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5cdc6b727d
transcriptor/main.py
t0is 5cdc6b727d init commit
2025-02-20 15:14:36 +01:00

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Python
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import os
import subprocess
import requests
import whisper
from datetime import datetime, time, timedelta
from zoneinfo import ZoneInfo
import json
# ---------------------------
# Configuration
# ---------------------------
# Make sure these environment variables are set:
# TWITCH_CLIENT_ID and TWITCH_CLIENT_SECRET
TWITCH_CLIENT_ID='a0fuj6tm5ct79clvim9816orphqkov'
TWITCH_CLIENT_SECRET='h7whj3yspxgj1909sgcafx6iz1p1es'
# CHANNEL_NAME = "kuruhs" # e.g. "examplechannel"
CHANNEL_NAME = os.environ.get("CHANNEL_NAME", "madmonq")
CHANNEL_LANGUAGE = os.environ.get("CHANNEL_LANGUAGE", "en")
SEARCH_KEYWORDS = ["madmonq", 'madmonge', 'madmong', 'medmong', 'medmonk', 'madmonk'] # keyword to search in the transcript
MODEL_NAME = "turbo" # Whisper model (e.g., "tiny", "base", "small", etc.)
# ---------------------------
# Twitch API Helper Functions
# ---------------------------
def get_access_token():
"""
Uses the client credentials flow to obtain an OAuth token.
"""
url = "https://id.twitch.tv/oauth2/token"
payload = {
"client_id": TWITCH_CLIENT_ID,
"client_secret": TWITCH_CLIENT_SECRET,
"grant_type": "client_credentials"
}
response = requests.post(url, data=payload)
response.raise_for_status()
data = response.json()
return data["access_token"]
def get_channel_id(channel_name, token):
headers = {
"Client-ID": TWITCH_CLIENT_ID,
"Authorization": f"Bearer {token}"
}
url = f"https://api.twitch.tv/helix/users?login={channel_name}"
response = requests.get(url, headers=headers)
response.raise_for_status()
data = response.json()
if data.get("data"):
return data["data"][0]["id"]
else:
print("Channel not found.")
return None
def get_vods_from_yesterday(channel_id, token):
headers = {
"Client-ID": TWITCH_CLIENT_ID,
"Authorization": f"Bearer {token}"
}
# Define Prague timezone
prague_tz = ZoneInfo("Europe/Prague")
# Get today's date in Prague, then compute yesterday's date
today_prague = datetime.now(prague_tz).date()
yesterday = today_prague - timedelta(days=0)
# Create timezone-aware datetime objects for the entire day in Prague
start_time = datetime.combine(yesterday, time.min).replace(tzinfo=prague_tz)
end_time = datetime.combine(yesterday, time.max).replace(tzinfo=prague_tz)
# Fetch up to 100 archived VODs for the channel
url = f"https://api.twitch.tv/helix/videos?user_id={channel_id}&type=archive&first=100"
response = requests.get(url, headers=headers)
response.raise_for_status()
vods = []
for vod in response.json().get("data", []):
# Parse the published_at timestamp (Twitch uses UTC)
published_at = datetime.fromisoformat(vod["published_at"].replace("Z", "+00:00"))
# Convert published_at to Prague time
published_at_prague = published_at.astimezone(prague_tz)
if start_time <= published_at_prague <= end_time:
vods.append(vod)
return vods
# ---------------------------
# VOD Processing Functions
# ---------------------------
def download_vod(vod_url, output_filename):
# Use yt-dlp to download the VOD
command = ["yt-dlp", "-o", output_filename, vod_url]
subprocess.run(command, check=True)
print(f"Downloaded VOD to {output_filename}")
def extract_audio(video_file, audio_file):
# Use ffmpeg to extract the audio from the video
command = ["ffmpeg", "-i", video_file, "-vn", "-acodec", "mp3", audio_file, "-y"]
subprocess.run(command, check=True)
print(f"Extracted audio to {audio_file}")
def transcribe_audio(audio_file, model_name):
global CHANNEL_LANGUAGE
model = whisper.load_model(model_name, download_root="/app/models")
result = model.transcribe(audio_file, language=CHANNEL_LANGUAGE)
return result
def search_transcription(result, keywords):
matches = []
# Whisper returns segments with approximate start and end timestamps.
if "segments" in result:
for segment in result["segments"]:
segment_text = segment["text"].lower()
# Check if any keyword is in the segment text
for keyword in keywords:
if keyword.lower() in segment_text:
matches.append(segment)
break # Prevent duplicate entries if more than one keyword matches
return matches
def scrape_chat_log(vod_id, output_filename):
"""
Scrapes the entire chat log for a given VOD using Twitch v5 API.
The chat log is saved to output_filename as JSON.
"""
headers = {
"Client-ID": TWITCH_CLIENT_ID,
"Accept": "application/vnd.twitchtv.v5+json"
}
base_url = f"https://api.twitch.tv/v5/videos/{vod_id}/comments"
comments = []
cursor = None
while True:
params = {}
if cursor:
params["cursor"] = cursor
response = requests.get(base_url, headers=headers, params=params)
if response.status_code != 200:
print(f"Error fetching chat comments for VOD {vod_id}: {response.text}")
break
data = response.json()
comments.extend(data.get("comments", []))
cursor = data.get("_next")
if not cursor:
break
with open(output_filename, "w", encoding="utf-8") as f:
json.dump(comments, f, ensure_ascii=False, indent=4)
print(f"Chat log saved to {output_filename}")
def create_clip_from_vod(video_file, match_start, vod_id):
"""
Extract a 1-minute clip from the video_file.
