semantic kernel

Semantic Kernel

Status

• Python
  
• .NET
  
  Using Semantic Kernel in Python
  Using Semantic Kernel in Java

  The quickest way to get started with the basics is to get an API key from either OpenAI or Azure OpenAI and to run one of the C#, Python, and Java console applications/scripts below.

  For C#:

  1. Go to the Quick start page here and follow the steps to dive in.
  2. After Installing the SDK, we advise you follow the steps and code detailed to write your first console app.

  For Python:

  1. Go to the Quick start page here and follow the steps to dive in.
  2. You'll need to ensure that you toggle to Python in the Choose a programming language table at the top of the page.

  For Java:

  The Java code is in the semantic-kernel-java repository. See semantic-kernel-java build for instructions on how to build and run the Java code.

  Please file Java Semantic Kernel specific issues in the semantic-kernel-java repository.

  Learning how to use Semantic Kernel

  The fastest way to learn how to use Semantic Kernel is with our C# and Python Jupyter notebooks. These notebooks demonstrate how to use Semantic Kernel with code snippets that you can run with a push of a button.

  • Getting Started with C# notebook
  • Getting Started with Python notebook

  Once you've finished the getting started notebooks, you can then check out the main walkthroughs on our Learn site. Each sample comes with a completed C# and Python project that you can run locally.

  1. Getting Started
  2. ? Detailed Samples
  3. Concepts

  Finally, refer to our API references for more details on the C# and Python APIs:

  • C# API reference
  • Python API reference
  • Java API reference (coming soon)

  Visual Studio Code extension: design semantic functions with ease

  The Semantic Kernel extension for Visual Studio Code makes it easy to design and test semantic functions. The extension provides an interface for designing semantic functions and allows you to test them with the push of a button with your existing models and data.

  Join the community

  We welcome your contributions and suggestions to SK community! One of the easiest ways to participate is to engage in discussions in the GitHub repository. Bug reports and fixes are welcome!

  For new features, components, or extensions, please open an issue and discuss with us before sending a PR. This is to avoid rejection as we might be taking the core in a different direction, but also to consider the impact on the larger ecosystem.

  To learn more and get started:

  • Read the documentation

  • Learn how to contribute to the project

  • Ask questions in the GitHub discussions

  • Ask questions in the Discord community

  • Attend regular office hours and SK community events

  • Follow the team on our blog

  Contributor Wall of Fame

  Code of Conduct

  This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact [email protected] with any additional questions or comments.

  License

  Copyright (c) Microsoft Corporation. All rights reserved.

  Licensed under the MIT license.