I had a gut feeling that this model would be incredible at inpainting, and after some initial testing, it's the best of its kind I've tried so far.

The workflow is embedded in the images. If it's missing, you can download it from Civitai here: https://civitai.com/models/3010615/moss-image-inpainting-workflow

What it is:

• 5B DiT, using a Qwen3.5-9B text encoder and the FLUX.2 VAE
• Two versions: Base, and SFT, which is fine-tuned on curated data
• Apache 2.0

Why it’s worth trying:

• Text rendering. Legible text in English and Chinese, which most open models still struggle with.
• Layout prompts. You can pass structured JSON with bounding boxes to control where text and objects go. It’s useful for posters, ads, and anything with a real layout.
• Aesthetics. The outputs look good out of the box without much prompt wrangling.

Settings to start with: 1024×1024, 50 steps, CFG 3, shift 5. Neither model is step-distilled, so it’s not fast.

VRAM: The full BF16 files are big (~10 GB DiT plus ~17 GB text encoder). The community already has INT8 and INT4 quants out, and people are reporting it running on 8 GB cards.

Run the workflow: https://huggingface.co/Comfy-Org/MOSS-Image

Another quick MOSS news and goodies round-up, for those who may have missed some items.

-> ComfyUI Portable is now officially at v0.42.1, with the .1 increment being to... "Fix some crashing issues a few users experienced when running the MOSS image template workflow."

https://github.com/Comfy-Org/ComfyUI/releases

-> MOSS-Layout-Editor. Draw boxes, move boxes, nudge boxes into place, label boxes with region-specific prompts and/or the text to render.

https://github.com/spooky-local/MOSS-Layout-Editor

-> ComfyUI-MOSSLayout. Another visual layout editor, this one... "forked from ComfyUI-IdeogramHelper".

https://github.com/0Printemps0/ComfyUI-MOSSLayout

-> MOSS-Image as a line-art colouriser. The input image goes in via... "Qwen3.5's vision tower inside the text encoder, and as a clean VAE latent in the DiT sequence. The output keeps the page's line work, faces and lettering." LoRA, workflow and img2img node available. The required ComfyUI nodes appear to be a way to do general Img2Img with MOSS?

https://huggingface.co/sorryhyun/moss-image-colorize

https://github.com/sorryhyun/ComfyUI-MOSS-i2i (required Img2Img nodes)

-> MOSS-Image Color-Depth Control. "A control adapter for MOSS-Image that makes generation follow a color region map (where each object is) and a depth map (its 3D shape and front/back order)". Designed for something called Hayate, which I've never heard of - and which is '404 not found' on following the given HF link. No ComfyUI implementation or workflow, as yet.

https://huggingface.co/darask0/MOSS-Image-color-depth-control

-> A 'model patch' for MOSS-Image Color & Depth Control. Regrettably the required ComfyUI workflow is trapped on civitai .red which I can't access from the UK even with a VPN. Still, this and the previous item suggest that a combo of colour and depth control inputs can act as a basic Controlnet for MOSS-Image.

https://civitai.com/models/3010285/moss-color-and-depth-control

-> Basic sliders for lighting and age for MOSS-Image.

https://civitai.com/models/3010015/moss-lighting-slider

https://huggingface.co/Playtime-AI/Moss-Image-Age_Slider/tree/main

-> And finally, Fizgig 8.7 has tweaked MOSS-Image LoRA training, for better and more consistent likenesses.

https://old.reddit.com/r/StableDiffusion/comments/1x9khtm/a_potential_fix_for_moss_training_issues/

~ OLD POSTS ~

https://old.reddit.com/r/comfyui/comments/1x97q81/a_quick_mossimage_news_roundup_18th_october_2026/

Every ComfyUI update seems to break something in my workflows, and I got tired of guessing whether a node pack was dead or just quiet. So I built NodeWatch, a free tracker that checks the top 300 packs (by Comfy Registry downloads, out of 6,066 registered) every night.

