Semantic Kernel Tutorial

[azaddhirajkumar]

No description provided.

[gemini-code-assist]

Summary of Changes

Hello @azaddhirajkumar, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request introduces a new, in-depth tutorial designed to help developers build semantic search applications. It focuses on integrating Microsoft's Semantic Kernel with Couchbase's robust vector search features via the Couchbase .NET Vector Store Connector. The tutorial covers the entire process, from setting up the development environment and defining data models to generating embeddings with OpenAI, ingesting data, and executing various vector search queries. It also provides extensive information on configuring different types of Couchbase vector indexes, offering a practical guide for leveraging AI-powered search capabilities.

Highlights

• New Tutorial Added: A comprehensive tutorial has been added, guiding users through building vector search applications using the Couchbase .NET Semantic Kernel Connector and OpenAI.
• Couchbase Integration with Semantic Kernel: The tutorial demonstrates seamless integration of Microsoft Semantic Kernel with Couchbase's vector search capabilities, covering BHIVE, Composite, and FTS index types.
• Embedding Generation and Storage: It explains how to generate text embeddings using OpenAI's text-embedding-ada-002 model and efficiently store them within Couchbase.
• Vector Search Operations: The tutorial details both pure and filtered vector search queries, illustrating their underlying translation to SQL++ with ANN_DISTANCE and WHERE clauses.
• Advanced Index Configuration: Detailed guidance is provided on configuring Couchbase vector indexes, including BHIVE, Composite, and FTS, along with explanations of parameters like centroids and quantization.

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[gemini-code-assist]

Code Review

This pull request adds a new tutorial for using the Semantic Kernel with Couchbase. The tutorial is comprehensive and well-structured. However, I've found several issues that need to be addressed before merging. There are critical errors in the provided JSON and SQL++ code snippets (missing commas, trailing commas) that will prevent them from working. Additionally, some links point to temporary or internal resources (a feature branch and a test documentation server), which should be updated to stable, public URLs. There are also some invalid tags in the frontmatter that will likely fail validation, and a section on embedding generation is potentially confusing. I've left specific comments with suggestions for each of these points.

[nithishr]

One minor thing. Feel free to fix it & merge.