# Kokoro

[hexgrad/Kokoro-82M](https://huggingface.co/hexgrad/Kokoro-82M) served
via [remsky/Kokoro-FastAPI](https://github.com/remsky/Kokoro-FastAPI).

## Why this stack exists

Lowest-latency English TTS in the fleet by a wide margin — ~300 ms
time-to-first-audio on GPU, 35-100x realtime, ~1 GB VRAM at fp16.
Native streaming (Kokoro's `KPipeline.__call__` is a per-phrase
generator) and the wrapper exposes it via OpenAI-compat `stream=true`
over chunked HTTP — drop-in for any OpenAI SDK client.

Complementary to the rest of the TTS slate:

| | use case |
|---|---|
| **Kokoro** | low-latency English, fixed voice library |
| **Chatterbox Turbo** | low-latency English w/ voice cloning + paralinguistic tags |
| **IndexTTS-2** | English voice cloning + emotion vector / text control |
| **Qwen3-TTS-1.7B-Base** | high-quality English voice cloning |
| **CosyVoice 3** | multilingual (Chinese-leaning) |
| **VibeVoice 1.5B** | long-form podcast / multi-speaker dialogue |

## API

OpenAI-compat at `http://10.100.79.3:8193`:

```bash
# List built-in voices (~60 of them, named like af_bella, am_adam, jf_*, zf_*).
curl http://10.100.79.3:8193/v1/audio/voices

# Single-shot synthesis.
curl -fsS -X POST http://10.100.79.3:8193/v1/audio/speech \
  -H 'Content-Type: application/json' \
  -d '{"model":"kokoro","input":"Hello there.","voice":"af_bella","response_format":"wav"}' \
  > out.wav

# Streaming — pipe straight into a player.
curl -fsS -X POST http://10.100.79.3:8193/v1/audio/speech \
  -H 'Content-Type: application/json' \
  -d '{"model":"kokoro","input":"long passage here…","voice":"af_bella","stream":true}' \
  | mpv --no-cache -

# Voice mixing — sum voicepacks with weights.
curl -fsS -X POST http://10.100.79.3:8193/v1/audio/speech \
  -H 'Content-Type: application/json' \
  -d '{"model":"kokoro","input":"hello","voice":"af_bella(2)+af_heart(1)","response_format":"wav"}' \
  > mix.wav
```

Web UI at `/web` (browse voices + try in-place); OpenAPI at `/docs`.

Supported `response_format`: `mp3 | wav | opus | flac | pcm`.

## Voices

- **Built-in**: 60+ in 8 languages (en-US, en-GB, ja, zh, es, fr, hi, it).
  Discoverable via `GET /v1/audio/voices` — naming convention is
  `<lang_code><gender_letter>_<name>` (e.g. `af_bella`, `am_adam`,
  `jf_alpha`, `zf_xiaobei`).
- **Custom blends**: weighted-average existing voicepacks into a new
  named voice using `playbooks/blend-kokoro-voice.yaml` (script:
  `scripts/blend_kokoro_voice.py`). Mirrors the wrapper's request-time
  `voice="a(w)+b(w)"` math but persists the result so it shows up in
  `/v1/audio/voices`. Example shipped: `athena = af_bella(2)+af_aoede(1)`
  normalized.

  ```bash
  scripts/elway irv-ml1 --playbook playbooks/blend-kokoro-voice.yaml \
    --var 'recipe=af_bella(1)+am_adam(1)' --var out_name=androgyne
  # add --var force=1 to overwrite an existing voice
  ```

  Persistence design: the wrapper enumerates exactly one directory
  (`VOICES_DIR`, default in-image `/app/api/src/voices/v1_0`).
  compose.yaml overrides `VOICES_DIR=/app/user_voices` (host bind
  mount `/worktank/kokoro/user_voices`) and adds a `command:` shim
  that `cp -r`'s the in-image built-ins into that dir on every
  container start. Result:
  * built-in voicepacks re-seed on each start, so image upgrades that
    add/change built-ins propagate automatically
  * custom blends written by the script live on the host bind mount —
    survive `docker restart`, `up --force-recreate`, image upgrade,
    and host reboot
  * one-time prereq: the host dir must be chowned to `1001:1001`
    (uid of `appuser` inside the container) so the shim's cp can
    write — handled by `playbooks/deploy-kokoro.yaml`
- **Cloned voices**: training a Kokoro voice from samples is non-
  trivial — consult the hexgrad community for how-to. For voice
  cloning use Chatterbox Turbo or IndexTTS-2 instead.

## Deploy

```bash
scripts/elway irv-ml1 --playbook playbooks/deploy-kokoro.yaml
```

First deploy: ~6.5 GB image pull from GHCR (~2-5 min on a fast link).
No model download on first run — Kokoro-82M weights are baked in.
Subsequent starts: a few seconds.

## License

Apache-2.0 for both the wrapper code (remsky/Kokoro-FastAPI) and the
Kokoro-82M weights (hexgrad).
