mirror of
https://github.com/zhenxun-org/zhenxun_bot.git
synced 2026-10-18 02:30:08 +08:00
✨ feat!(llm): 重构并升级大语言模型服务为全新 AI 智能体框架 (#2146)
* ✨ feat!(llm): 重构并升级大语言模型服务为全新 AI 智能体框架 - 【重构】将原 services/llm 重构并迁移至全新的 services/ai 架构，提供向下兼容垫片 - 【新增】引入 Agent、Team、Workflow 三大智能体与工作流编排范式 - 【新增】引入基于 RAG 的长期向量记忆与中期槽位记忆系统 - 【新增】引入基于 Docker 的安全代码执行沙箱环境 - 【新增】支持 MCP 协议，允许动态管理和调用 MCP 服务 - 【新增】引入输入输出安全合规护栏与自愈反思机制 - 【优化】重构并优化多厂商 API 适配器 (Gemini, OpenAI, DeepSeek, GLM 等) - 【优化】优化日志脱敏与 Token 预估机制 - 【移除】移除旧版 llm default 和 llm reset-key 命令，新增 llm mcp 管理命令 * 🔧 chore(deps): 更新项目依赖与配置 - 添加 mcp、jieba 和 aiodocker 依赖到配置文件及 requirements.txt - 在 pyright 配置中设置 reportMissingImports 为 none - 调整 .gitignore 中 resources 目录的忽略规则 * ♻️ refactor(tools): 重构工具终止机制并清理知识库日志输出 - 统一使用 `context.state["__end_run__"]` 替代 `EndRunResult` 控制任务结束 - 移除文件系统和向量知识库检索工具中 `ToolResult` 的 `.with_log` 调用 - 调整指令处理器（Directive）的返回值为 `tool_res.output` - 修复部分类型检查警告并优化联合类型判断语法 * ♻️ refactor(tools): 重构工具副作用指令与控制流熔断机制 - 引入 `DirectivePayload` 及 `ToolResult` 的子类以结构化表达工具副作用 - 移除通过 `context.state` 传递魔术变量的隐式控制流设计 - 重构 `DirectiveManager` 处理器接口，直接在处理器中修改 `AgentState` 并构建 `AgentRunResult` - 在 `StandardAgentExecutor` 中统一通过 `directive_manager` 调度工具返回的副作用指令 - 补全 `MessageBuilder` 中部分核心方法的文档注释 * 🐛 fix(sandbox): 修复 Docker 沙箱容器状态检测与会话清理逻辑 -【修复】修正 `is_alive` 中直接读取私有属性的问题，改用 `show()` 返回值 -【修复】解决 `execute_code` 中缓存的执行器与当前会话不一致的问题 -【优化】在清理工作区前增加容器存活检测，避免向已死容器发送请求 -【优化】创建容器时增加运行状态校验，若已停止则自动从缓存中移除并重建 -【优化】优化容器销毁和清理逻辑，静默处理容器不存在 (404) 的异常 * 📝 docs(core): 补充核心模块初始化方法的文档注释 * 🚨 auto fix by pre-commit hooks --------- Co-authored-by: webjoin111 <455457521@qq.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
This commit is contained in:
Rumio
co-authored by
webjoin111
pre-commit-ci[bot]
webjoin111
pre-commit-ci[bot]
parent
bdc1374848
commit
80fc5b86a7
@@ -0,0 +1,628 @@
|
||||
import asyncio
|
||||
from collections.abc import AsyncIterator, Callable, Sequence
|
||||
from typing import Any, cast
|
||||
|
||||
from pydantic import BaseModel, Field
|
||||
|
||||
from zhenxun.services.ai.core.messages import PromptInput
|
||||
from zhenxun.services.ai.flow.base import BaseRunnable
|
||||
from zhenxun.services.ai.flow.workflow.base import BaseNode
|
||||
from zhenxun.services.ai.flow.workflow.types import (
|
||||
BaseFailurePolicy,
|
||||
StepInput,
|
||||
StepOutput,
|
||||
StepType,
|
||||
)
|
||||
