这是另一个用于可视化美味佳肴的有趣提示。用 GPT Image 2 制作。

Here is another fun prompt for visualizing delicious meals. Made this with GPT Image 2. select reference_card from world_cuisine_encyclopedia where layout_template = '2x2_technical_cooking_grid' and card_structure = { 'continent_header': '[continent_name]', 'country_flag': '[iso_code]', 'dish_name': '[dish_name]', 'subtitle': 'inferred from dish context', 'hero_photo': '3/4 angle plated shot, natural lighting', 'key_science': [ {'label': '[technique_1]', 'close_up': 'macro process photo', 'desc': 'technical explanation'}, {'label': '[technique_2]', 'close_up': 'macro process photo', 'desc': 'technical explanation'} ], 'flavor_variants': { 'sweet': {'photo': 'variant', 'label': 'inferred adaptation'}, 'savory': {'photo': 'variant', 'label': 'inferred adaptation'}, 'spicy': {'photo': 'variant', 'label': 'inferred adaptation'}, 'umami': {'photo': 'variant', 'label': 'inferred adaptation'} }, 'ingredients_ratio': 'overhead grid of bowls, proportional quantities', 'step_by_step': '8 sequential process photos with 1-2 word labels', 'time_temperature': 'table with stages, time, temp f/c, altitude adjust', 'common_failures': 'problem | cause | fix table', 'tools_pans': 'illustrated equipment with labels', 'cultural_timeline': 'country silhouette + historical dates + icons' } and grid_layout = '2x2 — 4 different dishes from 4 continents' and dishes = [ {continent:'[continent_1]', country:'[country_1]', dish:'[dish_1]', type:'[type_1]'}, {continent:'[continent_2]', country:'[country_2]', dish:'[dish_2]', type:'[type_2]'}, {continent:'[continent_3]', country:'[country_3]', dish:'[dish_3]', type:'[type_3]'}, {continent:'[continent_4]', country:'[country_4]', dish:'[dish_4]', type:'[type_4]'} ] and bg_color = 'warm beige/cream # f5f1e8' and typography = 'clean sans headers, serif dish names, technical body copy' and photo_style = 'food photography, natural lighting, professional plating' and resolution = '8k_square_grid' order by educational_completeness desc limit 1;

这是另一个用于可视化美味佳肴的有趣提示。用 GPT Image 2 制作。 select reference_card from world_cuisine_encyclopedia where layout_template = '2x2_technical_cooking_grid' and card_structure = { 'continent_header': '[continent_name]', 'country_flag': '[iso_code]', 'dish_name': '[dish_name]', 'subtitle': 'inferred from dish context', 'hero_photo': '3/4 angle plated shot, natural lighting', 'key_science': [ {'label': '[technique_1]', 'close_up': 'macro process photo', 'desc': 'technical explanation'}, {'label': '[technique_2]', 'close_up': 'macro process photo', 'desc': 'technical explanation'} ], 'flavor_variants': { 'sweet': {'photo': 'variant', 'label': 'inferred adaptation'}, 'savory': {'photo': 'variant', 'label': 'inferred adaptation'}, 'spicy': {'photo': 'variant', 'label': 'inferred adaptation'}, 'umami': {'photo': 'variant', 'label': 'inferred adaptation'} }, 'ingredients_ratio': 'overhead grid of bowls, proportional quantities', 'step_by_step': '8 sequential process photos with 1-2 word labels', 'time_temperature': 'table with stages, time, temp f/c, altitude adjust', 'common_failures': 'problem | cause | fix table', 'tools_pans': 'illustrated equipment with labels', 'cultural_timeline': 'country silhouette + historical dates + icons' } and grid_layout = '2x2 — 4 different dishes from 4 continents' and dishes = [ {continent:'[continent_1]', country:'[country_1]', dish:'[dish_1]', type:'[type_1]'}, {continent:'[continent_2]', country:'[country_2]', dish:'[dish_2]', type:'[type_2]'}, {continent:'[continent_3]', country:'[country_3]', dish:'[dish_3]', type:'[type_3]'}, {continent:'[continent_4]', country:'[country_4]', dish:'[dish_4]', type:'[type_4]'} ] and bg_color = 'warm beige/cream # f5f1e8' and typography = 'clean sans headers, serif dish names, technical body copy' and photo_style = 'food photography, natural lighting, professional plating' and resolution = '8k_square_grid' order by educational_completeness desc limit 1;