Installation

Arch Linux: paru -S chough-bin macOS: brew install --cask hyperpuncher/tap/chough Windows: winget install chough Source: go install github.com/hyperpuncher/chough/cmd/chough@latest

Requires: ffmpeg for audio/video support

Quick Reference

# Basic transcription (text to stdout)
chough audio.mp3

# Pipe audio from stdin
cat audio.mp3 | chough

# JSON with timestamps
chough -f json podcast.mp3 > transcript.json

# WebVTT subtitles
chough -f vtt -o subs.vtt video.mp4

# Low memory (30s chunks)
chough -c 30 audiobook.mp3

# Use remote server (requires CHOUGH_URL)
chough --remote audio.mp3

Flags

Chunk Size Guide

• 15-30s: Low memory (~500MB), higher error rate
• 60s: Balanced (default) - ~1.6GB RAM

Remote Mode

Use --remote flag to transcribe via an HTTP server instead of local processing. Requires CHOUGH_URL environment variable.

# Set server URL
export CHOUGH_URL=http://localhost:8080

# Transcribe via remote server
chough --remote audio.mp3

Check for CHOUGH_URL env var → verify /health endpoint → use server if healthy, otherwise fallback to local CLI.

Endpoints

Examples

# Upload file
curl -X POST http://localhost:8080/transcribe \
  -F "file=@audio.mp3" \
  -F "format=json" \
  -F "chunk_size=60"

# Transcribe from URL
curl -X POST http://localhost:8080/transcribe \
  -H "Content-Type: application/json" \
  -d '{"url": "https://example.com/audio.mp3", "format": "vtt"}'

# Base64 audio
curl -X POST http://localhost:8080/transcribe \
  -H "Content-Type: application/json" \
  -d '{"base64": "...", "format": "text"}'

# Health check
curl http://localhost:8080/health

Performance

Troubleshooting

Out of memory: Use -c 30 or -c 15 Model fails: Check internet, verify $XDG_CACHE_HOME is writable ffmpeg errors: Ensure ffmpeg is installed

Notes

• First run downloads ~650MB model to $XDG_CACHE_HOME/chough/models
• Auto-extracts audio from video files
• Set CHOUGH_MODEL env var to use custom model path
• Set CHOUGH_URL env var for --remote mode (must start with http:// or https://)
• VTT groups tokens into subtitle cues automatically

Docs

• GitHub