from src.langgraphagenticai.state.state import State


class ChatbotWithToolNode:
    """
    chatbot logic enhanced with tool integration
    """
    def __init__(self, model):
        self.llm = model

    def process(self, state: State) -> dict:
        """
        Processes the input state and generates a response with tool integration.
        """
        user_input = state["messages"][-1] if state["messages"] else ""
        llm_response = self.llm.invoke([{"role": "user", "content": user_input}])

        # simulate tool-specific logic
        tools_response = f"Tool Integration for: '{user_input}'"

        return {"messages": [llm_response, tools_response]}

    def create_chatbot(self, tools):
        """
        Returns a chatbot node function
        """
        llm_with_tools = self.llm.bind_tools(tools)

        def chatbot_node(state: State):
            """
            Chatbot logic for processing the input state and returning a response
            """
            return {"messages": [llm_with_tools.invoke(state["messages"])]}

        return chatbot_node

    # def chatbot_node(state: State, llm_with_tools):
    #     """
    #     Chatbot logic for processing the input state and returning a response
    #     """
    #     return {"messages": [llm_with_tools.invoke(state["messages"])]}

    # def create_chatbot(self, tools):
    #     """
    #     Returns a chatbot node function
    #     """
    #     llm_with_tools = self.llm.bind_tools(tools)

    #     chatbot_node = self.chatbot_node(State, llm_with_tools)

    #     return chatbot_node