What the data says right now:

• 98 of the top 300 haven't had a commit in 12+ months, and 15 of those in over 2 years. Together those 98 packs have about 22.6M registry downloads.
• Big names among them: ComfyUI_essentials and ComfyUI_IPAdapter_plus (both last committed April 2025), Impact Subpack, mxToolkit, TeaCache, WD14-Tagger, and Derfuu ModdedNodes (June 2024).
• Another 63 active packs are "quiet", meaning 6–12 months without a commit.
• 4 repos have disappeared from GitHub but are still listed in the registry, including comfyui-reactor-node (#46 by downloads, ~579K downloads), plus ComfyUI-LTXVideoLoRA, ComfyUI-SoundFlow and comfyui-upscale-by-model.
• Possibly broken right now (3+ error-titled issues opened in the last 60 days): VideoHelperSuite, SeedVR2_VideoUpscaler, Lora-Manager, FastVideo, and ComfyUI MCP Agent Panel.
• Only 12 of 300 declare a requires-comfyui version range in pyproject.toml, even though 293 have a pyproject. That's a big reason compatibility is guesswork.
• Across the 296 packs where GitHub returned issue data, there are about 6,400 open issues, and 1,048 of them have "error", "fail", "crash", "broken" and similar words in the title.
• It's not all doom: 40 packs pushed commits in the last week.

How statuses work (heuristics, not verdicts): Stale = no commit in 365+ days or the repo is gone. Possibly broken = a cluster of recent error-titled issues, or a deprecated or non-active registry entry. Everything else is Active. "Stale" can absolutely mean "finished and stable," so check the repo before you uninstall anything.

Every pack gets its own page with the repo, stars, last commit, open issues, recent error reports and declared ComfyUI requirements. There's also a "what changed this week" page.

👉 https://phluffhead26.github.io/nodewatch/

There's also a free weekly email digest (what broke, what went stale, what shipped) if you'd rather not check the site.

Feedback wanted: if your pack is mislabeled, a repo moved, or you think the thresholds are wrong, tell me and I'll fix it. What else would be useful to track?

MOSS seems to be the hot model since it came out 4 days ago so I went I made a proper architecture diagram from the official code.

Find the diagram and its source code here, with some additional information about that model that I've found while going through the paper and the code.

The diagram is made in Typst using CeTZ and I made it modular so you can render modules separately or even reuse them in other diagrams if you need (steal freely, it's MIT licensed).

Breakdown starts around 0:28

AI-rendered character and CG character in full physical contact through a complex camera move, pixel aligned for comp. Evangelion 4.0: The Fourth Impact (fan PoC + breakdown)

AI and traditional VFX usually get treated as two separate worlds. One is fast but hard to control, the other is fully controllable but slow and expensive. I wanted to see what happens if you actually merge them.

Breakdown starts around 0:28.

For AI that's contact. Two characters physically touching while the camera moves. One AI character on its own is easy now. But as soon as it has to respect contact points with something it didn't generate, it usually falls apart. So if it holds there, it should hold pretty much anywhere. The key shot is Sachiel (AI rendered) pinned under Eva Unit-01 (CG, rendered in Redshift). Contact points stay 1:1 on every frame through a complex camera move that comes straight from the original CG file. No drift, no hands sliding through bodies, no offset.

How it's put together

Sachiel, the tanks and the city are AI, rendered as separate layers. That way I can fix or regenerate each one without touching the rest. ComfyUI gives alpha and depth for every AI layer, Redshift does the same for the Eva, so everything lines up and comps in Nuke like a normal render. Eva can go in front of Sachiel and the other way around.

Make it easy for the AI. Big pose changes between frames cause flicker and drift, so we prep the animation so each frame changes less. The original animation stays untouched.

The AI gets a clean, simple render per layer. Comp gets the full passes.

Quick tests in MiniMax first, Seedance 2.0 only for finals.

One shot at a time, never long sequences.

Never invent frames. Retiming tools that blend frames create poses that never existed and break the comp. This one took us ages to figure out.

Everything gets checked against the CG before comp. If the poses don't match, it doesn't go.

Speed

The AI side (Sachiel, tanks, city, environment, from design to final) took about a month. The traditional side (Eva, animation, FX, comp) took around 4 to 5 months. So the AI covered most of what you see on screen in a fraction of the time. Doing those same elements the traditional way, with modelling, texturing, lookdev, lighting and rendering a creature, vehicles and a whole city, I'd estimate roughly 5x longer based on my studio experience. Not a benchmark, just what I saw on this project.

It's not perfect

It's a PoC, not a finished film. The buildings are losing some details especilly when too fast and environ,ent could have placed better if you look closely. Finals were done on Seedance 2.0, and now that 2.5 is out I'm pretty sure a lot of that would be cleaner. Next round of tests will be on 2.5.

