■ InMemoryCache 클래스를 사용해 LLM 입출력 텍스트를 캐싱해서 동일한 입력 텍스트를 LLM 호출시 캐시를 활용하는 방법을 보여준다.
※ OPENAI_API_KEY 환경 변수 값은 .env 파일에 정의한다.
▶ main.py
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import langchain from dotenv import load_dotenv from langchain_openai import ChatOpenAI from langchain_community.cache import InMemoryCache load_dotenv() langchain.llm_cache = InMemoryCache() chatOpenAI = ChatOpenAI(model = "gpt-3.5-turbo-0125") llmResult1 = chatOpenAI.invoke("고양이 울음소리는?") print(llmResult1) llmResult2 = chatOpenAI.invoke("고양이 울음소리는?") print(llmResult2) llmResult3 = chatOpenAI.invoke("까마귀 울음소리는?") print(llmResult3) """ content = '야옹!' response_metadata = {'token_usage' : {'completion_tokens' : 4 , 'prompt_tokens' : 18, 'total_tokens' : 22}, 'model_name' : 'gpt-3.5-turbo-0125', 'system_fingerprint' : None, 'finish_reason' : 'stop', 'logprobs' : None} id = 'run-d77a8ca9-d93f-478d-94da-397d3881c8d3-0' usage_metadata = {'input_tokens' : 18, 'output_tokens' : 4 , 'total_tokens' : 22} content = '야옹!' response_metadata = {'token_usage' : {'completion_tokens' : 4 , 'prompt_tokens' : 18, 'total_tokens' : 22}, 'model_name' : 'gpt-3.5-turbo-0125', 'system_fingerprint' : None, 'finish_reason' : 'stop', 'logprobs' : None} id = 'run-d77a8ca9-d93f-478d-94da-397d3881c8d3-0' usage_metadata = {'input_tokens' : 18, 'output_tokens' : 4 , 'total_tokens' : 22} content = '까악 까악!' response_metadata = {'token_usage' : {'completion_tokens' : 10, 'prompt_tokens' : 20, 'total_tokens' : 30}, 'model_name' : 'gpt-3.5-turbo-0125', 'system_fingerprint' : None, 'finish_reason' : 'stop', 'logprobs' : None} id = 'run-c0c33aff-126c-483b-91bf-0ffb8b4ef1d3-0' usage_metadata = {'input_tokens' : 20, 'output_tokens' : 10, 'total_tokens' : 30} """ |
▶ requirements.txt
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aiohttp==3.9.5 aiosignal==1.3.1 annotated-types==0.7.0 anyio==4.4.0 async-timeout==4.0.3 attrs==23.2.0 certifi==2024.6.2 charset-normalizer==3.3.2 dataclasses-json==0.6.7 distro==1.9.0 exceptiongroup==1.2.1 frozenlist==1.4.1 greenlet==3.0.3 h11==0.14.0 httpcore==1.0.5 httpx==0.27.0 idna==3.7 jsonpatch==1.33 jsonpointer==3.0.0 langchain==0.2.5 langchain-community==0.2.5 langchain-core==0.2.9 langchain-openai==0.1.8 langchain-text-splitters==0.2.1 langsmith==0.1.80 marshmallow==3.21.3 multidict==6.0.5 mypy-extensions==1.0.0 numpy==1.26.4 openai==1.35.0 orjson==3.10.5 packaging==24.1 pydantic==2.7.4 pydantic_core==2.18.4 python-dotenv==1.0.1 PyYAML==6.0.1 regex==2024.5.15 requests==2.32.3 sniffio==1.3.1 SQLAlchemy==2.0.31 tenacity==8.4.1 tiktoken==0.7.0 tqdm==4.66.4 typing-inspect==0.9.0 typing_extensions==4.12.2 urllib3==2.2.2 yarl==1.9.4 |
※ pip install python-dotenv langchain-community langchain-openai 명령을 실행했다.