8000 improved heading · sirmnemonic/azure-sql-db-openai@12be68a · GitHub
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‎README.md

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The script `./vector-embeddings/02-create-vectors-table.sql` does exactly that. It creates two tables, one for the title embeddings and one for the content embeddings, and the creates a clustered columnstore on those tables to enable efficient vector processing.
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## Find similar articles calculating cosine distance
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## Find similar articles by calculating cosine distance
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The third script `./vector-embeddings/03-find-similar-articles.sql` starts invoking OpenAI to get the vector embeddings of an arbitrary text.
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