Add local Kokoro TTS server

.gitignore

@@ -191,3 +191,10 @@ tests/testbench/docs/dev_note.txt
 
 # yui-origin Live2D 模型源码打包在 assets/yui-origin.tar.gz；build_frontend 解压到此
 /static/yui-origin/
+
+# Local lightweight TTS model files are large runtime assets. Keep directory
+# placeholders in git, but do not commit downloaded ONNX / voice data files.
+local_server/local_tts_server/kokoro_models/*
+!local_server/local_tts_server/kokoro_models/.gitkeep
+.uv-cache-local/
+.venv-local-tts/

local_server/local_tts_server/README.md

@@ -0,0 +1,84 @@
+# NEKO Local Lightweight TTS
+
+This service is the first-phase local TTS bridge for NEKO. It deliberately
+implements the same WebSocket protocol expected by `local_cosyvoice_worker`, so
+NEKO can use it without changing the main TTS pipeline.
+
+## Protocol
+
+Endpoint:
+
+```text
+ws://127.0.0.1:50000/v1/audio/speech/stream
+```
+
+Client messages:
+
+```json
+{"voice":"kokoro:zf_001","speed":1.0}
+{"text":"Hello from NEKO."}
+{"text":"Local Kokoro TTS test."}
+{"event":"end"}
+```
+
+Server response:
+
+```text
+binary PCM s16le chunks, mono, 22050 Hz
+```
+
+NEKO's existing `local_cosyvoice_worker` then resamples this audio to 48 kHz.
+
+## Start
+
+From the repository root:
+
+```bash
+uv run python local_server/local_tts_server/server.py --host 127.0.0.1 --port 50000
+```
+
+In NEKO settings, use the existing local custom TTS path:
+
+```text
+ws://127.0.0.1:50000
+```
+
+Keep the existing custom/GPT-SoVITS toggle enabled, because the current router
+uses that switch to route `ws://` custom TTS URLs into `local_cosyvoice_worker`.
+
+## Voice Selector
+
+The service accepts a model prefix in `voice`:
+
+```text
+kokoro:<voice>
+melotts:<voice>
+melo:<voice>
+chattts:<voice>
+```
+
+If the prefix is missing, `LOCAL_TTS_DEFAULT_MODEL` is used. The default is
+`kokoro`.
+
+## Kokoro / MeloTTS / ChatTTS
+
+These are exposed through command adapters for now. The command must write a
+16-bit WAV file to `{out_file}`.
+
+The Kokoro launcher defaults to the Chinese-enhanced
+`hexgrad/Kokoro-82M-v1.1-zh` model and voice `zf_001`.
+If `local_server/local_tts_server/kokoro_models/Kokoro-82M-v1.1-zh` exists,
+the launcher uses that local model directory before falling back to Hugging
+Face cache/download.
+
+```bash
+set LOCAL_TTS_KOKORO_MODEL_DIR=F:\models\Kokoro-82M-v1.1-zh
+set LOCAL_TTS_KOKORO_REPO_ID=hexgrad/Kokoro-82M-v1.1-zh
+set LOCAL_TTS_KOKORO_DEFAULT_VOICE=zf_001
+set LOCAL_TTS_KOKORO_CMD=python F:\tts_wrappers\kokoro_cli.py "{text_file}" "{out_file}" "{voice}" {speed}
+set LOCAL_TTS_MELOTTS_CMD=python F:\tts_wrappers\melotts_cli.py --text-file "{text_file}" --out "{out_file}" --voice "{voice}" --speed {speed}
+set LOCAL_TTS_CHATTTS_CMD=python F:\tts_wrappers\chattts_cli.py --text-file "{text_file}" --out "{out_file}" --voice "{voice}" --speed {speed}
+```
+
+ChatTTS is AGPL-3.0. Keep it as an optional external backend unless the product
+licensing story is settled.

