from dotenv import load_dotenv
load_dotenv()

from langchain.messages import HumanMessage, SystemMessage, AIMessage, ToolMessage
import mlflow

from agent import getGraph
from utils.InterruptPayload import InterruptPayload
from utils.StreamGraph import streamGraph

# MLFLOW
mlflow.set_experiment("TEST PROJET") # VOIR AVEC LA COMMANDE "MLFLOW SERVER"
mlflow.langchain.autolog()

initial_input = {
        'messages':[HumanMessage("Recherche 'Recette de Monster' sur internet")]
    }

config={"configurable": {"thread_id": 'yes'}}

# Et je lance !
streamGraph(initial_input, config, getGraph())