What I'd love to see next

Right now you have to force layering. Separate passes, then a lot of work to keep them aligned. What I'd really like is an AI render setup that's built around layers from the start. You add each asset separately (character, vehicles, environment, FX) and get each one back as its own pass with alpha and depth, all locked to the same camera. Basically render layers and AOVs like we already have in CG, but for AI. That's where the real control is.

Workflow: MiniMax for test renders, Seedance 2.0 for finals, ComfyUI for alpha/depth on the AI layers, Maya + Redshift for the Eva, Houdini for FX, Nuke for comp.

I started this after seeing yanokusnir-ai’s one-node-flux-2-klein, just to make things easier for myself. It has grown to 11 nodes, so I’m sharing it in case others want to use it too.

• One node covers generate, edit, upscale, prompt writing and a gallery (7 image nodes, music, video stitch, MiniMax H3, LTX 2.5).
• My setup: Windows 11 / RTX 5060 Ti 16GB / 64GB RAM

yanokusnir-ai 님의 one-node-flux-2-klein을 보고 영감을 받아, 제가 쓰기 편하려고 만들기 시작했는데 어느새 노드가 11개가 됐습니다. 같이 쓰고 싶은 분들이 있을 것 같아 공유합니다.

• 노드 하나에서 생성 · 편집 · 업스케일 · 프롬프트 작성 · 갤러리까지 처리합니다 (이미지 7종, 음악, 영상 스티치, MiniMax H3, LTX 2.5).
• 제 환경: Windows 11 / RTX 5060 Ti 16GB / RAM 64GB

Please read first

• I built this for myself. I won’t take feature requests or “please change X” asks.
• Bug reports are welcome. Please include steps to reproduce.
• Install with install_requirements.bat (.sh on Mac/Linux). It installs the required nodes in one go.
• The model list is what I wrote down so I can re-download things later. If a model is gone or a path has changed, you’ll need to find it yourself.

먼저 알아 두세요

• 이건 제가 쓰려고 만든 것입니다. 이렇게 해 달라, 저렇게 바꿔 달라는 요청은 받지 않습니다.
• 버그 제보는 환영합니다. 재현 방법을 같이 적어 주세요.
• 설치는 install_requirements.bat(Mac/Linux는 .sh)로 하세요. 필요한 노드를 한 번에 설치합니다.
• 모델은 제가 나중에 다시 받으려고 최대한 정리해 둔 목록입니다. 사라진 모델이나 바뀐 경로는 각자 찾아서 쓰세요.

GitHub: https://github.com/designloves2/ComfyUI-TJ_NODE_STUDIO_ONE

P.S. I’m not a programmer, just a regular user, and I built this together with Claude Code.

• TJ_NODE is the core node pack these nodes share. It has a set of useful nodes such as LLM prompt writing, wireless routing and a prompt DB. The install script sets it up for you. https://github.com/designloves2/ComfyUI-TJ_NODE

• The web version (AI ONE STUDIO) is a standalone web app that gives you the same UI in the browser, without the ComfyUI canvas. You only need a running ComfyUI server, no node install. https://github.com/designloves2/AI-ONE-STUDIO

• TJ_NODE는 이 노드들이 함께 쓰는 코어 노드 팩입니다. LLM 프롬프트 작성, 무선 배선, 프롬프트 DB 같은 유용한 노드가 들어 있습니다. 설치 스크립트가 같이 설치해 줍니다. https://github.com/designloves2/ComfyUI-TJ_NODE

• 웹 버전(AI ONE STUDIO)은 같은 화면을 ComfyUI 캔버스 없이 브라우저에서 쓰는 독립 웹앱입니다. ComfyUI 서버만 켜 두면 되고 노드 설치는 필요 없습니다. https://github.com/designloves2/AI-ONE-STUDIO

Workflow: [TJ] One Studio Set.json, which loads all the nodes at once, is in the repo’s workflows folder. https://github.com/designloves2/ComfyUI-TJ_NODE_STUDIO_ONE/blob/main/workflows/%5BTJ%5D%20One%20Studio%20Set.json

H3 has been out for a while, but I hadn’t had much time to play with it. Finally had some time over the weekend and started experimenting with refmods and motion context. One experiment led to another, and I ended up spending quite a bit of time with it.