local_server/local_tts_server/kokoro_cli.py

@@ -0,0 +1,202 @@
+"""Minimal Kokoro v1.1-zh CLI wrapper for local_tts_server.
+
+Usage:
+    python kokoro_cli.py <text_file> <out_file> <voice> <speed>
+
+Reads text from <text_file>, synthesizes with kokoro, writes WAV to <out_file>.
+"""
+
+from __future__ import annotations
+
+import argparse
+import os
+import sys
+import wave
+from pathlib import Path
+
+import numpy as np
+
+
+DEFAULT_REPO_ID = "hexgrad/Kokoro-82M-v1.1-zh"
+DEFAULT_VOICE = "zf_001"
+SAMPLE_RATE = 24000
+SCRIPT_DIR = Path(__file__).resolve().parent
+DEFAULT_LOCAL_REPO = SCRIPT_DIR / "kokoro_models" / "Kokoro-82M-v1.1-zh"
+
+
+def _audio_from_result(result):
+    if hasattr(result, "audio"):
+        return result.audio
+    if isinstance(result, tuple) and result:
+        return result[-1]
+    return None
+
+
+def _infer_lang_code(voice: str) -> str:
+    # Kokoro uses single-letter lang codes: z=zh, a=en-us, b=en-gb.
+    if voice.startswith(("a", "af", "am")):
+        return "a"
+    if voice.startswith(("b", "bf", "bm")):
+        return "b"
+    return "z"
+
+
+def _speed_callable(base_speed: float):
+    """Mitigate rushed long Chinese phoneme sequences in v1.1-zh."""
+
+    base = base_speed if base_speed > 0 else 1.0
+
+    def speed_by_len(len_ps: int) -> float:
+        speed = 1.0
+        if len_ps > 83 and len_ps < 183:
+            speed = 1.0 - (len_ps - 83) / 500.0
+        elif len_ps >= 183:
+            speed = 0.8
+        return max(0.5, speed * base)
+
+    return speed_by_len
+
+
+def _resolve_local_model_dir() -> Path | None:
+    raw = os.getenv("LOCAL_TTS_KOKORO_MODEL_DIR", "").strip()
+    if raw:
+        path = Path(raw)
+        return path if path.is_dir() else None
+    return DEFAULT_LOCAL_REPO if DEFAULT_LOCAL_REPO.is_dir() else None
+
+
+def _find_model_file(model_dir: Path) -> Path | None:
+    preferred = model_dir / "kokoro-v1_1-zh.pth"
+    if preferred.is_file():
+        return preferred
+    candidates = sorted(model_dir.glob("*.pth"))
+    return candidates[0] if candidates else None
+
+
+def _resolve_voice(voice: str, model_dir: Path | None) -> str:
+    if not model_dir:
+        return voice
+    if voice.endswith(".pt"):
+        return voice
+    local_voice = model_dir / "voices" / f"{voice}.pt"
+    return str(local_voice) if local_voice.is_file() else voice
+
+
+def _available_local_voices(model_dir: Path | None) -> set[str]:
+    if not model_dir:
+        return set()
+    voices_dir = model_dir / "voices"
+    if not voices_dir.is_dir():
+        return set()
+    return {path.stem for path in voices_dir.glob("*.pt") if path.is_file()}
+
+
+def synthesize(text_path: str, out_path: str, voice: str, speed: float) -> int:
+    try:
+        import torch
+        from kokoro import KModel, KPipeline
+    except ImportError:
+        print(
+            'kokoro v1.1-zh deps missing. Run: uv pip install "kokoro>=0.8.2" "misaki[zh]>=0.8.2"',
+            file=sys.stderr,
+        )
+        return 1
+
+    text = Path(text_path).read_text(encoding="utf-8").strip()
+    if not text:
+        print("Empty text file", file=sys.stderr)
+        return 1
+
+    model_dir = _resolve_local_model_dir()
+    repo_id = os.getenv("LOCAL_TTS_KOKORO_REPO_ID", DEFAULT_REPO_ID).strip() or DEFAULT_REPO_ID
+    voice = (voice or "").strip() or os.getenv("LOCAL_TTS_KOKORO_DEFAULT_VOICE", DEFAULT_VOICE)
