Introduce CommunityToolkit.VectorData.SqlServer #16
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| // Licensed to the .NET Foundation under one or more agreements. | ||
| // The .NET Foundation licenses this file to you under the MIT license. | ||
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| # CommunityToolkit.VectorData.SqlServer | ||
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| SQL Server and Azure SQL provider for [Microsoft.Extensions.VectorData](https://learn.microsoft.com/en-us/dotnet/ai/vector-stores/overview). | ||
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| ## Usage | ||
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| ```csharp | ||
| using Microsoft.Extensions.VectorData; | ||
| using CommunityToolkit.VectorData.SqlServer; | ||
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Contributor
Author
There was a problem hiding this comment. Another change when compared to microsoft/DacFx#786, the namespace is |
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| // Define your record model | ||
| public sealed class BlogPost | ||
| { | ||
| [VectorStoreKey] | ||
| public int Id { get; set; } | ||
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| [VectorStoreData] | ||
| public string? Title { get; set; } | ||
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| [VectorStoreData] | ||
| public string? Url { get; set; } | ||
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| [VectorStoreData] | ||
| public string? Content { get; set; } | ||
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| [VectorStoreVector(Dimensions: 1536)] | ||
| public ReadOnlyMemory<float> ContentEmbedding { get; set; } | ||
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There was a problem hiding this comment. We may want to modernize these examples to use auto embedding generation. See https://learn.microsoft.com/en-us/dotnet/ai/vector-stores/define-your-data-model?tabs=attributes%2Ckey-attribute%2Cdata-attribute%2Cvector-attribute#automatic-embedding-generation-recommended [VectorStoreVector(Dimensions: 1536)]
public string ContentEmbedding => Content;This also requires configuring the vector store with an Embedding Generator, so if too complex for a simple inline example like this, feel free to ignore. And certainly feel free to do this in a follow up PR if you agree with the suggestion. |
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| } | ||
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| // Create the vector store and get a collection | ||
| using SqlServerVectorStore vectorStore = new(connectionString); | ||
| var collection = vectorStore.GetCollection<int, BlogPost>("BlogPosts"); | ||
| await collection.EnsureCollectionExistsAsync(); | ||
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| // Upsert records | ||
| await collection.UpsertAsync(new BlogPost | ||
| { | ||
| Id = 1, | ||
| Title = "Vector search in Azure SQL", | ||
| Content = "...", | ||
| ContentEmbedding = embedding // ReadOnlyMemory<float> from your embedding provider | ||
| }); | ||
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| // Search | ||
| var results = await collection.SearchAsync(queryEmbedding, top: 5).ToListAsync(); | ||
| ``` | ||
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| ## Documentation | ||
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| - [Vector stores in .NET](https://learn.microsoft.com/en-us/dotnet/ai/vector-stores/overview) | ||
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to other code reviewers: microsoft/DacFx#786 was our source of truth, what we needed was to change the license header from
// Copyright (c) Microsoft. All rights reserved.