E-commerce-Grade Product Photography: Structured Prompt Test of fibo-1.5

Create an e-commerce-grade product image using fibo-1.5's structured prompt paradigm: break down the subject's material, lighting, composition, color, and lens properties into readable JSON sections written into the prompt, rather than piling up a string of adjectives. This piece features a frosted glass perfume bottle; the prompt separately constrains the background material, the ratio of key light to fill light, the direction of highlights, depth of field, and color temperature, so that the model still adheres to the details even with few-step sampling. According to the public documentation of this model family, fibo-1.5 is trained with JSON-native structured prompts, and its attributes are relatively decoupled, making it easy to change only the lighting or only the background for multiple rounds of iteration without the entire prompt drifting; it is suitable for e-commerce image generation workflows that require reproducibility and batch fine-tuning. Applicable scenarios: product hero images and detail page visuals, material and proofing previews, and extension of multi-color/SKU variants under the same lighting scheme. If you only need a quick mood image, a short prompt will do; but to achieve controllable commercial-grade texture, it is recommended to follow this type of structured approach.