Blifai/blif-multi-agent

1from langchain import hub2from langchain.agents import AgentExecutor, create_react_agent3from langchain_openai import OpenAI4from langchain_community.tools import DuckDuckGoSearchResults5from langchain_community.tools.tavily_search import TavilySearchResults6from langchain.tools import tool7 8@tool9def search(query: str) -> str:10    """Search things online"""11    retriever = DuckDuckGoSearchResults()12    return retriever.run(query)13    14class ReActAgent:15  """16  A LangChain agent class with conversation history for contextual processing.17  """18 19  def __init__(self):20    """21    Initializes the agent with default tools, OpenAI LLM, and an empty history.22    """23    self.tools = [TavilySearchResults(max_results=15)]24    # self.tools = [DuckDuckGoSearchResults()]25    self.prompt = hub.pull("hwchase17/react-chat")26    self.llm = OpenAI()27    agent = self.create_agent()28    self.agent_executor = AgentExecutor(agent=agent, tools=self.tools, verbose=True)29  30  def create_agent(self):31    """32    Creates a ReAct agent based on the defined prompt, LLM, and history.33    """34    agent = create_react_agent(self.llm, self.tools, self.prompt)35    return agent36 37  def run(self, question,history=""):38    """39    Executes the agent with the provided question, verbosity option, and updates history.40    """41    answer = self.agent_executor.invoke({"input": question, "chat_history": history})42    return answer43      44