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/pipeline.py

@@ -0,0 +1,153 @@
+"""转写管线编排：提取音频 → ASR → 断句 → 翻译 → 写 SRT。
+
+任务状态机：
+    queued → extracting → transcribing → segmenting → translating → done
+    任一步失败 → failed
+
+模型不共驻：ASR 与翻译分阶段加载，翻译时先卸载 Whisper 释放显存跑大 batch。
+管线在后台线程跑（每个任务一个线程），通过 DB 更新状态与进度。
+"""
+
+from __future__ import annotations
+
+import logging
+import threading
+import traceback
+from datetime import datetime, timezone
+from pathlib import Path
+
+from ..config import get_settings
+from ..database import get_session_local
+from ..models.task import Task
+from . import ffmpeg_service, asr_service, segmenter, translate_service, srt_writer
+from .types import Subtitle
+
+logger = logging.getLogger("audio2text.pipeline")
+
+# 进度锚点（各阶段在 0-100 中的占比）
+P_EXTRACT = 5.0
+P_TRANSCRIBE_START = 5.0
+P_TRANSCRIBE_END = 55.0
+P_SEGMENT_START = 55.0
+P_SEGMENT_END = 60.0
+P_TRANSLATE_START = 60.0
+P_TRANSLATE_END = 98.0
+P_DONE = 100.0
+
+
+def enqueue_task(task_id: int) -> None:
+    """把任务交给后台线程处理（非阻塞，供 upload_service.complete 调用）。"""
+    t = threading.Thread(target=_run_task, args=(task_id,), daemon=True)
+    t.start()
+    logger.info("任务 %d 已入队（后台线程 %s）。", task_id, t.name)
+
+
+def _run_task(task_id: int) -> None:
+    """后台执行完整管线。所有异常都被捕获并写入 task.error。"""
+    db = get_session_local()()
+    try:
+        task = db.get(Task, task_id)
+        if task is None:
+            logger.error("任务 %d 不存在。", task_id)
+            return
+        _pipeline(db, task)
+    except Exception as exc:
+        logger.exception("任务 %d 失败：%s", task_id, exc)
+        _mark_failed(db, task_id, str(exc))
+    finally:
+        db.close()
+
+
+def _pipeline(db, task: Task) -> None:
+    s = get_settings()
+    src = s.upload_dir() / task.source_path
+
+    # ---------- 1. 提取音频 ----------
+    _set_status(db, task, "extracting", P_EXTRACT)
+    wav = s.work_dir() / f"task_{task.id}.wav"
+    ffmpeg_service.extract_audio(src, wav)
+
+    # 按配置决定是否删原始视频（提取成功后）
+    if s.processing.delete_original_after_extract and src.is_file():
+        try:
+            src.unlink()
+            logger.info("已删除原始视频 %s（delete_original_after_extract=true）。", src.name)
+        except OSError as exc:
+            logger.warning("删除原始视频失败 %s: %s", src, exc)
+
+    # ---------- 2. 语音识别 ----------
+    _set_status(db, task, "transcribing", P_TRANSCRIBE_START)
+    segments = asr_service.transcribe(wav)
+    _set_status(db, task, "transcribing", P_TRANSCRIBE_END,
+                note=f"识别出 {len(segments)} 段")
+
+    # ---------- 3. 断句 + 时间戳重算 ----------
+    _set_status(db, task, "segmenting", P_SEGMENT_START)
+    subs = segmenter.resegment(segments)
+    _set_status(db, task, "segmenting", P_SEGMENT_END,
+                note=f"重组为 {len(subs)} 条字幕")
+
+    # ---------- 4. 翻译 ----------
+    _set_status(db, task, "translating", P_TRANSLATE_START)
+    # 翻译阶段：model_manager 会自动卸载 ASR、加载翻译器（独占显存）
+    zh_texts = translate_service.translate(subs)
+    _set_status(db, task, "translating", P_TRANSLATE_END,
+                note=f"翻译 {len(zh_texts)} 条")
+
+    # ---------- 5. 写 SRT ----------
+    out_dir = s.output_dir()
+    stem = Path(task.filename).stem
+    en_path = out_dir / f"task_{task.id}/{stem}.en.srt"
+    zh_path = out_dir / f"task_{task.id}/{stem}.zh.srt"
+    bi_path = out_dir / f"task_{task.id}/{stem}.srt"
+
+    srt_writer.write_srt(subs, en_path)
+    # 中文 SRT（用译文 + 同时间戳）
+    zh_subs = [Subtitle(text=zh, start=sub.start, end=sub.end)
+               for zh, sub in zip(zh_texts, subs)]
+    srt_writer.write_srt(zh_subs, zh_path)
+    srt_writer.write_bilingual_srt(subs, zh_texts, bi_path)
+
+    # 记录相对路径
+    task.en_srt_path = str(en_path.relative_to(out_dir))
+    task.zh_srt_path = str(zh_path.relative_to(out_dir))
+    task.bilingual_srt_path = str(bi_path.relative_to(out_dir))
+    task.status = "done"
+    task.progress = P_DONE
+    task.updated_at = datetime.now(timezone.utc)
+    db.commit()
+
+    # 清理中间音频
+    if not s.processing.keep_audio and wav.is_file():
+        try:
+            wav.unlink()
+        except OSError:
+            pass
+
+    logger.info("任务 %d 完成：%s", task.id, bi_path.name)
+
+
+# ---------------- DB 状态更新 ----------------
+
+def _set_status(db, task: Task, status: str, progress: float, note: str = "") -> None:
+    task.status = status
+    task.progress = progress
+    task.updated_at = datetime.now(timezone.utc)
+    db.commit()
+    if note:
+        logger.info("任务 %d [%s %.0f%%] %s", task.id, status, progress, note)
+    else:
+        logger.info("任务 %d [%s %.0f%%]", task.id, status, progress)
+
+
+def _mark_failed(db, task_id: int, error: str) -> None:
+    try:
+        task = db.get(Task, task_id)
+        if task is None:
+            return
+        task.status = "failed"
+        task.error = error[:2000]
+        task.updated_at = datetime.now(timezone.utc)
+        db.commit()
+    except Exception:  # pragma: no cover
+        logger.error("写入失败状态时又失败：\n%s", traceback.format_exc())