laf VS self-workerd

LAF (https://github.com/labring/laf) now supports ChatGPT AI generation function, providing a seamless and efficient way for developers to deploy and scale AI applications on Alibaba Cloud Function Compute. With this new feature, developers can easily leverage the power of ChatGPT to generate high-quality text content and integrate it with their own applications.

Using LAF and ChatGPT, developers can quickly build and deploy AI applications, such as chatbots, recommendation systems, and content generators, without having to worry about infrastructure or scaling issues. With the automatic scaling capabilities of Function Compute, developers can focus on building the AI models and let LAF take care of the deployment and scaling aspects.

In addition, LAF provides a secure and reliable environment for AI application development, with features such as access control, logging, and exception handling. This ensures that your AI applications are always available and performing at their best.

Overall, the support of ChatGPT in LAF brings a new level of efficiency and scalability to AI application development, making it easier than ever before to build and deploy high-quality AI applications

So open source is a big trend, and Tencent Cloud developed open source alternatives https://github.com/labring/laf also because of this incident

Hi, this is more an experiment that a real production-tested project. You can create your own Function as a Service architecture, and self-host everywhere you want.

It leverages workerd, the Cloudflare worker runtime. And as deploy tutorial, it include a guide to host everything on Fly.

It support container-based deployment, so docker is your friend here.

The complete project is on: https://github.com/giuseppelt/self-workerd

Mind this a proof-of-concept, public exposed systems require more work.

It support container-based deployment, so you can host wherever you like. The complete project is on: github repository