Vector Store and Retriever Components
Explore how LangChainGo simplifies working with various vector databases by providing an abstraction layer through vector store and retriever components. Understand the use of interfaces like AddDocuments and SimilaritySearch for semantic search and the adapter pattern application to convert vector stores into retrievers, enabling efficient document retrieval in Go-based AI applications.
We'll cover the following...
Vector store component
The previous chapters demonstrated semantic search. However, they used features/APIs specific to the vector database (PostgreSQL, Pinecone, and Redis). The upcoming lessons will showcase the key value proposition of the langchaingo framework which provides an abstraction over multiple vector databases including PostgreSQL (using pgvector), Pinecone, Redis, OpenSearch, Weaviate, Milvus, etc.
The ...