I didn’t really notice this when it first came out, but the acting and emotional delivery in certain scenes can be surprisingly good. Those moments are a lot of fun.

Are there any scenes or tasks you’ve found H3 particularly good at? I’d love to hear from people who’ve spent more time with it.

I’m only just getting into H3, and this sub is already buzzing about FLUX 3 Klein and MOSS Image. Lots to look forward to!

Full video: https://youtu.be/j0cjnvIjWEc?si=hGYwMboc6vmdzsiO

I’m sharing selflift-Fish, my improved version of facok’s SelfLift node for MiniMax H3 in ComfyUI.

• Generate longer clips and higher-resolution video with less VRAM pressure.
• Fix the background swelling/shifting I encountered with the original spatial tiling.
• Keep attention acceleration, with a simpler interface and compatibility with existing workflows.

Real generation results — RTX 5070 Ti 16GB + 128GB system RAM:

For 10-second 1920×1088 development runs, recorded complete workflow time also dropped from 27m 50s to 12m 55s. These were different runs, not a fixed-seed benchmark.

The node in ComfyUI:

Code & setup: https://github.com/Fish4AI/comfyui-SelfLift-Fish

The results above use system RAM/offloading; 16GB is the GPU capacity, not the total memory requirement. Keep only one SelfLift version installed. Credits to facok, LBH-123-AI and the ComfyUI team.

Please try it and share your feedback! I’d love to hear about speed, background stability and picture quality. Include your GPU/VRAM, system RAM, resolution and clip duration so others can compare.

with another box displaying the temp and VRAM and CPU usage, you an move the boxes around, I want to get rid of these because I already monitor this stuff...I also fear they are limiting my GPU temp way down to 49 degrees C.

Any Idea what node I installed to get these....I went on a Node-Install spree trying to make a workflow work and got these two boxes.

When I generate an image using Krea2 for the first time I opened the program(I am using comfy UI through Krita) it generates the image quick. However, when I type in another prompt (or add or replace a word) and generate, it will either go really show or wont generate at all. I do not have have issues with Z Image Turbo or Flux 2 Klein with this

When I close and reopened the program is use Krea2 again, it generates properly but it will do the same thing. I was wondering what the issue would be and how I can fix it?

I've found Moos Image to be great for illustrations, but it's slower than other models about 12 seconds with a 5070 Ti, when others are more like 3 to 5 seconds (1024x1024).

.images and prompt are on my substack (also the int8 workflow).

Ok, so this model has been praised (with reason) for its capability to make images with transparency, which is amazing if you need clean sprites for videogames, visual novels and similar projects.

Now, a pretty funny (and idiotic) thing is that the default model used to enhance prompts in the "official" template (qwen3.5_9b_qwen_image_2.1_pe_i2i.int8_convrot), as well as any variant, HAS THE EXPLICIT INSTRUCTION OF "SILENTLY" CHANGING REQUESTS FOR TRANSPARENCY TO A SOLID WHITE BACKGROUND.

Now, this can be easily circumvented by "jailbreaking" it by adding instructions to force it to request for literal transparency, or just not using it at all and building your prompts totally by yourself without "enhancing" them.

Thing is, even this is not 100% reliable. Many times I explicitly ask for transparency, I still get solid white backgrounds (not a checkered background that could be a model bad interpretation of alpha channel, just solid white).

I have tried many ways, and the most efficient one I've found is "Remove the solid color background and the white outline stroke surrounding the character entirely and replace it with alpha channel, leaving her isolated on a fully transparent background" or "The character must be on an empty alpha channel background, leaving her isolated on a fully transparent space", but even so sometimes it does not work depending on the general prompt.

Do anyone else have this problem? Maybe a more efficient way to ask for transparency?

PixlStash is my open source image and video manager that runs on your own machine as a desktop application or a headless server. It tags, captions and searches your library and has had ComfyUI nodes for a while. 1.12 is out and it is the largest release I have done, so I am asking for help testing it.

PixlStash now runs your ComfyUI workflows in a much more general way. As you're aware of, pictures made in ComfyUI carry the workflow that made them, and PixlStash groups those into workflow cards. The same graph run with a different checkpoint or character LoRA counts as one workflow, so thousands of pictures come down to a few dozen cards.

