PGVector: Turn PostgreSQL into Vector Database (Python Tutorial)
Struggling to figure out where to store AI embeddings? In this tutorial, we show how to use PostgreSQL with PGVector to store and query embeddings from movie descriptions — no new database needed! You’ll see how to create a table, generate embeddings with OpenAI, insert them, and perform similarity search. By the end, you’ll have a working setup for building AI-powered search, recommendations, or RAG systems, all within the database you already know. Perfect for beginners looking to get hands-on with AI embeddings!
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GITHUB - https://github.com/sunny2309/postgres...
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Important Chapters:
0:00 - AI Embeddings in PostgreSQL (Pgvector)
0:54 - Code
1:18 - Install Pgvector Extension
3:04 - Enable Pgvector Extension
3:23 - Verify pgvector setup
4:05 - Store Embeddings in PostgreSQL DB
7:11 - Query Embeddings (Cosine Distance/Similarity)
10:41 - Distance Metrics
12:32 - Speedup Search using DB Indexes (IVFFlat & HNSW)
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