The repo also includes a Gitea Actions workflow at .gitea/workflows/ci.yml that tests and builds both packages on pushes to main and pull requests.

Docker backend (no image build)

Run the backend directly from an official Python image without creating a Dockerfile:

docker compose up backend

This uses python:3.14-slim, installs ffmpeg and openai-whisper at container startup, mounts this repo into the container, and serves the API on http://localhost:8000.

Backend setup

cd backend
pip install -e .
uvicorn server:app --app-dir src --host 0.0.0.0 --port 8000

The backend machine must already have the upstream whisper CLI available on PATH.

CLI setup

cd cli
pip install -e .
whisper-remote ./audio.mp3 --model base --language en --output-format txt

PowerShell:

$env:WHISPER_REMOTE = "http://your-server:8000"
whisper-remote .\audio.mp3 --model base --language en --output-format txt

Bash:

export WHISPER_REMOTE=http://your-server:8000
whisper-remote ./audio.mp3 --model base --language en --output-format txt

Supported v1 options

model selection
language forwarding
transcript output formats: txt, vtt, srt, tsv, json
file upload to the backend
backend-side cleanup of uploaded and generated files after each request

By default the CLI prints the returned transcript to stdout. Use --to-file to save it locally.