■ RunnableBinding 클래스의 batch 메소드를 사용해 복수 문자열 쿼리와의 유사성 기반으로 문서 리스트를 구하는 방법을 보여준다.
▶ main.py
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import os from langchain_core.documents import Document from langchain_core.runnables import RunnableLambda from langchain_chroma import Chroma from langchain_openai import OpenAIEmbeddings os.environ["OPENAI_API_KEY"] = "<OPENAI_API_KEY>" documentList = [ Document( page_content = "Dogs are great companions, known for their loyalty and friendliness.", metadata = {"source" : "mammal-pets-doc"} ), Document( page_content = "Cats are independent pets that often enjoy their own space.", metadata = {"source" : "mammal-pets-doc"}, ), Document( page_content = "Goldfish are popular pets for beginners, requiring relatively simple care.", metadata = {"source" : "fish-pets-doc"}, ), Document( page_content = "Parrots are intelligent birds capable of mimicking human speech.", metadata = {"source" : "bird-pets-doc"}, ), Document( page_content = "Rabbits are social animals that need plenty of space to hop around.", metadata = {"source" : "mammal-pets-doc"}, ), ] chroma = Chroma.from_documents( documentList, embedding = OpenAIEmbeddings(), ) runnableLambda = RunnableLambda(chroma.similarity_search) runnableBinding = runnableLambda.bind(k = 1) # 최상위 결과를 선택한다. searchResultList = runnableBinding.batch(["cat", "shark"]) print(searchResultList) """ [ [ Document( page_content = 'Cats are independent pets that often enjoy their own space.', metadata = {'source' : 'mammal-pets-doc'} ) ], [ Document( page_content = 'Goldfish are popular pets for beginners, requiring relatively simple care.', metadata = {'source' : 'fish-pets-doc'} ) ] ] """ |
▶ requirements.txt
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aiohttp==3.9.5 aiosignal==1.3.1 annotated-types==0.7.0 anyio==4.4.0 asgiref==3.8.1 async-timeout==4.0.3 attrs==23.2.0 backoff==2.2.1 bcrypt==4.1.3 build==1.2.1 cachetools==5.3.3 certifi==2024.6.2 charset-normalizer==3.3.2 chroma-hnswlib==0.7.3 chromadb==0.5.0 click==8.1.7 coloredlogs==15.0.1 Deprecated==1.2.14 distro==1.9.0 dnspython==2.6.1 email_validator==2.1.1 exceptiongroup==1.2.1 fastapi==0.111.0 fastapi-cli==0.0.4 filelock==3.14.0 flatbuffers==24.3.25 frozenlist==1.4.1 fsspec==2024.6.0 google-auth==2.30.0 googleapis-common-protos==1.63.1 greenlet==3.0.3 grpcio==1.64.1 h11==0.14.0 httpcore==1.0.5 httptools==0.6.1 httpx==0.27.0 huggingface-hub==0.23.3 humanfriendly==10.0 idna==3.7 importlib_metadata==7.1.0 importlib_resources==6.4.0 Jinja2==3.1.4 jsonpatch==1.33 jsonpointer==2.4 kubernetes==30.1.0 langchain==0.2.3 langchain-chroma==0.1.1 langchain-core==0.2.5 langchain-openai==0.1.8 langchain-text-splitters==0.2.1 langsmith==0.1.75 markdown-it-py==3.0.0 MarkupSafe==2.1.5 mdurl==0.1.2 mmh3==4.1.0 monotonic==1.6 mpmath==1.3.0 multidict==6.0.5 numpy==1.26.4 oauthlib==3.2.2 onnxruntime==1.18.0 openai==1.33.0 opentelemetry-api==1.25.0 opentelemetry-exporter-otlp-proto-common==1.25.0 opentelemetry-exporter-otlp-proto-grpc==1.25.0 opentelemetry-instrumentation==0.46b0 opentelemetry-instrumentation-asgi==0.46b0 opentelemetry-instrumentation-fastapi==0.46b0 opentelemetry-proto==1.25.0 opentelemetry-sdk==1.25.0 opentelemetry-semantic-conventions==0.46b0 opentelemetry-util-http==0.46b0 orjson==3.10.3 overrides==7.7.0 packaging==23.2 posthog==3.5.0 protobuf==4.25.3 pyasn1==0.6.0 pyasn1_modules==0.4.0 pydantic==2.7.3 pydantic_core==2.18.4 Pygments==2.18.0 PyPika==0.48.9 pyproject_hooks==1.1.0 python-dateutil==2.9.0.post0 python-dotenv==1.0.1 python-multipart==0.0.9 PyYAML==6.0.1 regex==2024.5.15 requests==2.32.3 requests-oauthlib==2.0.0 rich==13.7.1 rsa==4.9 shellingham==1.5.4 six==1.16.0 sniffio==1.3.1 SQLAlchemy==2.0.30 starlette==0.37.2 sympy==1.12.1 tenacity==8.3.0 tiktoken==0.7.0 tokenizers==0.19.1 tomli==2.0.1 tqdm==4.66.4 typer==0.12.3 typing_extensions==4.12.2 ujson==5.10.0 urllib3==2.2.1 uvicorn==0.30.1 uvloop==0.19.0 watchfiles==0.22.0 websocket-client==1.8.0 websockets==12.0 wrapt==1.16.0 yarl==1.9.4 zipp==3.19.2 |
※ pip install langchain langchain-chroma langchain-openai 명령을 실행했다.