Superside ComfyUI Nodes
df2c9c0beb
Root cause of nodes not appearing in ComfyUI: this package's node classes originally reused the exact same class names as the internal fal-flux-nodes package it was migrated from (e.g. NanoBananaProEditNode, SeedreamV45EditNode). ComfyUI's NODE_CLASS_MAPPINGS is a flat global dict - when both packages are installed, whichever loads first wins and the other's registration for that key is silently dropped, which is why none of the "Superside "-prefixed nodes were showing up. Every class is now uniquely prefixed (e.g. SupersideNanoBananaProEditNode), so this package can never collide with fal-flux-nodes, ComfyUI-fal-API, or any other node pack regardless of install order. Updated __init__.py, web/js/show_text.js's TEXT_DISPLAY_NODES list, and README.md to match.
125 lines
4.2 KiB
Python
125 lines
4.2 KiB
Python
import logging
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from .base_node import (
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SupersideFalNode,
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ImageProcessingMixin,
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APIClientMixin,
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API_KEY_INPUT_SPEC,
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)
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logging.basicConfig(level=logging.DEBUG)
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logger = logging.getLogger(__name__)
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class SupersideFluxKontextMaxMultiImageNode(
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SupersideFalNode, ImageProcessingMixin, APIClientMixin
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):
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"""
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Flux Kontext Multi-Image Node: Generate images using FLUX.1 Kontext [Max]
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with multiple image inputs for context-aware generation.
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This node allows up to 4 image inputs for advanced context-aware image
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generation using fal.ai API.
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"""
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {
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"prompt": (
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"STRING",
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{
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"multiline": True,
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"default": "Put the little duckling on top of the "
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"woman's t-shirt.",
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"placeholder": "Enter your prompt here",
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},
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),
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"api_key": API_KEY_INPUT_SPEC,
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},
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"optional": {
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"image_1": ("IMAGE",),
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"image_2": ("IMAGE",),
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"image_3": ("IMAGE",),
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"image_4": ("IMAGE",),
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"seed": ("INT", {"min": 0, "max": 0xFFFFFFFFFFFFFFFF}),
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"guidance_scale": (
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"FLOAT",
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{"default": 3.5, "min": 1, "max": 40.0, "step": 0.5},
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),
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"num_images": ("INT", {"default": 1, "min": 1, "max": 4}),
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"safety_tolerance": (["1", "2", "3", "4", "5", "6"], {"default": "2"}),
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"output_format": (["jpeg", "png"], {"default": "png"}),
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"aspect_ratio": (
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["21:9", "16:9", "4:3", "3:2", "1:1", "2:3", "3:4", "9:16", "9:21"],
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{"default": "3:4"},
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),
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},
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}
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RETURN_TYPES = ("IMAGE",)
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FUNCTION = "generate"
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DESCRIPTION = (
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"Generate images using FLUX.1 Kontext [Max] with multiple image "
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"inputs for context-aware generation"
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)
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def prepare_image_urls(self, client, **kwargs):
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"""Prepare list of image URLs from input images."""
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image_urls = []
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# Check for up to 4 images
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for i in range(1, 5):
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image_key = f"image_{i}"
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if image_key in kwargs and kwargs[image_key] is not None:
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try:
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url = self.upload_image(client, kwargs[image_key])
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image_urls.append(url)
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except Exception as e:
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logger.warning(f"Failed to upload {image_key}: {str(e)}")
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continue
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return image_urls
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def prepare_arguments(self, client, prompt, **kwargs):
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"""Prepare arguments for the API call."""
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# Get image URLs
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image_urls = self.prepare_image_urls(client, **kwargs)
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if not image_urls:
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raise ValueError(
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"At least one image is required for Flux Kontext generation"
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)
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arguments = {"prompt": prompt, "image_urls": image_urls}
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# Add optional parameters if provided
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if kwargs.get("seed") and kwargs["seed"] != 0:
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arguments["seed"] = kwargs["seed"]
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if kwargs.get("guidance_scale"):
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arguments["guidance_scale"] = kwargs["guidance_scale"]
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if kwargs.get("num_images"):
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arguments["num_images"] = kwargs["num_images"]
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if kwargs.get("safety_tolerance"):
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arguments["safety_tolerance"] = kwargs["safety_tolerance"]
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if kwargs.get("output_format"):
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arguments["output_format"] = kwargs["output_format"]
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if kwargs.get("aspect_ratio"):
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arguments["aspect_ratio"] = kwargs["aspect_ratio"]
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return arguments
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def generate(self, prompt, api_key, **kwargs):
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"""Main generation function."""
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try:
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client = self.get_client(api_key)
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arguments = self.prepare_arguments(client, prompt, **kwargs)
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result = self.call_api(client, "fal-ai/flux-pro/kontext/max/multi", arguments)
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return self.process_images(result)
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except Exception as e:
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logger.error(f"Generation failed: {str(e)}")
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raise
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