Bruno add scenario for vector search with SQL2025 #21
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DETAILS The Dockerfile has been modified to replace the previous SQL Server 2025 CTP 2.1 image with the official SQL Server 2025 Preview image for Ubuntu 22.04. The image line has been updated from `FROM mcr.microsoft.com/mssql/server:2025-CTP2.1-ubuntu-22.04` to `FROM mcr.microsoft.com/mssql/server:2025-latest`.
DETAILS This commit removes the `MemoryContext` class and its associated dependencies from `ProductEndpoints.cs`, `MemoryContext.cs`, `Products.csproj`, and `Program.cs`. This change signifies a transition away from in-memory storage for product data, potentially indicating a new data management strategy. Additionally, related logging and initialization logic have been eliminated, simplifying the product management process. References to the `VectorEntities` project have also been removed from the solution file.
DETAILS The `ProductVector.cs` file has been completely removed, which included the definition of the `ProductVector` class that inherited from `Product`. This class had properties for `Id`, `Name`, `Description`, `Price`, and a `Vector` of type `ReadOnlyMemory<float>`, all of which were overridden from the base class and included attributes for vector storage. The `VectorEntities.csproj` file has also been removed entirely. This project file defined the project settings, including the target framework (`net9.0`), implicit usings, nullable reference types, and a package reference to `Microsoft.Extensions.VectorData.Abstractions`. It also included a project reference to another project located in the `DataEntities` directory.
DETAILS Modified console output in `AISearch` to reflect "similar products" and added a filter to exclude products with IDs less than or equal to 0, ensuring only valid products are returned in the search results.
DETAILS Modified the LINQ query to directly select the product entity instead of creating an anonymous object with product name and distance. This change simplifies the result set and allows easier access to all properties of the `Product` entity.
DETAILS - Changed `Embedding` initialization in `Product` class to use an empty array `[]`. - Updated `AISearch` method in `ProductAiActions.cs` to include a `dimensions` parameter, modifying embedding generation and reducing returned products from 3 to 2. - Modified `DbInitializer` to pass the `dimensions` parameter for consistent embedding generation. - Changed embedding model name from `"text-embedding-ada-002"` to `"text-embedding-3-small"` in `Program.cs`. - Updated deployment configuration to align with the new embedding model name and version.
DETAILS - Added new using directives for Entity Framework Core and OpenAI namespaces. - Corrected the globalization environment variable from "fal" to "false". - Commented out the old method of adding DbContext with `AddSqlServerDbContext`. - Introduced a new approach to retrieve the connection string from configuration and initialize DbContext with vector search enabled. - Added comments for clarity on DbContext handling and Azure OpenAI client configuration.
DETAILS Removed the `ProductAiActions` class and integrated its `AISearch` method into `ProductApiActions`. Updated `using` directives to include necessary namespaces, refactored response construction for improved readability, and updated routing for the AISearch endpoint to ensure continued functionality.
DETAILS The project file `Products.csproj` has been updated to remove several package references, including `Aspire.Microsoft.EntityFrameworkCore.SqlServer`, `Microsoft.SemanticKernel.Connectors.InMemory`, `Microsoft.VisualStudio.Web.CodeGeneration.Design`, and `OpenTelemetry.Instrumentation.AspNetCore`. Additionally, the project reference to `VectorEntities.csproj` has been removed. The remaining package references are `Aspire.Azure.AI.OpenAI` and `EFCore.SqlServer.VectorSearch`.
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👋 Thanks for contributing @elbruno! We will review the pull request and get back to you soon. |
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This pull request introduces a new scenario, "SQL 2025 Preview," showcasing the integration of vector search and vector indexes in SQL Server 2025 within a .NET Aspire application. The changes include updates to documentation, project setup, and implementation of the scenario's core functionality, along with unit tests to ensure robustness.
SQL 2025 Scenario Implementation:
Scenario Documentation: Added a new entry for "SQL 2025 Preview" in
README.mdand created a dedicatedREADME.mdfor the scenario. This includes an overview, features, architecture diagram, deployment guidance, and cost/security considerations. [1] [2]Project Setup:
DataEntities.csprojtargeting.NET 9.0with nullable reference types enabled..editorconfigsettings to suppress specific warnings (CS8602andIDE0058).Core Functionality:
Productclass with support for SQL Server 2025's vector type and JSON serialization.ProductDataContextfor database operations and initialized sample product data with vector embeddings.AISearch()function inProductApiActionsto perform semantic search using vector embeddings.Unit Testing:
Products.Tests.csprojtargeting.NET 9.0with references toEntityFrameworkCore.InMemoryandMSTest.ProductApiActionsTests.Tooling and Configuration:
dotnet-eftodotnet-tools.jsonfor database migrations and management.These changes collectively enable semantic search capabilities in a .NET Aspire application using SQL Server 2025's vector search features.