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### Motivation and Context Adds two new Python demos demonstrating integration with Microsoft Copilot Studio (MCS). ### Description - `copilot_studio_agent` features a new subclass of `Agent` connecting to a Microsoft Copilot Studio agent via DirectLine API - `copilot_studio_skill` showcases how to extend MCS to connect directly to a Semantic Kernel Agent, by defining a _skill_ ### 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]>
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Semantic Kernel Demo Applications
Demonstration applications that leverage the usage of one or many SK features
| Type | Description |
|---|---|
| assistants_group_chat | A sample Agent demo that shows a chat functionality with an OpenAI Assistant agent. |
| booking_restaurant | A sample chat bot that leverages the Microsoft Graph and Bookings API as a Semantic Kernel plugin to make a fake booking at a restaurant. |
| copilot_studio_agent | A sample that shows how to invoke Microsoft Copilot Studio agents as first-party Agent in Semantic Kernel |
| copilot_studio_skill | A sample demonstrating how to extend Microsoft Copilot Studio to invoke Semantic Kernel agents |
| guided_conversations | A sample showing a framework for a pattern of use cases referred to as guided conversations. |
| processes_with_dapr | A sample showing the Semantic Kernel process framework used with the Python Dapr runtime. |
| telemetry_with_application_insights | A sample project that shows how a Python application can be configured to send Semantic Kernel telemetry to Application Insights. |