agent.py

from langchain_openai import ChatOpenAI
from typing import Annotated
from typing_extensions import TypedDict
from langgraph.graph import StateGraph, START, END
from langgraph.prebuilt import ToolNode
from langgraph.graph.message import add_messages

from websearch_tool import websearch_tool
from rag_tool import rag_tool

llm = ChatOpenAI(
            temperature=0.5,
            model="gpt-4o-mini"
        )

class State(TypedDict):
    messages: Annotated[list, add_messages]


tools = [websearch_tool(llm), rag_tool] 
llm_with_tools = llm.bind_tools(tools)

graph_builder = StateGraph(State)

def chatbot(state: State):
    return {"messages": [llm_with_tools.invoke(state["messages"])]}

tool_node = ToolNode(tools=tools)

def route_tools(
    state: State,
):
    """
    Use in the conditional_edge to route to the ToolNode if the last message
    has tool calls. Otherwise, route to the end.
    """
    if isinstance(state, list):
        ai_message = state[-1]
    elif messages := state.get("messages", []):
        ai_message = messages[-1]
    else:
        raise ValueError(f"No messages found in input state to tool_edge: {state}")
    if hasattr(ai_message, "tool_calls") and len(ai_message.tool_calls) > 0:
        return "tools"
    return END

graph_builder.add_node("chatbot", chatbot)
graph_builder.add_node("tools", tool_node)
graph_builder.add_edge(START, "chatbot")
graph_builder.add_conditional_edges(
    "chatbot",
    route_tools,
    {
        "tools": "tools", 
        END: END
    },
)
graph_builder.add_edge("tools", "chatbot")
agent = graph_builder.compile()