+
+# Say hi to LightDiffusion-Next 👋
+
+[](https://huggingface.co/spaces/Aatricks/LightDiffusion-Next)
+
+**LightDiffusion-Next** is the fastest AI-powered image generation WebUI, combining speed, precision, and flexibility in one cohesive tool.
+
+
+
+ 
+
+
+
+
+
+---
+
+As a refactored and improved version of the original [LightDiffusion repository](https://github.com/Aatrick/LightDiffusion), this project enhances usability, maintainability, and functionality while introducing a host of new features to streamline your creative workflows.
+
+
+## Motivation:
+
+**LightDiffusion** was originally meant to be made in Rust, but due to the lack of support for the Rust language in the AI community, it was made in Python with the goal of being the simplest and fastest AI image generation tool.
+
+That's when the first version of LightDiffusion was born which only counted [3000 lines of code](https://github.com/LightDiffusion/LightDiffusion-original), only using Pytorch. With time, the [project](https://github.com/Aatrick/LightDiffusion) grew and became more complex, and the need for a refactor was evident. This is where **LightDiffusion-Next** comes in, with a more modular and maintainable codebase, and a plethora of new features and optimizations.
+
+📚 Learn more in the [official documentation](https://aatricks.github.io/LightDiffusion-Next/)
+
+For a source-based breakdown of the optimization stack, see the [Implemented Optimizations Report](https://aatricks.github.io/LightDiffusion-Next/implemented-optimizations-report/).
+
+---
+
+## 🌟 Highlights
+
+
+
+**LightDiffusion-Next** offers a powerful suite of tools to cater to creators at every level. At its core, it supports **Text-to-Image** (Txt2Img) and **Image-to-Image** (Img2Img) generation, offering a variety of upscale methods and samplers, to make it easier to create stunning images with minimal effort.
+
+Advanced users can take advantage of features like **attention syntax**, **Hires-Fix** or **ADetailer**. These tools provide better quality and flexibility for generating complex and high-resolution outputs.
+
+**LightDiffusion-Next** is fine-tuned for **performance**. Features such as **Xformers** acceleration, **BFloat16** precision support, **WaveSpeed** dynamic caching, **Multi-scale diffusion**, and **Stable-Fast** model compilation (which offers up to a 70% speed boost) ensure smooth and efficient operation, even on demanding workloads.
+
+---
+
+## ✨ Feature Showcase
+
+Here’s what makes LightDiffusion-Next stand out:
+
+- **Speed and Efficiency**:
+ Enjoy industry-leading performance with built-in Xformers, Pytorch, Wavespeed and Stable-Fast optimizations, Multi-scale diffusion, deepcache, AYS (Align Your Steps) scheduler, and automatic prompt caching achieving 30% up to 200% faster speeds compared to the rest of the AI image generation backends in SD1.5 and Flux.
+
+- **Automatic Detailing**:
+ Effortlessly enhance faces and body details with AI-driven tools based on the [Impact Pack](https://github.com/ltdrdata/ComfyUI-Impact-Pack).
+
+- **State Preservation**:
+ Save and resume your progress with saved states, ensuring seamless transitions between sessions.
+
+- **Integration-Ready**:
+ Collaborate and create directly in Discord with [Boubou](https://github.com/Aatrick/Boubou), or preview images dynamically with the optional **TAESD preview mode**.
+
+- **Image Previewing**:
+ Get a real-time preview of your generated images with TAESD, allowing for user-friendly and interactive workflows.
+
+- **Image Upscaling**:
+ Enhance your images with advanced upscaling options like UltimateSDUpscaling, ensuring high-quality results every time.
+
+- **Prompt Refinement**:
+ Use the optional Ollama-powered prompt enhancer (defaults to `qwen3:0.6b`) to refine your prompts and generate more accurate and detailed outputs.
+
+- **LoRa and Textual Inversion Embeddings**:
+ Leverage LoRa and textual inversion embeddings for highly customized and nuanced results, adding a new dimension to your creative process.
+
+- **Low-End Device Support**:
+ Run LightDiffusion-Next on low-end devices with as little as 2GB of VRAM or even no GPU, ensuring accessibility for all users.