+    available_voices = _available_local_voices(model_dir)
+    if available_voices and voice not in available_voices:
+        fallback_voice = os.getenv("LOCAL_TTS_KOKORO_DEFAULT_VOICE", DEFAULT_VOICE).strip() or DEFAULT_VOICE
+        if fallback_voice not in available_voices:
+            fallback_voice = sorted(available_voices)[0]
+        print(
+            f"Kokoro voice '{voice}' not found in local model dir; falling back to '{fallback_voice}'.",
+            file=sys.stderr,
+        )
+        voice = fallback_voice
+    pipeline_voice = _resolve_voice(voice, model_dir)
+    lang = _infer_lang_code(voice)
+    device = os.getenv("LOCAL_TTS_KOKORO_DEVICE", "").strip()
+    if not device:
+        device = "cuda" if torch.cuda.is_available() else "cpu"
+
+    if model_dir:
+        config_path = model_dir / "config.json"
+        model_path = _find_model_file(model_dir)
+        if not config_path.is_file() or model_path is None:
+            print(
+                f"Invalid LOCAL_TTS_KOKORO_MODEL_DIR: {model_dir} "
+                "(expected config.json and a .pth model file)",
+                file=sys.stderr,
+            )
+            return 1
+        model = KModel(repo_id=repo_id, config=str(config_path), model=str(model_path)).to(device).eval()
+    else:
+        model = KModel(repo_id=repo_id).to(device).eval()
+
+    en_pipeline = None
+    en_callable = None
+    if lang == "z":
+        en_pipeline = KPipeline(lang_code="a", repo_id=repo_id, model=False)
+
+        def en_callable(text_part: str):
+            if text_part == "Kokoro":
+                return "kˈOkəɹO"
+            if text_part == "Sol":
+                return "sˈOl"
+            return next(en_pipeline(text_part)).phonemes
+
+    pipeline = KPipeline(
+        lang_code=lang,
+        repo_id=repo_id,
+        model=model,
+        en_callable=en_callable,
+    )
+    effective_speed = _speed_callable(speed) if lang == "z" else speed
+    generator = pipeline(text, voice=pipeline_voice, speed=effective_speed)
+
+    chunks: list[np.ndarray] = []
+    for result in generator:
+        audio = _audio_from_result(result)
+        if audio is not None:
+            chunks.append(np.asarray(audio, dtype=np.float32))
+
+    if not chunks:
+        print("No audio generated", file=sys.stderr)
+        return 1
+
+    pcm = np.concatenate(chunks)
+    pcm = np.clip(pcm, -1.0, 1.0)
+    pcm_int16 = (pcm * 32767.0).astype(np.int16)
+
+    with wave.open(out_path, "wb") as wf:
+        wf.setnchannels(1)
+        wf.setsampwidth(2)
+        wf.setframerate(SAMPLE_RATE)
+        wf.writeframes(pcm_int16.tobytes())
+
+    print(
+        f"Wrote {out_path}: {len(pcm_int16)} samples @ {SAMPLE_RATE} Hz "
+        f"repo={repo_id} model_dir={model_dir or '<hf-cache>'} voice={voice} device={device}"
+    )
+    return 0
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser(description="Kokoro CLI wrapper for local_tts")
+    parser.add_argument("text_file")
+    parser.add_argument("out_file")
+    parser.add_argument("voice")
+    parser.add_argument("speed", type=float)
+    args = parser.parse_args()
+    return synthesize(args.text_file, args.out_file, args.voice, args.speed)
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())

local_server/local_tts_server/kokoro_models/.gitkeep

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+