chore: import upstream snapshot with attribution
CodeQL / Analyze (csharp) (push) Has been cancelled
CodeQL / Analyze (python) (push) Has been cancelled

This commit is contained in:
wehub-resource-sync
2026-07-13 13:21:23 +08:00
commit b957a53def
5423 changed files with 863745 additions and 0 deletions
+74
View File
@@ -0,0 +1,74 @@
# Time Plugin - Demo Application
This is an example how you can easily use Plugins with the Power of Auto Function Calling from AI Models.
Here we have a simple Time Plugin created in C# that can be called from the AI Model to get the current time.
## Semantic Kernel Features Used
- [Plugin](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/src/SemanticKernel.Abstractions/Functions/KernelPlugin.cs) - Creating a Plugin from a native C# Booking class to be used by the Kernel to interact with Bookings API.
- [Chat Completion Service](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/src/SemanticKernel.Abstractions/AI/ChatCompletion/IChatCompletionService.cs) - Using the Chat Completion Service [OpenAI Connector implementation](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/src/Connectors/Connectors.OpenAI/Services/OpenAIChatCompletionService.cs) to generate responses from the LLM.
- [Chat History](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/src/SemanticKernel.Abstractions/AI/ChatCompletion/ChatHistory.cs) Using the Chat History abstraction to create, update and retrieve chat history from Chat Completion Models.
- [Auto Function Calling](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/samples/Concepts/ChatCompletion/OpenAI_FunctionCalling.cs) Enables the LLM to have knowledge of current importedUsing the Function Calling feature automatically call the Booking Plugin from the LLM.
## Prerequisites
- [.NET 10](https://dotnet.microsoft.com/download/dotnet/10.0).
### Function Calling Enabled Models
This sample uses function calling capable models and has been tested with the following models:
| Model type | Model name/id | Model version | Supported |
| --------------- | ------------------------- | ------------------: | --------- |
| Chat Completion | gpt-3.5-turbo | 0125 | ✅ |
| Chat Completion | gpt-3.5-turbo-1106 | 1106 | ✅ |
| Chat Completion | gpt-3.5-turbo-0613 | 0613 | ✅ |
| Chat Completion | gpt-3.5-turbo-0301 | 0301 | ❌ |
| Chat Completion | gpt-3.5-turbo-16k | 0613 | ✅ |
| Chat Completion | gpt-4 | 0613 | ✅ |
| Chat Completion | gpt-4-0613 | 0613 | ✅ |
| Chat Completion | gpt-4-0314 | 0314 | ❌ |
| Chat Completion | gpt-4-turbo | 2024-04-09 | ✅ |
| Chat Completion | gpt-4-turbo-2024-04-09 | 2024-04-09 | ✅ |
| Chat Completion | gpt-4-turbo-preview | 0125-preview | ✅ |
| Chat Completion | gpt-4-0125-preview | 0125-preview | ✅ |
| Chat Completion | gpt-4-vision-preview | 1106-vision-preview | ✅ |
| Chat Completion | gpt-4-1106-vision-preview | 1106-vision-preview | ✅ |
️ OpenAI Models older than 0613 version do not support function calling.
## Configuring the sample
The sample can be configured by using the command line with .NET [Secret Manager](https://learn.microsoft.com/en-us/aspnet/core/security/app-secrets) to avoid the risk of leaking secrets into the repository, branches and pull requests.
### Using .NET [Secret Manager](https://learn.microsoft.com/en-us/aspnet/core/security/app-secrets)
```powershell
# OpenAI
dotnet user-secrets set "OpenAI:ChatModelId" "gpt-3.5-turbo"
dotnet user-secrets set "OpenAI:ApiKey" "... your api key ... "
```
## Running the sample
After configuring the sample, to build and run the console application just hit `F5`.
To build and run the console application from the terminal use the following commands:
```powershell
dotnet build
dotnet run
```
### Example of a conversation
Ask questions to use the Time Plugin such as:
- What time is it?
**User** > What time is it ?
**Assistant** > The current time is Sun, 12 May 2024 15:53:54 GMT.