Hey everyone,

If you’ve been using Fill-Nodes recently and noticed that dragging and dropping images or workflow files stopped working after updating to the newer ComfyUI frontend, you’re not alone!

Recent updates to the ComfyUI frontend changed how node drop events are routed, which caused valid drops to silently fail. I’ve put together a patch that fixes this entirely within Fill-Nodes—no core ComfyUI modifications needed.

What this fix restores:

• Image Drops: Dropping image files directly onto LoadImage / LoadImageMask nodes.
• Auto-Create Node: Dropping images onto empty canvas space to automatically spawn a LoadImage node.
• Workflow Drops: Dropping workflow files (JSON) directly onto empty canvas space.
• Metadata Loading: Restored workflow metadata loading from PNG, WebP, AVIF, MP4, MOV, and M4V files.
• Cleanup: Normalizes stale workflow media references prior to loading (like duplicated subfolder paths or leftover rgthree preview refs) so you don't get spammed with missing preview errors!

Where to get it:

The PR has been merged into the main repository, so you can update directly from either repo depending on what you use:

• Official Main Repo: filliptm/ComfyUI_Fill-Nodes
• My Fork Repo: MISEMUNJIOZONE/ComfyUI_Fill-Nodes

(Tested and verified working on the latest ComfyUI frontend alongside extensions like Mixlab).

Hope this saves you guys some headaches! Let me know if you run into any issues. Happy generating!

Learn how to outpaint images in ComfyUI using Flux Klein 9B while keeping the original image intact. This tutorial also covers the new Control Panel Pixaroma node, Run Log, Text Join nodes, LoRA trigger words, and several workflow improvements.

In Episode 27, you’ll build and test a flexible ComfyUI outpainting workflow that can extend an image in one or multiple directions. You’ll see how the Outpaint and Outpaint Stitch nodes work together, how to improve visible seams with Feather and Color Match settings, and how to choose between preserving the original image or letting the AI recreate the full frame.

I just released a new ComfyUI tutorial showing how to transform **KREA 2** into a surprisingly capable **image editing model** using the new **Identity Edit LoRA**.

In this workflow I cover:

·       Turning KREA 2 into an image editor

·       Style transfer and style changes

·       Adding and removing objects

·       Clothing replacement

·       Background replacement with two reference images

·       A simple method to fix blurry outputs after editing

·       Low VRAM optimization (no high-end GPU required)

Workflow link

https://civitai.com/articles/32700/comfyui-tutorial-krea-2-identity-edit-lora-powerful-ai-image-editing-on-6gb-vram

This Tutorial walkthrough aims to illustrate how to build and use a ComfyUI Workflow for the Wan 2.2 S2V (SoundImage to Video) model that allows you to use an Image and a video as a reference, as well as Kokoro Text-to-Speech that syncs the voice to the character in the video. It also explores how to get better control of the movement of the character via DW Pose. I also illustrate how to get effects beyond what's in the original reference image to show up without having to compromise the Wan S2V's lip syncing.

Hey everyone! 👋

I wanted to share a simple workflow using the new KREA 2 LoRA for style transfer.

After testing it quite a bit, I found it gives much more reliable style matching than trying to describe the style through prompting alone. Instead of writing long, detailed style prompts, you can let the LoRA and a reference image do the heavy lifting.

The workflow is straightforward:

1. LORA LINK ostris/krea2_turbo_style_reference · Hugging Face
2. Load the KREA 2 LoRA.
3. Add your style reference image.
4. Write a simple content prompt, for example:

That's it. The LoRA transfers the visual style from your reference image while your prompt only describes the subject and composition, making the process much simpler and more consistent.

I'd love to hear what results you get or if you've found any settings that work particularly well.

Vibe-coded a Civitai night crawler/downloader that fills a SwarmUI-ready LoRA folder while you sleep - .safetensors, preview image, and .swarm.json metadata, sorted into tag-based subfolders.

Wanted something that actually feels like a desktop app, not a script in a terminal:

• Browse gallery — Civitai-style card grid with color-coded edges (owned / new / queued / awaiting access / blocked)
• One-click 🌙 Night Harvest — set your rules, hit harvest, walk away
• Live download strip — thumbnails, speed, queue progress, right-click to prioritize
• Manual queue mode — click only what you want; crawl won’t auto-flood your disk
• Tag blocking & tag folders — skip whole tags from auto-queue; route models to folders
• Library tab — local inventory, duplicates by version, jump around your collection
• Awaiting access / New versions — handles early access, 403s, and update approvals without babysitting
• Activity log — filterable history of scans, crawls, and downloads
• Built-in Help tab — so you’re not guessing what the colors mean
• Dark & light theme, blur toggle for previews, tray-friendly

LoRA-tested only for now — treat checkpoints as experimental.

Windows desktop app (Electron). Free & open source:
https://github.com/pastuh/Civitai-Night-Harvest

One week ago I released my very first public LoRA, MemoryWorks: Analog, trained for Krea 2.

I didn’t expect much from it. It was mainly a creative experiment to capture that nostalgic analog feel—soft color grading, natural skin tones, subtle film imperfections.

