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The official private preview documentation and code samples for the Vector search feature in Azure Cognitive Search.

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Vector search (public preview) - Azure Cognitive Search

DISCLAIMER Preview functionality is provided under Supplemental Terms of Use, without a service level agreement, and isn't recommended for production workloads.

This repository provides code samples for the vector search (preview) in Azure Cognitive Search.

The demos currently use alpha builds of the Azure SDKs. Instructions for downloading an alpha build can be found in the readme files for each sample.

Sample Purpose Description
.NET Creates vector representations of images or text A .NET Console App that calls Azure OpenAI to create vectorized data. We used this console app to create the sample data for the demo index. You can revise your copy of the notebook to test vector search with other data and your own schemas. See the sample readme for instructions on console app setup.
Python Creates vector representations of images or text A notebook that calls Azure OpenAI to create vectorized data. We used this notebook to create the sample data for the demo index. You can revise your copy of the notebook to test vector search with other data and your own schemas. See the sample readme for instructions on notebook setup.
JavaScript Creates vector representations of images or text A node.js version of the Python sample. See the sample readme for instructions on sample setup.
Postman collection Create, load, and query a search index that contains text and vector fields. A collection of REST API calls to an Azure Cognitive Search instance. The requests in this collection include an index schema, sample documents, and sample queries. The collection is documented in Quickstart: Vector search. Each query demonstrates key scenarios.

Use the Postman app and import the collection.

Set collection variables to provide your search service URI and admin key

If you're unfamiliar with Postman, see this Postman/REST quickstart for Cognitive Search.

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