ComfyUI was released on GitHub in January 2023. According to comfyanonymous, the creator, a major goal of the project was to improve on existing software designs in terms of the user interface.[3] The creator had been involved with Stability AI but by 3 June 2024 that involvement had ended and an organization called Comfy Org had been created along with the core developers.[4] In July 2024, Nvidia announced support for ComfyUI within its RTX Remixmodding software.[5] In August 2024, support was added for the Flux diffusion model developed by Black Forest Labs and Comfy Org joined the Open Model Initiative created by the Linux Foundation.[6][7] As of November 2024, the project has 58.6k stars on GitHub.[8]
Features
ComfyUI's main feature is that it is node based.[9][10] Each node has a function such as "load a model" or "write a prompt".[11] The nodes are connected to form a control-flow graph called a workflow.[12] When a prompt is queued, a highlighted frame appears around the currently executing node, starting from "load checkpoint" and ending with the final image and its save location.[11] Workflows commonly consist of tens of nodes, forming a complex directed acyclic graph.[12] Node types include loading a model, specifying prompts, samplers, VAE decoders, face restoration and upscaling models, LoRAs, embeddings, and ControlNets.[13] Workflows can be saved to a file, allowing users to re-use node workflows and share them with other users.[13][14][15] The file format for the workflows is in JSON and can be embedded in the generated images.[16] Users have also created custom extensions to the base system which are exposed as new nodes,[13][17] such as the extension for AnimateDiff, which aims to create videos.[18][19]ComfyUI has been described as more complex compared to other diffusion UIs such as Automatic1111.[20][21] A default node group is also included with the program.[11]
LLMVision extension compromise
In June 2024, a hacker group called "Nullbulge" compromised an extension of ComfyUI to add malicious code to it.[22] The compromised extension, called ComfyUI_LLMVISION, was used for integrating the interface with AI language models GPT-4 and Claude 3, and was hosted on GitHub. Nullbulge hosted a list of hundreds of ComfyUI users' login details across multiple services on its website, while users of the extension reported receiving numerous login notifications. vpnMentor conducted security research on the extension and claimed it could "steal crypto wallets, screenshot the user’s screen, expose device information and IP addresses, and steal files that contain certain keywords or extensions".
Nullbulge's website claims they targeted users who committed "one of our sins", which included AI-art generation, art theft, promoting cryptocurrency, and any other kind of theft from artists such as from Patreon. They claimed that they were "a collective of individuals who believe in the importance of protecting artists' rights and ensuring fair compensation for their work" and that they believed that "AI-generated artwork is detrimental to the creative industry and should be discouraged".[22]
^comfyanonymous. "ComfyUI". github. Retrieved 10 July 2024.
^Zhu, Andrew (2024). Using Stable Diffusion with Python: Leverage Python to control and automate high-quality AI image generation using Stable Diffusion. Packt Publishing. ISBN978-1835084311. ComfyUI is a node-based UI that utilizes Stable Diffusion. It allows users to construct tailored workflows, including image post-processing and conversions. It is a potent and adaptable graphical user interface for Stable Diffusion, characterized by its node-based design.
^ abXue, Xiangyuan; Lu, Zeyu; Huang, Di; Ouyang, Wanli; Bai, Lei (2 Sep 2024). "GenAgent: Build Collaborative AI Systems with Automated Workflow Generation -- Case Studies on ComfyUI". arXiv:2409.01392 [cs.CL].
^ abcGal, Rinon; Haviv, Adi; Alaluf, Yuval; Bermano, Amit H.; Cohen-Or, Daniel; Chechik, Gal (2024). "ComfyGen: Prompt-Adaptive Workflows for Text-to-Image Generation". arXiv:2410.01731 [cs.CL].
^Phoenix, James; Taylor, Mike (2024). "AUTOMATIC1111 Web User Interface". Prompt engineering for generative AI: future-proof inputs for reliable AI outputs at scale (First ed.). Beijing Boston: O'Reilly. ISBN978-1098153434. Advanced users may also want to explore ComfyUI, as it supports more advanced workflows and increased flexibility (including image-to-video), but we deemed this too complex for the majority of use cases, which can easily be handled by AUTOMATIC1111.
^Pérez-Colado, Iván J.; Freire-Morán, Manuel; Calvo-Morata, Antonio; Pérez-Colado, Víctor M.; Fernández-Manjón, Baltasar (8 May 2024). "AI Asyet Another Tool in Undergraduate Student Projects: Preliminary Results". 2024 IEEE Global Engineering Education Conference (EDUCON). pp. 1–7. doi:10.1109/EDUCON60312.2024.10578883. ISBN979-8-3503-9402-3.