Semantic Kernel
ℹ️ NOTE: This project is just like AI and will evolve quickly.
We invite you to join us in developing the Semantic Kernel together!
Please contribute by
using GitHub Discussions,
opening GitHub Issues,
sending us PRs,
joining our Discord community.
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 supports and encapsulates several design patterns from the latest
in AI research, such that developers can infuse their applications with plugins like prompt
chaining, recursive reasoning, summarization, zero/few-shot learning, contextual
memory, long-term memory, embeddings, semantic indexing,
planning, retrieval-augmented generation and accessing external
knowledge stores as well as your own data.
By joining the SK community, you can build AI-first apps faster and have a front-row
peek at how the SDK is being built. SK has been released as open-source so that more
pioneering developers can join us in crafting the future of this landmark moment
in the history of computing.
Get Started with Semantic Kernel ⚡
Semantic Kernel is available to explore AI and build apps with C#, Python and Java:
See the Feature Matrix to see a breakdown of feature parity between our currently supported languages.
The quickest way to get started with the basics is to get an API key
(OpenAI or Azure OpenAI)
and to run one of the C#, Python, and Java console applications/scripts:
For C#:
- Create a new console app.
- Add the semantic kernel nuget
Microsoft.SemanticKernel. - Copy the code from here into the app
Program.csfile. - Replace the configuration placeholders for API key and other params with your key and settings.
- Run with
F5ordotnet run
For Python:
- Install the pip package:
python -m pip install semantic-kernel. - Create a new script e.g.
hello-world.py. - Store your API key and settings in an
.envfile as described here. - Copy the code from here into the
hello-world.pyscript. - Run the python script.
For Java:
- Clone the repository:
git clone https://github.com/microsoft/semantic-kernel.git - Switch to
semantic-kerneldirectory and then checkout experimental Java branch:git checkout experimental-java - Follow the instructions here
Sample apps ⚡
The repository includes some sample applications, with a React frontend and
a backend web service using Semantic Kernel.
Follow the links for more information and instructions about running these apps.
| Simple chat summary | Use ready-to-use plugins and get plugins into your app easily. |
| Book creator | Use planner to deconstruct a complex goal and envision using the planner in your app. |
| Authentication and APIs | Use a basic connector pattern to authenticate and connect to an API and imagine integrating external data into your app's LLM AI. |
| GitHub repository Q&A | Use embeddings and memory to store recent data and allow you to query against it. |
| Copilot Chat Sample App | Build your own chat experience based on Semantic Kernel. |
Requirements:
- You will need an
Open AI API Key or
Azure Open AI service key
to get started. - Azure Functions Core Tools
are required to run the kernel as a local web service, used by the sample web apps. - .NET 6 SDK or .NET 7 SDK
- Yarn is used for installing web apps' dependencies.
Deploy Semantic Kernel to Azure in a web app service ☁️
Getting Semantic Kernel deployed to Azure as web app service is easy with one-click deployments. Click here to learn more on how to deploy to Azure.
Jupyter Notebooks ⚡
For a more hands-on overview, you can also check out the C# and Python Jupyter notebooks, starting
from here:
Requirements: C# notebooks require .NET 7
and the VS Code Polyglot extension.
Contributing and 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
- Join the Discord community
- Attend regular office hours and SK community events
- Follow the team on our blog
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 opencode@microsoft.com
with any additional questions or comments.
License
Copyright (c) Microsoft Corporation. All rights reserved.
Licensed under the MIT license.