103 lines
3.7 KiB
Python
103 lines
3.7 KiB
Python
from __future__ import annotations
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from abc import abstractmethod
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from langgraph.graph.state import CompiledStateGraph
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from src.agents.common.context import BaseContext
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from src.utils import logger
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class BaseAgent:
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"""
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定义一个基础 Agent 供 各类 graph 继承
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"""
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name = "base_agent"
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description = "base_agent"
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def __init__(self, **kwargs):
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self.graph = None # will be covered by get_graph
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self.context_schema = BaseContext
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@property
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def module_name(self) -> str:
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"""Get the module name of the agent class."""
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return self.__class__.__module__.split(".")[-2]
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@property
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def id(self) -> str:
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"""Get the agent's class name."""
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return self.__class__.__name__
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async def get_info(self):
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return {
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"id": self.id,
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"name": self.name if hasattr(self, "name") else "Unknown",
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"description": self.description if hasattr(self, "description") else "Unknown",
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"configurable_items": self.context_schema.get_configurable_items(),
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"has_checkpointer": await self.check_checkpointer(),
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}
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async def get_config(self):
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return self.context_schema.from_file(module_name=self.module_name)
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async def stream_values(self, messages: list[str], input_context=None, **kwargs):
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graph = await self.get_graph()
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context = self.context_schema.from_file(module_name=self.module_name, input_context=input_context)
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for event in graph.astream({"messages": messages}, stream_mode="values", context=context):
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yield event["messages"]
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async def stream_messages(self, messages: list[str], input_context=None, **kwargs):
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graph = await self.get_graph()
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context = self.context_schema.from_file(module_name=self.module_name, input_context=input_context)
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logger.debug(f"stream_messages: {context}")
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# TODO 的 Checkpointer 似乎还没有适配最新的 Context API
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async for msg, metadata in graph.astream(
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{"messages": messages}, stream_mode="messages", context=context, config={"configurable": input_context}
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):
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yield msg, metadata
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async def check_checkpointer(self):
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app = await self.get_graph()
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if not hasattr(app, "checkpointer") or app.checkpointer is None:
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logger.warning(f"智能体 {self.name} 的 Graph 未配置 checkpointer，无法获取历史记录")
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return False
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return True
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async def get_history(self, user_id, thread_id) -> list[dict]:
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"""获取历史消息"""
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try:
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app = await self.get_graph()
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if not await self.check_checkpointer():
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return []
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config = {"configurable": {"thread_id": thread_id, "user_id": user_id}}
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state = await app.aget_state(config)
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result = []
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if state:
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messages = state.values.get("messages", [])
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for msg in messages:
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if hasattr(msg, "model_dump"):
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msg_dict = msg.model_dump() # 转换成字典
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else:
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msg_dict = dict(msg) if hasattr(msg, "__dict__") else {"content": str(msg)}
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result.append(msg_dict)
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return result
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except Exception as e:
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logger.error(f"获取智能体 {self.name} 历史消息出错: {e}")
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return []
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@abstractmethod
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async def get_graph(self, **kwargs) -> CompiledStateGraph:
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"""
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获取并编译对话图实例。
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必须确保在编译时设置 checkpointer，否则将无法获取历史记录。
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例如: graph = workflow.compile(checkpointer=sqlite_checkpointer)
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"""
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pass
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