# SD.Next
**Wikidata**: [Q133730920](https://www.wikidata.org/wiki/Q133730920)  
**Source**: https://4ort.xyz/entity/sd-next

## Summary
SD.Next is a local AI art web interface and free software designed for generative artificial intelligence. Built using the Python programming language, it is based on the AUTOMATIC1111 Stable Diffusion Web UI. The platform provides users with an open-source tool to run AI image generation locally on their own hardware.

## Key Facts
*   **Classification:** SD.Next is an instance of free software and a local AI art web interface.
*   **Codebase:** It is based on the AUTOMATIC1111 Stable Diffusion Web UI.
*   **Programming Language:** The software is written in Python.
*   **Source Repository:** The code is hosted on GitHub at `https://github.com/vladmandic/automatic`.
*   **Documentation:** The official documentation website is `https://vladmandic.github.io/sdnext-docs/`.
*   **Support:** Issues can be tracked at `https://github.com/vladmandic/sdnext/issues`.
*   **Community:** The project has a Discord invite ID of `VjvR2tabEX`.
*   **License:** The software operates under license ID Q27017232.

## FAQs
### Q: What is SD.Next?
A: SD.Next is a free software interface for generative AI that allows users to run AI art generation locally. It is based on the AUTOMATIC1111 Stable Diffusion Web UI and is built using Python.

### Q: Where can the source code for SD.Next be found?
A: The source code repository is located on GitHub at `https://github.com/vladmandic/automatic`.

### Q: Is SD.Next free to use?
A: Yes, SD.Next is classified as free software, meaning it is distributed under terms that allow users to freely run, study, change, and distribute it.

## Why It Matters
SD.Next represents a significant tool in the landscape of open-source generative artificial intelligence. By offering a local AI art web interface, it addresses the growing demand for privacy, control, and accessibility in AI image generation. Unlike cloud-based solutions, a local interface allows users to utilize their own hardware (GPUs) to generate images without relying on external servers or subscription services.

The project matters because it lowers the barrier to entry for using complex diffusion models while maintaining the flexibility of free software. Being based on AUTOMATIC1111, one of the most popular open-source UIs for Stable Diffusion, ensures a degree of familiarity and reliability for users migrating from or experimenting with different interfaces. Furthermore, its implementation in Python—the standard language for machine learning and data science—ensures wide compatibility and extensibility within the existing developer ecosystem. It empowers users to modify the software to suit specific workflows, fostering innovation within the generative art community.

## Notable For
*   **Local Processing:** Functions as a local AI art web interface, enabling generation without cloud dependency.
*   **Open Source Foundation:** Distributed as free software, allowing for user modification and distribution.
*   **Lineage:** Directly based on the widely used AUTOMATIC1111 Stable Diffusion Web UI.
*   **Language:** Built entirely on Python, integrating seamlessly with standard AI development environments.

## Body
### Technical Overview
SD.Next is a software application categorized as a "local AI art web interface." It is constructed using the Python programming language, a standard in the artificial intelligence field. As a piece of free software, it adheres to the philosophy that users should have the liberty to run, study, change, and distribute the software and its modified versions.

### Development and Repository
The project is a derivative work based on the AUTOMATIC1111 Stable Diffusion Web UI. The active source code is maintained in a GitHub repository located at `https://github.com/vladmandic/automatic`. The project tracks bugs and feature requests via a dedicated issue tracker found at `https://github.com/vladmandic/sdnext/issues`.

### Resources and Community
Users and developers can access detailed information regarding the software via the official documentation site at `https://vladmandic.github.io/sdnext-docs/`. For real-time support and community interaction, the project maintains a Discord presence with the invite ID `VjvR2tabEX`. The software is released under the license identifier Q27017232.

## References

1. [Source](https://api.github.com/repos/vladmandic/automatic)