445 lines
16 KiB
Python
445 lines
16 KiB
Python
import os
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import subprocess
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import requests
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import whisper
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from faster_whisper import WhisperModel
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from datetime import datetime, time, timedelta
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from zoneinfo import ZoneInfo
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import json
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# ---------------------------
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# Configuration
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# ---------------------------
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TWITCH_CLIENT_ID = os.environ.get("TWITCH_CLIENT_ID", "")
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TWITCH_CLIENT_SECRET = os.environ.get("TWITCH_CLIENT_SECRET", "")
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CHANNEL_NAME = os.environ.get("CHANNEL_NAME", "madmonq")
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TIMEDELTA_DAYS = int(os.environ.get("TIMEDELTA_DAYS", "1"))
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TIMEDELTA_DAYS_EXACT = os.environ.get("TIMEDELTA_DAYS_EXACT", "false").lower() in ("true", "1", "yes")
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CLIP_CREATE_FROM_CHAT = os.environ.get("CLIP_CREATE_FROM_CHAT", "false").lower() in ("true", "1", "yes")
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CHANNEL_LANGUAGE = os.environ.get("CHANNEL_LANGUAGE", "cs")
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SEARCH_KEYWORDS = [
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"madmonq",
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"madmonge",
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"madmong",
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"medmong",
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"medmonk",
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"madmonk",
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"mad monk",
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"mad monq",
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"mad-monq",
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"mad-monk",
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"madmonck",
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"madmunk",
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"madmon",
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"madmonke",
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"madmonque",
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"matmonk",
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"matt monk",
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"mat monk"
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]
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MODEL_NAME = "turbo" # Whisper model
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# Define base directories for each file category under a folder named after the channel.
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base_dirs = {
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"vods": os.path.join("vods", CHANNEL_NAME),
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"audio": os.path.join("audio", CHANNEL_NAME),
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"transcripts": os.path.join("transcripts", CHANNEL_NAME),
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"chat": os.path.join("chat", CHANNEL_NAME),
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"clips_transcript": os.path.join("clips", CHANNEL_NAME, "from_vod"),
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"clips_chat": os.path.join("clips", CHANNEL_NAME, "from_chat")
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}
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# Create directories if they do not exist.
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for path in base_dirs.values():
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os.makedirs(path, exist_ok=True)
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# ---------------------------
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# Twitch API Helper Functions
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# ---------------------------
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def get_access_token():
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url = "https://id.twitch.tv/oauth2/token"
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payload = {
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"client_id": TWITCH_CLIENT_ID,
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"client_secret": TWITCH_CLIENT_SECRET,
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"grant_type": "client_credentials"
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}
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response = requests.post(url, data=payload)
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response.raise_for_status()
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data = response.json()
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return data["access_token"]
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def get_channel_id(channel_name, token):
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headers = {
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"Client-ID": TWITCH_CLIENT_ID,
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"Authorization": f"Bearer {token}"
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}
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url = f"https://api.twitch.tv/helix/users?login={channel_name}"
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response = requests.get(url, headers=headers)
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response.raise_for_status()
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data = response.json()
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if data.get("data"):
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return data["data"][0]["id"]
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else:
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print("Channel not found.")
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return None
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def get_vods(channel_id, token):
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headers = {
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"Client-ID": TWITCH_CLIENT_ID,
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"Authorization": f"Bearer {token}"
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}
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prague_tz = ZoneInfo("Europe/Prague")
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today_prague = datetime.now(prague_tz).date()
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# Define the search range based on TIMEDELTA_DAYS and TIMEDELTA_DAYS_EXACT
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if TIMEDELTA_DAYS == 0:
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# Only search for today
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start_date = today_prague
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end_date = today_prague
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else:
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if TIMEDELTA_DAYS_EXACT:
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# Only search for the day exactly TIMEDELTA_DAYS ago
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start_date = today_prague - timedelta(days=TIMEDELTA_DAYS)
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end_date = start_date
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else:
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# Search from TIMEDELTA_DAYS ago up to yesterday
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start_date = today_prague - timedelta(days=TIMEDELTA_DAYS)
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end_date = today_prague - timedelta(days=1)
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start_time = datetime.combine(start_date, time.min).replace(tzinfo=prague_tz)
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end_time = datetime.combine(end_date, time.max).replace(tzinfo=prague_tz)
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url = f"https://api.twitch.tv/helix/videos?user_id={channel_id}&type=archive&first=100"
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response = requests.get(url, headers=headers)
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response.raise_for_status()
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vods = []
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for vod in response.json().get("data", []):
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published_at = datetime.fromisoformat(vod["published_at"].replace("Z", "+00:00"))
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published_at_prague = published_at.astimezone(prague_tz)
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if start_time <= published_at_prague <= end_time:
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vods.append(vod)
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return vods
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# ---------------------------
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# VOD Processing Functions
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# ---------------------------
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def download_vod(vod_url, output_filename):
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if os.path.exists(output_filename):
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print(f"{output_filename} already exists. Skipping download.")
