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from src.Langgraph_Agentic_AI.state.state import State
class ChatbotWithToolNode:
"""
A class representing a chatbot node that can interact with tools.
"""
def __init__(self, model):
self.llm = model
def process(self, state: State) -> dict:
"""
Process the state and return the response from the model with tools.
"""
user_input = state["messages"][-1] if state["messages"] else ""
llm_response = self.model.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 |