feat: VRSub 单体应用(WOV 单机版)初始提交
为视频生成 VR 双眼字幕的单体实现:FastAPI 后端、调度器与全部节点 (提音/转写/翻译/ASS/抽帧/OCR/LLM 过滤)在单进程内运行。 - 节点协议(wov_sdk 数据模型)与分布式版保持一致,预留回退桥梁 - 工作流即数据:DAG 存于 workflows/*.json,模型/链路改动只改数据 - 调度器:拓扑顺序执行、断点续跑(产物重建)、任务暂停/继续 - 抽帧按帧间隔(select 按帧号精确取帧),VLM OCR 与 LLM 过滤使用 自适应线程池弹性并发,并打印数据处理速度进度日志 - 100% 行覆盖率(pytest --cov-fail-under=100)
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"""工作流调度器。
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轮询 SQLite 中的排队任务,按工作流 DAG 的拓扑顺序依次调用进程内节点
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处理器,并把节点产物登记为任务产物。单体版使用单线程顺序执行,节点在
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同一进程内直接调用,不再经过子进程与 HTTP 协议。
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"""
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from __future__ import annotations
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import threading
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import time
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from datetime import datetime, timezone
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from pathlib import Path
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from wov_sdk.models import InvokeRequest, WorkflowDefinition
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from wov_app import registry
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from wov_app.config import SCHEDULER_INTERVAL_SECONDS
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from wov_app.db import Database
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from wov_app.logging import get_logger
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# 调度器运行日志:节点进度、暂停/续跑等状态变化。
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logger = get_logger("scheduler")
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def _now_iso() -> str:
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"""返回当前 UTC 时间的 ISO 格式字符串。"""
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return datetime.now(timezone.utc).isoformat()
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def topological_sort(definition: WorkflowDefinition) -> list[str]:
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"""对工作流 DAG 做拓扑排序,返回可执行的节点 ID 顺序。"""
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nodes = {node.id: node for node in definition.nodes}
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# 统计每个节点的入度,并记录依赖关系。
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indegree = {node_id: 0 for node_id in nodes}
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dependents: dict[str, list[str]] = {node_id: [] for node_id in nodes}
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for edge in definition.edges:
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# 边引用了不存在的节点时直接报错。
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if edge.from_node not in nodes or edge.to_node not in nodes:
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raise ValueError(f"unknown edge: {edge.from_node} -> {edge.to_node}")
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indegree[edge.to_node] += 1
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dependents[edge.from_node].append(edge.to_node)
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# Kahn 算法:从入度为 0 的节点开始逐层取出。
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queue = [node_id for node_id, degree in indegree.items() if degree == 0]
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ordered: list[str] = []
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while queue:
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current = queue.pop(0)
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ordered.append(current)
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for dependent in dependents[current]:
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indegree[dependent] -= 1
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if indegree[dependent] == 0:
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queue.append(dependent)
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# 排序结果数量不足说明存在环,无法确定执行顺序。
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if len(ordered) != len(nodes):
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raise ValueError("workflow contains a cycle")
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return ordered
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class WorkflowScheduler:
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"""后台任务调度器:单线程轮询并执行排队中的工作流运行。"""
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def __init__(
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self,
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db: Database,
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storage_dir: Path,
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interval_seconds: float | None = None,
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) -> None:
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"""保存依赖并初始化轮询线程控制字段。"""
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self.db = db
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self.storage_dir = storage_dir
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self.interval_seconds = interval_seconds or SCHEDULER_INTERVAL_SECONDS
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self._thread: threading.Thread | None = None
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self._stopping = False
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def start(self) -> None:
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"""启动调度线程;重复调用无副作用。"""
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if self._thread is not None:
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return
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self._stopping = False
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self._thread = threading.Thread(
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target=self._loop,
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name="wov-workflow-scheduler",
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daemon=True,
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)
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self._thread.start()
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def stop(self) -> None:
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"""请求停止并等待轮询线程退出。"""
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self._stopping = True
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if self._thread is not None:
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self._thread.join(timeout=5)
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self._thread = None
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def _loop(self) -> None:
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"""轮询循环:有排队任务就立即执行,否则休眠一个间隔。"""
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while not self._stopping:
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run = self.db.next_queued_run()
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if run is not None:
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self.execute_run(run["id"])
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else:
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time.sleep(self.interval_seconds)
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def _resolve_ref(
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self,
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ref: str,
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run_input_uri: str | None,
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outputs_by_node: dict[str, dict[str, str]],
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) -> str | None:
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"""解析输入引用:input.xxx 取任务入口,node.key 取前序节点产物。"""
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# 入口引用以 input. 为前缀。
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if ref.startswith("input."):
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return run_input_uri
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# 其余引用必须形如 "节点ID.输出名"。
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node_id, separator, key = ref.partition(".")