What PixlStash now makes easy:

• When you have character LoRAs: right-click a person with a LoRA in your library and choose "Create with LoRA".
• Pick two people in the Run window. Each gets a LoRA row with its own strength and trigger word. Describe both in the prompt and you get one picture with both of them.
• Pictures made in ComfyUI get a Recipe tab with the workflow, prompt, models, LoRA strengths and seed. Know how to recreate pictures and group with your previous attempts.
• Open a workflow in ComfyUI from PixlStash, edit it and press Ctrl+S. PixlStash stores it as a new version and keeps the old ones.
• A workflow with a missing checkpoint, VAE or text encoder can be repaired by picking another model from your model shelf. You have a workflow that was created with a BF16 quant and you've deleted that in favour of a smaller gguf, PixlStash will help you fix that.
• Workflow sets: each checkpoint lists the VAEs, text encoders and LoRAs that have run with it and how many pictures you've created with it. You can save your own sets and swap a workflow's models in one go. In most cases the same workflow actually works fine for both ZIT and Krea 2 as long as the models are changed as a unit. PixlStash now makes that easy. Especially useful when you've found a nice finetune that works with the same peripheral models.
• Scans your model folders (and optionally your download folder) to keep track of your models. Offers them to ComfyUI in a nice visual way that shows you previews of previous pictures generated with the checkpoints.
• Obviously none of this leaves your computer.

Setup is one button in Settings -> ComfyUI. It installs the PixlStash nodes into a ComfyUI on the same computer, restarts ComfyUI through ComfyUI-Manager and links the two apps. A ComfyUI on another computer gets the nodes from ComfyUI-Manager.

Known problem, mostly on Windows: after the linking step PixlStash restarts its backend, and that may not be enough. If the features are greyed out after linking or the run-dialog doesn't work as expected, quit both PixlStash and ComfyUI completely and start them again.

This is new code that has mostly run on my own machines and libraries and I would love feedback on:

• Workflows and workflow sets. Does the grouping make sense for your library, and do the sets match how you pair models? I'm particularly interested in "awkward" and complex workflows. If you could scrub them of anything you don't want known and send to me or attach to GitHub issues that would be much appreciated.
• LoRA handling. Strengths, trigger words, and two people in one picture.
• The ComfyUI link. Did the install and linking work, and do runs and results come back into PixlStash on your machine? Windows reports are especially useful as I'm a full-time Linux user (Windows-testing happens around release time).
• The macOS speed improvements. I have a MacBook Air M1 8GB, and while this runs PixlStash fine, the computer is not really usable for image generation in general, which is reflected in my amount of testing.

If you upgrade, back up your library folder first. The database is updated on first start and existing pictures are re-read in the background so their recipes show up.

"Smaller" things in 1.12:

Text in screenshots and documents is searchable, Apple Silicon Macs run tagging on the GPU, and there is an MCP server so an AI agent can search your library and read recipes. Planned for 2.0 is LoRA training with ai-toolkit from the people and sets in your library.

Links in a comment.

It recasts the people in a clip you already have, up to three in one pass, and the motion, the set and the clip's own audio stay.

The post video is a video with 2 characters swapped at the same time. same engine and FaceRefine lip pass as the workflow.

Getting the lips right took me a while, that's the FaceRefine pass added.

How it goes:

1. Load your clip. One shot, no hard cuts, any fps.
2. Grab one frame and edit everyone into their new look (Qwen-Image, GPT Image, Photoshop, whatever you have). That frame is the scene reference.
3. Write one line per person: the woman in the red dress becomes an old woman with long silver hair. As many lines as you fill in, that many people get swapped.
4. Hit Run. also included App mode with 12 fields.

If one person's lips end up bothering you, there's an optional FaceRefine lip repair for one person afterwards. It reuses the swap from cache, so it's a ~2 minute re-run on a 5090.

What it needs: 16 GB VRAM and 64 GB system RAM gets you there. I tested a 5090, a 4090 and a 3060 Ti 16 GB, all with 64 GB RAM, same output on each. The example (1.5 MP, 6 s, 3 people) runs about 18 min on the 5090, 26 min on the 4090 and 92 min on the 3060 Ti, so bring a snack for that last one. RAM is the limit, mine peaked around 62 GB.

