ComfyUI nodes wrapping LongCat image generation and editing pipelines (diffusers-based). Includes text-to-image and multi-image edit flows with prompt rewriting, aspect-aware sizing, and latent decoding for ComfyUI.

Features

LongCatCheckpointLoader: Loads the LongCat model components (Model, CLIP, VAE).
TextEncodeLongCatImage / TextEncodeLongCatImageEdit: Encodes text prompts and reference images (for editing) into conditioning.
VAEEncodeLongCat / VAEDecodeLongCat: Encodes images to latents and decodes latents to images using the LongCat VAE.
LongCatSampler: Handles the sampling process (denoising) using the LongCat transformer.
LongCatImageSizeScale: Scales images to a target pixel area and rounds dimensions to multiples of 16.

Installation

Copy Folder: Copy the comfyui_longcat folder into your ComfyUI custom_nodes directory.
- Example: ComfyUI/custom_nodes/comfyui_longcat
Install Dependencies: Ensure your ComfyUI environment has the required packages:
```
pip install -r requirements.txt
```
(Note: requirements.txt is in the root of this repo, or check setup.py for list).
Model Weights: Place LongCat model weights in a directory accessible to ComfyUI.

Usage in ComfyUI

Put this plugin folder into ComfyUI custom_nodes, then restart.
Nodes appear under category longcat.
Workflow:
1. Load model with LongCatCheckpointLoader.
2. Connect CLIP to TextEncodeLongCatImage (T2I) or TextEncodeLongCatImageEdit (Edit).
3. Connect VAE to VAEEncodeLongCat (if using image input) and VAEDecodeLongCat.
4. Connect MODEL, CONDITIONING (Positive/Negative), and LATENT to LongCatSampler.
Set model_path to your downloaded LongCat checkpoint; on CUDA you may enable cpu_offload to save VRAM.

Development

Tests: pytest tests/test_nodes.py
Key modules: nodes.py, longcat_image/pipelines/*, longcat_image/models/longcat_image_dit.py.

To-Do

Add robust fallback when prompt rewriting model lacks generate.
Guard LongCatImageEditPipeline for image=None misuse.
Expand docs with example ComfyUI workflows and screenshots.
Provide sample model download script and config guidance.
Add more automated tests (pipeline smoke tests, dtype/device matrix).

Credits

LongCat base model & pipelines: original LongCat project (LongCat team).
diffusers (Hugging Face) for pipeline scaffolding.
transformers (Hugging Face) for text and vision encoders.
accelerate for optional CPU/GPU offload helpers.
PyTorch for core tensor and model runtime.
Pillow (PIL) and NumPy for image/tensor conversions.
OpenAI / DeepSeek API usage scaffold in misc/prompt_rewrite_api.py.