mirror of
https://github.com/microsoft/semantic-kernel.git
synced 2026-10-12 02:19:06 +00:00
### Motivation and Context <!-- Thank you for your contribution to the semantic-kernel repo! Please help reviewers and future users, providing the following information: 1. Why is this change required? 2. What problem does it solve? 3. What scenario does it contribute to? 4. If it fixes an open issue, please link to the issue here. --> There's an enum called `AuthorRole`. I replaced string literals with the enum values. PyCharm highlights this in some cases: Expected type 'AuthorRole', got 'str' instead I also fixed a bug in _function_invocation_filters_stream.py_ where the argument name was wrong. `author="assistant"` instead of `role="assistant"` ### Description <!-- Describe your changes, the overall approach, the underlying design. These notes will help understanding how your code works. Thanks! --> ### Contribution Checklist <!-- Before submitting this PR, please make sure: --> - [x] The code builds clean without any errors or warnings - [x] The PR follows the [SK Contribution Guidelines](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md) and the [pre-submission formatting script](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md#development-scripts) raises no violations - [x] All unit tests pass, and I have added new tests where possible - [x] I didn't break anyone 😄 --------- Co-authored-by: Evan Mattson <[email protected]> Co-authored-by: Eduard van Valkenburg <[email protected]>
Semantic Kernel Concepts by Feature
This section contains code snippets that demonstrate the usage of Semantic Kernel features.
| Features | Description |
|---|---|
| AutoFunctionCalling | Using Auto Function Calling to allow function call capable models to invoke Kernel Functions automatically |
| ChatCompletion | Using ChatCompletion messaging capable service with models |
| Filtering | Creating and using Filters |
| Functions | Invoking Method or Prompt functions with Kernel |
| Grounding | An example of how to perform LLM grounding |
| Logging | Showing how to set up logging |
| Memory | Using Memory AI concepts |
| On Your Data | Examples of using AzureOpenAI On Your Data |
| Planners | Showing the uses of Planners |
| Plugins | Different ways of creating and using Plugins |
| PromptTemplates | Using Templates with parametrization for Prompt rendering |
| RAG | Different ways of RAG (Retrieval-Augmented Generation) |
| Search | Using search services information |
| TextGeneration | Using TextGeneration capable service with models |