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comfyui

Generate images, video, and audio by running ComfyUI workflows via REST and WebSocket APIs.

Updated Jun 5, 2026
Search Tags:#workflow automation#image generation#video generation#flux#comfyui#stable diffusion#comfy-cli
One-click install
npx skills add https://github.com/xu1713/openhorse --skill comfyui-xu1713
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: comfyui
Source: https://github.com/xu1713/openhorse/tree/main/openhorse/openhorse/skills/creative/comfyui
Command: npx skills add https://github.com/xu1713/openhorse --skill comfyui-xu1713

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires comfy-cli, requests, websocket-client, and includes scripts (resource) and references (resource) components.

What problem does it solve? Running generative AI workflows in ComfyUI requires juggling installation, GPU compatibility, custom nodes, model downloads, and a low-level REST/WebSocket API. This Skill automates the full lifecycle — from hardware checks and setup to parameter injection, execution, monitoring, and output download — so you can generate media without manual server wrangling. ## Core Features & Use Cases - Automated Setup & Health Checks: Detect GPU/VRAM, choose local vs Comfy Cloud, install via comfy-cli, and verify with a one-line health check. - Workflow Execution with Parameter Injection: Run any API-format workflow JSON with custom prompts, seeds, and settings; supports img2img, inpainting, batch sweeps, and real-time WebSocket progress. - Dependency Management: Inspect workflows for required nodes, models, and embeddings, then auto-install missing pieces with comfy-cli. - Use Case: Ask to generate 8 variations of an SDXL image with random seeds — the Skill checks dependencies, submits the batch in parallel, and downloads every output to your chosen folder. ## Quick Start Ask the assistant to generate an image with a prompt like "a sunset over mountains" using the SDXL workflow, and it will check the server, inject your parameters, run the workflow, and return the output files.

Frequently Asked Questions about comfyui

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I run a ComfyUI workflow from the command line?▼

Use run_workflow.py with an API-format workflow JSON and a JSON args string for parameters like prompt, seed, and steps. The script submits the job to the server, monitors execution, and downloads outputs to your chosen directory.

How do I generate images with ComfyUI in the cloud without a GPU?▼

Sign up at comfy.org/cloud, generate an API key at platform.comfy.org, and set the COMFY_CLOUD_API_KEY environment variable. Then run workflows with --host https://cloud.comfy.org; note that running workflows via API requires a paid subscription.

What hardware do I need to run ComfyUI locally?▼

Local ComfyUI needs an NVIDIA GPU with at least 6 GB VRAM (8 GB for SDXL, 12 GB or more for Flux and video), an AMD GPU with ROCm on Linux, or an Apple Silicon Mac with at least 16 GB unified memory. The hardware_check.py script probes your machine and recommends local versus cloud.

Why does my ComfyUI workflow fail with class_type not found?▼

This error means a required custom node is not installed on the server. Run check_deps.py against the workflow to identify missing nodes and get the exact comfy node install command, or use auto_fix_deps.py to install them automatically.

Can I use img2img or inpainting with ComfyUI workflows?▼

Yes, pass --input-image to run_workflow.py to upload an image and inject it into the workflow automatically. For inpainting, supply both an image and a mask, where white mask pixels mark regions to regenerate.

What is the difference between editor format and API format workflows?▼

API format workflows have top-level node IDs with class_type fields and are directly executable via the REST API. Editor format contains nodes and links arrays for the visual UI and must be re-exported from ComfyUI using Workflow → Export (API) before scripts can run it.

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