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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"] 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 |