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CONTRIBUTING.md

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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
+
+```bash
+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:
+```bash
+uvx pre-commit run --all-files
+```
+
+## Running tests
+
+```bash
+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:
+
+```bash
+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.
+
+```bash
+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:
+
+![Architecture Diagram](./docs/model_arch.png)
+
+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_lm` in 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.