https://github.com/chenrensong/SS.SemanticKernel.Extensions

This is a SemanticKernel extension built on the [Embedding](https://github.com/chenrensong/Embedding) codebase. This extension enables you to generate text embeddings with a semantic-based kernel function.
https://github.com/chenrensong/SS.SemanticKernel.Extensions

Last synced: about 1 month ago
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This is a SemanticKernel extension built on the [Embedding](https://github.com/chenrensong/Embedding) codebase. This extension enables you to generate text embeddings with a semantic-based kernel function.

• Host: GitHub
• URL: https://github.com/chenrensong/SS.SemanticKernel.Extensions
• Owner: chenrensong
• License: mit
• Created: 2023-06-11T14:32:48.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2023-11-24T09:47:03.000Z (about 1 year ago)
• Last Synced: 2024-10-07T02:15:50.718Z (2 months ago)
• Language: C#
• Size: 174 KB
• Stars: 8
• Watchers: 1
• Forks: 2
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

• awesome-semantickernel - SS.SemanticKernel.Extensions - based kernel function. [](https://www.nuget.org/packages/SS.SemanticKernel.Extensions/) (Plugins)

README

        
# SemanticKernel Extension

[![NuGet Version](https://img.shields.io/nuget/v/SS.SemanticKernel.Extensions.svg?style=flat)](https://www.nuget.org/packages?q=SS.SemanticKernel.Extensions) 

This is a SemanticKernel extension built on the [Embedding](https://github.com/chenrensong/Embedding) codebase. This extension enables you to generate text embeddings with a semantic-based kernel function.

## Installation

Ensure you have the Embedding codebase installed. You can then install this extension by cloning this repository:

```

Install-Package SS.SemanticKernel.Extensions

```

## Configuration

To configure this extension, use the following code:

```csharp

kernelBuilder = kernelBuilder

.WithCoreTextEmbeddingGenerationService("text2vec-base-chinese", "http://127.0.0.1:8000/embeddings");

```

This configuration allows the SemanticKernel extension to utilize the `text2vec-base-chinese` model and the embedding service located at `http://127.0.0.1:8000/embeddings`.

## Contributing

Contributions of any kind are welcome. If you have any suggestions or issues with this project, feel free to open an issue or pull request.

## License

This project is licensed under the MIT License.

## Contact

If you have any questions, feel free to contact us at: [email protected]