Semantic Kernel

As explained in Building Distributed Applications that Work

Semantic Kernel is a collection of .NET libraries that provides interfaces for integrating large language models with application code.

How Building Distributed Applications that Work covers it

How deep it goes

Defines Semantic Kernel’s role and capabilities at a high level without detailing implementation steps.

Examples

Uses a locally hosted product-question assistant and streamed chat responses as application examples.

What you can do after

Build .NET AI features that interact with LLMs, including chat experiences that stream responses.

How it connects

Connects .NET application code with LLMs and is associated with Ollama, Aspire, and chat completion.

liveBookmanning.com

Read Building Distributed Applications that Work on liveBook Get the book at manning.com

Also explained in

• 

  liveBookmanning.com
  Generative AI in ActionSK is an AI application framework that provides abstractions for integrating language models with prompts, functions, and external services.
• 

  liveBookmanning.com
  AI Agents in ActionSemantic Kernel is an open-source Microsoft software development kit for building AI applications that orchestrate language-model capabilities, plugins, and related services.

Compare how 3 books explain Semantic Kernel →

Related concepts

• large language modeluses · A large language model is a machine-learning model, typically neural, trained on extensive text data to process and generate language.
• Ollamauses · Ollama is software for downloading, running, and serving language models locally.
• pluginuses · A plugin is an optional software component that extends or modifies a host application’s capabilities through an extension or integration mechanism.
• client librarykind of · A client library is reusable software that provides programmatic interfaces for an application to interact with a service, platform, or system.
• native functionconfigured by · A native function is a conventionally programmed function that can be invoked by an orchestration framework or language-model application.

This explainer was generated by Manning's knowledge graph from the text of Building Distributed Applications that Work. The section links point to the parts of the book it draws on.