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"First we need to define our logic for searching over documents. LangChain defines a [Retriever](/docs/modules/data_connection/retrievers/) interface which wraps an index that can return relevant `Documents` given a string query.\n",
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"First we need to define our logic for searching over documents. LangChain defines a [Retriever](/docs/modules/data_connection/retrievers/) interface which wraps an index that can return relevant `Documents` given a string query.\n",
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"The most common type of `Retriever` is the [VectorStoreRetriever](/docs/modules/data_connection/retrievers/vectorstore), which uses the similarity search capabilities of a vector store to facillitate retrieval. Any `VectorStore` can easily be turned into a `Retriever` with `VectorStore.as_retriever()`:"
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"The most common type of `Retriever` is the [VectorStoreRetriever](/docs/modules/data_connection/retrievers/vectorstore), which uses the similarity search capabilities of a vector store to facilitate retrieval. Any `VectorStore` can easily be turned into a `Retriever` with `VectorStore.as_retriever()`:"
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