kotaemon/knowledgehub/pipelines/agents/base.py
Tuan Anh Nguyen Dang (Tadashi_Cin) 8bb7ad91e0 Add Langchain Agent wrapper with OpenAI Function / Self-ask agent support (#82)
* update Param() type hint in MVP

* update default embedding endpoint

* update Langchain agent wrapper

* update langchain agent
2023-11-20 16:26:08 +07:00

62 lines
1.8 KiB
Python

from enum import Enum
from typing import Dict, List, Optional, Union
from kotaemon.llms import PromptTemplate
from kotaemon.llms.chats.base import ChatLLM
from kotaemon.llms.completions.base import LLM
from kotaemon.pipelines.tools import BaseTool
BaseLLM = Union[ChatLLM, LLM]
class AgentType(Enum):
"""
Enumerated type for agent types.
"""
openai = "openai"
openai_multi = "openai_multi"
openai_tool = "openai_tool"
self_ask = "self_ask"
react = "react"
rewoo = "rewoo"
vanilla = "vanilla"
@staticmethod
def get_agent_class(_type: "AgentType"):
"""
Get agent class from agent type.
:param _type: agent type
:return: agent class
"""
if _type == AgentType.rewoo:
from .rewoo.agent import RewooAgent
return RewooAgent
else:
raise ValueError(f"Unknown agent type: {_type}")
class BaseAgent(BaseTool):
name: str
"""Name of the agent."""
agent_type: AgentType
"""Agent type, must be one of AgentType"""
description: str
"""Description used to tell the model how/when/why to use the agent.
You can provide few-shot examples as a part of the description. This will be
input to the prompt of LLM."""
llm: Union[BaseLLM, Dict[str, BaseLLM]]
"""Specify LLM to be used in the model, cam be a dict to supply different
LLMs to multiple purposes in the agent"""
prompt_template: Optional[Union[PromptTemplate, Dict[str, PromptTemplate]]]
"""A prompt template or a dict to supply different prompt to the agent
"""
plugins: List[BaseTool] = []
"""List of plugins / tools to be used in the agent
"""
def add_tools(self, tools: List[BaseTool]) -> None:
"""Helper method to add tools and update agent state if needed"""
self.plugins.extend(tools)