cat-shark
b16e0e9f3c
调度与状态机： - 修复 PAUSED 任务被拾起后复活执行（点击暂停反而开始任务）：next_queued_run 只取 QUEUED，execute_run 以 PAUSED 进入直接返回，暂停必须显式 resume - 重启恢复：启动时 recover_interrupted_runs 把遗留 RUNNING 置 QUEUED（保留产物） - 暂停信号 paused.flag：暂停接口写、继续/重试清除，OCR 逐帧检查秒级中断， 节点内被暂停保持 PAUSED 不误报 FAILED - 调度轮询容错：_loop 异常不杀死线程（曾致任务永久停留 QUEUED） subtitle-ocr 节点级断点： - ocr_partial.jsonl 逐帧存档，重启/暂停后只处理未处理帧，产物与一次跑完一致 - 进度日志携带窗口平均耗时与线程数；取消后抑制进度日志井喷 llm-filter 过滤质量与限流自适应： - 上下文净化：喂给 LLM 的是过滤后的字幕（规则层垃圾从上下文剔除） - 正则确定性过滤：裸网址域名、HTML/水印模式直接删除 - 429/5xx 指数退避重试；worker 限流错误 report_failure 内存临时降最大线程数 并缩容（无错误窗口回升），失败条目降并发后重试一轮 - 保留长文本保护（noise 不删 ≥min_keep_len 文本，LLM 判定不稳的必要兜底） 前端： - 工作流编排页支持选择工作流编辑（加载最新/历史版本）、版本历史面板、 新建/编辑双模式；管理后台编辑跳转 workflow.html?edit=<id> 工作流：ocr-subtitle v7（filter pool_max_workers=20、pool_fast_threshold=1）
542 lines
22 KiB
Python
542 lines
22 KiB
Python
"""抽帧与字幕 OCR 节点单元测试。
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frame-extract 用 testdata 真实视频抽帧+裁切+720p 压缩；subtitle-ocr 的 OCR
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网络调用（vlm-ocr）按 I/O 边界 mock，但喂给它的帧图片是真实的 testdata 资产。
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应用层不再加工模型输出文本，只做长度上限校验（超长报错跳过）。
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"""
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import json
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from pathlib import Path
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from wov_sdk.models import InvokeRequest, InvokeResponse
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from nodes.frame_extract import invoke as frame_invoke
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from nodes.subtitle_ocr import _assemble_srt
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from nodes.subtitle_ocr import invoke as ocr_invoke
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# 单体根目录：tests/ 的上一级。
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WORKSPACE = Path(__file__).resolve().parent.parent
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TESTDATA = WORKSPACE / "testdata"
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# 10s 测试视频：SUB 001 在 1-4s、SUB 002 在 6-9s。
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VIDEO = TESTDATA / "subtitle_10s.mp4"
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TEXT_IMG = TESTDATA / "ocr_text.png"
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def _png_size(path: Path) -> tuple[int, int]:
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"""从 PNG 头读取宽高（真实图片尺寸断言）。"""
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data = path.read_bytes()
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assert data[:8] == b"\x89PNG\r\n\x1a\n", "not a real png"
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width = int.from_bytes(data[16:20], "big")
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height = int.from_bytes(data[20:24], "big")
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return width, height
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def _frame_request(tmp_path, video=VIDEO, **params) -> InvokeRequest:
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"""构造 frame-extract 调用请求。"""
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return InvokeRequest(
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run_id="run_fx",
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node_instance_id="",
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inputs={"video_uri": str(video)},
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params=params,
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output_dir=str(tmp_path / "out"),
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)
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# ---------------------------------------------------------------------------
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# frame-extract：抽帧 + 裁切 + 720p 压缩
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# ---------------------------------------------------------------------------
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def test_frame_extract_crop_and_manifest(tmp_path) -> None:
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"""真实视频抽帧：裁切下半 50% 后帧尺寸为 1280x360，清单时间轴正确。"""
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response = frame_invoke(
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_frame_request(tmp_path, interval_seconds=1, crop=[0, 0.5, 1, 0.5])
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)
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assert response.status == "completed", response.error
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manifest = json.loads(Path(response.outputs["frames_manifest"]).read_text(encoding="utf-8"))
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assert len(manifest) >= 9
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assert [round(item["time"], 3) for item in manifest] == [