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return
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command = [
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"yt-dlp",
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"--cookies", "cookies.txt",
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"-f", "worst",
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"-o", output_filename,
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vod_url
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]
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subprocess.run(command, check=True)
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print(f"Downloaded VOD to {output_filename}")
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def extract_audio(video_file, audio_file):
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if os.path.exists(audio_file):
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print(f"{audio_file} already exists. Skipping audio extraction.")
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return
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command = ["ffmpeg", "-i", video_file, "-vn", "-acodec", "mp3", audio_file, "-y"]
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subprocess.run(command, check=True)
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print(f"Extracted audio to {audio_file}")
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def transcribe_audio(audio_file, model_name):
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model = whisper.load_model(model_name, download_root="/app/models")
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result = model.transcribe(audio_file, language=CHANNEL_LANGUAGE)
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return result
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def transcribe_audio_fast(audio_file, model_name, language, vod_id):
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transcript_path = os.path.join(base_dirs["transcripts"], f"transcript_{vod_id}.json")
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if os.path.exists(transcript_path):
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print(f"faster_whisper -- Loading existing transcription for VOD {vod_id} from {transcript_path}")
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with open(transcript_path, "r", encoding="utf-8") as f:
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segments_data = json.load(f)
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return segments_data
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# Initialize the model and transcribe (passing language if provided)
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model_fast = WhisperModel("large-v3-turbo", device="auto", compute_type="int8", download_root="/app/models")
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segments, info = model_fast.transcribe(audio_file, language=language)
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print("faster_whisper -- Detected language '%s' with probability %f" % (info.language, info.language_probability))
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# Build a list of dictionaries for the segments.
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segments_data = []
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for seg in segments:
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segments_data.append({
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"start": seg.start,
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"end": seg.end,
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"text": seg.text
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})
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with open(transcript_path, "w", encoding="utf-8") as f:
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json.dump(segments_data, f, ensure_ascii=False, indent=4)
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print(f"faster_whisper -- Saved transcription to {transcript_path}")
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return segments_data
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def search_transcription(result, keywords):
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matches = []
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if "segments" in result:
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for segment in result["segments"]:
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segment_text = segment["text"].lower()
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for keyword in keywords:
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if keyword.lower() in segment_text:
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matches.append(segment)
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break # Stop checking further keywords for this segment
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return matches
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def scrape_chat_log(vod_id, output_filename):
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"""
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Uses TwitchDownloaderCLI to download the chat log for a given VOD.
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The chat log is saved in JSON format to output_filename.
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"""
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if os.path.exists(output_filename):
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print(f"{output_filename} already exists. Skipping chat log scrape.")
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return
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# Build the TwitchDownloaderCLI command.
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# The command downloads the chat log in JSON format for the specified VOD.
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command = [
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"TwitchDownloaderCLI", "chatdownload",
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"--id", vod_id,
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"--output", output_filename
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]
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try:
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subprocess.run(command, check=True)
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print(f"Chat log saved to {output_filename}")
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except subprocess.CalledProcessError as e:
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print(f"Error downloading chat log for VOD {vod_id}: {e}")
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def create_clip_from_vod(video_file, match_start, vod):
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clip_start = max(match_start - 15, 0)
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clip_duration = 60 # seconds
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clip_dir = base_dirs["clips_transcript"]
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vod_datetime = datetime.strptime(vod['created_at'], '%Y-%m-%dT%H:%M:%SZ')
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date_folder = vod_datetime.strftime('%d-%m-%y')
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# Create a subfolder inside clip_dir for the date.
