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Semantic Kernelis an SDK that integrates Large Language Models (LLMs) likeOpenAI,Azure OpenAI,andHugging Facewith conventional programming languages like C#, Python, and Java. Semantic Kernel achieves thisby allowing you to definepluginsthat can be chained togetherin just afew lines of code.

What makes Semantic Kernelspecial, however, is its ability toautomatically orchestrateplugins with AI. With Semantic Kernelplanners, youcan ask an LLM to generate a plan that achieves a user's unique goal. Afterwards,Semantic Kernel will execute the plan for the user.

The Semantic Kernel SDK is available in C#, Python, and Java. To get started, choose your preferred language below. See theFeature Matrix to see a breakdown offeature parity between our currently supported languages.

Using Semantic Kernel in C#

Using Semantic Kernel in Python

Using Semantic Kernel in Java

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

1. Create a new console app.
2. Add the semantic kernel nugetMicrosoft.SemanticKernel.
3. Copy the code fromhere into the appProgram.cs file.
4. Replace the configuration placeholders for API key and other params with your key and settings.
5. Run withF5 ordotnet run

1. Install the pip package:python -m pip install semantic-kernel.
2. Create a new script e.g.hello-world.py.
3. Store your API key and settings in an.env file as describedhere.
4. Copy the code fromhere into thehello-world.py script.
5. Run the python script.

The Java code is in thesemantic-kernel-java repository. Seesemantic-kernel-java build for instructions onhow to build and run the Java code.

Please file Java Semantic Kernel specific issues inthesemantic-kernel-java repository.

The fastest way to learn how to use Semantic Kernel is with our C# and Python Jupyter notebooks. These notebooksdemonstrate 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 walkthroughson our Learn site. Each sample comes with a completed C# and Python project that you can run locally.

1. 📖Overview of the kernel
2. 🔌Understanding AI plugins
3. 👄Creating semantic functions
4. 💽Creating native functions
5. ⛓️Chaining functions together
6. 🤖Auto create plans with planner
7. 💡Create and run a ChatGPT plugin

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

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

We welcome your contributions and suggestions to SK community! One of the easiestways 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 withus before sending a PR. This is to avoid rejection as we might be taking the corein a different direction, but also to consider the impact on the larger ecosystem.

To learn more and get started:

• Read thedocumentation
• Learn how tocontribute to the project
• Join theDiscord community
• Attendregular office hours and SK community events
• Follow the team on ourblog

This project has adopted theMicrosoft Open Source Code of Conduct.For more information see theCode of Conduct FAQor contactopencode@microsoft.comwith any additional questions or comments.

Copyright (c) Microsoft Corporation. All rights reserved.

Licensed under theMIT license.