from zhenxun.services.ai.run import RunContext
|
||||
from zhenxun.services.ai.run.di import DependencyInjector
|
||||
from zhenxun.services.log import logger
|
||||
|
||||
NodeSource = BaseNode | BaseRunnable | Callable
|
||||
"""工作流节点来源，可以是图元、可执行引擎或原生函数"""
|
||||
|
||||
|
||||
class Step(BaseNode):
|
||||
"""
|
||||
工作流中的最小执行单元门面 (Facade)。
|
||||
对外部隐藏了 AgentNode 和 FunctionNode 的具体实现。
|
||||
当实例化 Step 时，底层会自动根据 executor 的类型返回专属的节点对象。
|
||||
"""
|
||||
|
||||
def __new__(cls, *args, **kwargs):
|
||||
if cls is Step:
|
||||
executor = kwargs.get("executor")
|
||||
if executor is None and len(args) > 1:
|
||||
executor = args[1]
|
||||
|
||||
from zhenxun.services.ai.flow.base import BaseRunnable
|
||||
|
||||
if isinstance(executor, BaseRunnable):
|
||||
return object.__new__(RunnableNode)
|
||||
elif callable(executor):
|
||||
return object.__new__(FunctionNode)
|
||||
return object.__new__(cls)
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
name: str | None = None,
|
||||
executor: NodeSource | None = None,
|
||||
prompt: PromptInput | None = None,
|
||||
requires_confirmation: bool = False,
|
||||
confirmation_message: str | None = None,
|
||||
failure_policy: BaseFailurePolicy | None = None,
|
||||
):
|
||||
"""
|
||||
初始化工作流单元步骤（门面）。
|
||||
|
||||
参数:
|
||||
name: 步骤的名称，为空则自动取执行器的名称，默认 None。
|
||||
executor: 该步骤要运行的核心执行器（支持 RunnableNode 或 Callable 依赖注入）。
|
||||
prompt: 该步骤的初始输入或提示词定义，默认 None。
|
||||
requires_confirmation: 标记该节点在执行前是否需要人工介入授权，默认 False。
|
||||
confirmation_message: 挂起等待授权时展示的提示文案，默认 None。
|
||||
failure_policy: 该节点执行失败时的错误处理策略，默认使用中断策略。
|
||||
""" # noqa: E501
|
||||
actual_name = name or getattr(
|
||||
executor, "name", getattr(executor, "__name__", "unnamed_step")
|
||||
)
|
||||
super().__init__(
|
||||
name=actual_name,
|
||||
requires_confirmation=requires_confirmation,
|
||||
confirmation_message=confirmation_message,
|
||||
failure_policy=failure_policy,
|
||||
)
|
||||
self.executor = executor
|
||||
self.prompt = prompt
|
||||
|
||||
@property
|
||||
def node_type(self) -> StepType:
|
||||
return StepType.STEP
|
||||
|
||||
async def run_stream(
|
||||
self, step_input: StepInput, context: RunContext
|
||||
) -> AsyncIterator[Any]:
|
||||
if False:
|
||||
yield None
|
||||
raise NotImplementedError(
|
||||
"This is a facade. Real execution happens in subclasses."