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clip_date_dir = os.path.join(clip_dir, date_folder)
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os.makedirs(clip_date_dir, exist_ok=True)
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# Build the clip filename inside the date folder.
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clip_filename = os.path.join(clip_date_dir, f"clip_{vod['id']}_{int(match_start)}.mp4")
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command = [
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"ffmpeg",
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"-ss", str(clip_start),
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"-i", video_file,
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"-t", str(clip_duration),
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"-c", "copy",
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clip_filename,
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"-y"
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]
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subprocess.run(command, check=True)
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print(f"Clip created: {clip_filename}")
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return clip_filename
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def find_comments_by_keywords(chat_log, keywords):
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"""
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Searches the chat log for any comments containing one of the given keywords.
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Returns a list of matching comment objects.
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"""
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matching_comments = []
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if isinstance(chat_log, dict) and "comments" in chat_log:
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chat_log = chat_log["comments"]
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for comment in chat_log:
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if not isinstance(comment, dict):
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continue
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message_text = comment['message']['body'].lower()
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for keyword in keywords:
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if keyword.lower() in message_text:
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matching_comments.append(comment)
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break
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return matching_comments
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def create_clip_from_comment_timestamp(video_file, comment_timestamp, vod):
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clip_start = max(comment_timestamp - 15, 0)
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clip_duration = 60 # seconds
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clip_dir = base_dirs["clips_chat"]
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vod_datetime = datetime.strptime(vod['created_at'], '%Y-%m-%dT%H:%M:%SZ')
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date_folder = vod_datetime.strftime('%d-%m-%y')
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# Create a subfolder inside clip_dir for the date.
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clip_date_dir = os.path.join(clip_dir, date_folder)
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os.makedirs(clip_date_dir, exist_ok=True)
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# Build the clip filename inside the date folder.
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clip_filename = os.path.join(clip_date_dir, f"clip_{vod['id']}_{int(comment_timestamp)}.mp4")
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command = [
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"ffmpeg",
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"-ss", str(clip_start),
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"-i", video_file,
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"-t", str(clip_duration),
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"-c", "copy",
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clip_filename,
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"-y"
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]
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subprocess.run(command, check=True)
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print(f"Clip created: {clip_filename}")
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return clip_filename
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def seconds_to_timestamp(seconds):
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"""Convert seconds to HH:MM:SS format."""
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hours = int(seconds // 3600)
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minutes = int((seconds % 3600) // 60)
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secs = int(seconds % 60)
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return f"{hours:02}:{minutes:02}:{secs:02}"
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def download_vod_segment(vod, match_start, duration=60):
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"""
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Downloads a segment of a VOD using yt-dlp.
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Parameters:
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vod_url (str): The URL of the video.
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output_filename (str): The desired output filename.
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start_seconds (float): Start time in seconds (from faster-whisper).
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duration (int): Duration of the segment in seconds (default 60 seconds).
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"""
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clip_start = max(match_start - 15, 0)
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clip_dir = base_dirs["clips_transcript"]
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vod_datetime = datetime.strptime(vod['created_at'], '%Y-%m-%dT%H:%M:%SZ')
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date_folder = vod_datetime.strftime('%d-%m-%y')
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# Create a subfolder inside clip_dir for the date.