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round(i * 1.0, 3) for i in range(len(manifest))
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]
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first = Path(manifest[0]["image_uri"])
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assert first.is_file()
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# 1280x360 已在 720p 内，压缩不改变尺寸。
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assert _png_size(first) == (1280, 360)
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def test_frame_extract_default_params(tmp_path) -> None:
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"""未指定参数时使用默认值：抽帧间隔 0.5 秒 + 默认底部裁切区域。"""
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response = frame_invoke(_frame_request(tmp_path))
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assert response.status == "completed", response.error
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manifest = json.loads(Path(response.outputs["frames_manifest"]).read_text(encoding="utf-8"))
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assert manifest
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# 默认间隔 0.5s：25fps 下 step=round(12.5)=12（银行家舍入），
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# 帧时间按 step/fps=12/25=0.48s 步进（帧号精确，采样周期由帧量化决定）。
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assert [round(item["time"], 3) for item in manifest] == [
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round(i * 12 / 25, 3) for i in range(len(manifest))
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]
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def test_frame_extract_missing_video(tmp_path) -> None:
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"""缺少 video_uri 时返回失败。"""
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response = frame_invoke(
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InvokeRequest(
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run_id="r", node_instance_id="", inputs={}, output_dir=str(tmp_path)
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)
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)
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assert response.status == "failed"
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def test_frame_extract_bad_crop(tmp_path) -> None:
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"""crop 比例越界（超出画面）时返回失败。"""
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assert frame_invoke(_frame_request(tmp_path, crop=[0, 0.5, 1, 1.5])).status == "failed"
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assert frame_invoke(_frame_request(tmp_path, crop=[-0.1, 0, 1, 0.5])).status == "failed"
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assert frame_invoke(_frame_request(tmp_path, crop="abc")).status == "failed"
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assert frame_invoke(_frame_request(tmp_path, crop=[0, 0.5, 1])).status == "failed"
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# 各值域合法但 x+w 越出画面。
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assert frame_invoke(_frame_request(tmp_path, crop=[0.6, 0, 0.5, 0.3])).status == "failed"
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def test_frame_extract_video_missing_file(tmp_path) -> None:
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"""video_uri 指向不存在的文件时返回失败。"""
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response = frame_invoke(_frame_request(tmp_path, video=tmp_path / "none.mp4"))
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assert response.status == "failed"
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assert "not found" in response.error
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def test_frame_extract_bad_interval(tmp_path) -> None:
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"""间隔 <= 0 时返回失败。"""
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response = frame_invoke(_frame_request(tmp_path, interval_seconds=0))
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assert response.status == "failed"
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def test_frame_extract_ffmpeg_fails(monkeypatch, tmp_path) -> None:
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"""ffmpeg 抽帧失败时透传错误。"""
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import subprocess as sp
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monkeypatch.setattr("nodes.frame_extract._video_size", lambda *a, **k: (1280, 720))
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monkeypatch.setattr("nodes.frame_extract._video_fps", lambda *a, **k: 25.0)
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monkeypatch.setattr("nodes.frame_extract._video_duration", lambda *a, **k: 10.0)
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monkeypatch.setattr(
