Overview
Wolffish can convert any video file to MP3 audio in a single prompt. Drop in a video, tell it what you want, and the built-in ffmpeg capability handles the rest — no manual command-line work, no external tools.
Video Walkthrough
Setup
Required
- Wolffish installed and running
- DeepSeek V4 Pro API key — configured in Settings > Models. This workflow is simple enough that any model works, but DeepSeek V4 Pro is recommended — it handles the ffmpeg flag translation reliably at the lowest cost.
- FFmpeg — the agent checks for it automatically via
ffmpeg_check and offers to install it via ffmpeg_install if it’s missing. If you want to pre-install it yourself: brew install ffmpeg (macOS), sudo apt install ffmpeg (Linux), or choco install ffmpeg (Windows).
No Permissions Needed
This workflow uses shell execution and the ffmpeg capability only. No computer-use, no browser, no screen recording, no macOS permissions.
The Prompt
Attach your video file to the conversation, then send:
Convert this video to MP3 audio. Use high quality (192kbps).
Save it to the workspace folder with the same filename but
.mp3 extension.
Variations
Adjust the prompt to get exactly what you need:
| What You Want | Prompt |
|---|
| Lower file size | Convert this video to MP3 at 128kbps |
| Highest quality | Convert this video to MP3 at 320kbps |
| Just a clip | Extract audio from 1:30 to 3:45 as MP3 |
| Custom filename | Convert to MP3 and save as podcast-episode-12.mp3 |
| Different format | Convert this video to WAV or Convert to FLAC |
| Batch convert | Convert all .mp4 files in the workspace folder to MP3 |
How It Works
- The agent receives the attached video file.
- It calls
ffmpeg_check to verify ffmpeg is installed.
- If missing, it calls
ffmpeg_install to install it via your system’s package manager.
- It calls
ffmpeg_run with the appropriate arguments — something like:
-i input-video.mp4 -vn -acodec libmp3lame -ab 192k output-audio.mp3
- The converted MP3 appears in your workspace folder.
The -vn flag strips the video stream. The agent figures out the right codec and bitrate flags from your prompt — you don’t need to know ffmpeg syntax.
Limits
- File size — ffmpeg processes files on disk, so the practical limit is your available storage. The 500MB OOM-protection cap applies to audio buffers held in memory, not to file-based conversion.
- Codec support — ffmpeg supports virtually every audio and video format. If a codec is missing, the agent will attempt to install the required library.
- Processing time — proportional to file length and output quality. A 10-minute video converts in seconds. A 2-hour lecture takes a minute or two. No timeout is applied — the command runs until it finishes.
Cost & Model Guide
This is one of the cheapest workflows in Wolffish. The prompt is short, there’s no web research, and the heavy lifting happens in ffmpeg — not the LLM.
| Model | Approximate Cost |
|---|
| DeepSeek V4 Pro | < $0.001 |
| Claude Haiku | < $0.001 |
| Claude Sonnet | ~$0.002 |
| Claude Opus | ~$0.01 |
Use your cheapest available model. The LLM’s only job here is to translate your request into the right ffmpeg flags — any model handles that reliably.
Automating with Heartbeat
If you regularly receive video files that need audio extraction — say, meeting recordings or lecture captures — you can automate it. Open Settings > Heartbeat and add:
## Convert New Videos | Daily (09:00)
Check the workspace/recordings folder for any .mp4, .mov,
.webm, or .mkv files that don't already have a matching .mp3.
Convert each one to MP3 at 192kbps and save the .mp3 next to
the original video file. After converting, list what was
processed.
Change the folder path and schedule to match your workflow. Cron (*/30 * * * *) runs every 30 minutes for near-real-time conversion.
