80 lines
2.3 KiB
Python
80 lines
2.3 KiB
Python
"""整理澄清问题，等待用户补充"""
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import json
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from langchain_core.messages import HumanMessage, SystemMessage
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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.clarify import CLARIFY_SYSTEM_PROMPT
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from app.schemas.clarification import Clarification
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class ClarifyNode(BaseNode):
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name = "clarify_node"
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async def process(self, state: QueryState) -> QueryState:
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updated_state: QueryState = state.copy()
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intent = state["intent"]
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payload = {
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"intent": intent,
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"input_context": state["input_context"].model_dump(mode="json"),
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}
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if intent != "unclear":
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# 以需求节点的问题为依据补齐选项，不重新判断意图
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payload["requirement"] = state["requirement"].model_dump(mode="json")
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llm_client = get_llm(Clarification)
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clarification = await llm_client.ainvoke(
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[
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SystemMessage(content=CLARIFY_SYSTEM_PROMPT),
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HumanMessage(content=json.dumps(payload, ensure_ascii=False)),
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]
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)
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updated_state["clarification"] = clarification
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return updated_state
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if __name__ == "__main__":
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import asyncio
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import json
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from pydantic import BaseModel
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from app.clients.decision import close_decision_engine
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from app.processor.graph import query_app
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async def main():
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# 修改请求，通过完整流程测试澄清分支
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state: QueryState = {
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"request": {
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"prompt": "这个图不太对",
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"screen": {"canvas": {"width": 1920, "height": 1080}, "nodes": []},
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}
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}
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try:
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final_state = await query_app.ainvoke(
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state, config={"configurable": {"thread_id": "clarify-test"}}
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)
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finally:
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await close_decision_engine()
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print(
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json.dumps(
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{
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key: value.model_dump(mode="json")
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if isinstance(value, BaseModel)
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else value
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for key, value in final_state.items()
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},
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ensure_ascii=False,
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indent=2,
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default=str,
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)
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)
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asyncio.run(main())
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