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Contributing to Kyutai Pocket TTS
We welcome contributions from the community!
We recommend using uv to work on this project. While you can use pip too, uv is less error-prone and faster.
The instructions below assume you are using uv.
Installing the pre-commit
uvx pre-commit install
This will handle file formatting and linting.
If you want to manually run the pre-commit hooks on all files, use:
uvx pre-commit run --all-files
Running tests
uv run pytest -n 3 -v
This will run the test suite with 3 parallel workers.
Running the CLI locally
You can run the CLI commands with:
uv run pocket-tts generate
Coding agents
We use AGENTS.md to manage the coding agents context. If your coding agent does
not supports reading from this file directly, you can just
use a symlink. The most common ones are already added in the .gitignore file.
ln -s AGENTS.md CLAUDE.md
# or
ln -s AGENTS.md QWEN.md
How does this model work?
Here is a high-level overview of the architecture:
Overall the model has four main components:
- The mimi vae encoder, to encode the audio prompts into a latent representation.
- The text "encoder" which is just a simple tokenizer + embedding layer.
- The calm model (
flow_lmin the codebase) to generate autoregegressive the audio latents. - The mimi vae decoder to decode the audio latents into waveform.
Note that two threads run in parallel in the current implementation:
- One with the calm model generating the latents.
- One with the mimi vae decoder decoding the latents into audio.