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Returns a LangChain VectorStoreRetriever for use in chains and agents.
as_retriever(**kwargs) -> VectorStoreRetriever

Parameters

ParameterTypeDescription
**kwargsAnyArguments passed to VectorStoreRetriever (e.g., search_type, search_kwargs)

Returns

VectorStoreRetriever: A retriever backed by this vector store

Example Usage

from langchain.chains import RetrievalQA
from langchain_openai import ChatOpenAI

# Create a retriever from the vector store
retriever = store.as_retriever(
    search_type="similarity",
    search_kwargs={"k": 5}
)

# Use in a RetrievalQA chain
qa_chain = RetrievalQA.from_chain_type(
    llm=ChatOpenAI(),
    retriever=retriever
)

answer = qa_chain.invoke("What is machine learning?")

# MMR retriever for diverse results
mmr_retriever = store.as_retriever(
    search_type="mmr",
    search_kwargs={"k": 5, "fetch_k": 20, "lambda_mult": 0.5}
)