|
||||
)
|
||||
|
||||
|
||||
class RunnableNode(Step):
|
||||
"""专门处理 Agent/Team/Workflow 等 BaseRunnable 状态机执行的私有节点"""
|
||||
|
||||
async def run_stream(
|
||||
self, step_input: StepInput, context: RunContext
|
||||
) -> AsyncIterator[Any]:
|
||||
import copy
|
||||
|
||||
from zhenxun.services.ai.flow.base import BaseRunnable
|
||||
from zhenxun.services.ai.run import Task
|
||||
|
||||
executor = cast(BaseRunnable, self.executor)
|
||||
prompt_data = self.prompt if self.prompt is not None else step_input.input
|
||||
|
||||
if isinstance(prompt_data, Task):
|
||||
prompt_data = copy.copy(prompt_data)
|
||||
if step_input.previous_step_content:
|
||||
prev_content = str(step_input.previous_step_content)
|
||||
prompt_data.description = (
|
||||
f"### 🔙 [上游节点执行输出]\n{prev_content}\n\n"
|
||||
f"### 🎯 [当前需执行的任务]\n{prompt_data.description}"
|
||||
)
|
||||
context.run.user_input = prompt_data.description
|
||||
else:
|
||||
if step_input.previous_step_content:
|
||||
prompt_data = (
|
||||
f"[上游节点执行输出]:\n{step_input.previous_step_content}\n\n"
|
||||
f"[当前需执行的任务]:\n{prompt_data or ''}"
|
||||
)
|
||||
context.run.user_input = str(prompt_data) if prompt_data else ""
|
||||
|
||||
final_result = None
|
||||
sandbox_context = context.clone_for_member(self.name)
|
||||
|
||||
async with executor.run_stream(
|
||||
prompt=prompt_data, context=sandbox_context
|
||||
) as stream_result:
|
||||
async for event in stream_result.stream_events():
|
||||
from zhenxun.services.ai.run.models import AgentRunEnd
|
||||
|
||||
if isinstance(event, AgentRunEnd):
|
||||
final_result = event.result
|
||||
yield event
|
||||
|
||||
context.state.update(sandbox_context.state)
|
||||
yield StepOutput(
|
||||
content=final_result.output if final_result else "无返回",
|
||||
success=True,
|
||||
)
|
||||
|
||||
|
||||
class FunctionNode(Step):
|
||||
"""专门处理 Python Callable 依赖注入与执行的私有节点"""
|
||||
|
||||
async def run_stream(
|
||||
self, step_input: StepInput, context: RunContext
|
||||
) -> AsyncIterator[Any]:
|
||||
context.run.user_input = str(step_input.input) if step_input.input else ""
|
||||
|
||||
executor = cast(Callable, self.executor)
|
||||
res = await DependencyInjector.invoke(
|
||||
executor, {"step_input": step_input}, context
|
||||
)
|
||||
|
||||
if isinstance(res, StepOutput):
|
||||
yield res
|
||||
else:
|
||||
yield StepOutput(content=res, success=True)
|
||||
|
||||
|
||||
class StepMeta(BaseModel):
|
||||
"""承载工作流节点装饰器元数据的内部模型"""
|
||||
|
||||
name: str | None = None
|
||||
requires_confirmation: bool = False
|
||||
confirmation_message: str | None = None
|
||||
failure_policy: Any = None
|
||||
|
||||
|
||||
class ConditionMeta(BaseModel):
|
||||
name: str | None = None
|
||||
if_true: list[Any] = Field(default_factory=list)
|
||||
if_false: list[Any] = Field(default_factory=list)
|
||||
|
||||
|
||||
class RouterMeta(BaseModel):
|
||||
name: str | None = None
|
||||
choices: list[Any] = Field(default_factory=list)
|
||||
|
||||
|
||||
class Steps(BaseNode):
|
||||
"""串行执行的工作流容器。按照列表顺序依次执行。"""
|
||||
|
||||
def __init__(self, steps: Sequence[NodeSource], name: str = "StepsGroup"):
|
||||
"""
|
||||
初始化串行工作流容器。
|
||||
|
||||
参数:
|
||||
steps: 依次串行执行的节点/执行器列表。
