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tutorial/markdown/aspnet/semantic-kernel/semantic-kernel-tutorial.md

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# frontmatter
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path: "/tutorial-csharp-couchbase-vector-search-semantic-kernel"
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path: "/tutorial-csharp-semantic-kernel-vector-search-with-hyperscale-or-composite-vector-index"
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alt_paths: ["/tutorial-csharp-semantic-kernel-vector-search-with-hyperscale-vector-index", "/tutorial-csharp-semantic-kernel-vector-search-with-composite-vector-index"]
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# title and description do not need to be added to markdown, start with H2 (##)
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title: Build Vector Search with Couchbase .NET Semantic Kernel Connector and OpenAI
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title: Build Vector Search with Semantic Kernel, Couchbase Hyperscale and Composite Vector Index
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short_title: Vector Search with Semantic Kernel
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description:
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- Build a semantic search application using Couchbase Vector Search with Semantic Kernel.
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- Build a semantic search application using Semantic Kernel with Couchbase Hyperscale and Composite Vector Index.
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- Learn to use the Couchbase .NET Vector Store Connector for Microsoft Semantic Kernel.
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- Discover how to generate embeddings with OpenAI and store them in Couchbase.
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- Perform vector similarity searches with filtering using SQL++ and ANN_DISTANCE.
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content_type: tutorial
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filter: sdk
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technology:
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- hyperscale vector index
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- composite vector index
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- vector search
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- kv
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tags:
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- Semantic Kernel
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- OpenAI
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- Artificial Intelligence
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- Hyperscale Vector Index
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- Composite Vector Index
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sdk_language:
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- csharp
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length: 30 Mins
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---
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## Repository Links
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- **Connector Repository**: [couchbase-semantic-kernel](https://github.com/Couchbase-Ecosystem/couchbase-semantic-kernel) - The official Couchbase .NET Vector Store Connector for Microsoft Semantic Kernel
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- **This Example**: [CouchbaseVectorSearchDemo](https://github.com/couchbase-examples/couchbase-semantic-kernel-quickstart/tree/main/CouchbaseVectorSearchDemo) - Complete working example demonstrating vector search with Couchbase
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## Introduction
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This demo showcases the **Semantic Kernel Couchbase connector** - a .NET library that bridges Microsoft's Semantic Kernel framework with Couchbase's vector search capabilities. The connector provides a seamless integration that allows developers to build AI-powered applications using familiar Semantic Kernel abstractions while leveraging Couchbase's vector indexing for high-performance semantic search.
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This makes the connector ideal for RAG (Retrieval-Augmented Generation) applications, semantic search engines, hybrid search, and recommendation systems.
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### Repository Links
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- **Connector Repository**: [couchbase-semantic-kernel](https://github.com/Couchbase-Ecosystem/couchbase-semantic-kernel) - The official Couchbase .NET Vector Store Connector for Microsoft Semantic Kernel
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- **This Example**: [CouchbaseVectorSearchDemo](https://github.com/couchbase-examples/couchbase-semantic-kernel-quickstart/tree/main/CouchbaseVectorSearchDemo) - Complete working example demonstrating vector search with Couchbase
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## Prerequisites
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### Couchbase Server Setup

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