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A Coding Guide to Implement a pgvector-Powered Semantic, Hybrid, Sparse, and Quantized Vector Search System

MarkTechPost
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A Coding Guide to Implement a pgvector-Powered Semantic, Hybrid, Sparse, and Quantized Vector Search System
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In this tutorial, we build a complete pgvector playground inside Google Colab and explore how PostgreSQL can work as a powerful vector database for modern AI applications.

We start by installing PostgreSQL, compiling the pgvector extension, connecting through Psycopg, and registering vector types for smooth Python integration.

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Original source: MarkTechPost

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