Initial commit: InkFlow — EPUB vers livre audio local (MLX/Kokoro)

backend/inkflow/tts/qwen3.py

@@ -0,0 +1,58 @@
+"""Backend Qwen3-TTS (qualite + clonage par audio de reference) — rendu final.
+
+Deux modes :
+- voix preglee : `voice` (ex "Chelsie") + `language` ("French").
+- clonage     : `ref_audio` (+ `ref_text` transcription du clip) pour imiter une
+  voix de la voicebank, attribuee a un personnage.
+"""
+from __future__ import annotations
+
+import numpy as np
+
+from ..settings import get_settings
+from .base import TTSBackend, VoiceSpec, to_mono_float32
+from .chunk import chunk_text
+
+# Qwen3 tolere des sequences plus longues que Kokoro, mais on borne quand meme.
+_QWEN_MAX_CHARS = 500
+
+
+class Qwen3Backend(TTSBackend):
+    name = "qwen3"
+
+    def __init__(self, model_id: str | None = None, language: str | None = None):
+        settings = get_settings()
+        self.model_id = model_id or settings.qwen3_model
+        self.language = language or settings.language
+        self._model = None
+        self._sample_rate = 24000
+
+    def _ensure_loaded(self) -> None:
+        if self._model is None:
+            from mlx_audio.tts.utils import load_model
+            self._model = load_model(self.model_id)
+
+    def default_voice(self) -> VoiceSpec:
+        return VoiceSpec(preset=get_settings().qwen3_default_voice)
+
+    def _gen_kwargs(self, voice: VoiceSpec) -> dict:
+        kwargs: dict = {"language": self.language, "speed": voice.speed}
+        if voice.ref_audio:  # mode clonage
+            kwargs["ref_audio"] = voice.ref_audio
+            if voice.ref_text:
+                kwargs["ref_text"] = voice.ref_text
+        else:                # mode voix preglee
+            kwargs["voice"] = voice.preset or get_settings().qwen3_default_voice
+        return kwargs
+
+    def synthesize(self, text: str, voice: VoiceSpec) -> tuple[np.ndarray, int]:
+        self._ensure_loaded()
+        kwargs = self._gen_kwargs(voice)
+        pieces: list[np.ndarray] = []
+        for chunk in chunk_text(text, max_chars=_QWEN_MAX_CHARS):
+            for result in self._model.generate(text=chunk, **kwargs):
+                self._sample_rate = getattr(result, "sample_rate", self._sample_rate)
+                pieces.append(to_mono_float32(result.audio))
+        if not pieces:
+            return np.zeros(0, dtype=np.float32), self._sample_rate
+        return np.concatenate(pieces), self._sample_rate