Flux.2-Klein-Edit-Ultra-Fast

Flux.2-Klein-Edit-Ultra-Fast (Flux.2-Klein-Small-Decoder-Only) is a high-performance image editing and generation platform powered by the black-forest-labs/FLUX.2-klein-4B model paired with the black-forest-labs/FLUX.2-small-decoder VAE. The suite enables fast 4-step image-to-image editing, multi-image reference manipulation, and text-to-image generation directly on CUDA hardware.

The application uses a FastAPI backend server (gradio.Server) paired with a dark-mode frontend single-page application (SPA). Features include an A/B image comparison slider, a result history filmstrip, quick prompt chips, and a dual-view canvas.

Key Features

• Optimized Small Decoder VAE: Uses the FLUX.2-small-decoder VAE alongside FLUX.2-klein-4B to accelerate decoding cycles while preserving visual details and prompt adherence.
• Dual-Mode Generation (I2I & T2I): Performs image editing when input images are supplied, or falls back seamlessly to text-to-image generation if the input gallery is empty.
• Multi-Image Reference Editing: Accepts multiple reference inputs to guide transformations—such as transferring accessories or outfits from reference photos onto target subjects.
• Studio SPA Interface: An interactive single-page web app built with vanilla web components, offering an A/B image comparison slider, history filmstrip, prompt chips, and drag-and-drop file uploaders.
• Automatic Aspect-Ratio Snapping: Calculates dimensions from the first input image, scaling parameters to fit within 1024px while snapping width and height to multiples of 8.

Repository Structure

├── examples/
│   ├── 1.jpg
│   ├── 2.jpg
│   ├── 3.jpg
│   ├── 4.jpg
│   ├── I1.jpg
│   └── I2.jpg
├── app.py
├── index.html
├── LICENSE.txt
├── pre-requirements.txt
├── pyproject.toml
├── README.md
├── requirements.txt
└── uv.lock

Installation and Requirements

To set up the Flux.2-Klein-Edit-Ultra-Fast environment locally, configure your system according to the specifications below. A modern CUDA-enabled GPU is required.

• Python Version: Minimum Python 3.10.13 or above is required; Python 3.12 or 3.14 is recommended.
• PyTorch Version: torch==2.11.0 or above is required for best compatibility.
• CUDA Version: CUDA 13.0 is recommended (--extra-index-url https://download.pytorch.org/whl/cu130), matching the environment used on the live Hugging Face demo.

Running with uv (Recommended)

uv is an ultra-fast Python package and project manager written in Rust. It ensures rapid virtual environment setup and exact dependency synchronization based on the uv.lock file.

Step 1 — Install uv

• macOS / Linux: curl -LsSf https://astral.sh/uv/install.sh | sh
• Windows: powershell -c "irm https://astral.sh/uv/install.ps1 | iex"

Step 2 — Clone the repository

git clone https://github.com/PRITHIVSAKTHIUR/Flux.2-Klein-Small-Decoder-Only.git
cd Flux.2-Klein-Small-Decoder-Only

Step 3 — Initialize the project and install dependencies

uv sync

Step 4 — Run the script

uv run app.py

Standard PIP Implementation

1. Update Package Manager Upgrade your local package manager:

pip install pip>=26.1.2

2. Install Core Dependencies Install the primary deep learning stack, transformer libraries, and core computing utilities listed in requirements.txt:

pip install -r requirements.txt

Core Requirements List (requirements.txt)

--extra-index-url https://download.pytorch.org/whl/cu130
torch==2.11.0
torchvision==0.26.0
transformers==5.14.1
accelerate==1.14.0
diffusers==0.39.0
peft==0.19.1
gradio==6.22.0
av==17.1.0
spaces==0.51.1
huggingface-hub==1.24.0

Usage

Once the web server initializes, open your browser to the local address output in your terminal (typically http://127.0.0.1:7860/).

1. Upload Asset (Optional): Drag and drop images into the main canvas workspace, paste an image from your clipboard, or click the upload icon in the left rail. Leave empty for text-to-image generation.
2. Refine Instructions: Type your instructions inside the prompt field, or click one of the Quick Prompts chips to fill it. Press ⌘/Ctrl + Enter or click Edit Image.
3. Compare & Chain: Use the Compare tool on the left rail to view an A/B slider of the before and after states. Click Use as Input to chain multiple edits sequentially.

License and Source

• License: Apache License 2.0
• GitHub Repository: https://github.com/PRITHIVSAKTHIUR/Flux.2-Klein-Small-Decoder-Only.git
• Hugging Face Live Space: https://huggingface.co/spaces/prithivMLmods/Flux.2-Klein-Edit-Ultra-Fast