Refactor agents and tools (#91)

* Move tools to agents

* Move agents to dedicate place

* Remove subclassing BaseAgent from BaseTool

knowledgehub/agents/base.py

@@ -0,0 +1,68 @@
+from enum import Enum
+from typing import Optional, Union
+
+from theflow import Node, Param
+
+from kotaemon.base import BaseComponent
+from kotaemon.llms import PromptTemplate
+from kotaemon.llms.chats.base import ChatLLM
+from kotaemon.llms.completions.base import LLM
+
+from .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(BaseComponent):
+    """Define base agent interface"""
+
+    name: str = Param(help="Name of the agent.")
+    agent_type: AgentType = Param(help="Agent type, must be one of AgentType")
+    description: str = Param(
+        help="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]] = Node(
+        help="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]]] = Param(
+        help="A prompt template or a dict to supply different prompt to the agent"
+    )
+    plugins: list[BaseTool] = Param(
+        default_callback=lambda _: [],
+        help="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)