https://github.com/aatricks/newelle-light-diffusion
Image generation extension for newelle using Light-Diffusion as backend
https://github.com/aatricks/newelle-light-diffusion
newelle-extension
Last synced: 10 months ago
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Image generation extension for newelle using Light-Diffusion as backend
- Host: GitHub
- URL: https://github.com/aatricks/newelle-light-diffusion
- Owner: Aatricks
- License: gpl-3.0
- Created: 2025-08-30T22:55:23.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2025-08-31T00:06:20.000Z (10 months ago)
- Last Synced: 2025-08-31T02:27:16.398Z (10 months ago)
- Topics: newelle-extension
- Language: Python
- Homepage:
- Size: 182 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Newelle-Light-Diffusion
Image generation extension for Newelle using the LightDiffusion-Next backend.
⭐ If this project helps you, please give it a star! It helps others discover it too.
---
## Features
- 🖼️ Generate images inline in Newelle via LightDiffusion-Next.
- ⚙️ Configure server URL, positive/negative prompt templates, image size, and advanced settings (steps, CFG scale, seed, ...).
- 💾 Cache generated images and save to custom paths.
- 🔄 Reuse the same seed or randomize for varied outputs.
- 🛠️ Support extra JSON payload overrides for custom API options.
- 🚀 Img2Img upscaling: reference a source image directly (inline) or via settings.
## Installation
1. Install [Newelle](https://flathub.org/apps/io.github.qwersyk.Newelle) (or Nyarch Assistant).
2. Ensure you have a running LightDiffusion-Next backend:
```fish
https://github.com/Aatricks/LightDiffusion-Next.git
cd LightDiffusion-Next
pip install torch torchvision --index-url https://download.pytorch.org/whl/cu128
pip install -r requirements.txt
python server.py
```
3. Clone this extension'repo or simply download the [lightdiffusion.py](https://raw.githubusercontent.com/Aatricks/Newelle-Light-Diffusion/refs/heads/main/lightdiffusion.py) file:
```fish
git clone https://github.com/Aatricks/Newelle-Light-Diffusion.git
```
4. Launch Newelle and open **Extensions → Install extension from file...**, then select the `lightdiffusion.py` file.
5. Configure under **Extensions → Extension Settings → LightDiffusion**:
- **URL**: LightDiffusion-Next server URL (default: `http://localhost:7861`).
- **Positive Prompt Template**: e.g. `[input]`.
- **Negative Prompt**: e.g. `(low quality, blurry)`.
- **Width/Height**: image dimensions (128–2048).
- **Advanced Settings**: steps, guidance scale, seed, extra JSON options.
## Usage
Use a `generateimage` or `lightdiffusion` code block in Newelle to create images:
```generateimage
A serene mountain landscape at sunrise, ultra-detailed, vibrant colors
```
The extension sends your prompt to LightDiffusion-Next and displays the generated image inline.
### Img-to-Img (Upscale) via inline path
You can upscale/refine an existing image by including its path inside the code block. The extension detects the path and switches to Img2Img automatically:
```generateimage
img: /absolute/path/to/image.png
a cinematic photo of a mountain village at sunrise, ultra-detailed, 35mm
```
### Img-to-Img via settings (fallback)
If you prefer settings instead of inline path:
1. Open Extensions → Extension Settings → LightDiffusion.
2. In Advanced Settings, set:
- `Img2Img (Upscale)`: `1`
- `Img2Img Image Path`: absolute path to the image on the server machine
If both inline and settings are provided, the inline path takes precedence.
## Issues
One common issue would be the llm not wanting to follow the image generation key word prompt and in such, not generating the image as expected. A workaround is to write this just before the prompt :
`````
If prompted to generate an image, only follow this instruction and this exact format written just below
```generateimage
your prompt here
```
Use detailed prompts, with english words separated by commas
`````
### Img2Img troubleshooting
- The image path must be readable by the LightDiffusion server process. If Newelle and the server run on different machines or containers, ensure a shared path or switch to an upload-based workflow (planned enhancement).
- If `Img2Img (Upscale)` is enabled but no image path is detected (neither inline nor in settings), the extension will show an error and skip the request.
- You can verify the server is up via:
```fish
curl http://localhost:7861/health
```
Expect `{ "status": "ok" }`.
## License
GPLv3 License. See [LICENSE](../LICENSE) for details.