+
+- **CFG++**:
+ Uses samplers modified to use CFG++ for better quality results compared to traditional methods.
+
+- **Newelle Extension**:
+ LightDiffusion-Next is also available as a backend to the [Newelle LightDiffusion extension](https://github.com/Aatricks/Newelle-Light-Diffusion) permitting to generate images inline during conversations with llms.
+
+---
+
+## ⚡ Performance Benchmarks
+
+**LightDiffusion-Next** dominates in performance:
+
+| **Tool** | **Speed (it/s)** |
+|------------------------------------|------------------|
+| **LightDiffusion with Stable-Fast** | 2.8 |
+| **LightDiffusion** | 1.9 |
+| **ComfyUI** | 1.4 |
+| **SDForge** | 1.3 |
+| **SDWebUI** | 0.9 |
+
+(All benchmarks are based on a 1024x1024 resolution with a batch size of 1 using BFloat16 precision without tweaking installations. Made with a 3060 mobile GPU using SD1.5.)
+
+With its unmatched speed and efficiency, LightDiffusion-Next sets the benchmark for AI image generation tools.
+
+---
+
+## 🛠 Installation
+
+> [!NOTE]
+> **Platform Support:** LightDiffusion-Next supports NVIDIA GPUs (CUDA), AMD GPUs (ROCm), and Apple Silicon (Metal/MPS). For AMD and Apple Silicon setup instructions, see the [ROCm and Metal/MPS Support Guide](https://aatrick.github.io/LightDiffusion/rocm-metal-support/).
+
+> [!WARNING]
+> **Disclaimer:** On Linux, the fastest way to get started is with the Docker setup below. Windows users often encounter an `EOF` build error when using Docker; if that happens, set up a local virtual environment instead and install SageAttention inside it.
+
+> [!NOTE]
+> You will need to download the [flux vae](https://huggingface.co/black-forest-labs/FLUX.1-schnell/blob/main/ae.safetensors) separately given its gated repo on Huggingface. Drop it in the `/include/vae` folder.
+
+### Quick Start
+
+1. Download a release or clone this repository.
+2. Run `run.bat` in a terminal.
+3. The modern React frontend will launch automatically at `http://localhost:5173` (proxied to the FastAPI backend at `http://localhost:7861`).
+
+**Recommended Launch Command:**
+```bash
+# Start both backend and frontend development server
+python server.py --frontend
+```
+
+**Production-style local run:**
+```bash
+# Serve the built React UI from FastAPI on a single port
+python server.py --port 7860
+```
+
+**ZeroGPU / Gradio launch:**
+```bash
+# Launch the Hugging Face ZeroGPU-compatible Gradio UI
+python app.py
+```
+
+### 🌌 Flux Support
+
+LightDiffusion-Next now features first-class support for **Flux2 Klein**. To get started, you need to download the required model components (Diffusion Model, Text Encoder, and VAE).
+
+We provide a convenient script to handle this automatically:
+```bash
+python download_flux.py
+```
+This will download approximately 16GB of weights into the `include/` directory.
+
+### 🤗 ZeroGPU / Gradio Space
+
+This repository now includes a Gradio `app.py` entrypoint for Hugging Face
+**ZeroGPU**. ZeroGPU is only supported for Gradio SDK Spaces, and the
+GPU-bound generation function is wrapped with `@spaces.GPU`.
+
+Recommended defaults for ZeroGPU:
+- keep `Keep Models Loaded` disabled
+- use 512x512 or 768x768 resolutions
+- generate 1 image at a time
+- prefer 10-25 steps with `ays`
+
+### 🐳 Docker Setup
+
+Run LightDiffusion-Next in a containerized environment with GPU acceleration.
+The Docker path remains available for local or dedicated GPU deployments and
+serves the built React frontend from the FastAPI backend on port `7860`.
+
+> [!IMPORTANT]
+> Confirm you have Docker Desktop configured with the NVIDIA Container Toolkit and at least 12-16GB of memory. Builds expect an NVIDIA GPU with compute capability 8.0 or higher and CUDA 12.0+ support for SageAttention/SpargeAttn.
