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