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comfy-org/comfyui

111,631PythonAudience · vibe coderComplexity · 3/5ActiveLicenseSetup · hard

tl;dr

Visual node-based interface for building custom AI generation workflows with images, video, audio, and 3D models. Connect nodes to control every step of the generation process.

vibe map

mindmap
  root((ComfyUI))
    What it does
      Node-based workflows
      Image generation
      Video and audio
      3D content
    Models supported
      Diffusion models
      LoRAs and embeddings
      ControlNets
      Upscalers
    Tech stack
      Python
      PyTorch
      GPU support
    Use cases
      Custom pipelines
      Batch processing
      Production setups
      API integration
    Hardware
      NVIDIA GPUs
      AMD and Intel
      Apple Silicon
      CPU-only mode
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Code map

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what people make with this

VIBE 1

Build multi-step image generation workflows by connecting nodes for prompts, models, sampling, and post-processing.

VIBE 2

Create video generation pipelines that combine image models with temporal processing and upscaling.

VIBE 3

Run batch jobs to generate hundreds of variations with different parameters without manual intervention.

VIBE 4

Expose custom AI workflows through an API for integration into production applications or web services.

stack

PythonPyTorchNVIDIA CUDAAMD ROCmIntel ArcApple Metal

setup vibes

Difficulty · hard time til it works · 1day+

Requires GPU drivers (CUDA/ROCm/Metal), PyTorch compilation, and likely model downloads, multi-platform GPU support adds complexity.

Use it freely, but any project you distribute that includes this code must also be GPL-licensed and open source.

in plain english

ComfyUI is a desktop and cloud application for generating images, videos, 3D models, and audio using AI diffusion models. The README describes it as the most powerful and modular AI engine for content creation, aimed at visual professionals who want fine-grained control over every model and parameter. Instead of typing a prompt into a single box, users build a flowchart on a canvas where each box, called a node, performs one step, loading a model, applying a prompt, sampling an image, upscaling it, masking an area, and so on, and wires connect the outputs of one node into the inputs of the next. This node-graph approach lets people experiment with and reuse complicated pipelines without writing code, and the same graph can be shared by saving it as a JSON file or even by exporting the workflow embedded inside a generated PNG, WebP, or FLAC file. ComfyUI natively supports a long list of open-source models for images, image editing, video, audio, and 3D, listed in the README, and it can also call paid closed-source models through optional API nodes. The README highlights smart memory management that can run large models on GPUs with as little as 1 GB of video memory by offloading, support for running on CPU when no GPU is available, an asynchronous queue, and the ability to expose a finished workflow as a simple app via App Mode. Someone would use ComfyUI when they want repeatable, controllable generative workflows for production work, rather than one-off prompts in a hosted chat product. It runs on Windows, Linux, and macOS, with NVIDIA, AMD, Intel, Apple Silicon, and Ascend GPUs, and is written in Python on PyTorch.

prompts (copy fr)

prompt 1
Show me how to set up a basic ComfyUI workflow that loads a Stable Diffusion model, takes a text prompt, and saves the generated image.
prompt 2
How do I create a ComfyUI workflow that uses ControlNet to guide image generation with a sketch or pose?
prompt 3
Walk me through building a ComfyUI pipeline that generates an image, upscales it, and applies inpainting to refine specific areas.
prompt 4
How can I expose a ComfyUI workflow as an API endpoint so other applications can trigger generations?
prompt 5
What's the best way to optimize a ComfyUI workflow to run on a GPU with limited VRAM?
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