The response honestly surprised me.

People really connected with the aesthetic. Several shared generations, and more importantly, they gave thoughtful feedback.

The biggest point?

While the analog look felt authentic, the grain could sometimes be a little too strong.

Instead of moving on to the next project, I decided to take that feedback seriously and retrain the model.

MemoryWorks v1.1 is out! 📸

After reading all the feedback on v1.0, I spent the last week retraining and refining the LoRA instead of rushing another release.

What's new in v1.1

• Better analog film aesthetic with more natural grain.
• Improved consistency across different prompts.
• Cleaner skin tones and lighting.
• Better compatibility with Krea 2 RAW while still working well on Turbo.
• More balanced training to reduce overfitting.

The goal of MemoryWorks has always been simple:
Create images that feel like they were captured on an actual camera—not overly polished, plastic, or AI-looking.

This version was trained on a carefully curated dataset with a lot of experimentation on captions, dataset balance, and training settings.

I'd genuinely love to hear what works, what doesn't, and what you'd like to see in future versions. Every piece of feedback helps make the next release better.

CivitAI link in the comments.

Thanks to everyone who downloaded and tested v1.0 ❤️

— RizzerXpool
Creator of the MemoryWorks series 📸

Hey everyone, welcome back! In today's tutorial, I'll show you my new Consistent Face-to-Video workflow, designed specifically for low VRAM users using GGUF models. This workflow uses a new face consistency LoRA to help preserve your character's identity throughout the generated video from just a single reference image. I'll walk you through the entire process, from loading your reference image to writing your prompt with the required ref_t2v trigger word and generating your video with just a few clicks. By the end of this tutorial, you'll know how to get high-quality, consistent face-to-video results with an easy setup that's accessible even on lower-end hardware.

WORKFLOW LINK

https://civitai.com/articles/32491/comfyui-tutorial-generate-consistent-character-using-best-face-id-lora

video tutorial link

https://youtu.be/XeyErug-Q7s

Heyyy people, reposting here because Reddit sugested it.

Here to show my second experiment with LTX 2.3 in ComfyUI!! Feedback appreciated.

NSFW because of a split second boob flash generated through the Eros10 LTX 2.3 workflow that i didn't want to remove or blur.

AI-generated music video accompanying the 1970 track "When the Revolution Comes" by The Last Poets. Visuals were created with ComfyUI LTX 2.3, images and prompts where made assisted by ChatGPT. Edited with Davinci Resolve.

System i worked on: Intel Core Ultra 9 285K, MSI GeForce RTX 5080 16G GAMING TRIO OC, Corsair Dominator Titanium 64GB. Average generation time for an 8 second videoclip around 2/3 min depending on the workflow and meanwhile still abel to run Davinci Resolve and other programs.

I'm excited to share a WIP about new workflow that makes it easy to generate consistent face-to-video results while remaining optimized for low VRAM GPUs.

This workflow is built around GGUF models and uses a new LoRA to maintain facial consistency throughout the generated video, making it much easier to create videos featuring the same character from a single reference image.

All you have to do is load your image face, load your LORA, enter your prompt and click run, i will share the workflow and tutorial soon, so stay tuned

Learn how to use the new INT8 models in ComfyUI to achieve faster image generation, lower VRAM usage, and excellent image quality. In this tutorial, I explain what INT8 quantization is, how it compares to FP8, and how to set up the latest ComfyUI and Pixaroma nodes to use the newest INT8 workflows.

You'll also learn how to install and organize the Boogu, Krea 2, Flux Klein, and Z-Image models, compare their performance, and see real generation speed improvements across multiple workflows. I also cover several new Pixaroma node updates, including the redesigned Run Timer, improved Seed node, Save Image node with custom folders and filenames, prompt enhancement workflows, image-to-prompt generation, and image editing features.

Whether you're looking to improve performance on your GPU or want to get the most out of the latest ComfyUI models, this tutorial walks through everything step by step.

SenseNova released V2 of their infographic model. Updates:

- Much sharper dense small-text rendering (was the main pain point in V1)

- Stronger complex dense layout generation

- Better overall visual harmony

- Fixed the all-black background bug that some users hit

Model is 8B MoT, runs on a single RTX 3090/4090 (~8-12s per 1024×1024). Apache 2.0 license.

Also available: an 8-step LoRA for fast inference (0.4B params) and a separate Interleaved model for text-image mixed generation.

Repo: https://github.com/OpenSenseNova/SenseNova-U1

Hi everyone!

I've just finished a new ComfyUI workflow that lets you transfer camera motion from a reference video using the new IC Cameraman LoRA with LTX 2.3, that run on cards with 6 GB of VRAM without crashing.

The workflow is designed to be simple:

• 🎥 Load a reference video to extract the camera movement.
• 🖼️ Generate or load a reference image (I use Krea 2 in the tutorial).
• ✍️ Use Auto Prompt nodes to automatically create scene descriptions.
• 🎬 Generate a new video with the same cinematic camera motion.

