dynworkflow
dynworkflow 是一个 Python 3.12 库，用于编排动态工作流，工作流节点可以调用一个或多个 ACP Agent。
安装
使用项目包管理器安装：
uv sync
运行时依赖为 websockets，开发依赖包括 pytest 和 mypy。
快速开始
import dynworkflow as d
flow = d.Flow(
"document-flow",
agent=d.AgentClient("ws://127.0.0.1:7433/acp?k=a"),
)
@flow.node("summarize")
def summarize() -> d.TaskGenerator:
result = yield d.Agent("Summarize the documents in docs/test", path="docs/test")
return d.Result(result)
flow.execute(summarize())
使用 @flow.node(name) 声明节点。普通节点可以返回 None、Result 或一个或多个下游 Execute 任务。生成器节点可以 yield Agent 或 MultiAgent，接收 Agent 结果后返回节点结果。
公共 API
Flow：创建并执行工作流。Flow.node(name)：注册节点函数。Flow.execute(*tasks)：在当前进程中执行任务，并在所有节点结束后抛出节点异常。Flow.run(*tasks)：在 fork 子进程中运行工作流，并监听 stdin 中的 JSONL 控制命令。Agent：描述一次 Agent 请求。MultiAgent：并发运行多个 Agent 请求。AgentClient：连接 ACP WebSocket 端点。Result：保存节点的最终结果。
执行语义
- 相互独立的节点会并发运行。
- 节点失败后会立即变为
error状态，并在启用上报时立即发送状态。 - 失败节点不会停止兄弟节点。
- 所有节点异常会在最后统一以
ExceptionGroup抛出。 - 节点和 Agent 的终止命令只影响指定目标；工作流关闭会终止整个工作流。
缓存与状态上报
缓存默认启用。可以使用 Flow(..., cache=False) 关闭缓存。缓存文件位于 .alkaid0/workflow.db；设置 ALKAID0_WORKFLOW_SESSION_ID 可以隔离不同会话。
可以通过 Flow(..., report=True) 或环境变量 ALKAID0_WORKFLOW_REPORT=1 开启 JSONL 状态上报。Flow.run() 会自动开启上报。事件包括 graph、node、agent、agents_start、node_code 和 node_log。
示例
参见 example.py，其中包含使用 AgentClient、Agent、MultiAgent、分支和回退参数的完整工作流示例。
测试
运行测试套件：
python -m pytest -q
运行静态编译检查：
python -m compileall -q src tests
文档索引
docs/SKILL.md：仅供 AI Agent 读取的使用说明，保持英文。docs/architecture.md：面向人的实现与生命周期说明。docs/protocol.md：stdin 控制命令和 JSONL 上报事件说明。docs/test/ai_must_read.md：示例工作流读取的测试文档。
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