221 lines
8.0 KiB
Python
221 lines
8.0 KiB
Python
from __future__ import annotations
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import os
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from abc import abstractmethod
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from pathlib import Path
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from langgraph.checkpoint.memory import InMemorySaver
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from langgraph.checkpoint.sqlite.aio import AsyncSqliteSaver, aiosqlite
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from langgraph.graph.state import CompiledStateGraph
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from yuxi import config as sys_config
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from yuxi.agents.context import BaseContext
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from yuxi.storage.postgres.manager import pg_manager
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from yuxi.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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capabilities: list[str] = [] # 智能体能力列表，如 ["file_upload", "web_search"] 等
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context_schema: type[BaseContext] = BaseContext # 智能体上下文 schema
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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.checkpointer = None
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self._async_conn = None
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self.workdir = Path(sys_config.save_dir) / "agents" / self.module_name
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self.workdir.mkdir(parents=True, exist_ok=True)
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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, include_configurable_items: bool = True):
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# metadata 固定在代码中，由各 Agent 的类属性提供
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metadata = self.load_metadata()
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configurable_items = {}
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if include_configurable_items:
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configurable_items = self.context_schema.get_configurable_items()
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# Merge metadata with class attributes, metadata takes precedence
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return {
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"id": self.id,
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"name": getattr(self, "name", "Unknown"),
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"description": getattr(self, "description", "Unknown"),
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"metadata": metadata,
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"configurable_items": configurable_items,
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"capabilities": getattr(self, "capabilities", []), # 智能体能力列表
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}
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async def get_config(self):
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return self.context_schema()
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async def stream_values(self, messages: list[str], input_context=None, **kwargs):
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context = self.context_schema()
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context.update_from_dict(input_context or {})
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graph = await self.get_graph(context=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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context = self.context_schema()
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context.update_from_dict(input_context or {})
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graph = await self.get_graph(context=context)
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logger.debug(f"stream_messages: {context=}")
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# 构建配置：LangGraph 会自动从 checkpointer 恢复 state
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input_config = {
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"configurable": {"thread_id": context.thread_id, "user_id": context.user_id},
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"recursion_limit": 300,
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}
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async for msg, metadata in graph.astream(
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{"messages": messages},
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stream_mode="messages",
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context=context,
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config=input_config,
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):
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yield msg, metadata
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async def invoke_messages(self, messages: list[str], input_context=None, **kwargs):
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context = self.context_schema()
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context.update_from_dict(input_context or {})
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graph = await self.get_graph(context=context)
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logger.debug(f"invoke_messages: {context}")
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# 构建配置
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input_config = {
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"configurable": {"thread_id": context.thread_id, "user_id": context.user_id},
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"recursion_limit": 100,
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}
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msg = await graph.ainvoke(
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{"messages": messages},
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context=context,
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config=input_config,
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)
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return msg
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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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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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def reload_graph(self):
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"""重置 graph 缓存，强制下次调用 get_graph 时重新构建"""
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self.graph = None
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logger.info(f"{self.name} graph 缓存已清空，将在下次调用时重新构建")
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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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async def _get_checkpointer(self):
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if self.checkpointer is not None:
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return self.checkpointer
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checkpointer = None
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backend = os.getenv("LANGGRAPH_CHECKPOINTER_BACKEND", "sqlite").strip().lower()
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if backend == "postgres":
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checkpointer = await self._create_postgres_checkpointer()
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if checkpointer is None:
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try:
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checkpointer = AsyncSqliteSaver(await self.get_async_conn())
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except Exception as e:
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logger.error(f"构建 sqlite checkpointer 失败: {e}, 尝试使用内存存储")
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checkpointer = InMemorySaver()
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self.checkpointer = checkpointer
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return self.checkpointer
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async def _create_postgres_checkpointer(self):
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postgres_url = os.getenv("POSTGRES_URL")
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if not postgres_url:
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logger.warning("POSTGRES_URL 未配置，无法启用 postgres checkpointer，回退 sqlite")
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return None
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try:
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from langgraph.checkpoint.postgres.aio import AsyncPostgresSaver # type: ignore
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except Exception as e:
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logger.warning(f"langgraph postgres checkpointer 不可用，回退 sqlite: {e}")
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return None
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try:
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saver = AsyncPostgresSaver(pg_manager.langgraph_pool)
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logger.info(f"{self.name} 使用 postgres checkpointer")
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return saver
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except Exception as e:
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logger.warning(f"初始化 postgres checkpointer 失败，回退 sqlite: {e}")
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return None
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async def get_async_conn(self) -> aiosqlite.Connection:
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"""获取异步数据库连接"""
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if self._async_conn is not None:
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return self._async_conn
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conn = await aiosqlite.connect(os.path.join(self.workdir, "aio_history.db"))
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# Patch: langgraph's AsyncSqliteSaver expects is_alive() method which aiosqlite may not have
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if not hasattr(conn, "is_alive"):
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conn.is_alive = lambda: True
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self._async_conn = conn
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return self._async_conn
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async def get_aio_memory(self) -> AsyncSqliteSaver:
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"""获取异步存储实例"""
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return AsyncSqliteSaver(await self.get_async_conn())
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def load_metadata(self) -> dict:
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"""Load metadata from agent class attribute."""
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metadata = getattr(self, "metadata", {})
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if isinstance(metadata, dict):
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return metadata
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logger.warning(f"Agent {self.module_name} metadata is not a dict, fallback to empty metadata")
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return {}
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