You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
83 lines
2.7 KiB
83 lines
2.7 KiB
import os
|
|
|
|
from swarms.prompts.prompts import EVAL_PREFIX, EVAL_SUFFIX
|
|
from swarms.tools.main import BaseToolSet
|
|
from swarms.tools.main import ToolsFactory
|
|
|
|
|
|
from langchain.chat_models.base import BaseChatModel
|
|
from langchain.schema import BaseOutputParser
|
|
from langchain.callbacks.base import BaseCallbackManager
|
|
|
|
from .chat_agent import ConversationalChatAgent
|
|
from .llm import ChatOpenAI
|
|
from .EvalOutputParser import EvalOutputParser
|
|
|
|
|
|
class AgentBuilder:
|
|
def __init__(self, toolsets: list[BaseToolSet] = []):
|
|
self.llm: BaseChatModel = None
|
|
self.parser: BaseOutputParser = None
|
|
self.global_tools: list = None
|
|
self.toolsets = toolsets
|
|
|
|
def build_llm(self, callback_manager: BaseCallbackManager = None, openai_api_key: str = None):
|
|
self.llm = ChatOpenAI(
|
|
temperature=0, callback_manager=callback_manager, verbose=True, openai_api_key=openai_api_key
|
|
)
|
|
self.llm.check_access()
|
|
|
|
def build_parser(self):
|
|
self.parser = EvalOutputParser()
|
|
|
|
def build_global_tools(self):
|
|
if self.llm is None:
|
|
raise ValueError("LLM must be initialized before tools")
|
|
|
|
toolnames = ["wikipedia"]
|
|
|
|
if os.environ["SERPAPI_API_KEY"]:
|
|
toolnames.append("serpapi")
|
|
if os.environ["BING_SEARCH_URL"] and os.environ["BING_SUBSCRIPTION_KEY"]:
|
|
toolnames.append("bing-search")
|
|
|
|
self.global_tools = [
|
|
*ToolsFactory.create_global_tools_from_names(toolnames, llm=self.llm),
|
|
*ToolsFactory.create_global_tools(self.toolsets),
|
|
]
|
|
|
|
def get_parser(self):
|
|
if self.parser is None:
|
|
raise ValueError("Parser is not initialized yet")
|
|
|
|
return self.parser
|
|
|
|
def get_global_tools(self):
|
|
if self.global_tools is None:
|
|
raise ValueError("Global tools are not initialized yet")
|
|
|
|
return self.global_tools
|
|
|
|
def get_agent(self):
|
|
if self.llm is None:
|
|
raise ValueError("LLM must be initialized before agent")
|
|
|
|
if self.parser is None:
|
|
raise ValueError("Parser must be initialized before agent")
|
|
|
|
if self.global_tools is None:
|
|
raise ValueError("Global tools must be initialized before agent")
|
|
|
|
return ConversationalChatAgent.from_llm_and_tools(
|
|
llm=self.llm,
|
|
tools=[
|
|
*self.global_tools,
|
|
*ToolsFactory.create_per_session_tools(
|
|
self.toolsets
|
|
), # for names and descriptions
|
|
],
|
|
system_message=EVAL_PREFIX.format(bot_name=os.environ["BOT_NAME"]),
|
|
human_message=EVAL_SUFFIX.format(bot_name=os.environ["BOT_NAME"]),
|
|
output_parser=self.parser,
|
|
max_iterations=30,
|
|
) |