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"nodes.frame_extract.subprocess.run",
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lambda *a, **k: sp.CompletedProcess([], 1, stderr="boom"),
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)
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response = frame_invoke(_frame_request(tmp_path))
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assert response.status == "failed"
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assert "boom" in response.error
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def test_video_size_unreadable(monkeypatch) -> None:
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"""ffmpeg -i 输出不含视频流信息时返回 None。"""
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import subprocess as sp
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from nodes.frame_extract import _video_size
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monkeypatch.setattr(
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"nodes.frame_extract.subprocess.run",
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lambda *a, **k: sp.CompletedProcess([], 0, stderr="no video stream"),
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)
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assert _video_size(Path("/tmp/x.mp4"), "ffmpeg") is None
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def test_frame_extract_video_size_unknown(monkeypatch, tmp_path) -> None:
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"""无法读取视频分辨率时返回失败。"""
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monkeypatch.setattr("nodes.frame_extract._video_size", lambda *a, **k: None)
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response = frame_invoke(_frame_request(tmp_path))
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assert response.status == "failed"
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assert "video size" in response.error
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def test_video_duration_unreadable(monkeypatch) -> None:
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"""ffmpeg -i 输出缺少 Duration 时返回 None。"""
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import subprocess as sp
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from nodes.frame_extract import _video_duration
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monkeypatch.setattr(
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"nodes.frame_extract.subprocess.run",
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lambda *a, **k: sp.CompletedProcess([], 0, stderr="no duration info"),
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)
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assert _video_duration(Path("/tmp/x.mp4"), "ffmpeg") is None
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class _FakeReader:
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"""模拟 stderr 读取对象。"""
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def __init__(self, content: str = "") -> None:
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self._content = content
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def read(self) -> str:
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return self._content
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class FakePopen:
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"""模拟 ffmpeg 进程：stdout 可迭代 -progress 行，可配置返回码与 stderr。"""
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def __init__(self, lines=(), returncode: int = 0, stderr: str = "") -> None:
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self.stdout = list(lines)
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self.stderr = _FakeReader(stderr)
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self.returncode = returncode
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def wait(self) -> int:
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return self.returncode
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def _fake_popen(lines=(), returncode: int = 0, stderr: str = ""):
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"""构造替换 subprocess.Popen 的工厂函数。"""
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return lambda *a, **k: FakePopen(lines, returncode, stderr)
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def test_parse_progress_line() -> None:
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"""-progress 行解析：frame=N 返回数值，其他行与非法值返回 None。"""
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from nodes.frame_extract import _parse_progress_line
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assert _parse_progress_line("frame=25\n") == 25
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assert _parse_progress_line("progress=continue") is None
