9_Memory_agent.py

import os
from typing import TypedDict, List, Union
from langchain_core.messages import HumanMessage, AIMessage
from langchain_openai import ChatOpenAI
from langgraph.graph import StateGraph, START, END
from dotenv import load_dotenv

load_dotenv()

class AgentState(TypedDict):
    messages: List[Union[HumanMessage, AIMessage]]

llm = ChatOpenAI(model='gpt-4o-mini')

def process(state: AgentState) -> AgentState:
    """This node will solve the request from the input"""
    response = llm.invoke(state['messages'])
    state['messages'].append(AIMessage(content=response.content))
    print(f"\n AI: {response.content}")
    print(f"Current state: {state['messages']}")
    return state

graph = StateGraph(AgentState)
graph.add_node("process", process)
graph.add_edge(START, 'process')
graph.add_edge('process', END)

agent = graph.compile()

conversation_history = []

user_input = input("Enter:")
while user_input != "exit":
    conversation_history.append(HumanMessage(content=user_input))
    result = agent.invoke({'messages': conversation_history})
    print(result['messages'])
    conversation_history = result['messages']
    user_input = input("Enter: ")

with open('logging.txt', 'w') as file:
    file.write("Your conversation Log:\n")
    for message in conversation_history:
        if isinstance(message, HumanMessage):
            file.write(f"You: {message.content}\n")
        elif isinstance(message, AIMessage):
            file.write(f"AI: {message.content}\n")
    file.write("End of Conversation")

print("Conversation saved to logging.txt")