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if not separator:
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return None
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return outputs_by_node.get(node_id, {}).get(key)
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def execute_run(self, run_id: str) -> None:
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"""执行单个任务:加载 DAG、按拓扑顺序调用节点并登记产物。"""
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run = self.db.get_run(run_id)
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# 任务不存在或不在可执行状态(排队/暂停)时直接返回,避免重复执行。
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if run is None or run["status"] not in ("QUEUED", "PAUSED"):
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return
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# 工作流或版本记录丢失时把任务标记为失败。
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workflow = self.db.get_workflow(run["workflow_id"])
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if workflow is None:
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self.db.update_run(run_id, status="FAILED", error="workflow not found", updated_at=_now_iso())
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return
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version = self.db.get_workflow_version(run["workflow_id"], run["workflow_version"])
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if version is None:
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self.db.update_run(run_id, status="FAILED", error="workflow version not found", updated_at=_now_iso())
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return
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# 解析并校验 DAG,随后计算拓扑执行顺序。
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definition = WorkflowDefinition.from_dict(version["definition"])
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definition.validate()
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ordered = topological_sort(definition)
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# 从已登记产物重建已完成节点的输出,支持暂停后断点续跑。
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outputs_by_node = self.db.restore_run_outputs(run_id)
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run_started = time.monotonic()
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self.db.update_run(run_id, status="RUNNING", progress=0, updated_at=_now_iso())
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try:
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for index, node_id in enumerate(ordered):
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# 暂停检查:用户暂停后调度器在节点边界停下,保持 PAUSED 等待续跑。
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current = self.db.get_run(run_id)
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if current is None or current["status"] == "PAUSED":
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logger.info("任务 %s 已暂停,停止在节点 %s 之前", run_id, node_id)
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return
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# 断点续跑:跳过已产出结果的节点(其产物已作为输入可用)。
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if node_id in outputs_by_node:
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continue
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# 当前节点进度 = 已完成节点数 / 总节点数。
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node_spec = next(item for item in definition.nodes if item.id == node_id)
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self.db.update_run(
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run_id,
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current_node_id=node_id,
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progress=index / len(ordered),
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updated_at=_now_iso(),
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)
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# 解析节点声明的每个输入引用,缺任一输入即失败。
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invoke_inputs: dict[str, str] = {}
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for input_name, ref in node_spec.inputs.items():
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value = self._resolve_ref(ref, run.get("input_uri"), outputs_by_node)
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if value is None:
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raise ValueError(f"missing input {input_name} for node {node_id}")
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invoke_inputs[input_name] = value
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# 前端框选的 crop 等参数覆盖:按节点 ID 合并进节点参数。
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node_params = dict(node_spec.params)
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overrides = run.get("param_overrides") or {}
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node_params.update(overrides.get(node_id, {}))
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# 每个任务的每个节点使用独立产物目录,避免并发冲突。
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node_started = time.monotonic()
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output_dir = (
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self.storage_dir
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/ "runs"
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/ run_id
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/ "steps"
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/ node_id
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)
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response = registry.invoke(
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node_spec.node_type,
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InvokeRequest(
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run_id=run_id,
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node_instance_id="",
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inputs=invoke_inputs,
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params=node_params,
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output_dir=str(output_dir),
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),
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)
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# 节点返回非 completed 即视为步骤失败。
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if response.status != "completed":
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raise RuntimeError(response.error or f"node {node_id} failed")
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# 记录节点输出,供后续节点引用和最终产物映射使用。
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outputs_by_node[node_id] = {
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str(key): str(value) for key, value in response.outputs.items()
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}
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for key, uri in outputs_by_node[node_id].items():
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# 产物名带节点前缀,例如 asr.srt_uri,避免跨节点重名。
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artifact = {
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"run_id": run_id,
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"node_id": node_id,
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"name": f"{node_id}.{key}",
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"uri": uri,
