■ ConversationBufferMemory 클래스를 사용해 LCEL에 메모리를 추가하는 방법을 보여준다.
※ OPENAI_API_KEY 환경 변수 값은 .env 파일에 정의한다.
▶ main.py
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from dotenv import load_dotenv from langchain.memory import ConversationBufferMemory from langchain_core.runnables import RunnableLambda from operator import itemgetter from langchain_core.runnables import RunnablePassthrough from langchain_core.prompts import ChatPromptTemplate from langchain_core.prompts import MessagesPlaceholder from langchain_openai import ChatOpenAI load_dotenv() conversationBufferMemory = ConversationBufferMemory(memory_key = "chat_history", return_messages = True) runnableAssign = RunnablePassthrough.assign(chat_history = RunnableLambda(conversationBufferMemory.load_memory_variables) | itemgetter("chat_history")) chatPromptTemplate = ChatPromptTemplate.from_messages( [ ("system", "You are a helpful chatbot"), MessagesPlaceholder(variable_name = "chat_history"), ("human", "{input}") ] ) chatOpenAI = ChatOpenAI(model = "gpt-4o-mini") runnableSequence = runnableAssign | chatPromptTemplate | chatOpenAI print(conversationBufferMemory.load_memory_variables({})) print("-" * 50) inputString1 = "만나서 반갑습니다. 제 이름은 홍길동 입니다." print(inputString1) print("-" * 50) responseAIMessage = runnableSequence.invoke({"input" : inputString1}) print(responseAIMessage.content) print("-" * 50) conversationBufferMemory.save_context({"human" : inputString1}, {"ai" : responseAIMessage.content}) print(conversationBufferMemory.load_memory_variables({})) print("-" * 50) inputString2 = "제 이름이 무엇이었는지 기억하세요?" print(inputString2) print("-" * 50) responseAIMessage = runnableSequence.invoke({"input" : inputString2}) print(responseAIMessage.content) print("-" * 50) """ {'chat_history': []} -------------------------------------------------- 만나서 반갑습니다. 제 이름은 홍길동 입니다. -------------------------------------------------- 반갑습니다, 홍길동님! 어떻게 도와드릴까요? -------------------------------------------------- {'chat_history': [HumanMessage(content='만나서 반갑습니다. 제 이름은 홍길동 입니다.', additional_kwargs={}, response_metadata={}), AIMessage(content='반갑습니다, 홍길동님! 어떻게 도와드릴까요?', additional_kwargs={}, response_metadata={})]} -------------------------------------------------- 제 이름이 무엇이었는지 기억하세요? -------------------------------------------------- 네, 홍길동님이라고 하셨습니다! 다른 궁금한 점이 있으신가요? -------------------------------------------------- """ |
▶ requirements.txt
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aiohappyeyeballs==2.4.4 aiohttp==3.11.11 aiosignal==1.3.2 annotated-types==0.7.0 anyio==4.8.0 async-timeout==4.0.3 attrs==24.3.0 certifi==2024.12.14 charset-normalizer==3.4.1 distro==1.9.0 exceptiongroup==1.2.2 frozenlist==1.5.0 greenlet==3.1.1 h11==0.14.0 httpcore==1.0.7 httpx==0.28.1 idna==3.10 jiter==0.8.2 jsonpatch==1.33 jsonpointer==3.0.0 langchain==0.3.14 langchain-core==0.3.29 langchain-openai==0.3.0 langchain-text-splitters==0.3.5 langsmith==0.2.10 multidict==6.1.0 numpy==1.26.4 openai==1.59.6 orjson==3.10.14 packaging==24.2 propcache==0.2.1 pydantic==2.10.5 pydantic_core==2.27.2 python-dotenv==1.0.1 PyYAML==6.0.2 regex==2024.11.6 requests==2.32.3 requests-toolbelt==1.0.0 sniffio==1.3.1 SQLAlchemy==2.0.37 tenacity==9.0.0 tiktoken==0.8.0 tqdm==4.67.1 typing_extensions==4.12.2 urllib3==2.3.0 yarl==1.18.3 |
※ pip install python-dotenv langchain langchain_openai 명령을 실행했다.