import os

from typing import Union, Dict, TypedDict, List

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() # Load environment variables from .env file

class AgentState(TypedDict):

messages: List[Union[HumanMessage, AIMessage]]

llm = ChatOpenAI(model="gpt-4o")

def process(state:AgentState) -> AgentState:

"""This node will solve the request and append the response to the messages."""

response = llm.invoke(state["messages"])

state["messages"].append(AIMessage(content = response.content))

print(f"\n AI: {response.content}")

return state

graph = StateGraph(AgentState)

graph.add_node("processor", process)

graph.add_edge(START, "processor")

graph.add_edge("processor", END)

agent = graph.compile()

converstatin_history = []

user_input = input("Enter:")

while user_input!= "exit":

converstatin_history.append(HumanMessage(content=user_input))

result = agent.invoke({"messages": converstatin_history})

converstatin_history = result["messages"] # Update the conversation history with the latest messages

user_input = input("Enter:")

with open("logging.txt", "w") as file:

file.write("Your conversation log:\n")

for message in converstatin_history:

if isinstance(message, HumanMessage):

file.write(f"You: {message.content}\n")

elif isinstance(message, AIMessage):

file.write(f"AI: {message.content}")

file.write("End of conversation")

print("Convesation saved to logging.txt")