comfy-resolve 0.1.0

ComfyUI Workflow Dependency Resolver — automatically find and download every model a workflow needs

comfy-resolve

A CLI dependency manager for ComfyUI workflows.

ComfyUI workflow files reference models by filename only — no URLs, no sources. comfy-resolve fills that gap: it parses your workflow, hunts down every referenced model on HuggingFace and Civitai, and downloads them to the right folders in your ComfyUI install.

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Installation

pip install comfy-resolve

Or with pipx (keeps it isolated, recommended):

pipx install comfy-resolve

Requires Python 3.10+

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Quick Start

Resolve a specific workflow

comfy-resolve resolve my_workflow.json

Pick from your ComfyUI workflows folder

Run with no arguments and comfy-resolve will scan your ComfyUI install for workflows and let you pick:

comfy-resolve resolve

── Select a Workflow ─────────────────────────────────────
  #  Filename                    Size
  1  flux_portrait.json         12.4 KB
  2  sdxl_upscale.json           8.1 KB
  3  ltx2_inpaint.json         142.5 KB

Found 3 workflow(s) in C:\ComfyUI\user\default\workflows

Enter a number, a file path, or blank to abort.
Workflow:

First run

The first time you run any command, you'll be asked for your ComfyUI installation path. Everything else is inferred automatically:

Welcome to comfy-resolve!
ComfyUI installation directory: C:/programs/ComfyUI
✓ Config written to ~/.config/comfy-resolve/config.toml

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How it works

Resolution pipeline

For each asset in the workflow, comfy-resolve tries these steps in order, stopping at the first hit:

1. Local filesystem — scans your ComfyUI model directories for exact or fuzzy matches
2. Cache — previously confirmed resolutions are reused
3. Config mappings — static overrides you define in the config file
4. HuggingFace — queries the HF Hub API
5. Civitai — queries the Civitai API (public search, no token needed to find; token needed to download)
6. Heuristic match — fuzzy filename normalisation as a last resort

Confidence levels

Level	Meaning
✓ HIGH	Exact filename match from local filesystem, cache, or known repo
? MEDIUM	Fuzzy match above ~80% similarity
! LOW	Heuristic guess — probably right, worth reviewing
✗ UNKNOWN	No match found

Interactive review

After resolution, every asset is shown in a numbered table sorted worst-first. You can jump to any row by number — including HIGH confidence ones — to edit the source, change the download destination, or skip it entirely:

── Asset Resolution Review ──────────────────────────────────────────
 #  Asset                          Type    Source              Conf
 1  missing_model.safetensors      loras   UNRESOLVED          ✗ UNKNOWN
 2  some_lora_v1.safetensors       loras   Civitai: civ:12345  ! LOW
 3  clip_l.safetensors             text    HuggingFace: ...    ✓ HIGH
...

<number> edit  •  accept proceed as-is  •  skip all unknown/low  •  quit

Pre-download review

Before any file is written to disk you get a final review with destinations shown, bulk actions, and per-asset overrides:

── Pre-Download Review ──────────────────────────────────────────────
 #  Asset                   Source                  Size    Dest        Action
 1  clip_l.safetensors      HuggingFace: comfy/...  246 MB  .../text_e  download
 2  my_lora.safetensors     Civitai: civ:99999      384 MB  .../loras   download
 3  local_model.safetensors Local: .../checkpoints  6.9 GB  —           already local

go  •  <number> edit  •  all bulk action  •  quit

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API keys

comfy-resolve works without any API keys for most public models. Keys unlock additional access:

Key	Where to get it	What it unlocks
HuggingFace	huggingface.co/settings/tokens	Gated / private models
Civitai	civitai.com/user/account	Downloading from Civitai (searching is free)

Set via environment variable (recommended):

# Linux / Mac
export COMFY_HF_TOKEN="hf_..."
export COMFY_CIVITAI_TOKEN="..."

# Windows PowerShell
$env:COMFY_HF_TOKEN="hf_..."
$env:COMFY_CIVITAI_TOKEN="..."

Or directly in the config file:

[api_keys]
huggingface = "hf_..."
civitai = "..."