+
+**Quick Start with Docker:**
+```bash
+# Build and run with docker-compose
+docker-compose up --build
+
+# Or build and run manually
+docker build -t lightdiffusion-next .
+docker run --gpus all -p 7860:7860 -e PORT=7860 -v ./output:/app/output lightdiffusion-next
+```
+
+**Custom GPU Architecture (Optional):**
+```bash
+# For faster builds, specify your GPU architecture (e.g., RTX 5060 = 12.0)
+docker-compose build --build-arg TORCH_CUDA_ARCH_LIST="12.0"
+
+# Default builds for: 8.0 (A100), 8.6 (RTX 30xx), 8.9 (RTX 40xx), 9.0 (H100), 12.0 (RTX 50xx)
+```
+
+**Built-in Optimizations:**
+The Docker image can optionally build the following acceleration paths:
+- ✨ **SageAttention** - 15% speedup with INT8 quantization (all supported GPUs)
+- 🚀 **SpargeAttn** - 40-60% speedup with sparse attention (compute 8.0-9.0 only)
+- ⚡ **Stable-Fast** - Optional UNet compilation for up to 70% faster SD1.5 inference
+
+Control them through build arguments (defaults shown below):
+
+```bash
+docker-compose build \
+ --build-arg TORCH_CUDA_ARCH_LIST="8.0;8.6;8.9;9.0;12.0" \
+ --build-arg INSTALL_SAGEATTENTION=0 \
+ --build-arg INSTALL_SPARGEATTN=0 \
+ --build-arg INSTALL_STABLE_FAST=1 \
+ --build-arg INSTALL_OLLAMA=0
+```
+
+Set `INSTALL_STABLE_FAST=1` to enable stable-fast, `INSTALL_SAGEATTENTION=1`
+or `INSTALL_SPARGEATTN=1` to opt into the heavier attention-kernel builds, and
+`INSTALL_OLLAMA=1` to bake in the prompt enhancer runtime.
+
+> [!NOTE]
+> RTX 50 series (compute 12.0) GPUs currently use SageAttention when the SageAttention kernel is installed. SpargeAttn remains limited to earlier supported architectures.
+
+**Access the Web Interface:**
+- **FastAPI + React UI**: `http://localhost:7860`
+
+**Volume Mounts:**
+- `./output:/app/output` - Persist generated images
+- `./checkpoints:/app/include/checkpoints` - Store model files
+- `./loras:/app/include/loras` - Store LoRA files
+- `./embeddings:/app/include/embeddings` - Store embeddings
+
+### Advanced Setup
+
+- **Install from Source**:
+ Install dependencies via:
+ ```bash
+ pip install -r requirements.txt
+ ```
+ Add your SD1/1.5 safetensors model to the `checkpoints` directory, then launch the application.
+
+- **⚡Stable-Fast Optimization**:
+ Follow [this guide](https://github.com/chengzeyi/stable-fast?tab=readme-ov-file#installation) to enable Stable-Fast mode for optimal performance.
+ In Docker environments, set `INSTALL_STABLE_FAST=1` to compile it during the image build or `INSTALL_STABLE_FAST=0` (default) to skip.
+
+- **🚀 SageAttention & SpargeAttn Acceleration**:
+ Boost inference speed by up to 60% with advanced attention backends:
+
+ **Prerequisites:**
+ - [CUDA toolkit](https://developer.nvidia.com/cuda-toolkit-archive) installed with version compatible with your PyTorch installation
+
+ **SageAttention (15% speedup, Windows compatible):**
+ ```bash
+ cd SageAttention
+ pip install -e . --no-build-isolation
+ ```
+
+ **SpargeAttn (40-60% total speedup, requires WSL2/Linux):**
+> [!CAUTION]
+> SpargeAttn cannot be built with the default Windows linker. Use WSL2 or a native Linux environment and set the correct `TORCH_CUDA_ARCH_LIST` before installation.
