Building LLMs for Production

LangChain’s Indexes and Retrievers

As seen earlier, an index in LangChain is a data structure that organizes and stores data to facilitate quick and efficient searches. A retriever effectively uses this index to find and provide relevant data in response to specific queries. LangChain’s indexes and retrievers provide modular, adaptable, and customizable options for handling unstructured data with LLMs. The primary index types in LangChain are based on vector databases, mainly emphasizing indexes using embeddings.

The role of retrievers is to extract relevant documents for integration into language model prompts. In LangChain, a retriever employs a get_relevant_documents method, taking a query string as input and generating a list of documents ...