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assert _parse_progress_line("fps=25.0") is None
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assert _parse_progress_line("frame=abc") is None
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def test_frame_extract_progress_logging(monkeypatch, tmp_path) -> None:
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"""ffmpeg -progress 的 frame=N 被解析并打印抽帧进度与速度。"""
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import logging
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monkeypatch.setattr("nodes.frame_extract._video_size", lambda *a, **k: (1280, 720))
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monkeypatch.setattr("nodes.frame_extract._video_fps", lambda *a, **k: 25.0)
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monkeypatch.setattr("nodes.frame_extract._video_duration", lambda *a, **k: 10.0)
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monkeypatch.setattr(
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"nodes.frame_extract.subprocess.Popen",
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_fake_popen(lines=["fps=25.0", "frame=20", "progress=continue", "frame=50", "progress=continue"]),
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)
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captured: list[str] = []
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class CaptureHandler(logging.Handler):
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def emit(self, record):
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captured.append(record.getMessage())
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logger = logging.getLogger("vrsub.frame-extract")
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logger.addHandler(CaptureHandler())
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try:
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response = frame_invoke(_frame_request(tmp_path))
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finally:
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logger.removeHandler(logger.handlers[-1])
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assert response.status == "completed", response.error
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assert any("抽帧进度" in message and "帧/s" in message for message in captured)
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def test_frame_extract_ffmpeg_fails(monkeypatch, tmp_path) -> None:
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"""ffmpeg 抽帧失败时透传错误。"""
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monkeypatch.setattr("nodes.frame_extract._video_size", lambda *a, **k: (1280, 720))
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monkeypatch.setattr("nodes.frame_extract._video_fps", lambda *a, **k: 25.0)
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monkeypatch.setattr("nodes.frame_extract._video_duration", lambda *a, **k: 10.0)
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monkeypatch.setattr(
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"nodes.frame_extract.subprocess.Popen",
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_fake_popen(lines=["frame=1", "progress=end"], returncode=1, stderr="boom"),
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)
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response = frame_invoke(_frame_request(tmp_path))
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assert response.status == "failed"
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assert "boom" in response.error
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def test_frame_extract_duration_unknown(monkeypatch, tmp_path) -> None:
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"""无法读取视频时长时返回失败。"""
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monkeypatch.setattr("nodes.frame_extract._video_size", lambda *a, **k: (1280, 720))
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monkeypatch.setattr("nodes.frame_extract._video_duration", lambda *a, **k: None)
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response = frame_invoke(_frame_request(tmp_path))
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assert response.status == "failed"
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assert "duration" in response.error
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def test_frame_extract_fps_unknown(monkeypatch, tmp_path) -> None:
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"""无法读取视频帧率时返回失败。"""
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monkeypatch.setattr("nodes.frame_extract._video_size", lambda *a, **k: (1280, 720))
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monkeypatch.setattr("nodes.frame_extract._video_duration", lambda *a, **k: 10.0)
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monkeypatch.setattr("nodes.frame_extract._video_fps", lambda *a, **k: None)