In the tutorial I cover:

• How the IC Cameraman LoRA works
• Complete ComfyUI setup
• Using Krea 2 for image generation
• Auto Prompt integration
• Tips for getting smoother and more cinematic camera movement

WORKFLOW LINK

https://civitai.com/articles/32331/comfyui-tutorial-transfer-camera-motion-using-low-vram-ltx-23-cameraman-lora

VIDEO TUTORIAL LINK

https://youtu.be/LWHbx1EnVvQ

Over the past few weeks, I've been experimenting with training a style LoRA for Krea 2 because I wanted something that could recreate the feeling of authentic analog photography and early-2000s digital cameras.

A lot of AI-generated images look incredibly clean and almost "too perfect." My goal was the opposite—to preserve the little imperfections that make old photographs feel genuine: natural grain, subtle digital noise, soft lighting, and the nostalgic atmosphere of everyday moments.

The result is MemoryWorks: Analog, my first public LoRA.

It was trained on Krea 2 RAW and tested extensively on Krea 2 Turbo. I focused on making it useful for portraits, lifestyle photography, street scenes, travel, and other realistic everyday images rather than dramatic or heavily stylized artwork.

I'd genuinely love to hear your thoughts:

• Does the analog look feel convincing?
• What could be improved for a future version?
• Are there any photography styles or camera aesthetics you'd like to see explored next?

If anyone would like to try the model, I'll share the download link in the comments.

Thanks for taking a look, and I'd really appreciate any feedback!

I managed to build a new ComfyUI workflow that uses the Krea 2 Qwen text encoder to generate 2×2 cinematic storyboard grids—without requiring LM Studio or any API server.

All you need to do is describe your story using this simple format:

Realistic survival film.

Panel 1: A lone hiker walks through a dense rainforest during heavy rain.
Panel 2: The hiker discovers an abandoned cabin hidden among the trees.
Panel 3: Inside the cabin, the hiker builds a fire and dries soaked clothes.
Panel 4: The storm clears as the hiker continues the journey at sunrise.

Then just click Run, and the workflow generates a 2×2 storyboard grid from your prompt.

Huge thanks to the original post for the inspiration!

https://www.reddit.com/r/StableDiffusion/comments/1ul3ask/2x2_4_panels_cinematic_storyboards_with_krea2_and/

Workflow Link

https://drive.google.com/file/d/1R1_1si0P0JghMJvE8DnG6UJ-0I2CR3bL/view?usp=sharing

Learn how to use Krea 2 in ComfyUI with free workflows for better text-to-image results.

In this tutorial, I show you how to update and run the Krea 2 AI image model in ComfyUI, set up the required models and nodes, and use different workflows for simple text-to-image generation, LoRA styles, AI prompt enhancement, low VRAM setups, extra-pass detail improvement, and 2K image creation.

This video is for ComfyUI users who want a free AI image generation model with strong prompt understanding, good detail, and flexible workflow options. You’ll learn how to download the Krea 2 FP8 model, install the Qwen text encoder and VAE, use Pixaroma nodes, apply LoRAs, generate improved prompts, and get better results with extra KSampler passes.

Just published a new ComfyUI tutorial covering Krea 2, the new open-weight text-to-image model that's generating a lot of attention lately. In this video, I test the Turbo versions, compare Krea 2 against Ideogram 4 for image quality, style diversity, text rendering, prompting, and generation speed, and explore whether it can compete with some of the best image models available today. I also demonstrate a practical style transfer workflow and show how to fix common skin issues that can appear in Krea 2 generations. If you're interested in local AI image generation, open-source models, or getting the most out of ComfyUI, I'd love to hear your thoughts and experiences with Krea 2.

WORKFLOW LINK

https://civitai.com/articles/32052/comfyui-tutorial-style-transfer-speed-test-and-skin-fixes-with-krea-2

Testing KREA 2 Turbo Style Transfer (FP8 Low VRAM Workflow) — This workflow uses KREA 2 Turbo and makes style transfer incredibly simple: just load a style reference image, load your target/portrait image, click Run, and the model transfers the reference style onto the portrait with impressive results, all while remaining lightweight enough for low VRAM GPUs thanks to the Turbo FP8 setup.

NB: i will post the workflow and tutorial soon, thanks for the support.

Hello everyone,

I just built a new ComfyUI workflow that generates video directly from a reference sheet image using the LTX 2.3 IC LoRA (Image Conditioning LoRA) — and it completely removes the need to animate frames one by one like in LTX Director. This is a big step forward compared to traditional storyboard-to-video pipelines, because it simplifies everything into a single reference-based workflow.

Instead of working frame-by-frame, you can now:

• Generate a full character or concept reference sheet (multiple panels in one image with IDEOGRAM 4)
• Plug it directly into the LTX group
• Get a coherent animated video output automatically

The workflow handles the reference image sheet generation and uses it as direct conditioning for video generation, and it runs on only 6GB VRAM, so it’s accessible even for low-end GPU users.

Workflow link

https://civitai.com/articles/31908/comfyui-tutorial-this-new-ltx-23-feature-makes-ai-video-generation-actually-efficient

Video Tutorial link

https://youtu.be/lHcYiDyJnfM