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| from src.langgraphagenticai.state.state import State | |
| from src.langgraphagenticai.tools.search_tool import get_tavily_search_tool | |
| class ChatbotWithToolNode: | |
| """ | |
| Chatbot logic enhanced with tool integration | |
| """ | |
| def __init__(self,model): | |
| self.llm = model | |
| def process(self,state:State): | |
| """ | |
| Processes the input state and generates response with the tool integration. | |
| """ | |
| user_input = state["messages"][-1] if state["messages"] else "" | |
| llm_response = self.llm.invoke([{"role":"user","content":user_input}]) | |
| # Tool invocation | |
| tool = get_tavily_search_tool() | |
| tools_response = tool.invoke({"query":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 the response. | |
| """ | |
| return {"messages": [llm_with_tools.invoke(state["messages"])]} | |
| return chatbot_node | |