comfy-nodekit 0.2.1

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Comfy Nodekit

Utilities for working with ComfyUI node graphs from Python. The project provides typed wrappers around ComfyUI nodes, lightweight graph primitives, and helpers for exporting a workflow back to the JSON format that the ComfyUI API expects.

• Typed Node and Edge models (Pydantic) for tracking dependencies and serialising graphs.
• A generated nodes.py module that mirrors the ComfyUI node catalogue with Python callables.
• Tooling (nodes_to_py.py) to regenerate those bindings directly from a running ComfyUI server.
• Example workflow builder scaffolding that shows how to stitch nodes into higher-level pipelines.

Requirements

• Python 3.12+
• requests and pydantic (installed automatically when the package is installed)
• Access to a running ComfyUI server when regenerating node bindings

Installation

uv add comfy_nodekit
# pip install comfy_nodekit

Generate node bindings (required before usage)

Before using the factory functions, generate nodes.py from your running ComfyUI:

uv run python -m comfy_nodekit.nodes_to_py http://127.0.0.1:8188/
# or: just run

If you omit the URL, it defaults to http://127.0.0.1:8188/. This writes nodes.py based on the server's /object_info. Re-run whenever your ComfyUI nodes change.

You can also generate from a local JSON schema (previously fetched from /object_info):

# From default server (same as before)
uv run python -m comfy_nodekit.nodes_to_py

# From a specific server and write to a custom path
uv run python -m comfy_nodekit.nodes_to_py http://127.0.0.1:8188/ ./nodes.py

# From a local JSON file and write to a custom path
uv run python -m comfy_nodekit.nodes_to_py ./object_info.json ./nodes.py

Usage

Create nodes the same way you would wire a ComfyUI graph. Each factory function from nodes.py returns a typed Edge that keeps track of its originating node. When you are ready to export the workflow, grab the source_node of your terminal edge and call build_json_workflow().

from comfy_nodekit.models import Edge
from comfy_nodekit.nodes import (
    CheckpointLoaderSimple,
    CLIPTextEncode,
    EmptyLatentImage,
    KSampler,
    VAEDecode,
)

# Load base models
model, clip, vae = CheckpointLoaderSimple("juggernautXL_v9Rdphoto2Lightning.safetensors")

# Encode prompts
positive = CLIPTextEncode(text="a cinematic portrait of an astronaut", clip=clip)
negative = CLIPTextEncode(text="", clip=clip)

# Create latents and sample
latent = EmptyLatentImage(width=1024, height=1024, batch_size=1)
sampled = KSampler(
    model=model,
    seed=42,
    steps=20,
    cfg=7.5,
    sampler_name="euler",
    scheduler="normal",
    positive=positive,
    negative=negative,
    latent_image=latent,
    denoise=1.0,
)
decoded = VAEDecode(samples=sampled, vae=vae)

# Export to ComfyUI JSON format
workflow = decoded.source_node.build_json_workflow()

# Optionally: print or send to a ComfyUI server
import json
print(json.dumps(workflow, indent=2))

Notes

• The generator downloads the node schema, sanitises type names, and rewrites nodes.py with updated classes and helper functions.
• The just recipe just run wraps the generation command if you prefer using just.

Acknowledgments

Thanks to ComfyScript for inspiration and prior art.