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"mime_type": self._mime_type(uri),
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"size": self._file_size(uri),
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}
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self.db.create_artifact(artifact)
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# 进度日志:节点序号/总数、耗时与任务累计运行时间(数据速度可观测)。
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logger.info(
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"任务 %s 进度 %d/%d 节点: %s 耗时 %.1fs, 运行累计 %.1fs",
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run_id, index + 1, len(ordered), node_id,
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time.monotonic() - node_started,
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time.monotonic() - run_started,
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)
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# 处理 final_outputs,为用户端提供简洁的下载别名。
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for alias, ref in definition.final_outputs.items():
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resolved = self._resolve_ref(ref, run.get("input_uri"), outputs_by_node)
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if resolved is not None:
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# 最终产物按 上传文件名.标识.时间戳 重命名,区分语言与版本。
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resolved = self._final_artifact_uri(resolved, run, definition, alias, ref)
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self.db.create_artifact(
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{
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"run_id": run_id,
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"node_id": ref.partition(".")[0],
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"name": alias,
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"uri": resolved,
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"mime_type": self._mime_type(resolved),
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"size": self._file_size(resolved),
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}
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)
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# 全部节点成功后标记完成;期间被暂停则保持 PAUSED,等待续跑补做收尾。
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if self.db.get_run(run_id)["status"] == "PAUSED":
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logger.info("任务 %s 节点全部完成但已暂停,保持 PAUSED", run_id)
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return
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self.db.update_run(
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run_id,
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status="COMPLETED",
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current_node_id=None,
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progress=1.0,
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updated_at=_now_iso(),
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)
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except Exception as exc: # noqa: BLE001
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# 任一步骤异常都结束任务并记录错误,等待用户重试。
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self.db.update_run(
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run_id,
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status="FAILED",
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error=str(exc),
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updated_at=_now_iso(),
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)
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def _final_artifact_uri(
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self,
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resolved: str,
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run: dict,
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definition: WorkflowDefinition,
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alias: str,
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ref: str,
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) -> str:
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"""把最终产物重命名为 上传文件名.标识.时间戳 并返回新 URI。
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标识优先取产出节点的 target_language 参数(如 zh-CN),否则回退为
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产物别名;时间戳取当前时刻,用于区分同一上传文件的多次运行版本。
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重命名在原地进行(同目录),不复制文件。
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"""
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source = Path(resolved)
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# 续跑等场景下源文件可能已被上次收尾重命名过:不再重命名,原样返回。
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if not source.is_file():
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return resolved
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# 基础名来自上传文件名;无上传文件时退回通用名称 subtitle。
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base = Path(run["input_uri"]).stem if run.get("input_uri") else "subtitle"
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# 通过最终输出引用定位产出节点,取其语言参数作为标识。
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node_id = ref.partition(".")[0]
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node = next((item for item in definition.nodes if item.id == node_id), None)
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tag = (node.params.get("target_language") if node else None) or alias
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timestamp = datetime.now(timezone.utc).strftime("%Y%m%d%H%M%S")
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new_path = source.with_name(f"{base}.{tag}.{timestamp}{source.suffix}")
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source.rename(new_path)
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return str(new_path)
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@staticmethod
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def _mime_type(uri: str) -> str:
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"""按扩展名推断产物 MIME 类型,未知类型使用通用二进制类型。"""
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path = Path(uri)
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suffix = path.suffix.lower()
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return {
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".srt": "application/x-subrip",
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".ass": "text/plain",
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".wav": "audio/wav",
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".mp4": "video/mp4",
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".txt": "text/plain",
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}.get(suffix, "application/octet-stream")
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@staticmethod
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def _file_size(uri: str) -> int:
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"""读取产物文件大小;文件缺失时按 0 处理。"""
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try:
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return Path(uri).stat().st_size
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except OSError:
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return 0
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