You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Copy file name to clipboardExpand all lines: README.md
+2-2Lines changed: 2 additions & 2 deletions
Original file line number
Diff line number
Diff line change
@@ -8,12 +8,12 @@ products:
8
8
urlFragment: azure-sql-db-openai
9
9
name: Vector similarity search with Azure SQL & Azure OpenAI
10
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
11
+
Use Azure OpenAI from Azure SQL database to get the vector embeddings of any chosen text, and then calculate the cosine similarity to find related topics
12
12
---
13
13
14
14
# Vector similarity search with Azure SQL & Azure OpenAI
15
15
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.
16
+
This example shows how to use Azure OpenAI from Azure SQL database to get the vector embeddings of any chosen 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.
17
17
18
18
For an introduction on text and code embeddings, check out this OpenAI article: [Introducing text and code embeddings](https://openai.com/blog/introducing-text-and-code-embeddings).
0 commit comments