|
||||
name: 该串行容器 of 名称，默认 "StepsGroup"。
|
||||
"""
|
||||
super().__init__(name=name)
|
||||
self.steps = [NodeFactory.build(step) for step in steps]
|
||||
|
||||
@property
|
||||
def node_type(self) -> StepType:
|
||||
return StepType.STEPS
|
||||
|
||||
async def run_stream(
|
||||
self, step_input: StepInput, context: RunContext
|
||||
) -> AsyncIterator[Any]:
|
||||
current_input = StepInput(
|
||||
input=step_input.input,
|
||||
previous_step_content=step_input.previous_step_content,
|
||||
additional_data=step_input.additional_data.copy(),
|
||||
)
|
||||
|
||||
all_outputs: list[StepOutput] = []
|
||||
for step_obj in self.steps:
|
||||
out_box: list[StepOutput] = []
|
||||
async for event in self._forward_stream(
|
||||
step_obj.aexecute_stream(current_input, context), out_box
|
||||
):
|
||||
yield event
|
||||
step_out = out_box[0] if out_box else None
|
||||
|
||||
if step_out:
|
||||
all_outputs.append(step_out)
|
||||
current_input.previous_step_content = step_out.content
|
||||
if step_out.stop:
|
||||
break
|
||||
|
||||
yield StepOutput(
|
||||
content=all_outputs[-1].content if all_outputs else "No steps executed",
|
||||
success=all(o.success for o in all_outputs),
|
||||
is_paused=any(getattr(o, "is_paused", False) for o in all_outputs),
|
||||
steps=all_outputs,
|
||||
)
|
||||
|
||||
|
||||
class Condition(BaseNode):
|
||||
"""根据条件函数的返回结果，决定走向 steps 还是 else_steps"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
evaluator: Any,
|
||||
steps: Sequence[NodeSource],
|
||||
else_steps: Sequence[NodeSource] | None = None,
|
||||
name: str = "ConditionGroup",
|
||||
):
|
||||
"""
|
||||
初始化条件分支节点。
|
||||
|
||||
参数:
|
||||
evaluator: 用于评估条件真假的布尔值、表达式或可调用函数。
|
||||
steps: 当 evaluator 求值为真时，将执行的步骤序列。
|
||||
else_steps: 当 evaluator 求值为假时，将执行的备用步骤序列，默认 None。
|
||||
name: 该条件分支容器的名称，默认 "ConditionGroup"。
|
||||
"""
|
||||
super().__init__(name=name)
|
||||
self.evaluator = evaluator
|
||||
self.steps = [NodeFactory.build(step) for step in steps]
|
||||
self.else_steps = [NodeFactory.build(step) for step in (else_steps or [])]
|
||||
|
||||
@property
|
||||
def node_type(self) -> StepType:
|
||||
return StepType.CONDITION
|
||||
|
||||
async def run_stream(
|
||||
self, step_input: StepInput, context: RunContext
|
||||
) -> AsyncIterator[Any]:
|
||||
if callable(self.evaluator):
|
||||
condition_result = await DependencyInjector.invoke(
|
||||
self.evaluator, {"step_input": step_input}, context
|
||||
)
|
||||
else:
|
||||
condition_result = bool(self.evaluator)
|
||||
|
||||
target_steps = self.steps if condition_result else self.else_steps
|
||||
branch_name = "if" if condition_result else "else"
|
||||
|
||||
if not target_steps:
|
||||
yield StepOutput(
|
||||
content=f"条件求值为 {condition_result}，无对应步骤需执行。",
|
||||
success=True,
|
||||
)
|
||||
return
|
||||
|
||||
steps_container = Steps(
|
||||
steps=target_steps, name=f"{self.name}_{branch_name}_branch"
|
||||
)
|
||||
out_box: list[StepOutput] = []
|
||||
async for event in self._forward_stream(
|
||||
steps_container.aexecute_stream(step_input, context), out_box
|
||||
):
|
||||
yield event
|
||||
if out_box:
|
||||
yield out_box[0]
|
||||
|
||||
|
||||
class Router(BaseNode):
