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72 lines
2.3 KiB
Python
72 lines
2.3 KiB
Python
from langchain.chat_models.base import BaseChatModel
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from langchain.output_parsers.base import BaseOutputParser
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from core.prompts.input import EVAL_PREFIX, EVAL_SUFFIX
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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 env import settings
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from .chat_agent import ConversationalChatAgent
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from .llm import ChatOpenAI
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from .parser import EvalOutputParser
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class AgentBuilder:
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def __init__(self, toolsets: list[BaseToolSet] = []):
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self.llm: BaseChatModel = None
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self.parser: BaseOutputParser = None
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self.global_tools: list = None
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self.toolsets = toolsets
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def build_llm(self):
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self.llm = ChatOpenAI(temperature=0)
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def build_parser(self):
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self.parser = EvalOutputParser()
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def build_global_tools(self):
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if self.llm is None:
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raise ValueError("LLM must be initialized before tools")
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toolnames = ["wikipedia"]
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if settings["SERPAPI_API_KEY"]:
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toolnames.append("serpapi")
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if settings["BING_SEARCH_URL"] and settings["BING_SUBSCRIPTION_KEY"]:
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toolnames.append("bing-search")
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self.global_tools = [
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*ToolsFactory.create_global_tools_from_names(toolnames, llm=self.llm),
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*ToolsFactory.create_global_tools(self.toolsets),
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]
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def get_global_tools(self):
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if self.global_tools is None:
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raise ValueError("Global tools are not initialized yet")
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return self.global_tools
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def get_agent(self):
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if self.llm is None:
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raise ValueError("LLM must be initialized before agent")
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if self.parser is None:
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raise ValueError("Parser must be initialized before agent")
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if self.global_tools is None:
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raise ValueError("Global tools must be initialized before agent")
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return ConversationalChatAgent.from_llm_and_tools(
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llm=self.llm,
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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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), # for names and descriptions
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],
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system_message=EVAL_PREFIX.format(bot_name=settings["BOT_NAME"]),
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human_message=EVAL_SUFFIX.format(bot_name=settings["BOT_NAME"]),
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output_parser=self.parser,
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max_iterations=30,
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)
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