# Semantic Kernel

[![Python package](https://img.shields.io/pypi/v/semantic-kernel)](https://pypi.org/project/semantic-kernel/)
[![Nuget package](https://img.shields.io/nuget/vpre/Microsoft.SemanticKernel)](https://www.nuget.org/packages/Microsoft.SemanticKernel/)
[![dotnet Docker](https://github.com/microsoft/semantic-kernel/actions/workflows/dotnet-ci-docker.yml/badge.svg?branch=main)](https://github.com/microsoft/semantic-kernel/actions/workflows/dotnet-ci-docker.yml)
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[![License: MIT](https://img.shields.io/github/license/microsoft/semantic-kernel)](https://github.com/microsoft/semantic-kernel/blob/main/LICENSE)
[![Discord](https://img.shields.io/discord/1063152441819942922?label=Discord&logo=discord&logoColor=white&color=d82679)](https://aka.ms/SKDiscord)

[Semantic Kernel](https://learn.microsoft.com/en-us/semantic-kernel/overview/)
is an SDK that integrates Large Language Models (LLMs) like
[OpenAI](https://platform.openai.com/docs/introduction),
[Azure OpenAI](https://azure.microsoft.com/en-us/products/ai-services/openai-service),
and [Hugging Face](https://huggingface.co/)
with conventional programming languages like C#, Python, and Java. Semantic Kernel achieves this
by allowing you to define [plugins](https://learn.microsoft.com/en-us/semantic-kernel/ai-orchestration/plugins)
that can be chained together
in just a [few lines of code](https://learn.microsoft.com/en-us/semantic-kernel/ai-orchestration/chaining-functions?tabs=Csharp#using-the-runasync-method-to-simplify-your-code).

What makes Semantic Kernel _special_, however, is its ability to _automatically_ orchestrate
plugins with AI. With Semantic Kernel
[planners](https://learn.microsoft.com/en-us/semantic-kernel/ai-orchestration/planner), you
can ask an LLM to generate a plan that achieves a user's unique goal. Afterwards,
Semantic Kernel will execute the plan for the user.

#### Please star the repo to show your support for this project!

![Orchestrating plugins with planner](https://learn.microsoft.com/en-us/semantic-kernel/media/kernel-infographic.png)



## Getting started with Semantic Kernel

The Semantic Kernel SDK is available in C#, Python, and Java. To get started, choose your preferred language below. See the [Feature Matrix](https://learn.microsoft.com/en-us/semantic-kernel/get-started/supported-languages) to see a breakdown of
feature parity between our currently supported languages.

<table width=100%>
  <tbody>
    <tr>
      <td>
        <img align="left" width=52px src="https://user-images.githubusercontent.com/371009/230673036-fad1e8e6-5d48-49b1-a9c1-6f9834e0d165.png">
        <div>
          <a href="dotnet/README.md">Using Semantic Kernel in C#</a> &nbsp<br/>
        </div>
      </td>
      <td>
        <img align="left" width=52px src="https://raw.githubusercontent.com/devicons/devicon/master/icons/python/python-original.svg">
        <div>
          <a href="python/README.md">Using Semantic Kernel in Python</a>
        </div>
      </td>
      <td>
        <img align="left" width=52px height=52px src="https://upload.wikimedia.org/wikipedia/en/3/30/Java_programming_language_logo.svg" alt="Java logo">
        <div>
          <a href="https://github.com/microsoft/semantic-kernel/blob/main/java/README.md">Using Semantic Kernel in Java</a>
        </div>
      </td>
    </tr>
  </tbody>
</table>

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. Create a new console app.
2. Add the semantic kernel nuget [Microsoft.SemanticKernel](https://www.nuget.org/packages/Microsoft.SemanticKernel/).
3. Copy the code from [here](dotnet/README.md) into the app `Program.cs` file.
4. Replace the configuration placeholders for API key and other params with your key and settings.
5. Run with `F5` or `dotnet run`

### For Python:

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 described [here](python/README.md).
4. Copy the code from [here](python/README.md) into the `hello-world.py` script.
5. Run the python script.

