fix: generate_video 任务接入 Feature Flag 灰度引擎选择
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问题:一键生成(generate_video)任务硬编码使用 UnifiedRenderService, 完全没有接入 render_engine Feature Flag,导致灰度开关形同虚设, 无法控制新旧引擎切换。 修复: 1. 新增 _resolve_render_engine(user_id) 函数,复用 RenderEngineResolver 2. 新增 _render_with_legacy_engine() 函数,实现旧引擎等价渲染 - 使用 filter_complex + concat 模式 - 保持原帧率(无 fps 归一化),与旧引擎行为一致 - 音频 192k AAC,与旧引擎一致 - 支持 one_take / pip / voice_over / voice_pip 全部模式 3. 在 generate_video 任务入口处根据 Feature Flag 选择引擎 4. 渲染日志新增 engine 字段,便于灰度观测 单测:8 个测试覆盖 flag 各场景 + legacy 渲染验证
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@@ -114,6 +114,7 @@ from video_processing.oss_helpers import (
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upload_to_oss,
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)
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from video_processing.unified_render_service import UnifiedRenderService
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from video_processing.render_engine_resolver import ENGINE_LEGACY, ENGINE_UNIFIED
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# ── 虚拟 Plan / Clip(内存中构建,不写数据库) ────────────────────────────────
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@@ -573,6 +574,135 @@ def _validate_template_exists(template_id: str) -> None:
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session.close()
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# ── 渲染引擎选择 ─────────────────────────────────────────────────────────────
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def _resolve_render_engine(user_id: str) -> str:
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"""根据 Feature Flag 决定使用哪个渲染引擎。
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Returns:
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"legacy" 或 "unified"
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"""
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try:
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from video_processing.render_engine_resolver import get_render_engine_resolver
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resolver = get_render_engine_resolver()
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return resolver.get_engine(user_id=user_id)
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except Exception as exc:
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logger.warning("获取渲染引擎配置失败,fallback 到 unified: %s", exc)
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return ENGINE_UNIFIED
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# ── 旧引擎渲染(FFmpeg filter_complex) ────────────────────────────────────────
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def _render_with_legacy_engine(
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task_id: str,
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virtual_clips: list[_VirtualClip],
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asset_path_map: dict[str, Path],
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work_dir: Path,
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output_path: Path,
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) -> tuple[float, int]:
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"""旧引擎渲染路径:手动构建 FFmpeg filter_complex 命令。
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说明:generate_video 任务使用虚拟 clips(无 EditPlan 数据库记录),
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因此无法直接复用 VideoComposeService。这里手动构建等价的 filter_complex
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命令,与旧引擎行为一致(scale → crop → setpts → trim → setpts,
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无 fps 归一化,保持原帧率)。
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支持模式:one_take / pip / voice_over / voice_pip
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- 所有模式统一走 concat 滤镜(与旧引擎多片段逻辑一致)
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Returns:
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(duration_seconds, file_size_bytes)
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"""
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import subprocess
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main_clips = [
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c for c in virtual_clips
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if c.clip_type in ("main", "b_roll", "background")
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or (c.clip_type == "main" and c.config.get("role") == "b_roll")
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]
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if not main_clips:
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main_clips = virtual_clips[:1]
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input_args: list[str] = []
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video_filters: list[str] = []
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audio_filters: list[str] = []
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for i, clip in enumerate(main_clips):
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local_path = asset_path_map.get(clip.asset_id)
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if not local_path:
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continue
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input_args.extend(["-i", str(local_path)])
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duration = clip.duration or 0.0
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# 视频滤镜:scale → crop → setpts → trim → setpts(与旧引擎一致)
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vf = (
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f"[{i}:v]"
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f"scale={OUTPUT_WIDTH}:{OUTPUT_HEIGHT}:force_original_aspect_ratio=increase,"
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f"crop={OUTPUT_WIDTH}:{OUTPUT_HEIGHT},"
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f"setpts=PTS-STARTPTS,"
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f"trim=0:{duration:.3f},"
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f"setpts=PTS-STARTPTS"
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f"[v{i}]"
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)
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video_filters.append(vf)
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# 音频滤镜:atrim → asetpts
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af = f"[{i}:a]atrim=0:{duration:.3f},asetpts=PTS-STARTPTS[a{i}]"
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audio_filters.append(af)
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n = len(main_clips)
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if n == 1:
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video_label = "[v0]"
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audio_label = "[a0]"
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else:
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# concat 视频
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v_inputs = "".join(f"[v{i}]" for i in range(n))
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video_filters.append(f"{v_inputs}concat=n={n}:v=1:a=0[outv]")
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# concat 音频
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a_inputs = "".join(f"[a{i}]" for i in range(n))
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audio_filters.append(f"{a_inputs}concat=n={n}:v=0:a=1[outa]")
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video_label = "[outv]"
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audio_label = "[outa]"
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# 组装 filter_complex
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fc_parts = video_filters + audio_filters
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filter_complex = ";".join(fc_parts)
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command = [
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FFMPEG_BIN, "-y",
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*input_args,
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"-filter_complex", filter_complex,
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"-map", video_label,
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"-map", audio_label,
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"-c:v", "libx264",
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"-crf", "23",
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"-preset", "medium",
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"-c:a", "aac",
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"-b:a", "192k",
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"-movflags", "+faststart",