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response = frame_invoke(_frame_request(tmp_path))
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assert response.status == "failed"
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assert "fps" in response.error
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def test_frame_step_conversion() -> None:
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"""帧间隔换算：step=round(间隔秒×fps)，至少为 1。"""
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from nodes.frame_extract import _frame_step
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assert _frame_step(fps=25.0, interval=0.2) == 5
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assert _frame_step(fps=25.0, interval=1.0) == 25
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assert _frame_step(fps=29.97, interval=1.0) == 30
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# fps 很低时 step 也不会小于 1（每帧都取）。
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assert _frame_step(fps=1.0, interval=0.2) == 1
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def test_video_fps_parse(monkeypatch) -> None:
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"""帧率解析：支持小数（29.97）与有理数（30000/1001）。"""
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import subprocess as sp
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from nodes.frame_extract import _video_fps
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monkeypatch.setattr(
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"nodes.frame_extract.subprocess.run",
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lambda *a, **k: sp.CompletedProcess(
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[], 0, stderr="Stream #0:0: Video: h264, 1280x720, 30000/1001 fps, 30000/1001 tbr"
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),
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)
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assert _video_fps(Path("/tmp/x.mp4"), "ffmpeg") == 30000 / 1001
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monkeypatch.setattr(
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"nodes.frame_extract.subprocess.run",
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lambda *a, **k: sp.CompletedProcess(
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[], 0, stderr="Stream #0:0: Video: h264, 1280x720, 25 fps, 25 tbr"
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),
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)
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assert _video_fps(Path("/tmp/x.mp4"), "ffmpeg") == 25.0
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monkeypatch.setattr(
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"nodes.frame_extract.subprocess.run",
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lambda *a, **k: sp.CompletedProcess([], 0, stderr="no video stream"),
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)
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assert _video_fps(Path("/tmp/x.mp4"), "ffmpeg") is None
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def test_frame_extract_one_second_exact_frames(tmp_path) -> None:
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"""真实视频 1s 间隔按秒 seek 精确抽帧：10s 视频应得 10 帧，时间 0..9。"""
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response = frame_invoke(
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_frame_request(tmp_path, interval_seconds=1, crop=[0, 0.7, 1, 0.3])
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)
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assert response.status == "completed", response.error
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manifest = json.loads(Path(response.outputs["frames_manifest"]).read_text(encoding="utf-8"))
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assert [round(item["time"], 3) for item in manifest] == [
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round(i * 1.0, 3) for i in range(len(manifest))
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]
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assert len(manifest) == 10
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def test_frame_files_read_order_matches_frame_number(tmp_path) -> None:
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"""真实任务留存数据：帧文件按帧号数值排序读取，而非字典序。
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回归用例：ffmpeg 的 %04d 编号在超过 9999 帧后自动扩为 5 位
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（frame_10000.png 等），此时 sorted() 默认字典序会把 5 位编号排在
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4 位编号之前（如 frame_10009 < frame_1009），导致帧号回退、manifest
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时间与图像错位。testdata/frames_boundary/ 是 2026-08 真实任务
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run_339ec7ee437f（14236 帧 / 2 小时视频）中跨越该边界的真实帧文件。
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"""
