■ Chroma 클래스의 as_retriever 메소드에서 search_type/search_kwargs 인자를 사용해 VectorStoreRetriever 객체를 만드는 방법을 보여준다. (similarity_score_threshold)
※ OPENAI_API_KEY 환경 변수 값은 .env 파일에 정의한다.
▶ main.py
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from dotenv import load_dotenv from langchain.text_splitter import RecursiveCharacterTextSplitter from langchain_community.document_loaders import TextLoader from langchain_openai.embeddings import OpenAIEmbeddings from langchain_chroma import Chroma load_dotenv() recursiveCharacterTextSplitter = RecursiveCharacterTextSplitter(chunk_size = 600, chunk_overlap = 0) textLoader1 = TextLoader("nlp-keywords.txt" ) textLoader2 = TextLoader("finance-keywords.txt") splitDocumentList1 = textLoader1.load_and_split(recursiveCharacterTextSplitter) splitDocumentList2 = textLoader2.load_and_split(recursiveCharacterTextSplitter) chroma = Chroma.from_documents(documents = splitDocumentList1 + splitDocumentList2, embedding = OpenAIEmbeddings(), collection_name = "test") vectorStoreRetriever = chroma.as_retriever( search_type = "similarity_score_threshold", search_kwargs = {"score_threshold" : 0.8} ) retrieveDocumentList = vectorStoreRetriever.invoke("Word2Vec에 대하여 알려줘") print(retrieveDocumentList) |
▶ 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 asgiref==3.8.1 async-timeout==4.0.3 attrs==24.3.0 backoff==2.2.1 bcrypt==4.2.1 build==1.2.2.post1 cachetools==5.5.0 certifi==2024.12.14 charset-normalizer==3.4.1 chroma-hnswlib==0.7.6 chromadb==0.5.23 click==8.1.8 coloredlogs==15.0.1 dataclasses-json==0.6.7 Deprecated==1.2.15 distro==1.9.0 durationpy==0.9 exceptiongroup==1.2.2 fastapi==0.115.6 filelock==3.16.1 flatbuffers==24.12.23 frozenlist==1.5.0 fsspec==2024.12.0 google-auth==2.37.0 googleapis-common-protos==1.66.0 greenlet==3.1.1 grpcio==1.69.0 h11==0.14.0 httpcore==1.0.7 httptools==0.6.4 httpx==0.28.1 httpx-sse==0.4.0 huggingface-hub==0.27.1 humanfriendly==10.0 idna==3.10 importlib_metadata==8.5.0 importlib_resources==6.5.2 jiter==0.8.2 jsonpatch==1.33 jsonpointer==3.0.0 kubernetes==31.0.0 langchain==0.3.14 langchain-chroma==0.2.0 langchain-community==0.3.14 langchain-core==0.3.29 langchain-openai==0.3.0 langchain-text-splitters==0.3.5 langsmith==0.2.10 markdown-it-py==3.0.0 marshmallow==3.25.1 mdurl==0.1.2 mmh3==5.0.1 monotonic==1.6 mpmath==1.3.0 multidict==6.1.0 mypy-extensions==1.0.0 numpy==1.26.4 oauthlib==3.2.2 onnxruntime==1.20.1 openai==1.59.7 opentelemetry-api==1.29.0 opentelemetry-exporter-otlp-proto-common==1.29.0 opentelemetry-exporter-otlp-proto-grpc==1.29.0 opentelemetry-instrumentation==0.50b0 opentelemetry-instrumentation-asgi==0.50b0 opentelemetry-instrumentation-fastapi==0.50b0 opentelemetry-proto==1.29.0 opentelemetry-sdk==1.29.0 opentelemetry-semantic-conventions==0.50b0 opentelemetry-util-http==0.50b0 orjson==3.10.14 overrides==7.7.0 packaging==24.2 posthog==3.8.3 propcache==0.2.1 protobuf==5.29.3 pyasn1==0.6.1 pyasn1_modules==0.4.1 pydantic==2.10.5 pydantic-settings==2.7.1 pydantic_core==2.27.2 Pygments==2.19.1 PyPika==0.48.9 pyproject_hooks==1.2.0 python-dateutil==2.9.0.post0 python-dotenv==1.0.1 PyYAML==6.0.2 regex==2024.11.6 requests==2.32.3 requests-oauthlib==2.0.0 requests-toolbelt==1.0.0 rich==13.9.4 rsa==4.9 shellingham==1.5.4 six==1.17.0 sniffio==1.3.1 SQLAlchemy==2.0.37 starlette==0.41.3 sympy==1.13.3 tenacity==9.0.0 tiktoken==0.8.0 tokenizers==0.20.3 tomli==2.2.1 tqdm==4.67.1 typer==0.15.1 typing-inspect==0.9.0 typing_extensions==4.12.2 urllib3==2.3.0 uvicorn==0.34.0 uvloop==0.21.0 watchfiles==1.0.4 websocket-client==1.8.0 websockets==14.1 wrapt==1.17.2 yarl==1.18.3 zipp==3.21.0 |
※ pip install python-dotenv langchain-community langchain_openai langchain_chroma 명령을 실행했다.
nlp-keywords.txt
finance-keywords.txt