feat: Integrate IndexTTS2 model and update related schemas and frontend components

qwen3-tts-backend/core/audiobook_service.py

@@ -573,6 +573,16 @@ async def generate_project(project_id: int, user: User, db: Session, chapter_ind
                             "language": "zh",
                             "instruct": _get_gendered_instruct(char.gender, design.instruct),
                         })
+                elif char.use_indextts2 and design.ref_audio_path and Path(design.ref_audio_path).exists():
+                    from core.tts_service import IndexTTS2Backend
+                    indextts2 = IndexTTS2Backend()
+                    audio_bytes = await indextts2.generate(
+                        text=seg.text,
+                        spk_audio_prompt=design.ref_audio_path,
+                        output_path=str(audio_path),
+                        emo_text=char.instruct or None,
+                        emo_alpha=0.6,
+                    )
                 else:
                     if design.voice_cache_id:
                         from core.cache_manager import VoiceCacheManager

qwen3-tts-backend/core/model_manager.py

@@ -121,3 +121,40 @@ class ModelManager:
             }
             for name, path in self.MODEL_PATHS.items()
         }
+
+
+class IndexTTS2ModelManager:
+    _instance = None
+    _lock = asyncio.Lock()
+
+    def __init__(self):
+        self.tts = None
+
+    @classmethod
+    async def get_instance(cls):
+        if cls._instance is None:
+            async with cls._lock:
+                if cls._instance is None:
+                    cls._instance = cls()
+        return cls._instance
+
+    async def get_model(self):
+        if self.tts is None:
+            await self._load()
+        return self.tts
+
+    async def _load(self):
+        from indextts.infer_indextts2 import IndexTTS2
+        from pathlib import Path
+        model_dir = Path(settings.MODEL_BASE_PATH) / "IndexTTS2"
+        loop = asyncio.get_event_loop()
+        self.tts = await loop.run_in_executor(
+            None,
+            lambda: IndexTTS2(
+                cfg_path=str(model_dir / "config.yaml"),
+                model_dir=str(model_dir),
+                is_fp16=False,
+                use_cuda_kernel=False,
+                use_deepspeed=False,
+            )
+        )

qwen3-tts-backend/core/tts_service.py

@@ -427,6 +427,73 @@ class AliyunTTSBackend(TTSBackend):
         return local_speaker
 
 
+class IndexTTS2Backend:
+    _gpu_lock = asyncio.Lock()
+
+    # Emotion keyword → index mapping
+    # Order: [happy, angry, sad, fear, hate, low, surprise, neutral]
+    _EMO_KEYWORDS = [
+        ['喜', '开心', '快乐', '高兴', '欢乐', '愉快', 'happy', '热情', '兴奋', '愉悦', '激动'],
+        ['怒', '愤怒', '生气', '恼', 'angry', '气愤', '愤慨'],
+        ['哀', '悲伤', '难过', '忧郁', '伤心', '悲', 'sad', '感慨', '沉重', '沉痛', '哭'],
+        ['惧', '恐惧', '害怕', '恐', 'fear', '担心', '紧张'],
+        ['厌恶', '厌', 'hate', '讨厌', '反感'],
+        ['低落', '沮丧', '消沉', 'low', '抑郁', '颓废'],
+        ['惊喜', '惊讶', '意外', 'surprise', '惊', '吃惊', '震惊'],
+        ['自然', '平静', '中性', '平和', 'neutral', '平淡', '冷静', '稳定'],
+    ]
+
+    @staticmethod
+    def _emo_text_to_vector(emo_text: str) -> Optional[list]:
+        text = emo_text.lower()
+        matched = []
+        for idx, words in enumerate(IndexTTS2Backend._EMO_KEYWORDS):
+            for word in words:
+                if word in text:
+                    matched.append(idx)
+                    break
+        if not matched:
+            return None
+        vec = [0.0] * 8
+        score = 0.8 if len(matched) == 1 else 0.5
+        for idx in matched:
+            vec[idx] = score
+        return vec
+
+    async def generate(
+        self,
+        text: str,
+        spk_audio_prompt: str,
+        output_path: str,
+        emo_text: str = None,
+        emo_alpha: float = 0.6,
+    ) -> bytes:
+        from core.model_manager import IndexTTS2ModelManager
+        manager = await IndexTTS2ModelManager.get_instance()
+        tts = await manager.get_model()
+        loop = asyncio.get_event_loop()
+
+        emo_vector = None
+        if emo_text and len(emo_text.strip()) > 0:
+            emo_vector = self._emo_text_to_vector(emo_text)
+            logger.info(f"IndexTTS2 emo_text={repr(emo_text)} → emo_vector={emo_vector}")
+
+        async with IndexTTS2Backend._gpu_lock:
+            await loop.run_in_executor(
+                None,
+                functools.partial(
+                    tts.infer,
+                    spk_audio_prompt=spk_audio_prompt,
+                    text=text,
+                    output_path=output_path,
+                    emo_vector=emo_vector,
+                    emo_alpha=1.0,
+                )
+            )
+        with open(output_path, 'rb') as f:
+            return f.read()
+
+
 class TTSServiceFactory:
     _local_backend: Optional[LocalTTSBackend] = None
     _aliyun_backend: Optional[AliyunTTSBackend] = None