Microsoft.SemanticKernel.Abstractions 0.12.207.1-preview

About Semantic Kernel

Semantic Kernel (SK) is a lightweight SDK enabling integration of AI Large Language Models (LLMs) with conventional programming languages. The SK extensible programming model combines natural language semantic functions, traditional code native functions, and embeddings-based memory unlocking new potential and adding value to applications with AI.

SK supports prompt templating, function chaining, vectorized memory, and intelligent planning capabilities out of the box.

Semantic Kernel is designed to support and encapsulate several design patterns from the latest in AI research, such that developers can infuse their applications with complex skills like prompt chaining, recursive reasoning, summarization, zero/few-shot learning, contextual memory, long-term memory, embeddings, semantic indexing, planning, and accessing external knowledge stores as well as your own data.

A skill refers to a domain of expertise made available to the kernel as a single function, or as a group of functions related to the skill. The design of SK skills has prioritized maximum flexibility for the developer to be both lightweight and extensible.

Getting Started ⚡

• Check out the GitHub repository for the latest updates
• Learn more at the documentation site