Initial commit: add Trading Studio voice-over pipeline for quant trading review videos.

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-06-12 13:19:44 +08:00
commit 5e95d3af2f
10 changed files with 1862 additions and 0 deletions
@@ -0,0 +1,155 @@
+"""
+Faster-Whisper CUDA 语音识别服务
+封装本地 GPU 加速的音频转写逻辑，适配 RTX 3060 Ti 8GB 显存。
+"""
+
+from __future__ import annotations
+
+import logging
+import traceback
+from typing import Optional, Tuple
+
+from config import (
+    WHISPER_COMPUTE_TYPE,
+    WHISPER_DEVICE,
+    WHISPER_LANGUAGE,
+    WHISPER_MODEL_SIZE,
+)
+
+logger = logging.getLogger(__name__)
+
+# 全局懒加载模型实例，避免 Gradio 重复初始化占用显存
+_model = None
+_model_error: Optional[str] = None
+
+
+def _is_cuda_error(exc: BaseException) -> bool:
+    """判断异常是否与 CUDA/GPU 相关。"""
+    msg = str(exc).lower()
+    cuda_keywords = (
+        "cuda",
+        "cudnn",
+        "cublas",
+        "gpu",
+        "out of memory",
+        "no kernel image",
+        "device-side assert",
+    )
+    return any(k in msg for k in cuda_keywords)
+
+
+def get_whisper_model():
+    """
+    获取或初始化 Faster-Whisper 模型。
+    强制 device=cuda, compute_type=float16。
+    """
+    global _model, _model_error
+
+    if _model is not None:
+        return _model, None
+
+    if _model_error is not None:
+        return None, _model_error
+
+    try:
+        from faster_whisper import WhisperModel
+
+        logger.info(
+            "正在加载 Whisper 模型: size=%s, device=%s, compute_type=%s",
+            WHISPER_MODEL_SIZE,
+            WHISPER_DEVICE,
+            WHISPER_COMPUTE_TYPE,
+        )
+        _model = WhisperModel(
+            WHISPER_MODEL_SIZE,
+            device=WHISPER_DEVICE,
+            compute_type=WHISPER_COMPUTE_TYPE,
+        )
+        logger.info("Whisper 模型加载成功。")
+        return _model, None
+
+    except ImportError as exc:
+        _model_error = (
+            "未安装 faster-whisper，请执行: pip install faster-whisper\n"
+            f"原始错误: {exc}"
+        )
+        logger.exception("faster-whisper 导入失败")
+        return None, _model_error
+
+    except Exception as exc:
+        if _is_cuda_error(exc):
+            _model_error = (
+                "CUDA 初始化失败，请检查 NVIDIA 驱动、CUDA 运行时及 cuDNN 是否正确安装。\n"
+                f"错误详情: {exc}\n"
+                f"{traceback.format_exc()}"
+            )
+        else:
+            _model_error = f"Whisper 模型加载失败: {exc}\n{traceback.format_exc()}"
+        logger.exception("Whisper 模型加载异常")
+        return None, _model_error
+
+
+def transcribe_audio(audio_path: str) -> Tuple[bool, str]:
+    """
+    将音频文件转写为中文文本。
+
+    Args:
+        audio_path: 本地音频文件绝对或相对路径
+
+    Returns:
+        (success, text_or_error_message)
+    """
+    if not audio_path:
+        return False, "未提供音频文件路径。"
+
+    model, init_error = get_whisper_model()
+    if model is None:
+        return False, init_error or "Whisper 模型不可用。"
+
+    try:
+        segments, info = model.transcribe(
+            audio_path,
+            language=WHISPER_LANGUAGE,
+            beam_size=5,
+            vad_filter=True,
+        )
+
+        text_parts = []
+        for segment in segments:
+            text_parts.append(segment.text.strip())
+
+        result_text = "".join(text_parts).strip()
+
+        if not result_text:
+            return False, (
+                "识别结果为空，请检查音频是否有效、音量是否足够，"
+                f"或尝试更换格式。检测到语言: {getattr(info, 'language', 'unknown')}"
+            )
+
+        logger.info(
+            "转写完成: 语言=%s, 概率=%.2f, 字数=%d",
+            getattr(info, "language", "?"),
+            getattr(info, "language_probability", 0.0),
+            len(result_text),
+        )
+        return True, result_text
+
+    except Exception as exc:
+        if _is_cuda_error(exc):
+            err = (
+                "CUDA 推理异常：显存可能不足或 GPU 状态异常。"
+                "建议关闭其他占用显存的进程后重试。\n"
+                f"错误详情: {exc}"
+            )
+        else:
+            err = f"音频转写失败: {exc}\n{traceback.format_exc()}"
+
+        logger.exception("transcribe_audio 失败")
+        return False, err
+
+
+def reset_whisper_model() -> None:
+    """释放模型引用（用于调试或显存回收）。"""
+    global _model, _model_error
+    _model = None
+    _model_error = None