■ ChatMessageHistory 클래스에서 채팅 메시지 히스토리를 요약해서 LLM과 채팅하는 방법을 보여준다.
※ OPENAI_API_KEY 환경 변수 값은 .env 파일에 정의한다.
▶ main.py
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from dotenv import load_dotenv from langchain_core.prompts import ChatPromptTemplate from langchain_openai import ChatOpenAI from langchain_community.chat_message_histories import ChatMessageHistory from langchain_core.runnables.history import RunnableWithMessageHistory from langchain_core.runnables import RunnablePassthrough load_dotenv() chatPromptTemplate = ChatPromptTemplate.from_messages( [ ("system" , "You are a helpful assistant. Answer all questions to the best of your ability."), ("placeholder", "{chat_history}"), ("human" , "{input}") ] ) chatOpenAI = ChatOpenAI(model = "gpt-4o-mini") runnableSequence1 = chatPromptTemplate | chatOpenAI chatMessageHistory = ChatMessageHistory() chatMessageHistory.add_user_message("Hey there! I'm Nemo.") chatMessageHistory.add_ai_message("Hello!") chatMessageHistory.add_user_message("How are you today?") chatMessageHistory.add_ai_message("Fine thanks!") runnableWithMessageHistory = RunnableWithMessageHistory( runnableSequence1, lambda session_id : chatMessageHistory, input_messages_key = "input", history_messages_key = "chat_history" ) def summarizeMessageList(inputDictionary): messageList = chatMessageHistory.messages if len(messageList) == 0: return False summarizeChatPromptTemplate = ChatPromptTemplate.from_messages( [ ("placeholder", "{chat_history}"), ("user" , "Distill the above chat messages into a single summary message. Include as many specific details as you can.") ] ) summarizeRunnableSequence = summarizeChatPromptTemplate | chatOpenAI summaryResponseAIMessage = summarizeRunnableSequence.invoke({"chat_history" : messageList}) chatMessageHistory.clear() chatMessageHistory.add_message(summaryResponseAIMessage) return True runnableSequence2 = RunnablePassthrough.assign(is_summarized = summarizeMessageList) | runnableWithMessageHistory responseAIMessage = runnableSequence2.invoke({"input" : "What did I say my name was?"}, {"configurable" : {"session_id" : "unused"}}) print(responseAIMessage.content) """ You mentioned that your name is Nemo. """ |
▶ requirements.txt
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aiohappyeyeballs==2.4.4 aiohttp==3.11.10 aiosignal==1.3.1 annotated-types==0.7.0 anyio==4.7.0 attrs==24.2.0 certifi==2024.8.30 charset-normalizer==3.4.0 colorama==0.4.6 dataclasses-json==0.6.7 distro==1.9.0 frozenlist==1.5.0 greenlet==3.1.1 h11==0.14.0 httpcore==1.0.7 httpx==0.28.1 httpx-sse==0.4.0 idna==3.10 jiter==0.8.0 jsonpatch==1.33 jsonpointer==3.0.0 langchain==0.3.10 langchain-community==0.3.10 langchain-core==0.3.22 langchain-openai==0.2.11 langchain-text-splitters==0.3.2 langsmith==0.1.147 marshmallow==3.23.1 multidict==6.1.0 mypy-extensions==1.0.0 numpy==2.2.0 openai==1.57.0 orjson==3.10.12 packaging==24.2 propcache==0.2.1 pydantic==2.10.3 pydantic-settings==2.6.1 pydantic_core==2.27.1 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==2.0.36 tenacity==9.0.0 tiktoken==0.8.0 tqdm==4.67.1 typing-inspect==0.9.0 typing_extensions==4.12.2 urllib3==2.2.3 yarl==1.18.3 |
※ pip install python-dotenv langchain-community langchain-openai 명령을 실행했다.