27 lines
1.6 KiB
Python
27 lines
1.6 KiB
Python
from .base import SiliconFlowBaseNode
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from .api_client import fetch_image_models
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class SiliconFlowFlux1Dev(SiliconFlowBaseNode):
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@classmethod
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def INPUT_TYPES(cls):
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models = [m for m in fetch_image_models() if "flux.1-dev" in m.lower() and "kontext" not in m.lower()]
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if not models: models = ["black-forest-labs/FLUX.1-dev"]
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return {
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"required": {
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"model": (models, {"default": models[0], "tooltip": "FLUX.1 Dev model ID."}),
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"prompt": ("STRING", {"multiline": True, "tooltip": "Description."}),
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"image_size": (["1024x1024", "960x1280", "768x1024", "720x1440", "720x1280", "others"], {"default": "1024x1024", "tooltip": "Size presets (max 2.3M pixels)."}),
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"num_inference_steps": ("INT", {"default": 20, "min": 1, "max": 30, "tooltip": "Inference steps (1-30)."}),
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"seed": ("INT", {"default": -1, "min": -1, "max": 9999999999, "tooltip": "Random seed. Use -1 for random."}),
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},
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"optional": {
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"prompt_enhancement": ("BOOLEAN", {"default": False, "tooltip": "Detail-optimized prompt."}),
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}
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}
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def generate(self, model, prompt, image_size, num_inference_steps, seed, prompt_enhancement=False):
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return self._generate_common(model, prompt, image_size=image_size, num_inference_steps=num_inference_steps, seed=seed, prompt_enhancement=prompt_enhancement)
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NODE_CLASS_MAPPINGS = {"SiliconFlowFlux1Dev": SiliconFlowFlux1Dev}
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NODE_DISPLAY_NAME_MAPPINGS = {"SiliconFlowFlux1Dev": "🎨 SiliconFlow — FLUX.1 Dev"}
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