LangChain_Memory/2_ConversationBufferMemory.py

"""
Data Scientist.: Dr.Eddy Giusepe Chirinos Isidro

Objetivo: Estudar o uso de Memória no LangChain,
          para ter ChatBots mais inteligentes.
"""
import os
import openai
from dotenv import find_dotenv, load_dotenv
_ = load_dotenv(find_dotenv()) # read local .env file
openai.api_key  = os.getenv('OPENAI_API_KEY')

from langchain.chat_models import ChatOpenAI
from langchain.chains import ConversationChain
from langchain.memory import ConversationBufferMemory


memory = ConversationBufferMemory()

llm = ChatOpenAI(temperature=0.0,
                 max_tokens=150,
                 verbose=False
                )

conversation = ConversationChain(llm=llm,
                                 verbose=False,
                                 memory=memory
                                )

# Salvando o Prompt e o Modelo:
#conversation.llm.save("eddy_LLM.json") # AttributeError: 'ChatOpenAI' object has no attribute 'save'
conversation.prompt.save("eddy_prompt.json")

# memory.chat_memory.add_user_message("Meu nome é Eddy Giusepe.")
# memory.chat_memory.add_user_message("Eu sou Cientista de dados e trabalho na central IT.")
# memory.chat_memory.add_user_message("Eu sou Peruano.")

print("Digite a sua pergunta para começar uma conversa com a AI: ")
while True:
    query = input("Human: ")
    result = conversation({"input": query})
    #print(result)
    print("AI: " + result['response'])
    memory.chat_memory.add_user_message(query)
    memory.chat_memory.add_ai_message(result['response'])
    memory.save_context({"input": query}, {"output": result['response']})
    memory_variables = memory.load_memory_variables({})
    print("🤗🤗🤗")
    #print(memory_variables)
    #print("#"*30)
    #print(memory_variables['history'])
    
    if not query:
        break