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| 1 | +--- |
| 2 | +page_type: sample |
| 3 | +languages: |
| 4 | +- sql |
| 5 | +products: |
| 6 | +- azure-openai |
| 7 | +- azure-sql-database |
| 8 | +urlFragment: azure-sql-db-openai |
| 9 | +name: Vector similarity search with Azure SQL & Azure OpenAI |
| 10 | +description: | |
| 11 | + Use Azure OpenAI from Azure SQL database to get the vector embeddings of any choosen text, and then calculate the cosine similarity to find related topics |
| 12 | +--- |
| 13 | + |
1 | 14 | # Vector similarity search with Azure SQL & Azure OpenAI |
2 | 15 |
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3 | 16 | This example shows how to use Azure OpenAI from Azure SQL database to get the vector embeddings of any choosen text, and then calculate the [cosine similarity](https://learn.microsoft.com/en-us/azure/storage/common/storage-sas-overview) against the Wikipedia articles (for which vector embeddings have been already calculated,) to find the articles that covers topics that are close - or similar - to the provided text. |
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