■ VectorStoreRetriever 클래스의 configurable_fields 메소드에서 search_kwargs 인자에 ConfigurableField 객체를 설정하는 방법을 보여준다.
▶ main.py
|
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 |
from langchain_community.retrievers import BM25Retriever from langchain_openai import OpenAIEmbeddings from langchain_community.vectorstores import FAISS from langchain_core.runnables import ConfigurableField from langchain.retrievers import EnsembleRetriever stringList1 = [ "I like apples", "I like oranges", "Apples and oranges are fruits" ] bm25Retriever = BM25Retriever.from_texts(stringList1, metadatas = [{"source" : 1}] * len(stringList1)) bm25Retriever.k = 2 stringList2 = [ "You like apples", "You like oranges" ] openAIEmbeddings = OpenAIEmbeddings() faiss = FAISS.from_texts(stringList2, openAIEmbeddings, metadatas = [{"source" : 2}] * len(stringList2)) vectorStoreRetriever = faiss.as_retriever(search_kwargs = {"k" : 2}) runnableConfigurableFields = vectorStoreRetriever.configurable_fields( search_kwargs = ConfigurableField( id = "search_kwargs_faiss", name = "Search Kwargs", description = "The search kwargs to use", ) ) ensembleRetriever = EnsembleRetriever(retrievers = [bm25Retriever, runnableConfigurableFields], weights = [0.5, 0.5]) configurationDictionary = {"configurable" : {"search_kwargs_faiss" : {"k" : 1}}} documentList = ensembleRetriever.invoke("apples", config = configurationDictionary) for document in documentList: print(document.page_content) |
▶ requirements.txt
|
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 |
aiohappyeyeballs==2.4.0 aiohttp==3.10.5 aiosignal==1.3.1 annotated-types==0.7.0 anyio==4.4.0 attrs==24.2.0 certifi==2024.8.30 charset-normalizer==3.3.2 colorama==0.4.6 dataclasses-json==0.6.7 distro==1.9.0 faiss-cpu==1.8.0.post1 frozenlist==1.4.1 greenlet==3.1.0 h11==0.14.0 httpcore==1.0.5 httpx==0.27.2 idna==3.8 jiter==0.5.0 jsonpatch==1.33 jsonpointer==3.0.0 langchain==0.2.16 langchain-community==0.2.16 langchain-core==0.2.39 langchain-openai==0.1.23 langchain-text-splitters==0.2.4 langsmith==0.1.120 marshmallow==3.22.0 multidict==6.1.0 mypy-extensions==1.0.0 numpy==1.26.4 openai==1.45.0 orjson==3.10.7 packaging==24.1 pydantic==2.9.1 pydantic_core==2.23.3 PyYAML==6.0.2 rank-bm25==0.2.2 regex==2024.9.11 requests==2.32.3 sniffio==1.3.1 SQLAlchemy==2.0.34 tenacity==8.5.0 tiktoken==0.7.0 tqdm==4.66.5 typing-inspect==0.9.0 typing_extensions==4.12.2 urllib3==2.2.3 yarl==1.11.1 |
※ install langchain-community langchain-openai faiss-cpu rank_bm25 명령을 실행했다.