+ ```bash
+ # On WSL2 or Linux only (Windows linker has path length limitations)
+ cd SpargeAttn
+ export TORCH_CUDA_ARCH_LIST="9.0" # Or your GPU architecture (8.0, 8.6, 8.9, 9.0)
+ pip install -e . --no-build-isolation
+ ```
+
+ **Priority System:** SpargeAttn > SageAttention > PyTorch SDPA
+ - Both are automatically detected and used when available
+ - Graceful fallback for unsupported head dimensions
+
+- **🦙 Prompt Enhancer**:
+ Turn on the Ollama-backed enhancer to automatically restructure prompts. By default the app targets `qwen3:0.6b`:
+ ```bash
+ # Local install
+ pip install ollama
+ curl -fsSL https://ollama.com/install.sh | sh
+
+ # Start the Ollama daemon (keep this terminal open)
+ ollama serve
+
+ # New terminal: pull the default prompt enhancer model
+ ollama pull qwen3:0.6b
+ export PROMPT_ENHANCER_MODEL=qwen3:0.6b
+ ```
+ In Docker builds, set `--build-arg INSTALL_OLLAMA=1` (or update `docker-compose.yml`) to install Ollama and pre-pull the model automatically. You can override the runtime model/prefix with the `PROMPT_ENHANCER_MODEL` and `PROMPT_ENHANCER_PREFIX` environment variables. See the [Ollama guide](https://github.com/ollama/ollama?tab=readme-ov-file) for details.
+
+- **🤖 Discord Integration**:
+ Set up the Discord bot by following the [Boubou installation guide](https://github.com/Aatrick/Boubou).
+
+### Third-Party Licenses
+- This project distributes builds that depend on third-party open source components. For attribution details and the full license text, refer to `THIRD_PARTY_LICENSES.md`.
+
+---
+
+🎨 Enjoy exploring the powerful features of LightDiffusion-Next!
+
+> [!TIP]
+> ⭐ If this project helps you, please give it a star! It helps others discover it too.
diff --git a/THIRD_PARTY_LICENSES.md b/THIRD_PARTY_LICENSES.md
new file mode 100644
index 0000000000000000000000000000000000000000..2ea2b1db2f2d4d26e10218b5ea96e81e0ec90bb9
--- /dev/null
+++ b/THIRD_PARTY_LICENSES.md
@@ -0,0 +1,948 @@
+# Third-Party Notices
+
+This project depends on the following third-party components. The notices below satisfy the attribution requirements of their respective licenses.
+
+## SageAttention (thu-ml/SageAttention)
+- Source: https://github.com/thu-ml/SageAttention
+- License: Apache License 2.0 (see full text below)
+- Notes: LightDiffusion-Next applies a build-time patch (`docker/sageattention_setup.patch`) to SageAttention's `setup.py` to honor the `TORCH_CUDA_ARCH_LIST` environment variable during compilation.
+
+## SpargeAttn (thu-ml/SpargeAttn)
+- Source: https://github.com/thu-ml/SpargeAttn
+- License: Apache License 2.0 (see full text below)
+- Notes: Used as provided, without local source modifications.
+
+## ComfyUI (comfyanonymous/ComfyUI)
+- Source: https://github.com/comfyanonymous/ComfyUI
+- License: GNU General Public License v3.0 (full text distributed in the repository root `LICENSE`)
+- Notes: Provides the node-graph runtime and execution engine extended by LightDiffusion-Next.
+
+## ComfyUI Ultimate SD Upscale (ssitu/ComfyUI_UltimateSDUpscale)
+- Source: https://github.com/ssitu/ComfyUI_UltimateSDUpscale
+- License: GNU General Public License v3.0 (full text distributed in the repository root `LICENSE`)
+- Notes: LightDiffusion-Next adapts the Ultimate SD Upscale script to integrate with its sampler interface.
+
+## ADetailer (Bing-su/adetailer)
+- Source: https://github.com/Bing-su/adetailer
+- License: GNU Affero General Public License v3.0 (see full text below)
+- Notes: Supplies detector-driven post-processing for face, hand, and subject refinements. No local source code changes are applied.
+
+## Stable Fast (chengzeyi/stable-fast)
+- Source: https://github.com/chengzeyi/stable-fast
+- License: MIT License (see full text below)
+- Notes: Imported as a wheel distribution to enable graph compilation speedups for Stable Diffusion pipelines.
