Add Krea2 formatting and scalable scene pools

README.md

@@ -9,6 +9,7 @@ The node is registered as:
 - `prompt_builder / SxCP Seed Control`
 - `prompt_builder / SxCP Camera Control`
 - `prompt_builder / SxCP Caption Naturalizer`
+- `prompt_builder / SxCP Krea2 Formatter`
 - `prompt_builder / SxCP Insta/OF Options`
 - `prompt_builder / SxCP Insta/OF Prompt Pair`
 
@@ -65,6 +66,35 @@ It outputs:
 - `natural_caption`
 - `method`
 
+`SxCP Krea2 Formatter` rewrites an existing prompt or `metadata_json` into a
+Krea2-oriented natural-language paragraph. It is a formatter, not a safety or
+content downgrade pass: hardcore items, role graphs, sexual pose wording, and
+camera controls are preserved. Negative prompts stay separate.
+
+Important behavior:
+
+- Age wording is preserved deliberately. Phrases like `21-year-old adult`,
+  `late 20s adult woman`, and `all participants 21+ and visibly adult` are kept
+  because they help avoid unwanted young-looking outputs.
+- Trigger words are removed by default because Krea2 prompting generally reads
+  better as natural language. Enable `preserve_trigger` if you still need a LoRA
+  trigger in the positive prompt.
+- `style_mode`: `preserve` keeps the current generated style text,
+  `photographic` converts the style tail toward creator-photo language, and
+  `minimal` omits most style text.
+- For Insta/OF paired metadata, the node returns both `krea_softcore_prompt` and
+  `krea_hardcore_prompt`, with separate softcore and hardcore negatives.
+
+It outputs:
+
+- `krea_prompt`
+- `negative_prompt`
+- `krea_softcore_prompt`
+- `krea_hardcore_prompt`
+- `softcore_negative_prompt`
+- `hardcore_negative_prompt`
+- `method`
+
 `SxCP Insta/OF Prompt Pair` is a special paired-output mode. It creates one
 shared primary creator descriptor, then returns both a softcore prompt and a
 hardcore prompt from that same descriptor. This is useful when you want the same
@@ -180,6 +210,46 @@ provided, the node uses a generic composer that selects subject appearance,
 scene, pose, expression, composition, and a random item from the selected
 subcategory.
 
+Reusable location banks can be defined with top-level `scene_pools` in any
+`categories/*.json` file. Categories, subcategories, and items can reference
+them with `scene_pools`; referenced pools are merged with any local `scenes`.
+This keeps location expansion scalable without duplicating the same bedroom,
+selfie, mirror, creator, or group-sex locations across every subcategory.
+
+Set `"inherit_scenes": false` on a subcategory or item when it should use only
+its own `scenes` and `scene_pools` instead of also inheriting parent category
+locations. This is useful for narrow subcategories such as group scenes, vehicle
+sets, outdoor-only sets, or any category where a generic parent room would be a
+bad match.
+
+Example:
+
+```json
+{
+  "scene_pools": {
+    "creator_selfie_rooms": [
+      {
+        "slug": "bedroom_phone_tripod",
+        "prompt": "private creator bedroom with a phone tripod, rumpled bedding, and warm lamps"
+      }
+    ]
+  },
+  "categories": [
+    {
+      "name": "Example",
+      "subcategories": [
+        {
+          "name": "Selfie set",
+          "inherit_scenes": false,
+          "scene_pools": ["creator_selfie_rooms"],
+          "items": ["simple outfit prompt"]
+        }
+      ]
+    }
+  ]
+}
+```
+
 For large categories, prefer `item_templates` plus `item_axes` instead of writing
 every final item by hand:
 

