Vector Databases are specialized systems designed to store and retrieve high-dimensional data, supporting processes like machine learning and artificial intelligence by efficiently handling vectors. Their architecture optimizes similarity search and data analysis, ensuring rapid data access. Vector Databases utilize structures like HNSW and FAISS to manage vectors, facilitating swift similarity searches. By leveraging indexing and retrieval mechanisms, these databases are crucial for...
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We use Chroma for RAG (Retrieval-augmented generation).