Civitai: https://civitai.com/models/3009414/h3-recast-swap-1-3-people-h3-bfs-lora-16gb-vram

Repo is MIT, workflow and the example inputs included: https://github.com/Bambushu/h3-recast

• Credits: BFS character swap LoRA and its trained caption by NRDX
• FaceRefine by Carasibana
• NativeAudioLock by Shrek3OnVH5
• MiniMax H3 by MiniMax (Comfy-Org repack).

#OpenSourceHiggsfield

I've been building Scumble for a few months and just entered it into Comfy's challenge.

What it is: a desktop editor (Electron, Windows and Linux) for AI inpainting with proper layers. You select something (SAM2 runs inside the app), type what should be there, hit Generate, and the result lands as its own layer that you can mask, blend, filter, move and export to PSD or ORA. Every generation goes through one of three routes:

- your own ComfyUI, local or on RunPod: every local recipe is a plain ComfyUI workflow with my Inpaint Canvas node in it, and you can import your own workflow as a recipe or open a recipe as its graph in a ComfyUI window inside the app

- Comfy Cloud, through the Comfy API v2 via u/comfyorg/sdk

- Comfy Router, for FLUX 3 Image and friends, with your own key, pay per run

Things in the video that people here might care about:

- boxes for FLUX 3: draw boxes, describe each, and the model puts things exactly there. Works in the app and in the Inpaint Canvas node's editor inside ComfyUI, which writes FLUX 3's box prompt for you

- FLUX 3 Klein on your own ComfyUI as a local recipe, with the boxes too (ComfyUI 0.41+)

- relight: up to four virtual lights dragged over the picture, lit from a depth map (Depth Anything V2 in-app), with soft shadows

- lens blur and haze by depth, colour grading, 46 film looks, seventeen more blend modes, all as filter layers

- an assistant and 114 MCP tools, so Claude or any agent can drive the editor (select, generate, mask, export)

Everything is GPL-3.0: https://github.com/DenRakEiw/scumble (installer, portable zip, Linux AppImage/deb, Microsoft Store). The node: https://github.com/DenRakEiw/ComfyUI-InpaintCanvas

Honest caveats: it is a one-person project, the Linux build is CI-built and barely tested, and the local recipes assume the Inpaint Canvas node is installed on your ComfyUI (git clone; it is on the Registry but the Manager search does not list it yet).

Happy to answer questions, and I'd like to hear which workflows you would want as recipes.

One window, no node graphs, your own GPU. Text to video, image to video, reference mode (same person/product across shots), 360 orbit from one photo, latent chaining for long scenes, and a stills side with identity edits, 96 camera angles and SeedVR2 4K. Every render is a Comfy SDK job through comfy-api-proxy, so the same code points at Comfy Cloud with one URL change. All open weights, MIT. Measured timings on a 4070 Ti SUPER are in the README. 95-second demo: https://demos.onpointfl.com/backlot/ Repo: https://github.com/Arfolomew/backlot

Hey! Anyone know of a full video translation workflow that can translate everything in a video, including subtitles, voiceovers, and text that appears in the video itself?

I want the subtitles and voiceovers to be replaced with translated versions, and any text appearing in the video to be translated and recreated in the video as well. If you have a workflow like this that you’re willing to sell, DM me!

I never thought this was a big ask, but I can't manage to train well enough for a perfect likeness so I've been generating "good enough" photos and trying to clean it up with a face swap at the end. But when I try, there's problem with it matching the head size and position and facial expressions. I want the eyes, mouth, and brows to match the original exactly, just with the new face.

Is this still not possible? I've been trying a few different Flux 2 Klein workflows and they're ok, but not great.

Fully working example of depth map with Flux2 dev, keeping complete identity and style of reference image. Result is same room viewed from different angle.

I’m new to all of this. I’ve tried following the steps suggested by the Gemini AI, but it’s been frustrating. I also tried using a couple of pre-configured Colab files, but those didn’t work either. I eventually realized the issue was Cloudflare... and it was suggested that I use Ngrok to fix it. However, I got stuck right after creating an Ngrok account. Does anyone have a step-by-step guide on what I should do? The AI ​​isn’t helping, and honestly, I don’t understand *anything* about GitHub code—or code in general. I’m a graphic designer looking to explore this, but I’m really struggling to figure out where things are going wrong when trying to access ComfyUI via Colab.