badcce5d2d
用户修复外部问题后输入 resume，会从失败 action 重新执行，而不是结束整个流程。 回滚从 workflow 中拆出，新增显式命令： chat：rollback [IP] CLI：rollback --checkpoint ... [--ip ...] [--stop-first|--no-stop-first] 旧 confirm approve/reject 只保留为旧 checkpoint 兼容入口，新流程不再推荐使用。 LangGraph workflow 已移除回滚确认 interrupt 节点，失败暂停和续跑走业务 checkpoint。 README、打包 README、run.sh --help、流程图、todo、提示词基线和测试都已同步。
137 lines
5.2 KiB
Python
137 lines
5.2 KiB
Python
"""PAM 部署 Agent 的 LangGraph 图工厂。"""
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from __future__ import annotations
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from typing import Any
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from .agent import PamDeployAgent
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from .langgraph_runtime import GraphFlow
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def build_langgraph(agent: PamDeployAgent | None = None, flow: GraphFlow = "deploy"):
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"""构建兼容旧输入格式的 action 级 LangGraph 部署图。
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输入 state 支持直接传 `params`，图内会先调用 `create_state`；CLI/chat
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默认使用 `LangGraphDeploymentRuntime`，该 runtime 直接接收 `AgentState`
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并由业务 checkpoint 支撑断点续跑。
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"""
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try:
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from langgraph.graph import END, START, StateGraph
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except ImportError as exc: # pragma: no cover - 依赖可选安装状态
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raise RuntimeError("未安装 langgraph。请先执行 `pip install -e .` 安装项目依赖。") from exc
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runtime = agent or PamDeployAgent()
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def create_state_node(state: dict[str, Any]) -> dict[str, Any]:
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"""根据输入参数创建 AgentState。"""
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if "agent_state" in state:
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return {"agent_state": state["agent_state"]}
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agent_state = runtime.create_state(
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params=state["params"],
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execution_strategy=state.get("execution_strategy", "hybrid_node_mcp"),
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run_id=state.get("run_id"),
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script_entry=state.get("script_entry"),
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config_path=state.get("config_path"),
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trace_file_path=state.get("trace_file_path"),
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checkpoint_path=state.get("checkpoint_path"),
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target_ips=state.get("target_ips"),
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)
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return {"agent_state": agent_state}
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def global_action_node(state: dict[str, Any]) -> dict[str, Any]:
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"""执行一个全局 action。"""
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agent_state = state["agent_state"]
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action = runtime.next_global_action(agent_state)
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if action:
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runtime.run_global_action(agent_state, action)
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return {"agent_state": agent_state}
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def prepare_ip_node(state: dict[str, Any]) -> dict[str, Any]:
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"""选择下一个 IP action。"""
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agent_state = state["agent_state"]
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work = runtime.next_ip_action(agent_state)
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if work is None:
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return {"agent_state": agent_state, "current_ip": "", "current_ip_action": ""}
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ip, action = work
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return {"agent_state": agent_state, "current_ip": ip, "current_ip_action": action}
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def ip_action_node(state: dict[str, Any]) -> dict[str, Any]:
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"""执行一个 IP action。"""
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agent_state = state["agent_state"]
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ip = str(state.get("current_ip", ""))
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action = str(state.get("current_ip_action", ""))
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if ip and action:
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runtime.run_ip_action(agent_state, ip, action)
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return {"agent_state": agent_state, "current_ip": "", "current_ip_action": ""}
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def report_node(state: dict[str, Any]) -> dict[str, Any]:
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"""渲染最终部署报告。"""
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return {
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"agent_state": state["agent_state"],
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"report": runtime.render_report(state["agent_state"]),
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}
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def route_entry(state: dict[str, Any]) -> str:
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"""入口路由。"""
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agent_state = state["agent_state"]
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if agent_state.pending_confirmation:
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return "report"
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if runtime.next_global_action(agent_state):
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return "global_action"
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if flow == "global":
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return "report"
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return "prepare_ip"
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def route_after_global(state: dict[str, Any]) -> str:
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"""全局 action 后路由。"""
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agent_state = state["agent_state"]
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if runtime.next_global_action(agent_state):
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return "global_action"
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if flow == "global":
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return "report"
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return "prepare_ip"
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def route_after_prepare_ip(state: dict[str, Any]) -> str:
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"""IP 准备节点后路由。"""
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agent_state = state["agent_state"]
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if agent_state.pending_confirmation:
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return "report"
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if state.get("current_ip_action"):
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return "ip_action"
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return "report"
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graph = StateGraph(dict)
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graph.add_node("create_state", create_state_node)
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graph.add_node("global_action", global_action_node)
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graph.add_node("prepare_ip", prepare_ip_node)
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graph.add_node("ip_action", ip_action_node)
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graph.add_node("report", report_node)
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graph.add_edge(START, "create_state")
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graph.add_conditional_edges(
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"create_state",
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route_entry,
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{"global_action": "global_action", "prepare_ip": "prepare_ip", "report": "report"},
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)
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graph.add_conditional_edges(
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"global_action",
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route_after_global,
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{"global_action": "global_action", "prepare_ip": "prepare_ip", "report": "report"},
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)
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graph.add_conditional_edges(
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"prepare_ip",
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route_after_prepare_ip,
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{"ip_action": "ip_action", "report": "report"},
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)
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graph.add_edge("ip_action", "prepare_ip")
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graph.add_edge("report", END)
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return graph.compile()
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def build_graph_or_none(agent: PamDeployAgent | None = None, flow: GraphFlow = "deploy"):
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"""在未安装 LangGraph 时返回 None，便于调用方降级。"""
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try:
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return build_langgraph(agent=agent, flow=flow)
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except RuntimeError:
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return None
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