mirror of
https://github.com/corca-ai/EVAL
synced 2024-11-01 03:20:10 +00:00
3ec0cc786c
* refactor: api, core * feat: static uploader * doc: update readme * fix: mkdir static file * doc: typo
68 lines
2.1 KiB
Python
68 lines
2.1 KiB
Python
from typing import Dict
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from langchain.agents.tools import BaseTool
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from langchain.agents.agent import Agent, AgentExecutor
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from langchain.chains.conversation.memory import ConversationBufferMemory
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from langchain.memory.chat_memory import BaseChatMemory
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from core.tools.base import BaseToolSet
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from core.tools.factory import ToolsFactory
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from .builder import AgentBuilder
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class AgentManager:
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def __init__(
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self,
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agent: Agent,
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global_tools: list[BaseTool],
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toolsets: list[BaseToolSet] = [],
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):
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self.agent: Agent = agent
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self.global_tools: list[BaseTool] = global_tools
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self.toolsets: list[BaseToolSet] = toolsets
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self.executors: Dict[str, AgentExecutor] = {}
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def create_memory(self) -> BaseChatMemory:
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return ConversationBufferMemory(memory_key="chat_history", return_messages=True)
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def create_executor(self, session: str) -> AgentExecutor:
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memory: BaseChatMemory = self.create_memory()
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return AgentExecutor.from_agent_and_tools(
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agent=self.agent,
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tools=[
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*self.global_tools,
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*ToolsFactory.create_per_session_tools(
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self.toolsets,
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get_session=lambda: (session, self.executors[session]),
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),
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],
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memory=memory,
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verbose=True,
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)
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def remove_executor(self, session: str) -> None:
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if session in self.executors:
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del self.executors[session]
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def get_or_create_executor(self, session: str) -> AgentExecutor:
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if not (session in self.executors):
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self.executors[session] = self.create_executor(session=session)
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return self.executors[session]
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@staticmethod
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def create(toolsets: list[BaseToolSet]) -> "AgentManager":
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builder = AgentBuilder(toolsets)
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builder.build_llm()
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builder.build_parser()
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builder.build_global_tools()
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agent = builder.get_agent()
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global_tools = builder.get_global_tools()
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return AgentManager(
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agent=agent,
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global_tools=global_tools,
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toolsets=toolsets,
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)
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