ", message=message) |
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for (comment, comment_id), reply in zip(comments, replies): |
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embed = discord.Embed(description=f"**λκΈ**: {comment}\n**λ΅κΈ**: {reply}") |
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await thread.send(embed=embed) |
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if __name__ == "__main__": |
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discord_client = MyClient(intents=intents) |
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discord_client.run(os.getenv('DISCORD_TOKEN')) |