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clip_date_dir = os.path.join(clip_dir, date_folder)
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os.makedirs(clip_date_dir, exist_ok=True)
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clip_filename = os.path.join(clip_date_dir, f"clip_{vod['id']}_{int(clip_start)}.mp4")
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end_seconds = clip_start + duration
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start_ts = seconds_to_timestamp(clip_start)
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end_ts = seconds_to_timestamp(end_seconds)
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# yt-dlp download sections format: "*HH:MM:SS-HH:MM:SS"
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segment = f"*{start_ts}-{end_ts}"
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command = [
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"yt-dlp",
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"--cookies", "cookies.txt",
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"--download-sections", segment,
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"-o", clip_filename,
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vod["url"]
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]
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subprocess.run(command, check=True)
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print(f"Downloaded segment from {start_ts} to {end_ts} into {clip_filename}")
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# ---------------------------
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# Main Processing Pipeline
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# ---------------------------
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def handle_matches_fast(vod, video_filename, segments_data):
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matches_fast = []
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for segment in segments_data:
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segment_text = segment["text"].lower()
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for keyword in SEARCH_KEYWORDS:
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if keyword.lower() in segment_text:
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matches_fast.append(segment)
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break
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if matches_fast:
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print(f"faster_whisper -- Found {len(matches_fast)} mention(s) of {SEARCH_KEYWORDS} in VOD {vod['id']}:")
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for match in matches_fast:
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start = match["start"]
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text = match["text"]
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print(f" - At {start:.2f}s: {text}")
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# create_clip_from_vod(video_filename, start, vod)
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download_vod_segment(vod, start)
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else:
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print("faster_whisper -- No mentions of keywords.")
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def handle_matches(vod, video_filename, result):
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matches = search_transcription(result, SEARCH_KEYWORDS)
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if matches:
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print(f"Found {len(matches)} mention(s) of {SEARCH_KEYWORDS} in VOD {vod['id']}:")
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for match in matches:
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start = match["start"]
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text = match["text"]
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print(f" - At {start:.2f}s: {text}")
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create_clip_from_vod(video_filename, start, vod)
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else:
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print(f"No mentions of {SEARCH_KEYWORDS} found in VOD {vod['id']}.")
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def download_vod_audio(vod_url, output_filename):
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if os.path.exists(output_filename):
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print(f"{output_filename} already exists. Skipping download.")
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return
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command = [
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"yt-dlp",
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"--cookies", "cookies.txt",
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"-f", "worst",
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"--extract-audio",
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"--audio-format", "mp3",
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"-o", output_filename,
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vod_url
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]
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subprocess.run(command, check=True)
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print(f"Downloaded audio from VOD to {output_filename}")
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def main():
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print("Obtaining access token...")
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token = get_access_token()
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print("Access token obtained.")
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channel_id = get_channel_id(CHANNEL_NAME, token)
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if not channel_id:
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return
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vods = get_vods(channel_id, token)
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if not vods:
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print("No VODs from yesterday found.")
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return
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for vod in vods:
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vod_url = vod["url"]
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vod_id = vod["id"]
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# Define file paths in the respective directories
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video_filename = os.path.join(base_dirs["vods"], f"vod_{vod_id}.mp4")
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audio_filename = os.path.join(base_dirs["audio"], f"vod_{vod_id}.mp3")
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transcript_filename = os.path.join(base_dirs["transcripts"], f"transcript_{vod_id}.json")
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chat_log_filename = os.path.join(base_dirs["chat"], f"chat_{vod_id}.json")
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print(f"\nProcessing VOD: {vod_url}")
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# download_vod(vod_url, video_filename)
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# extract_audio(video_filename, audio_filename)
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download_vod_audio(vod_url, audio_filename)
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print("Transcribing audio. This may take some time...")
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# Pass language and vod_id so that the transcript is saved and reused if available.
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segments_data = transcribe_audio_fast(audio_filename, MODEL_NAME, language=CHANNEL_LANGUAGE, vod_id=vod_id)
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if CLIP_CREATE_FROM_CHAT:
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scrape_chat_log(vod_id, chat_log_filename)
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handle_matches_fast(vod, video_filename, segments_data)
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if CLIP_CREATE_FROM_CHAT:
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try:
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with open(chat_log_filename, "r", encoding="utf-8") as f:
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chat_log = json.load(f)
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except Exception as e:
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print(f"Error loading chat log: {e}")
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chat_log = []
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# Search chat log using an array of keywords (using the same keywords as for transcript)
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comment_matches = find_comments_by_keywords(chat_log, SEARCH_KEYWORDS)
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if comment_matches:
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for comment in comment_matches:
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# Try to get the timestamp from the "offset" field (or fallback to "content_offset_seconds")
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timestamp = comment["content_offset_seconds"]
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print(f"Found a matching comment at {timestamp} seconds.")
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create_clip_from_comment_timestamp(video_filename, timestamp, vod)
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else:
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print("No matching comments found.")
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if __name__ == "__main__":
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main() |