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from nodes.frame_extract import _sorted_frame_files
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boundary = TESTDATA / "frames_boundary"
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files = _sorted_frame_files(boundary)
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# 从文件名解析帧号：读取顺序必须等于帧号数值递增序（无回退）。
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nums = [int(p.stem.split("_", 1)[1]) for p in files]
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assert nums == sorted(nums)
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# 边界关键对：5 位编号必须排在 4 位编号之后，禁止字典序错位。
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assert nums.index(10000) > nums.index(9999)
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assert nums.index(10009) > nums.index(1009)
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# ---------------------------------------------------------------------------
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# subtitle-ocr：OCR 循环 + 长度上限 + 合并 + SRT 组装
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# ---------------------------------------------------------------------------
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def _frames_manifest(tmp_path, frame_specs) -> Path:
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"""构造真实 frames.json；frame_specs=[(time, image_path), ...]。"""
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items = [{"time": time, "image_uri": str(image)} for time, image in frame_specs]
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path = tmp_path / "frames.json"
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path.write_text(json.dumps(items), encoding="utf-8")
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return path
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def test_assemble_srt_real_timeline() -> None:
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"""SRT 组装：起始=帧时间，结束=最后可见帧时间+采样间隔。"""
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lines = _assemble_srt([(0.0, 6.0, "A"), (6.0, 8.0, "B")], interval_seconds=2.0)
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text = "\n".join(lines)
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assert text.startswith("1\n")
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# A 最后可见帧 6.0 + 间隔 2.0 = 8.0（而非下一条字幕的出现时间）。
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assert "00:00:00,000 --> 00:00:08,000" in text
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assert "00:00:06,000 --> 00:00:10,000" in text
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def test_sampling_interval_from_manifest() -> None:
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"""采样间隔从帧清单时间轴推导：均匀间隔取相邻差，退化清单回退默认值。"""
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from nodes.subtitle_ocr import _sampling_interval
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manifest = [{"time": i * 0.2, "image_uri": f"f{i}.png"} for i in range(10)]
|
||
assert _sampling_interval(manifest, 2.0) == 0.2
|
||
# 单帧（无法算差）与异常时间序：回退默认值。
|
||
assert _sampling_interval([{"time": 0.0, "image_uri": "f0.png"}], 2.0) == 2.0
|
||
assert _sampling_interval(
|
||
[{"time": 0.0}, {"time": 0.0}, {"time": 0.2}], 2.0
|
||
) == 0.2
|
||
|
||
def test_ocr_merges_consecutive_same_text(monkeypatch, tmp_path) -> None:
|
||
"""连续帧相同字幕合并为一条；消失时间=最后可见帧+间隔，空白段保留。"""
|
||
# SUB 001 在 0/2s，4s 为空帧，SUB 002 在 6/8s。
|
||
frame_texts = [
|
||
(0.0, "SUB 001"), (2.0, "SUB 001"), (4.0, ""),
|
||
(6.0, "SUB 002"), (8.0, "SUB 002"),
|
||
]
|
||
frames = []
|
||
for index, (time, _text) in enumerate(frame_texts):
|
||
image = tmp_path / f"f{index}.png"
|
||
image.write_bytes(TEXT_IMG.read_bytes())
|
||
frames.append((time, image))
|
||
mapping = {str(image): text for (time, image), (_, text) in zip(frames, frame_texts)}
|
||
|
||
def fake_vlm(node_id, request):
|
||
return InvokeResponse(status="completed", outputs={"text": mapping[request.inputs["image_uri"]]})
|
||
|
||
monkeypatch.setattr("wov_app.registry.invoke", fake_vlm)
|
||
manifest = _frames_manifest(tmp_path, frames)
|
||
response = ocr_invoke(
|
||
InvokeRequest(
|
||
run_id="run_ocr",
|
||
node_instance_id="",
|
||
inputs={"frames_manifest": str(manifest)},
|
||
params={},
|
||
output_dir=str(tmp_path / "out"),
|
||
)
|
||
)
|
||
assert response.status == "completed", response.error
|
||
srt = Path(response.outputs["srt_uri"]).read_text(encoding="utf-8")
|
||
assert srt.count("SUB 001") == 1
|
||
assert srt.count("SUB 002") == 1
|
||
# SUB 001 最后可见帧 2.0 + 间隔 2.0 = 4.0 消失（而非拖到 SUB 002 出现）。
|
||
assert "00:00:00,000 --> 00:00:04,000" in srt
|
||
assert "00:00:06,000 --> 00:00:10,000" in srt
|
||
|
||
|
||
def test_ocr_skips_failed_frames(monkeypatch, tmp_path) -> None:
|
||
"""个别帧 OCR 失败时跳过，不影响其余帧汇总。"""
|
||
frames = []
|
||
for index in range(3):