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str(output_path),
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]
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logger.info("[task_id=%s] [渲染] legacy 引擎 FFmpeg 开始: clips=%d", task_id, n)
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try:
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run_ffmpeg(command)
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except subprocess.CalledProcessError as e:
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logger.error(
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"[task_id=%s] [渲染] legacy 引擎 FFmpeg 失败: %s\nfilter_complex: %s",
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task_id, e, filter_complex[:500],
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)
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raise
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file_size = output_path.stat().st_size if output_path.exists() else 0
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duration = probe_duration(output_path)
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return duration, file_size
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# ── Celery Task ──────────────────────────────────────────────────────────────
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@@ -730,31 +860,56 @@ def generate_video(self, task_id: str) -> dict:
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)
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_flush_logs(task_id, gen_task)
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# 使用 UnifiedRenderService 渲染
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logger.info("[task_id=%s] [渲染] FFmpeg 渲染开始", task_id)
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# 3. 根据 Feature Flag 选择渲染引擎
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user_id = getattr(gen_task, "created_by_user_id", "") if gen_task else ""
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engine = _resolve_render_engine(user_id) if user_id else ENGINE_UNIFIED
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logger.info("[task_id=%s] [渲染] 引擎选择: %s (user_id=%s)", task_id, engine, user_id)
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render_start = time.monotonic()
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render_service = UnifiedRenderService(
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plan=virtual_plan,
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clips=virtual_clips,
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asset_path_map=asset_path_map,
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work_dir=temp_path,
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output_width=OUTPUT_WIDTH,
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output_height=OUTPUT_HEIGHT,
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output_fps=int(OUTPUT_FPS),
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)
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render_result = render_service.render()
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render_elapsed = time.monotonic() - render_start
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logger.info(
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"[task_id=%s] [渲染] FFmpeg 渲染完成: 耗时=%.1fs",
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task_id,
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render_elapsed,
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)
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render_output_path = temp_path / f"rendered-{task_id}.mp4"
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if engine == ENGINE_LEGACY:
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# 旧引擎:filter_complex + concat(保持原帧率,无 fps 归一化)
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render_duration, render_file_size = _render_with_legacy_engine(
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task_id=task_id,
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virtual_clips=virtual_clips,
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asset_path_map=asset_path_map,
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work_dir=temp_path,
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output_path=render_output_path,
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)
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render_elapsed = time.monotonic() - render_start
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logger.info(
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"[task_id=%s] [渲染] legacy 引擎完成: 耗时=%.1fs, 时长=%.2fs",
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task_id, render_elapsed, render_duration,
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)
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else:
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# 新引擎:UnifiedRenderService 图层架构
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logger.info("[task_id=%s] [渲染] unified 引擎 FFmpeg 渲染开始", task_id)
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render_service = UnifiedRenderService(
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plan=virtual_plan,
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clips=virtual_clips,
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asset_path_map=asset_path_map,
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work_dir=temp_path,
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output_width=OUTPUT_WIDTH,
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output_height=OUTPUT_HEIGHT,
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output_fps=int(OUTPUT_FPS),
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)
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render_result = render_service.render()
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render_output_path = render_result.output_path
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render_duration = render_result.duration
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render_file_size = render_result.file_size
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render_elapsed = time.monotonic() - render_start
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logger.info(
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"[task_id=%s] [渲染] unified 引擎完成: 耗时=%.1fs",
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task_id, render_elapsed,
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)
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if gen_task:
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gen_task.append_log(
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"渲染",
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f"FFmpeg 渲染完成, 耗时={render_elapsed:.1f}s",
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f"引擎={engine}, 耗时={render_elapsed:.1f}s",
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duration=round(render_elapsed, 2),
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engine=engine,
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)
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_flush_logs(task_id, gen_task)
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@@ -762,14 +917,14 @@ def generate_video(self, task_id: str) -> dict:
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if audio_path:
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final_path = temp_path / f"final-{task_id}.mp4"
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try:
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_mux_audio_track(render_result.output_path, audio_path, final_path)
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_mux_audio_track(render_output_path, audio_path, final_path)
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# 混音成功,使用混音后的文件
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output_path = final_path
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except Exception as mux_err:
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logger.warning("[task_id=%s] [混音] 音频混合失败,使用无音频版本: %s", task_id, mux_err)
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output_path = render_result.output_path
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output_path = render_output_path
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else:
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output_path = render_result.output_path
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output_path = render_output_path
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file_size = output_path.stat().st_size
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duration = probe_duration(output_path)
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