__init__.py

@@ -21,6 +21,7 @@ try:
         subcategory_choices,
     )
     from .caption_naturalizer import naturalize_caption
+    from .krea_formatter import format_krea2_prompt
 except ImportError:
     from prompt_builder import (
         build_camera_config_json,
@@ -40,6 +41,7 @@ except ImportError:
         subcategory_choices,
     )
     from caption_naturalizer import naturalize_caption
+    from krea_formatter import format_krea2_prompt
 
 
 class SxCPPromptBuilder:
@@ -277,6 +279,75 @@ class SxCPCaptionNaturalizer:
         )
 
 
+class SxCPKrea2Formatter:
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "source_text": ("STRING", {"default": "", "multiline": True}),
+                "input_hint": (["auto", "metadata_json", "prompt"], {"default": "auto"}),
+                "target": (["auto", "single", "softcore", "hardcore"], {"default": "auto"}),
+                "detail_level": (["balanced", "concise", "dense"], {"default": "balanced"}),
+                "style_mode": (["preserve", "photographic", "minimal"], {"default": "preserve"}),
+                "preserve_trigger": ("BOOLEAN", {"default": False}),
+            },
+            "optional": {
+                "metadata_json": ("STRING", {"default": "", "multiline": True}),
+                "negative_prompt": ("STRING", {"default": "", "multiline": True}),
+                "extra_positive": ("STRING", {"default": "", "multiline": True}),
+                "extra_negative": ("STRING", {"default": "", "multiline": True}),
+            },
+        }
+
+    RETURN_TYPES = ("STRING", "STRING", "STRING", "STRING", "STRING", "STRING", "STRING")
+    RETURN_NAMES = (
+        "krea_prompt",
+        "negative_prompt",
+        "krea_softcore_prompt",
+        "krea_hardcore_prompt",
+        "softcore_negative_prompt",
+        "hardcore_negative_prompt",
+        "method",
+    )
+    FUNCTION = "build"
+    CATEGORY = "prompt_builder"
+
+    def build(
+        self,
+        source_text,
+        input_hint,
+        target,
+        detail_level,
+        style_mode,
+        preserve_trigger,
+        metadata_json="",
+        negative_prompt="",
+        extra_positive="",
+        extra_negative="",
+    ):
+        row = format_krea2_prompt(
+            source_text=source_text or "",
+            metadata_json=metadata_json or "",
+            negative_prompt=negative_prompt or "",
+            input_hint=input_hint,
+            target=target,
+            detail_level=detail_level,
+            style_mode=style_mode,
+            preserve_trigger=preserve_trigger,
+            extra_positive=extra_positive or "",
+            extra_negative=extra_negative or "",
+        )
+        return (
+            row["krea_prompt"],
+            row["negative_prompt"],
+            row["krea_softcore_prompt"],
+            row["krea_hardcore_prompt"],
+            row["softcore_negative_prompt"],
+            row["hardcore_negative_prompt"],
+            row["method"],
+        )
+
+
 class SxCPInstaOFOptions:
     @classmethod
     def INPUT_TYPES(cls):
@@ -417,6 +488,7 @@ NODE_CLASS_MAPPINGS = {
     "SxCPSeedControl": SxCPSeedControl,
     "SxCPCameraControl": SxCPCameraControl,
     "SxCPCaptionNaturalizer": SxCPCaptionNaturalizer,
+    "SxCPKrea2Formatter": SxCPKrea2Formatter,
     "SxCPInstaOFOptions": SxCPInstaOFOptions,
     "SxCPInstaOFPromptPair": SxCPInstaOFPromptPair,
 }
@@ -426,6 +498,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "SxCPSeedControl": "SxCP Seed Control",
     "SxCPCameraControl": "SxCP Camera Control",
     "SxCPCaptionNaturalizer": "SxCP Caption Naturalizer",
+    "SxCPKrea2Formatter": "SxCP Krea2 Formatter",
     "SxCPInstaOFOptions": "SxCP Insta/OF Options",
     "SxCPInstaOFPromptPair": "SxCP Insta/OF Prompt Pair",
 }

