youtube-transcription-generator（YouTube 转录生成器）

YouTube Transcription Generator (VLM Run)

Generate transcriptions from YouTube videos using vlmrun for speech-to-text and optional timestamps. This skill:

1. Downloads the YouTube video (or audio) with yt-dlp.
2. Transcribes the video with vlmrun (Orion visual AI).
3. Saves the transcript to a file (plain text or with timestamps).

Refer to vlmrun-cli-skill for vlmrun CLI setup, environment variables, and all vlmrun chat options.

How the assistant should use this skill

• Check .env for API key

- Ensure .env (or .env.local) contains VLMRUN_API_KEY. - If missing, instruct the user to set it before running any vlmrun commands.

• Use vlmrun for transcription only

- For transcription (and optional timestamps), use the vlmrun CLI with a video file as input (-i <video>). - vlmrun accepts video files (e.g. .mp4). For YouTube, the skill first downloads the video with yt-dlp, then passes the file to vlmrun.

• Workflow

- User provides a YouTube URL (and optionally output path). - Download the video (or audio-only for faster/smaller) with yt-dlp. - Run: vlmrun chat "Transcribe this video with timestamps for each section. Output the full transcript in a clear, readable format." -i <downloaded_file> -o <output_dir>. - Capture vlmrun’s response and save it as the transcript file (e.g. transcript.txt).

Prerequisites

• Python 3.10+
• VLMRUN_API_KEY (required for vlmrun)
• vlmrun CLI (vlmrun[cli])
• yt-dlp (for downloading YouTube videos)

See vlmrun-cli-skill for detailed vlmrun usage and examples (including video transcription).

Installation & Setup

From the youtube-transcription-generator directory:

Windows (PowerShell):

cd path\	o\youtube-transcription-generator
uv venv
.venv\Scripts\Activate.ps1
uv pip install -r requirements.txt

macOS/Linux:

cd path/to/youtube-transcription-generator
uv venv
source .venv/bin/activate
uv pip install -r requirements.txt

Copy .env_template to .env and set VLMRUN_API_KEY.

Quick Start: Transcribe a YouTube Video

Option A: Run the script (recommended)

# From youtube-transcription-generator directory, with venv activated
python scripts/run_transcription.py "https://www.youtube.com/watch?v=VIDEO_ID" -o ./output

This will:

1. Download the video with yt-dlp into the output directory.
2. Run vlmrun to transcribe the video.
3. Save the transcript as output/transcript.txt (and keep artifacts in output/).

Option B: Manual vlmrun (after downloading the video yourself)

# 1) Download with yt-dlp
yt-dlp -f "bv*[ext=mp4]+ba/best[ext=mp4]/best" -o video.mp4 "https://www.youtube.com/watch?v=VIDEO_ID"

# 2) Transcribe with vlmrun (see vlmrun-cli-skill for options)
vlmrun chat "Transcribe this video with timestamps for each section. Output the full transcript in a clear, readable format." -i video.mp4 -o ./output

Capture the vlmrun stdout and save it as your transcript, or use --json if you need structured output.

Prompt variants for vlmrun

• With timestamps:

"Transcribe this video with timestamps for each section. Output the full transcript in a clear, readable format."

• Plain transcript only:

"Transcribe everything said in this video. Output only the spoken text, no timestamps."

• Structured (e.g. JSON):

Use --json and ask for a structured format in the prompt (e.g. list of { "time": "...", "text": "..." }).

Workflow checklist

• [ ] Confirm vlmrun is installed and VLMRUN_API_KEY is set (see vlmrun-cli-skill).
• [ ] Install dependencies: uv pip install -r requirements.txt (includes vlmrun[cli] and yt-dlp).
• [ ] Run python scripts/run_transcription.py <youtube_url> -o ./output or download + vlmrun manually.
• [ ] Find transcript in the output directory (e.g. output/transcript.txt).

Troubleshooting

• vlmrun not found

Activate the venv and run: uv pip install "vlmrun[cli]". See vlmrun-cli-skill.

• Authentication errors

Verify VLMRUN_API_KEY in .env or the current shell.

• yt-dlp fails

Update yt-dlp: uv pip install -U yt-dlp. Check the URL is a valid public YouTube video.

• Large or long videos

Use audio-only download in the script (e.g. -f bestaudio) to reduce size and speed up transcription.