Overview
ComfyUI-Copilot is an AIGC assistant that installs into ComfyUI as a custom node, built by Alibaba International Digital Commerce. ComfyUI's node graph is powerful but tedious to assemble by hand, and most of the friction is in three places: getting a first working graph, understanding why a graph errors, and finding good parameter values. Copilot targets all three from a chat panel inside the ComfyUI interface itself, so you never leave the canvas you are working on.
Version 2.0 reframed the tool from a helper into what the project calls a workflow development coworker, covering the whole lifecycle — generation, debugging, rewriting and parameter tuning. Ask for a workflow in plain language and it returns several candidates: high-quality graphs from its library plus one generated for your request, importable to the canvas in a click. Click Debug on a canvas and it analyses errors, pinpoints bad parameters and broken connections, suggests repairs, and prompts you to download any model it identifies as missing. Describe what you disliked about a result and it will rewrite the graph — adjusting parameters, adding nodes and reworking the logic. The agent is aware of your local ComfyUI environment, so its suggestions reflect what you actually have installed.
Parameter tuning gets its own tool: set ranges for the parameters you care about and it batch-executes the combinations, then lays the outputs out as a visual comparison so you can pick the best configuration by eye. The project is MIT-licensed and carries an ACL 2025 demo paper. Note one operational detail from the maintainers: the hosted API service behind node-information queries, job recommendations and workflow generation has been suspended, so you now supply your own API key and base URL on the Settings page; the agent capabilities are unaffected.
What it does
- Generate a first-draft workflow from a text description, returning library graphs plus an AI-generated one, each importable to the canvas in one click
- One-click debug that analyses canvas errors, identifies bad parameters and broken connections, and offers repair suggestions
- Missing-model detection with a prompt to download, plus a keyword-search model downloader
- Workflow rewriting — describe what you want changed and it adjusts parameters, adds nodes and reworks the graph's logic
- Parameter tuning by batch execution over ranges you set, with visual side-by-side comparison of the results
- Environment-aware agent that takes your local ComfyUI installation into account when proposing solutions
Getting started
Copilot is a ComfyUI custom node. Install it into `custom_nodes`, install its Python dependencies, then activate it from the ComfyUI panel and point it at a model. The maintainers recommend the git install over ComfyUI Manager, which they note is more error-prone.
Clone into ComfyUI's custom_nodes directory
Install it alongside your other ComfyUI extensions.
cd ComfyUI/custom_nodes
git clone https://github.com/AIDC-AI/ComfyUI-CopilotInstall its dependencies
Run pip against the extension's requirements file.
cd ComfyUI/custom_nodes/ComfyUI-Copilot
pip install -r requirements.txtOn Windows, use the embedded Python
Portable ComfyUI builds ship their own interpreter — install into that one rather than a system Python.
python_embeded\python.exe -m pip install -r ComfyUI\custom_nodes\ComfyUI-Copilot\requirements.txtActivate and configure a model
Start ComfyUI and click the Copilot activation button on the left of the panel to launch its service. Then open settings and configure the chat model and the workflow-generation model separately — you supply your own API key and base URL (OpenAI-compatible endpoints and LM Studio both work). Keep the extension updated with `git pull` or the Manager's Update button to pick up new features.
Commands and code are distilled from the project's own documentation — always check the official repo for the latest.
When to use it
- Get a working first-draft ComfyUI graph for an unfamiliar task instead of assembling nodes from scratch
- Diagnose a red, failing canvas without reading the console — including finding which model you are missing
- Iterate on a result you were not happy with by describing the change rather than rewiring nodes by hand
- Find good sampler, step or CFG values by sweeping ranges and comparing the outputs side by side
How ComfyUI-Copilot compares
ComfyUI-Copilot alongside other open-source image generation tools AI/TLDR tracks, ranked by GitHub stars.
| Tool | Stars | What it does |
|---|---|---|
| Stable Diffusion web UI (AUTOMATIC1111) | ★ 165k | A browser interface for running Stable Diffusion image generation locally with extensions and fine-grained controls. |
| ComfyUI | ★ 134k | A node-based visual editor for building and running image and video generation pipelines like Stable Diffusion and FLUX locally. |
| Fooocus | ★ 53.1k | A simplified image generation app built on Stable Diffusion that hides technical settings for easy prompting. |
| InvokeAI | ★ 28.2k | A self-hosted creative tool and canvas for generating and editing images with open diffusion models. |
| Stability-AI generative-models | ★ 27.3k | Stability AI's official code for its Stable Diffusion family of image and video generation models. |
| FLUX | ★ 26k | Black Forest Labs' open-weight diffusion models and inference code for generating and editing images from text prompts. |
| Z-Image | ★ 12k | Alibaba Tongyi's 6B-parameter open image model that produces photorealistic images quickly on a single GPU. |
| ComfyUI-Copilot | ★ 5.5k | An assistant inside ComfyUI that builds, debugs and rewrites your generation graphs |