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comfy-ui

comfy-ui

Use ComfyUI as a modular AI content-creation engine: launch and automate the server, submit API workflows, validate graph JSON, author custom nodes, and configure model paths/backends.

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill 문서

GitHub

name: comfy-ui description: "Use ComfyUI as a modular AI content-creation engine: launch and automate the server, submit API workflows, validate graph JSON, author custom nodes, and configure model paths/backends." disable-model-invocation: true metadata: disco-role: operating license: GPL 3.0

ComfyUI

Use this repo skill when a user asks for help with ComfyUI workflows, automation, server/API usage, custom nodes, model folder configuration, backend/memory flags, or prompt graph debugging.

ComfyUI is a node-graph AI creation engine for image, video, audio, 3D, and model-tooling workflows. Treat it as an application/runtime with a Python launch script, HTTP/websocket APIs, a node registry, JSON prompt graphs, model-folder conventions, optional hosted API nodes, and hardware-sensitive backend behavior.

Start Here

  1. Identify the task surface: server/API automation, prompt graph execution, node authoring, or model/backend setup.
  2. If the user has a workflow JSON, decide whether it is API prompt JSON or UI workflow JSON before sending it to /prompt.
  3. If the user has a model-loading error, separate graph-node input issues from model search path/backend issues.
  4. If the user has a custom node problem, inspect mappings and node schemas before debugging prompt execution.
  5. If the user is exposing a server, make network, CORS, TLS, credential, and API-node choices explicit.

Routes

  • sub-skills/server-api/: launch ComfyUI, choose server-facing CLI flags, queue API prompt JSON over HTTP, monitor websocket progress, fetch history/output files, use app/user/model/assets routes, and troubleshoot server/API failures.
  • sub-skills/workflow-execution/: validate and debug API prompt JSON, distinguish UI workflow exports from executable prompts, reason about graph links, caching, async/lazy execution, blueprints/templates, and inference failure boundaries.
  • sub-skills/custom-nodes/: implement, scaffold, inspect, and troubleshoot custom nodes using classic INPUT_TYPES classes, NODE_CLASS_MAPPINGS, hidden inputs, async validation, public comfy_api APIs, and API-provider nodes.
  • sub-skills/models-config/: configure model folders and extra_model_paths.yaml, understand checkpoint/LoRA/VAE/controlnet categories, choose backend/VRAM flags, diagnose missing models, and reason about supported model families/quantization.

Common Decisions

  • Launching locally: start local-only unless remote access is required: python main.py --listen 127.0.0.1 --port 8188.
  • Submitting workflows: use API-format prompt JSON for /prompt; normal UI workflow JSON contains canvas metadata and must be exported/converted first.
  • Getting outputs: queue with /prompt, wait on /ws or poll /history/{prompt_id}, then download file outputs with /view using exact history metadata.
  • Using API nodes: pass hosted Comfy API credentials through request extra_data or hidden node credentials; never hardcode API keys in workflow JSON or scripts.
  • Model placement: put each model file in the category its loader node searches, or register shared paths through extra_model_paths.yaml.
  • Backend failures: simplify to explicit CPU/CUDA/ROCm/MPS/DirectML flags, disable custom/API nodes while isolating startup failures, then re-enable pieces gradually.

Bundled References

  • references/troubleshooting.md covers cross-cutting install/import, launch, prompt, custom-node, model-path, backend, credential, and security failures.
  • references/repo-provenance.md records the source snapshot and evidence paths used to create this skill for future staleness checks.

Bundled Scripts

Most reusable scripts are owned by sub-skills because they operate on a specific surface:

  • sub-skills/server-api/scripts/comfy_api_client.py: validate, queue, wait for history, and download outputs through REST.
  • sub-skills/server-api/scripts/comfy_websocket_monitor.py: queue and monitor websocket progress while ignoring binary preview frames by default.
  • sub-skills/workflow-execution/scripts/validate_prompt_graph.py: structurally validate API prompt JSON without importing ComfyUI or loading models.
  • sub-skills/custom-nodes/scripts/scaffold_custom_node.py: generate a safe starter custom node package.
  • sub-skills/custom-nodes/scripts/inspect_node_definitions.py: statically inspect classic node mappings and common schema mistakes.
  • sub-skills/models-config/scripts/validate_extra_model_paths.py: validate extra_model_paths.yaml shape and referenced directories.

Safety Notes

  • Do not expose ComfyUI on a public interface with permissive CORS and no external authentication boundary.
  • Do not run untrusted custom nodes or hosted API-node workflows without reviewing network, credential, and filesystem effects.
  • Do not assume a workflow that validates structurally can execute: model files, node registry contents, optional dependencies, credentials, and backend hardware still matter.
  • Do not embed local paths, API keys, generated output paths, or private server URLs in reusable workflows or scripts.
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