Initial commit: audio2text 双语字幕生成服务

- 音频/视频转双语(英/中)SRT 字幕，Docker 容器化，CPU 开发/GPU 生产同一份代码
- faster-whisper ASR(词级时间戳) + 断句时间戳重算 + NLLB 翻译(模型不共驻)
- 分片上传(断点续传) + SQLite 持久化 + 主页/历史/日志页面
- 历史页文件名搜索；缓存定时清理(默认保留7天，可配置)
- 双 Dockerfile(cpu/gpu) + setup/start/stop 脚本

app/services/model_manager.py

@@ -0,0 +1,136 @@
+"""模型管理器：ASR 与翻译模型不共驻，任一时刻 GPU 上只有一个模型。
+
+设计：
+- 单例 ModelManager 跟踪当前加载的模型类型（none / asr / translator）
+- get_asr(): 若翻译器在内存 → 先卸载（del + gc + empty_cache）→ 加载 faster-whisper
+- get_translator(): 若 ASR 在内存 → 先卸载 → 加载 NLLB
+- 翻译阶段独占显存，可用大 batch_size；ASR 阶段同理
+
+这样在 24G 3090 上无需担心显存叠加，CPU dev 时也省内存。
+"""
+
+from __future__ import annotations
+
+import gc
+import logging
+import threading
+from typing import Any
+
+from ..config import get_settings
+
+logger = logging.getLogger("audio2text.models")
+
+# 全局单例 + 锁：模型加载/卸载必须串行
+_lock = threading.Lock()
+
+
+def _free_memory() -> None:
+    """释放 Python 对象与 GPU 缓存。"""
+    gc.collect()
+    try:
+        import torch
+        if torch.cuda.is_available():
+            torch.cuda.empty_cache()
+            torch.cuda.synchronize()
+    except Exception:  # pragma: no cover
+        pass
+
+
+class ModelManager:
+    """ASR / 翻译模型的不共驻管理器。"""
+
+    def __init__(self) -> None:
+        self._asr: Any = None       # faster_whisper.WhisperModel
+        self._translator: Any = None  # transformers pipeline
+        self._current: str = "none"  # none | asr | translator
+
+    # ---------------- ASR ----------------
+
+    def get_asr(self) -> Any:
+        """返回已加载的 faster-whisper 模型；必要时先卸载翻译器。"""
+        with _lock:
+            if self._asr is not None:
+                return self._asr
+            if self._translator is not None:
+                self._unload_translator_locked()
+            s = get_settings().asr
+            logger.debug("加载 ASR 模型 model=%s device=%s compute_type=%s",
+                        s.model, s.device, s.compute_type)
+            from faster_whisper import WhisperModel
+            # device/compute_type 组合：cpu+int8 / cuda+float16
+            self._asr = WhisperModel(
+                s.model, device=s.device, compute_type=s.compute_type,
+            )
+            self._current = "asr"
+            logger.debug("ASR 模型已就绪。")
+            return self._asr
+
+    def unload_asr(self) -> None:
+        with _lock:
+            self._unload_asr_locked()
+
+    def _unload_asr_locked(self) -> None:
+        if self._asr is None:
+            return
+        logger.debug("卸载 ASR 模型（释放显存供翻译器独占）。")
+        # faster-whisper 模型无显式 close，del 即可
+        del self._asr
+        self._asr = None
+        self._current = "none" if self._translator is None else "translator"
+        _free_memory()
+
+    # ---------------- 翻译器 ----------------
+
+    def get_translator(self) -> Any:
+        """返回已加载的 NLLB 翻译 pipeline；必要时先卸载 ASR。"""
+        with _lock:
+            if self._translator is not None:
+                return self._translator
+            if self._asr is not None:
+                self._unload_asr_locked()
+            s = get_settings().translation
+            logger.debug("加载翻译模型 model=%s device=%s", s.model, s.device)
+            from transformers import pipeline
+            self._translator = pipeline(
+                "translation",
+                model=s.model,
+                device=s.device,
+                src_lang=s.src_lang,
+                tgt_lang=s.tgt_lang,
+            )
+            self._current = "translator"
+            logger.debug("翻译模型已就绪（独占显存，可用大 batch）。")
+            return self._translator
+
+    def unload_translator(self) -> None:
+        with _lock:
+            self._unload_translator_locked()
+
+    def _unload_translator_locked(self) -> None:
+        if self._translator is None:
+            return
+        logger.debug("卸载翻译模型。")
+        # 释放 pipeline 持有的 model + tokenizer
+        mdl = getattr(self._translator, "model", None)
+        tok = getattr(self._translator, "tokenizer", None)
+        del self._translator, mdl, tok
+        self._translator = None
+        self._current = "none" if self._asr is None else "asr"
+        _free_memory()
+
+    # ---------------- 状态 ----------------
+
+    @property
+    def current(self) -> str:
+        return self._current
+
+
+# 进程级单例
+_manager: ModelManager | None = None
+
+
+def get_model_manager() -> ModelManager:
+    global _manager
+    if _manager is None:
+        _manager = ModelManager()
+    return _manager