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Configuration

Location:

• Linux / Mac: ~/.config/comfy-resolve/config.toml
• Windows: C:\Users\<you>\.config\comfy-resolve\config.toml

comfyui_dir = "C:/programs/ComfyUI"

# Model paths are inferred from comfyui_dir automatically.
# Uncomment any line to override a specific path:
# [paths]
# checkpoints   = "D:/models/checkpoints"
# loras         = "D:/models/loras"
# vae           = "D:/models/vae"
# text_encoders = "D:/models/text_encoders"
# unet          = "D:/models/unet"

[api_keys]
huggingface = ""
civitai = ""

[download]
concurrent = 2      # parallel downloads
max_retries = 3

[resolution]
preferred_source = "huggingface"    # "huggingface" | "civitai" | "any"
auto_confidence_threshold = "high"  # used with --auto

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Commands

resolve

comfy-resolve resolve [WORKFLOW] [OPTIONS]

Option	Description
--auto	Skip interactive prompts; use HIGH confidence resolutions only
--auto-all	Skip prompts; use all resolutions regardless of confidence
--dry-run	Show what would be downloaded without downloading anything
--no-cache	Ignore cached mappings and re-resolve everything fresh
--download-dir PATH	Override destination directory for all asset types
--concurrent N	Number of parallel downloads (1–16)
--verbose / -v	Show debug logs

cache-list

comfy-resolve cache-list

Show all cached asset→source mappings.

cache-clear

comfy-resolve cache-clear [NAME]

Remove a specific cached mapping by filename, or all mappings if no name is given.

config-show

comfy-resolve config-show

Print the active config with API keys redacted.

config-init

comfy-resolve config-init

Re-run the first-time setup wizard.

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Supported asset types

Type	Folder	Extensions
Checkpoints	models/checkpoints	.safetensors, .ckpt
LoRAs	models/loras	.safetensors, .pt
VAE	models/vae	.safetensors, .pt
Text encoders / CLIP	models/text_encoders	.safetensors, .gguf
UNet / diffusion models	models/unet	.safetensors, .gguf
ControlNet	models/controlnet	.safetensors, .pth
Upscale models	models/upscale_models	.pth, .pt
Embeddings	models/embeddings	.pt, .bin
IP-Adapter	models/ipadapter	.safetensors, .bin
GGUF quantized models	models/unet or models/text_encoders	.gguf

GGUF routing is automatic: diffusion model GGUFs go to unet, text encoder GGUFs (T5, CLIP, Gemma, LLaMA, Qwen VL) go to text_encoders.

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Download features

• Concurrent downloads — configurable parallel transfers
• Resume support — picks up where it left off after interruption (Ctrl+C cleans up partial files)
• Integrity verification — SHA-256 checked when available; mismatches warn but never silently delete
• Disk space check — warns before starting if space is tight
• Smart skipping — files already present locally are never re-downloaded

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Troubleshooting

"Gated model / access denied" Visit the model page on HuggingFace and request access, then retry.

"Civitai token required to download" Searching Civitai is free, but downloading requires a token. Set COMFY_CIVITAI_TOKEN or add it to the config.

SHA-256 mismatch warning The downloaded file's hash doesn't match what was expected — usually because the repo updated the file without renaming it. The file is kept (not deleted). Run comfy-resolve cache-clear model.safetensors then re-resolve with --no-cache if you want to try again.

Downloads are slow

comfy-resolve resolve workflow.json --concurrent 4

Wrong model folder Override per-session with --download-dir, or set permanent path overrides in the [paths] section of the config.

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Development

git clone https://github.com/YOUR_USERNAME/comfy-resolve.git
cd comfy-resolve
python -m venv .venv
.venv\Scripts\activate      # Windows
source .venv/bin/activate   # Linux / Mac
pip install -e .

# Run tests
pytest tests/ -v

# Type check
mypy comfy_resolve/

# Lint
ruff check comfy_resolve/

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License

MIT — see LICENSE for details.

Contributing

Issues and PRs welcome. The most useful contributions right now are additional node type mappings for custom node packs — if you find a node whose assets resolve to the wrong folder, open an issue with the node name and expected folder.

Acknowledgements

Built for the ComfyUI community. Uses the HuggingFace Hub and Civitai APIs.