|
||||
"""根据选择器函数的返回值(名称)，从候选项中挑选步骤执行"""
|
||||
|
||||
def __init__(
|
||||
self, choices: Sequence[NodeSource], selector: Any, name: str = "RouterGroup"
|
||||
):
|
||||
"""
|
||||
初始化选择路由器节点。
|
||||
|
||||
参数:
|
||||
choices: 包含所有候选执行路由分支的步骤序列。
|
||||
selector: 用于决定路由流向的匹配值、或者是返回分支名称的动态选择器函数。
|
||||
name: 该路由器容器的名称，默认 "RouterGroup"。
|
||||
"""
|
||||
super().__init__(name=name)
|
||||
self.choices = [NodeFactory.build(c) for c in choices]
|
||||
self.selector = selector
|
||||
self._choice_map = {}
|
||||
for c in self.choices:
|
||||
if c.name:
|
||||
self._choice_map[c.name] = c
|
||||
|
||||
@property
|
||||
def node_type(self) -> StepType:
|
||||
return StepType.ROUTER
|
||||
|
||||
async def run_stream(
|
||||
self, step_input: StepInput, context: RunContext
|
||||
) -> AsyncIterator[Any]:
|
||||
if callable(self.selector):
|
||||
selected = await DependencyInjector.invoke(
|
||||
self.selector, {"step_input": step_input}, context
|
||||
)
|
||||
else:
|
||||
selected = self.selector
|
||||
|
||||
if not isinstance(selected, list):
|
||||
selected = [selected]
|
||||
|
||||
target_steps = []
|
||||
for s in selected:
|
||||
if isinstance(s, str):
|
||||
if s in self._choice_map:
|
||||
target_steps.append(self._choice_map[s])
|
||||
else:
|
||||
logger.warning(f"Router '{self.name}' 选择了未知的步骤: '{s}'")
|
||||
else:
|
||||
target_steps.append(NodeFactory.build(s))
|
||||
|
||||
if not target_steps:
|
||||
yield StepOutput(content="没有命中任何有效路由分支。", success=True)
|
||||
return
|
||||
|
||||
steps_container = Steps(steps=target_steps, name=f"{self.name}_routed_steps")
|
||||
out_box: list[StepOutput] = []
|
||||
async for event in self._forward_stream(
|
||||
steps_container.aexecute_stream(step_input, context), out_box
|
||||
):
|
||||
yield event
|
||||
if out_box:
|
||||
yield out_box[0]
|
||||
|
||||
|
||||
class Loop(BaseNode):
|
||||
"""循环执行工作流，直至达到最大次数或满足结束条件"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
steps: Sequence[NodeSource],
|
||||
max_iterations: int = 3,
|
||||
end_condition: Any = None,
|
||||
name: str = "LoopGroup",
|
||||
):
|
||||
"""
|
||||
初始化循环控制器节点。
|
||||
|
||||
参数:
|
||||
steps: 每次循环中需要顺序运行的步骤序列。
|
||||
max_iterations: 最大允许循环执行的迭代次数上限，默认 3。
|
||||
end_condition: 决定是否可以提前终止循环的条件布尔值或可调用判定函数，
|
||||
默认 None。
|
||||
name: 该循环容器的名称，默认 "LoopGroup"。
|
||||
"""
|
||||
super().__init__(name=name)
|
||||
self.steps = [NodeFactory.build(step) for step in steps]
|
||||
self.max_iterations = max_iterations
|
||||
self.end_condition = end_condition
|
||||
|
||||
@property
|
||||
def node_type(self) -> StepType:
|
||||
return StepType.LOOP
|
||||
|
||||
async def run_stream(
|
||||
self, step_input: StepInput, context: RunContext
|
||||
) -> AsyncIterator[Any]:
|
||||
logger.debug(
|
||||
f" 🔁 开始循环: [Loop] `{self.name}` (最大 {self.max_iterations} 次)"
|
||||
)
|
||||
|
||||
iteration = 0
|
||||
all_results: list[StepOutput] = []
|
||||
current_input = StepInput(
|
||||
input=step_input.input,
|
||||
previous_step_content=step_input.previous_step_content,
|
||||
additional_data=step_input.additional_data.copy(),
|
||||
)
|
||||
|
||||
while iteration < self.max_iterations:
|
||||
logger.debug(f" ┃ 🔄 第 {iteration + 1} 次迭代...")