|
||
image = tmp_path / f"f{index}.png"
|
||
image.write_bytes(TEXT_IMG.read_bytes())
|
||
frames.append((index * 2.0, image))
|
||
|
||
def fake_vlm(node_id, request):
|
||
if "f1" in request.inputs["image_uri"]:
|
||
return InvokeResponse(status="failed", error="boom")
|
||
return InvokeResponse(status="completed", outputs={"text": "SUB 001"})
|
||
|
||
monkeypatch.setattr("wov_app.registry.invoke", fake_vlm)
|
||
manifest = _frames_manifest(tmp_path, frames)
|
||
response = ocr_invoke(
|
||
InvokeRequest(
|
||
run_id="run_ocr",
|
||
node_instance_id="",
|
||
inputs={"frames_manifest": str(manifest)},
|
||
params={},
|
||
output_dir=str(tmp_path / "out"),
|
||
)
|
||
)
|
||
assert response.status == "completed", response.error
|
||
srt = Path(response.outputs["srt_uri"]).read_text(encoding="utf-8")
|
||
assert "SUB 001" in srt
|
||
|
||
|
||
def test_ocr_missing_manifest(tmp_path) -> None:
|
||
"""缺少 frames_manifest 或清单文件不存在时返回失败。"""
|
||
response = ocr_invoke(
|
||
InvokeRequest(run_id="r", node_instance_id="", inputs={}, output_dir=str(tmp_path))
|
||
)
|
||
assert response.status == "failed"
|
||
response = ocr_invoke(
|
||
InvokeRequest(
|
||
run_id="r", node_instance_id="",
|
||
inputs={"frames_manifest": str(tmp_path / "none.json")},
|
||
output_dir=str(tmp_path),
|
||
)
|
||
)
|
||
assert response.status == "failed"
|
||
|
||
|
||
def test_ocr_skips_oversized_output(monkeypatch, tmp_path) -> None:
|
||
"""超长输出（模型重复循环等）直接报错跳过该帧，不进入 SRT。"""
|
||
frames = []
|
||
for index in range(3):
|
||
image = tmp_path / f"o{index}.png"
|
||
image.write_bytes(TEXT_IMG.read_bytes())
|
||
frames.append((index * 2.0, image))
|
||
|
||
def fake_vlm(node_id, request):
|
||
if "o0" in request.inputs["image_uri"]:
|
||
return InvokeResponse(status="completed", outputs={"text": "重复字幕\n" * 50})
|
||
if "o1" in request.inputs["image_uri"]:
|
||
# 空输出帧跳过。
|
||
return InvokeResponse(status="completed", outputs={"text": ""})
|
||
return InvokeResponse(status="completed", outputs={"text": "SUB 001"})
|
||
|
||
monkeypatch.setattr("wov_app.registry.invoke", fake_vlm)
|
||
manifest = _frames_manifest(tmp_path, frames)
|
||
response = ocr_invoke(
|
||
InvokeRequest(
|
||
run_id="run_ocr",
|
||
node_instance_id="",
|
||
inputs={"frames_manifest": str(manifest)},
|
||
params={"max_result_chars": 200},
|
||
output_dir=str(tmp_path / "out"),
|
||
)
|
||
)
|
||
assert response.status == "completed", response.error
|
||
srt = Path(response.outputs["srt_uri"]).read_text(encoding="utf-8")
|
||
assert "SUB 001" in srt
|
||
assert "重复字幕" not in srt
|
||
|
||
|
||
def test_ocr_passes_short_text_through(monkeypatch, tmp_path) -> None:
|
||
"""不超过上限的模型输出原样进入 SRT（不再做应用层过滤）。"""
|
||
image = tmp_path / "s0.png"
|
||
image.write_bytes(TEXT_IMG.read_bytes())
|
||
frames = [(0.0, image)]
|
||
|
||
def fake_vlm(node_id, request):
|
||
return InvokeResponse(status="completed", outputs={"text": " SUB 001 "})
|
||
|
||
monkeypatch.setattr("wov_app.registry.invoke", fake_vlm)
|
||
manifest = _frames_manifest(tmp_path, frames)
|
||
response = ocr_invoke(
|
||
InvokeRequest(
|
||
run_id="run_ocr", node_instance_id="",
|
||
inputs={"frames_manifest": str(manifest)},
|
||
params={},
|
||
output_dir=str(tmp_path / "out"),
|
||
)
|
||
)
|
||
assert response.status == "completed", response.error
|
||
srt = Path(response.outputs["srt_uri"]).read_text(encoding="utf-8")
|
||
assert "SUB 001" in srt
|
||
|
||
|
||
def test_ocr_interrupts_on_pause_flag(monkeypatch, tmp_path) -> None:
|
||
"""暂停信号：任务被暂停（paused.flag 存在）时 OCR 立即中断。
|
||
|
||
output_dir = <storage>/runs/<run_id>/steps/ocr，run 根目录为其父父目录；
|
||
调度器/API 在暂停时向 run 根写入 paused.flag，节点逐帧检查到即中止：
|
||
不调用 vlm-ocr、不写该帧断点存档，invoke 返回 failed（由调度器识别为
|
||
"被暂停"并保持 PAUSED，等待 resume 后从断点续跑）。
|
||
"""
|
||
image = tmp_path / "s0.png"
|
||
image.write_bytes(TEXT_IMG.read_bytes())
|
||
frames = [(i * 2.0, image) for i in range(4)]
|
||
|
||
# 暂停信号位于 run 根目录（steps/ocr 的父父目录）。
|
||
run_root = tmp_path / "run_root"
|
||
out_dir = run_root / "steps" / "ocr"
|
||
out_dir.mkdir(parents=True)
|
||
(run_root / "paused.flag").write_text("", encoding="utf-8")
|
||
|
||
calls: list[str] = []
|
||
|
||
def fake_vlm(node_id, request):
|
||
calls.append(request.inputs["image_uri"])
|
||
return InvokeResponse(status="completed", outputs={"text": "SUB 001"})
|
||
|
||
monkeypatch.setattr("wov_app.registry.invoke", fake_vlm)
|
||
manifest = _frames_manifest(tmp_path, frames)
|
||
response = ocr_invoke(
|
||
InvokeRequest(
|
||
run_id="run_paused_flag",
|
||
node_instance_id="",
|
||
inputs={"frames_manifest": str(manifest)},
|
||
params={},
|
||
output_dir=str(out_dir),
|
||
)
|
||
)
|
||
# 节点以"被暂停"失败：调度器会据此保持 PAUSED 而不标 FAILED。
|
||
assert response.status == "failed"
|
||
assert "暂停" in (response.error or "")
|
||
assert calls == [] # 一帧都没有真正 OCR。
|
||
assert not (out_dir / "ocr_partial.jsonl").exists() # 未处理帧不入存档。
|