The Python SQL Server Collection uses pyodbc to connect, that can be installed by the command below, but you will need to install the ODBC driver for SQL Server separately, this differs by platform, see theAzure
使用Azure SQL 和 Semantic 在您自己的數據上建置終極聊天機器人 |公開的數據 取代為 Anna Hoffman, Davide Mauri 公開的資料 2024年11月14日 瞭解如何使用RAG、NL2SQL和Semantic Kernel來建置Ultimate Chatbot,以查詢所有數據、結構化和非結構化。 瞭解 AI 的實際運作方式,...
Microsoft.SemanticKernel.Connectors.AzureCosmosDBMongoDB Microsoft.SemanticKernel.Connectors.AzureCosmosDBNoSQL Microsoft.SemanticKernel.Connectors.AzureOpenAI Microsoft.SemanticKernel.Connectors.Chroma Microsoft.SemanticKernel.Connectors.DuckDB Microsoft.SemanticKernel.Connectors.Google ...
We’ve heard from many in the community who want to use Semantic Kernel to query their relational database using natural language expressions. We are excited to share this sandbox that enables you explore the capabilities of LLM to generate SQL queries (or SELECT statements):NL2SQL. This has ...
@eavanvalkenburg internally raised the good question of our SQL Server text mapping (nvarchar(255) vs. nvarchar(max)). This is indeed a tricky aspect of SQL Server (not of SQL databases in general, SQLite/PG are fine). nvarchar(max) cann...
博主这里选择的是 mcpdotnet,假设我们希望在 Semantic Kernel 中集成Playwright MCP Server。此时,我们可以编写下面的代码来连接到对应的 MCP Server: varclientOptions=newMcpClientOptions(){ClientInfo=newMcpDotNet.Protocol.Types.Implementation(){Name=name,Version="1.0.0"},};varserverConfig=newMcpServerConfig(...
["https://github.com/microsoft/semantic-kernel/blob/main/dotnet/src/SemanticKernel/Memory/Volatile/VolatileMemoryStore.cs"] ="C# class that defines a volatile embedding store", ["https://github.com/microsoft/semantic-kernel/tree/main/samples/dotnet/KernelHttpServer/README.md"] ...
An example that shows how to use Semantic Kernel and Kernel Memory to work with embeddings in a .NET application using SQL Server as Vector Database. - marcominerva/OpenAIEmbeddingSample
Much like Azure Cognitive Search, a SQL Database can be consumed by Semantic Kernel using the same technique. Again, we start by implementing a Plugin: This is slightly more complex - we added three Semantic Functions: GetTables: Gets all tables in the database; ...
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