### For Java:

1. Clone the repository: `git clone https://github.com/microsoft/semantic-kernel.git`
    1. To access the latest Java code, clone and checkout the Java development branch: `git clone -b java-development https://github.com/microsoft/semantic-kernel.git`
2. Follow the instructions [here](https://github.com/microsoft/semantic-kernel/blob/main/java/samples/sample-code/README.md)

## 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](dotnet/notebooks/00-getting-started.ipynb)
- [Getting Started with Python notebook](python/notebooks/00-getting-started.ipynb)

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. 📖 [Overview of the kernel](https://learn.microsoft.com/en-us/semantic-kernel/ai-orchestration/)
1. 🔌 [Understanding AI plugins](https://learn.microsoft.com/en-us/semantic-kernel/ai-orchestration/plugins)
1. 👄 [Creating semantic functions](https://learn.microsoft.com/en-us/semantic-kernel/ai-orchestration/semantic-functions)
1. 💽 [Creating native functions](https://learn.microsoft.com/en-us/semantic-kernel/ai-orchestration/native-functions)
1. ⛓️ [Chaining functions together](https://learn.microsoft.com/en-us/semantic-kernel/ai-orchestration/chaining-functions)
1. 🤖 [Auto create plans with planner](https://learn.microsoft.com/en-us/semantic-kernel/ai-orchestration/planner)
1. 💡 [Create and run a ChatGPT plugin](https://learn.microsoft.com/en-us/semantic-kernel/ai-orchestration/chatgpt-plugins)

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

- [C# API reference](https://learn.microsoft.com/en-us/dotnet/api/microsoft.semantickernel?view=semantic-kernel-dotnet)
- Python API reference (coming soon)

## Chat Copilot: see what's possible with Semantic Kernel

If you're interested in seeing a full end-to-end example of how to use Semantic Kernel, check out
our [Chat Copilot](https://github.com/microsoft/chat-copilot) reference application. Chat Copilot
is a chatbot that demonstrates the power of Semantic Kernel. By combining plugins, planners, and personas,
we demonstrate how you can build a chatbot that can maintain long-running conversations with users while
also leveraging plugins to integrate with other services.

![Chat Copilot answering a question](https://learn.microsoft.com/en-us/semantic-kernel/media/chat-copilot-in-action.gif)

You can run the app yourself by downloading it from its [GitHub repo](https://github.com/microsoft/chat-copilot).

## Visual Studio Code extension: design semantic functions with ease

The [Semantic Kernel extension for Visual Studio Code](https://learn.microsoft.com/en-us/semantic-kernel/vs-code-tools/)
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 a push of a button with your
existing models and data.

![Semantic Kernel extension for Visual Studio Code](https://learn.microsoft.com/en-us/semantic-kernel/media/vs-code-extension.png)

In the above screenshot, you can see the extension in action:

- Syntax highlighting for semantic functions
- Code completion for semantic functions
- LLM model picker
- Run button to test the semantic function with your input data

## Check out our other repos!

If you like Semantic Kernel, you may also be interested in other repos the Semantic Kernel team supports:

| Repo                                                                              | Description                                                                                   |
| --------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------- |
| [Chat Copilot](https://github.com/microsoft/chat-copilot)                         | A reference application that demonstrates how to build a chatbot with Semantic Kernel.        |
| [Semantic Kernel Docs](https://github.com/MicrosoftDocs/semantic-kernel-docs)     | The home for Semantic Kernel documentation that appears on the Microsoft learn site.          |
| [Semantic Kernel Starters](https://github.com/microsoft/semantic-kernel-starters) | Starter projects for Semantic Kernel to make it easier to get started.                        |
| [Kernel Memory](https://github.com/microsoft/kernel-memory)                       | A scalable Memory service to store information and ask questions using the RAG pattern.       |

## 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](https://aka.ms/sk/learn)
- Learn how to [contribute](https://learn.microsoft.com/en-us/semantic-kernel/get-started/contributing) to the project
- Join the [Discord community](https://aka.ms/SKDiscord)
- Attend [regular office hours and SK community events](COMMUNITY.md)
- Follow the team on our [blog](https://aka.ms/sk/blog)

## Contributor Wall of Fame

[![semantic-kernel contributors](https://contrib.rocks/image?repo=microsoft/semantic-kernel)](https://github.com/microsoft/semantic-kernel/graphs/contributors)

## Code of Conduct

This project has adopted the
[Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).
For more information see the
[Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/)
or contact [opencode@microsoft.com](mailto:opencode@microsoft.com)
with any additional questions or comments.

## License

Copyright (c) Microsoft Corporation. All rights reserved.

Licensed under the [MIT](LICENSE) license.
