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| import sys | |
| import os | |
| sys.path.append(os.path.join(os.path.dirname(__file__), '..', '..')) | |
| from src.state.state import graphstate | |
| class ChatbotWithToolNodes: | |
| def __init__(self, model): | |
| self.llm = model | |
| def peocess(self, state: graphstate): | |
| 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: graphstate): | |
| """ | |
| Chatbot logic for processing the input state and returning a response. | |
| """ | |
| return {"messages": [llm_with_tools.invoke(state["messages"])]} | |
| return chatbot_node |