+
+## ComfyUI-GGUF (city96/comfyui-gguf)
+- Source: https://github.com/city96/comfyui-gguf
+- License: Apache License 2.0 (see full text below)
+- Notes: Provides GGUF model loader nodes used by LightDiffusion-Next without modification.
+
+## WaveSpeed (ComfyUI-WaveSpeed)
+- Source: https://github.com/Fannovel16/ComfyUI-WaveSpeed (original project reference)
+- License: MIT License (see full text below)
+- Notes: LightDiffusion-Next vendors the WaveSpeed caching utilities as-is for first-block cache optimisations.
+
+---
+
+## Apache License
+
+```
+Apache License
+Version 2.0, January 2004
+http://www.apache.org/licenses/
+
+TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
+
+1. Definitions.
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+5. Submission of Contributions. Unless You explicitly state otherwise,
+any Contribution intentionally submitted for inclusion in the Work
+by You to the Licensor shall be under the terms and conditions of
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+Contributor provides its Contributions) on an "AS IS" BASIS,
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+
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+whether in tort (including negligence), contract, or otherwise,
+unless required by applicable law (such as deliberate and grossly
+negligent acts) or agreed to in writing, shall any Contributor be
+liable to You for damages, including any direct, indirect, special,
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+END OF TERMS AND CONDITIONS
+
+APPENDIX: How to apply the Apache License to your work.
+
+To apply the Apache License to your work, attach the following
+boilerplate notice, with the fields enclosed by brackets "[]"
+replaced with your own identifying information. (Don't include
+the brackets!) The text should be enclosed in the appropriate
+comment syntax for the file format. We also recommend that a
+file or class name and description of purpose be included on the
+same "printed page" as the copyright notice for easier
+identification within third-party archives.
+
+ Copyright [yyyy] [name of copyright owner]
+
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
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+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
+```
+
+---
+
+## MIT License (Stable Fast)
+
+```
+MIT License
+
+Copyright (c) 2023 C
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
+```
+
+---
+
+## GNU Affero General Public License v3.0 (ADetailer)
+
+```
+ GNU AFFERO GENERAL PUBLIC LICENSE
+ Version 3, 19 November 2007
+
+ Copyright (C) 2007 Free Software Foundation, Inc.
+
+
+
+
+ setControlsOpen(true)} />
+
+
+
+
+
+
+ Advanced controls
+
+ Sampling, conditioning, optimization, and history for the next run.
+
+
+
+
+
+ );
+}
diff --git a/frontend/src/api/client.ts b/frontend/src/api/client.ts
new file mode 100644
index 0000000000000000000000000000000000000000..cb282b24f6cb0be5d704214676fc862ca965a942
--- /dev/null
+++ b/frontend/src/api/client.ts
@@ -0,0 +1,70 @@
+import axios from 'axios';
+import type {
+ GenerationSettings,
+ GenerationResponse,
+ ImageMetadata,
+ ModelInfo,
+ SettingsPreferences,
+ SettingsSnapshot,
+} from '../types';
+
+const api = axios.create({
+ baseURL: '/api', // Proxy handles redirection to localhost:7861
+});
+
+export const listModels = async (): Promise
+
+
+
+
+ {gallery.length === 0 ? (
+ Recent
++ {gallery.length === 0 ? 'No saved frames yet' : `${gallery.length} saved`} +
+
+ Generated images will collect here for quick comparison.
+
+ ) : (
+
+ {gallery.map((image, index) => {
+ const isSelected = image === currentImage;
+
+ return (
+
+ );
+ })}
+
+
+
+
+
+
+
+
+
+
+
+
+ + Generate the next frame. +
++ Choose a model, write the prompt, and run. Advanced controls stay out of the way until you need them. +
+
+
+ {!serverStatus ? (
+ Engine offline
+ ) : null}
+
+
+
+
+
+ + {activeModel ? `${activeModel.type} ready` : 'Models load automatically when the backend is available.'} +
+
+
+
+
+
+
+