|
||||
|
||||
steps_container = Steps(
|
||||
steps=self.steps, name=f"{self.name}_iter_{iteration + 1}"
|
||||
)
|
||||
out_box: list[StepOutput] = []
|
||||
async for event in self._forward_stream(
|
||||
steps_container.aexecute_stream(current_input, context), out_box
|
||||
):
|
||||
yield event
|
||||
iter_output = out_box[0] if out_box else None
|
||||
|
||||
should_stop = False
|
||||
if iter_output:
|
||||
all_results.append(iter_output)
|
||||
if self.end_condition:
|
||||
if callable(self.end_condition):
|
||||
should_stop = await DependencyInjector.invoke(
|
||||
self.end_condition,
|
||||
{"iteration_results": iter_output.steps or [iter_output]},
|
||||
context,
|
||||
)
|
||||
else:
|
||||
should_stop = bool(self.end_condition)
|
||||
|
||||
iteration += 1
|
||||
if should_stop or iter_output.stop:
|
||||
break
|
||||
current_input.previous_step_content = iter_output.content
|
||||
else:
|
||||
iteration += 1
|
||||
break
|
||||
|
||||
yield StepOutput(
|
||||
content=all_results[-1].content if all_results else "No iterations run",
|
||||
success=all(o.success for o in all_results),
|
||||
is_paused=any(getattr(o, "is_paused", False) for o in all_results),
|
||||
steps=all_results,
|
||||
)
|
||||
|
||||
logger.debug(f" ✅ 循环结束: [Loop] `{self.name}` (共执行 {iteration} 次)")
|
||||
|
||||
|
||||
class Parallel(BaseNode):
|
||||
"""并发执行的工作流容器。无序地并发执行内部所有步骤，并最终聚合成一个输出。"""
|
||||
|
||||
def __init__(self, *args: NodeSource | str, name: str | None = None):
|
||||
"""
|
||||
初始化并发工作流容器。
|
||||
|
||||
参数:
|
||||
*args: 并发执行的任务节点/执行器，支持混入字符串覆盖作为 Parallel 的名字。
|
||||
name: 该并发容器的名称，默认 "ParallelGroup"。
|
||||
"""
|
||||
super().__init__(name=name or "ParallelGroup")
|
||||
self.steps = []
|
||||
for arg in args:
|
||||
if isinstance(arg, str):
|
||||
self.name = arg
|
||||
else:
|
||||
self.steps.append(NodeFactory.build(arg))
|
||||
|
||||
@property
|
||||
def node_type(self) -> StepType:
|
||||
return StepType.PARALLEL
|
||||
|
||||
async def run_stream(
|
||||
self, step_input: StepInput, context: RunContext
|
||||
) -> AsyncIterator[Any]:
|
||||
logger.debug(f" 🔀 [并发] `{self.name}` 开启了 {len(self.steps)} 个并发任务")
|
||||
|
||||
queue = asyncio.Queue()
|
||||
bg_tasks = []
|
||||
|
||||
async def worker(idx: int, s_obj: Any, c_ctx: RunContext):
|
||||
try:
|
||||
async for evt in s_obj.aexecute_stream(step_input, c_ctx):
|
||||
await queue.put(("event", evt))
|
||||
except asyncio.CancelledError:
|
||||
pass
|
||||
except Exception as e:
|
||||
await queue.put(("error", e, getattr(s_obj, "name", f"step_{idx}")))
|
||||
finally:
|
||||
await queue.put(
|
||||
("done", idx, c_ctx.state, getattr(c_ctx, "upstream_results", {}))
|
||||
)
|
||||
|
||||
for i, step_obj in enumerate(self.steps):
|
||||
child_context = context.clone_for_execution()
|
||||
task = asyncio.create_task(worker(i, step_obj, child_context))
|
||||
bg_tasks.append(task)
|
||||
|
||||
completed = 0
|
||||
all_outputs: list[StepOutput] = []
|
||||
aggregated_content_parts = [f"## 并发执行结果汇总 [{self.name}]\n"]
|
||||
has_any_failure = False
|
||||
early_stopped = False
|
||||
|
||||
while completed < len(self.steps):
|
||||
msg_type, *data = await queue.get()
|
||||
if msg_type == "event":
|
||||
if isinstance(data[0], StepOutput):
|
||||
out = cast(StepOutput, data[0])
|
||||
all_outputs.append(out)
|
||||
if not out.success:
|
||||
has_any_failure = True
|
||||
status_icon = "✅ 成功" if out.success else "❌ 失败"
|
||||
aggregated_content_parts.append(
|
||||
f"### {status_icon}: {out.step_name}\n{out.content}"
|
||||
)
|
||||
if out.stop and not early_stopped:
|
||||
early_stopped = True
|
||||
logger.info(
|
||||
f"并行分支 '{out.step_name}' 请求终止，"
|
||||
"正在取消其他并发任务..."