The clip starts 15 seconds before match_start (or at 0 if match_start < 15).
"""
# Adjust start time to include 15 seconds of context (but not before the beginning)
clip_start = max(match_start - 15, 0)
clip_duration = 60 # seconds
clip_dir = os.path.join("clips", CHANNEL_NAME)
os.makedirs(clip_dir, exist_ok=True)
clip_filename = os.path.join(clip_dir, f"clip_{vod_id}_{int(match_start)}.mp4")
command = [
"ffmpeg",
"-ss", str(clip_start), # Start time for the clip
"-i", video_file, # Input video file
"-t", str(clip_duration), # Duration of the clip
"-c", "copy", # Copy the streams without re-encoding
clip_filename,
"-y" # Overwrite output file if exists
]
subprocess.run(command, check=True)
print(f"Clip created: {clip_filename}")
return clip_filename
def find_comments_by_keyword(chat_log, keyword):
"""
Given a chat log (list of comments) and a keyword,
return a list of comments that contain the keyword.
Each comment is expected to have a 'content_offset_seconds' field.
"""
matching_comments = []
for comment in chat_log:
# Adjust the key access based on the chat log's structure.
# For v5 API, each comment typically has:
# comment["message"]["body"]
text = comment.get("message", {}).get("body", "").lower()
if keyword.lower() in text:
matching_comments.append(comment)
return matching_comments
def create_clip_from_comment_timestamp(video_file, comment_timestamp, vod_id):
"""
Extract a 1-minute clip from the VOD starting 15 seconds before the comment timestamp.
"""
# Start the clip 15 seconds before the comment timestamp (if possible)
clip_start = max(comment_timestamp - 15, 0)
clip_duration = 60 # seconds
clip_filename = f"clip_{vod_id}_{int(comment_timestamp)}.mp4"
command = [
"ffmpeg",
"-ss", str(clip_start), # Start time for the clip
"-i", video_file, # Input video file
"-t", str(clip_duration), # Duration of the clip
"-c", "copy", # Copy streams without re-encoding
clip_filename,
"-y" # Overwrite if exists
]
subprocess.run(command, check=True)
print(f"Clip created: {clip_filename}")
return clip_filename
# ---------------------------
# Main Processing Pipeline
# ---------------------------
def main():
# Step 0: Get Twitch access token using client credentials
print("Obtaining access token...")
token = get_access_token()
print("Access token obtained.")
# Step 1: Get channel ID
channel_id = get_channel_id(CHANNEL_NAME, token)
if not channel_id:
return
# Step 2: Get yesterday's VODs
vods = get_vods_from_yesterday(channel_id, token)
if not vods:
print("No VODs from yesterday found.")
return
for vod in vods:
vod_url = vod["url"]
vod_id = vod["id"]
video_filename = f"vod_{vod_id}.mp4"
# video_filename = "vod_2382031096.mp4"
audio_filename = f"vod_{vod_id}.mp3"
# audio_filename = "vod_2382031096.mp3"
print(f"\nProcessing VOD: {vod_url}")
# Download the VOD
download_vod(vod_url, video_filename)
# Extract the audio track
extract_audio(video_filename, audio_filename)
# Transcribe using Whisper (this may take a while for long audio files)
# print("Transcribing audio. This may take some time...")
# result = transcribe_audio(audio_filename, MODEL_NAME)
# # Search for the keyword in the transcription
# matches = search_transcription(result, SEARCH_KEYWORDS)
print("Transcribing audio. This may take some time...")
result = transcribe_audio(audio_filename, MODEL_NAME)
chat_log_filename = f"chat_{vod_id}.json"
print("Scraping chat log...")
scrape_chat_log(vod_id, chat_log_filename)
transcripts_dir = os.path.join("transcripts", CHANNEL_NAME)
os.makedirs(transcripts_dir, exist_ok=True)
transcript_filename = os.path.join(transcripts_dir, f"transcript_{vod_id}.json")
with open(transcript_filename, "w", encoding="utf-8") as f:
json.dump(result, f, ensure_ascii=False, indent=4)
print(f"Transcript saved to {transcript_filename}")
# Search for the keyword in the transcription
matches = search_transcription(result, SEARCH_KEYWORDS)
if matches:
print(f"Found {len(matches)} mention(s) of '{SEARCH_KEYWORDS}' in VOD {vod_id}:")
for match in matches:
start = match["start"]
end = match["end"]
text = match["text"]
print(f" - At {start:.2f}s to {end:.2f}s: {text}")
create_clip_from_vod(video_filename, start, vod_id)
else:
print(f"No mentions of '{SEARCH_KEYWORDS}' found in VOD {vod_id}.")
# keyword = "your_keyword_here"
matches = find_comments_by_keyword(chat_log_filename, "Madmonq")
if matches:
for comment in matches:
# Use the content_offset_seconds from the comment as the timestamp.
timestamp = comment.get("content_offset_seconds")
print(f"Found a matching comment at {timestamp} seconds.")
create_clip_from_comment_timestamp(video_filename, timestamp, vod_id)
else:
print("No matching comments found.")
if __name__ == "__main__":
main()
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