155 lines
6.3 KiB
Python
155 lines
6.3 KiB
Python
"""分析失败动作，生成下一次修正建议"""
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import json
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from langchain_core.exceptions import OutputParserException
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from langchain_core.messages import HumanMessage, SystemMessage
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from pydantic import BaseModel, ValidationError
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from app.actions.plan import plan_materials
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from app.clients.llm import get_llm
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from app.processor.base import BaseNode
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from app.processor.state import QueryState
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from app.prompt.reflection import REFLECTION_SYSTEM_PROMPT
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from app.schemas.action_repair import ActionRepairPlan
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class ReflectionNode(BaseNode):
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name = "reflection_node"
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async def process(self, state: QueryState) -> QueryState:
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# 浅拷贝状态
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updated_state: QueryState = state.copy()
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llm_client = get_llm(ActionRepairPlan)
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# 汇总原始上下文、需求和失败信息，让模型基于实际错误提出修正建议
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payload = {
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"input_context": state["input_context"].model_dump(mode="json"),
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"requirement": state["requirement"].model_dump(mode="json"),
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# 动作可能在生成或解析阶段就失败，没有动作时传入空列表
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"actions": [
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action.model_dump(mode="json") for action in state.get("actions") or []
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],
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# 将校验错误转成字典，保留错误类型、动作下标和具体原因
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"validation_errors": [
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error.model_dump() for error in state["validation_errors"]
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],
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# 如果已有修正建议，一并提供给模型，帮助分析上次修正后仍失败的原因
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"previous_repair_plan": state["repair_plan"].model_dump()
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if state.get("repair_plan")
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else None,
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}
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# 如果动作来自大屏规划，补充规划和新增组件物料，避免修正时偏离规划或物料定义
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if state.get("screen_plan") is not None:
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payload["screen_plan"] = state["screen_plan"].model_dump(mode="json")
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payload["component_materials"] = plan_materials(state)
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# 只捕获输出结构和解析错误，配置、网络等异常继续向上抛出
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try:
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# 异步生成修正建议，本节点不直接修改动作
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result = await llm_client.ainvoke(
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[
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# 系统消息提供稳定的失败分析和修正规则
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SystemMessage(content=REFLECTION_SYSTEM_PROMPT),
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# 用户消息承载本轮待分析的具体资料，序列化时保留中文
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HumanMessage(content=json.dumps(payload, ensure_ascii=False)),
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]
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)
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# 将模型对象转成字典后统一校验，非模型返回值直接交给协议校验
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plan = ActionRepairPlan.model_validate(
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result.model_dump() if isinstance(result, BaseModel) else result
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)
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except (ValidationError, OutputParserException):
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# 如果未能得到合法建议，清空旧修正计划，避免再次使用已失效的建议
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updated_state["repair_plan"] = None
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# 记录无法继续修正的原因，交给后续路由和失败处理流程
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updated_state["failure_reason"] = "未能生成有效的动作修正建议"
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return updated_state
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# 保存通过校验的修正建议，供后续路由判断及动作重新生成使用
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updated_state["repair_plan"] = plan
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# 仅在建议允许重试时将次数加一，缺少历史计数时从零开始，不可重试时保持原次数
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updated_state["retry_count"] = state.get("retry_count", 0) + int(plan.retryable)
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# 可以重试时清空旧失败原因，否则使用建议中的原因说明为何停止修正
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updated_state["failure_reason"] = None if plan.retryable else plan.reason
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# 返回修正建议、重试次数和失败原因，由后续路由决定重新生成动作还是结束
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return updated_state
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if __name__ == "__main__":
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import asyncio
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from app.processor.nodes.input_node import InputNode
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from app.schemas.action_validation import ActionValidationError
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from app.schemas.actions import UpdateAction
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from app.schemas.requirement import Requirement
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async def main():
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state = InputNode().process(
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{
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"request": {
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"prompt": "把标题改成月度销售额",
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"screen": {
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"canvas": {"width": 1920, "height": 1080},
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"nodes": [
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{
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"id": "chart",
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"type": "chart",
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"layout": {
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"x": 100,
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"y": 200,
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"width": 400,
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"height": 300,
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},
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"props": {"title": "销售额"},
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}
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],
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},
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}
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}
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)
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state["requirement"] = Requirement(
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intent="modify_screen",
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goal="修改标题",
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needs_clarification=False,
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changes=[
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{
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"target_scope": "nodes",
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"target_ids": ["chart"],
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"operation": "update",
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"parameters": {"title": "月度销售额"},
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}
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],
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)
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state["actions"] = [
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UpdateAction(
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target_id="chart",
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section="props",
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path=["option", "title"],
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value="月度销售额",
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)
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]
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state["validation_passed"] = False
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state["validation_errors"] = [
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ActionValidationError(
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action_index=0,
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code="execution_error",
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message="中间路径不存在: props ['option']",
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)
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]
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node = ReflectionNode()
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final_state = await node.process(state)
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print(
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json.dumps(
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final_state,
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ensure_ascii=False,
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indent=2,
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default=lambda value: value.model_dump(mode="json"),
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)
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)
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asyncio.run(main())
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