|
||||
)
|
||||
for t in bg_tasks:
|
||||
if not t.done():
|
||||
t.cancel()
|
||||
else:
|
||||
yield data[0]
|
||||
elif msg_type == "error":
|
||||
err, s_name = data
|
||||
logger.error(f"并发步骤 '{s_name}' 执行崩溃: {err}")
|
||||
out = StepOutput(
|
||||
step_name=s_name,
|
||||
step_type=StepType.STEP,
|
||||
content=f"执行崩溃: {err}",
|
||||
success=False,
|
||||
error=str(err),
|
||||
)
|
||||
all_outputs.append(out)
|
||||
has_any_failure = True
|
||||
aggregated_content_parts.append(f"### ❌ 失败: {s_name}\n{err}")
|
||||
elif msg_type == "done":
|
||||
_, child_state, child_upstream_results = data
|
||||
context.state.update(child_state)
|
||||
context.upstream_results.update(child_upstream_results)
|
||||
completed += 1
|
||||
|
||||
yield StepOutput(
|
||||
content="\n\n".join(aggregated_content_parts),
|
||||
success=not has_any_failure,
|
||||
is_paused=any(getattr(o, "is_paused", False) for o in all_outputs),
|
||||
steps=all_outputs,
|
||||
stop=any(getattr(o, "stop", False) for o in all_outputs),
|
||||
)
|
||||
|
||||
logger.debug(f" ✅ [并发] `{self.name}` 执行完毕")
|
||||
|
||||
|
||||
class NodeFactory:
|
||||
"""统一节点装配工厂"""
|
||||
|
||||
@classmethod
|
||||
def _create_step(
|
||||
cls,
|
||||
executor: NodeSource,
|
||||
name: str | None = None,
|
||||
requires_confirmation: bool = False,
|
||||
confirmation_message: str | None = None,
|
||||
failure_policy: Any = None,
|
||||
) -> BaseNode:
|
||||
"""底层物理实例化分发"""
|
||||
from zhenxun.services.ai.flow.base import BaseRunnable
|
||||
|
||||
kwargs = {
|
||||
"name": name,
|
||||
"executor": executor,
|
||||
"requires_confirmation": requires_confirmation,
|
||||
"confirmation_message": confirmation_message,
|
||||
"failure_policy": failure_policy,
|
||||
}
|
||||
if isinstance(executor, BaseRunnable):
|
||||
return RunnableNode(**kwargs)
|
||||
elif callable(executor):
|
||||
return FunctionNode(**kwargs)
|
||||
raise ValueError(f"执行器类型 {type(executor)} 无法转换为叶子节点(Step)。")
|
||||
|
||||
@staticmethod
|
||||
def build(item: NodeSource, name: str | None = None) -> BaseNode:
|
||||
if isinstance(item, BaseNode):
|
||||
if name and item.name in (
|
||||
"unnamed_step",
|
||||
"StepsGroup",
|
||||
"ParallelGroup",
|
||||
"ConditionGroup",
|
||||
"RouterGroup",
|
||||
"LoopGroup",
|
||||
):
|
||||
item.name = name
|
||||
return item
|
||||
|
||||
if isinstance(item, BaseRunnable) or callable(item):
|
||||
cond_meta = getattr(item, "__workflow_condition_meta__", None)
|
||||
if cond_meta:
|
||||
final_name = name or cond_meta.name or "ConditionGroup"
|
||||
return Condition(
|
||||
evaluator=item,
|
||||
steps=cond_meta.if_true,
|
||||
else_steps=cond_meta.if_false,
|
||||
name=final_name,
|
||||
)
|
||||
|
||||
router_meta = getattr(item, "__workflow_router_meta__", None)
|
||||
if router_meta:
|
||||
final_name = name or router_meta.name or "RouterGroup"
|
||||
return Router(
|
||||
selector=item,
|
||||
choices=router_meta.choices,
|
||||
name=final_name,
|
||||
)
|
||||
|
||||
step_meta = getattr(item, "__workflow_step_meta__", None)
|
||||
if step_meta:
|
||||
final_name = name or step_meta.name
|
||||
return NodeFactory._create_step(
|
||||
executor=item,
|
||||
name=final_name,
|
||||
requires_confirmation=step_meta.requires_confirmation,
|
||||
confirmation_message=step_meta.confirmation_message,
|
||||
failure_policy=step_meta.failure_policy,
|
||||
)
|
||||
|
||||
return NodeFactory._create_step(executor=item, name=name)
|
||||
|
||||
raise ValueError(
|
||||
f"无法将类型 {type(item)} 装配为工作流节点。"
|
||||
"支持的类型：BaseRunnable, Callable 或 BaseNode。"
|
||||
)
|
||||
Reference in New Issue
Block a user