categories/default_categories.json

@@ -14,13 +14,136 @@
           "name": "Streetwear",
           "slug": "streetwear",
           "weight": 1.0,
-          "items": [
+          "scene_pools": ["casual_urban_scenes"],
-            "oversized hoodie with slim jeans and clean sneakers",
+          "items": ["streetwear outfit generator"],
-            "cropped bomber jacket with cargo pants and chunky trainers",
+          "item_templates": [
-            "graphic tee under an open flannel with fitted denim",
+            "{outerwear} layered over {top}, with {bottom}, {footwear}, and {accessory}",
-            "sleek track jacket with joggers and minimal sneakers",
+            "{top} with {bottom}, {outerwear}, {footwear}, and {detail}",
-            "denim-on-denim outfit with a fitted white tee"
+            "{set_piece} styled with {footwear}, {accessory}, and {color_mood}",
+            "{outerwear} with {bottom}, {bag}, {footwear}, and {texture_detail}",
+            "{top} tucked into {bottom}, paired with {footwear}, {jewelry}, and {detail}",
+            "{outerwear} half-zipped over {top}, with {bottom}, {bag}, and {color_mood}",
+            "{set_piece} with {outerwear}, {footwear}, {jewelry}, and {texture_detail}",
+            "{top} under {outerwear}, with {bottom}, {accessory}, {bag}, and {footwear}"
           ],
+          "item_axes": {
+            "accessory": [
+              "a ribbed beanie",
+              "thin sunglasses",
+              "a baseball cap",
+              "wire-frame glasses",
+              "a silk neck scarf",
+              "fingerless gloves",
+              "a chunky belt",
+              "a low-profile headphones detail"
+            ],
+            "bag": [
+              "a small crossbody bag",
+              "a canvas tote",
+              "a compact shoulder bag",
+              "a mini backpack",
+              "a waist pack worn crossbody",
+              "a structured leather satchel",
+              "a nylon sling bag",
+              "a glossy phone pouch"
+            ],
+            "bottom": [
+              "relaxed cargo pants",
+              "straight-leg jeans",
+              "wide-leg denim",
+              "pleated utility trousers",
+              "fitted black jeans",
+              "soft joggers",
+              "a denim mini skirt with tights",
+              "tailored track pants",
+              "high-waist cropped trousers",
+              "washed grey jeans"
+            ],
+            "color_mood": [
+              "muted city neutrals",
+              "black and cream contrast",
+              "soft grey-blue tones",
+              "washed denim colors",
+              "olive and charcoal accents",
+              "clean monochrome styling",
+              "warm brick-red accents",
+              "navy, white, and graphite layers"
+            ],
+            "detail": [
+              "rolled cuffs",
+              "visible layered hems",
+              "a sharp cropped silhouette",
+              "clean oversized proportions",
+              "a relaxed off-duty fit",
+              "asymmetric tucked fabric",
+              "subtle graphic print details",
+              "a neat high-waist line"
+            ],
+            "footwear": [
+              "clean white sneakers",
+              "chunky trainers",
+              "platform sneakers",
+              "minimal leather sneakers",
+              "black ankle boots",
+              "retro running shoes",
+              "canvas high-tops",
+              "sleek street boots"
+            ],
+            "jewelry": [
+              "small hoop earrings",
+              "layered chain necklaces",
+              "a simple watch",
+              "stacked rings",
+              "a thin choker",
+              "minimal silver earrings",
+              "a pendant necklace",
+              "a narrow bracelet"
+            ],
+            "outerwear": [
+              "oversized hoodie",
+              "cropped bomber jacket",
+              "open flannel shirt",
+              "sleek track jacket",
+              "denim jacket",
+              "boxy leather jacket",
+              "lightweight varsity jacket",
+              "oversized zip hoodie",
+              "short trench jacket",
+              "quilted street jacket"
+            ],
+            "set_piece": [
+              "denim-on-denim outfit",
+              "matching track set",
+              "monochrome hoodie-and-jogger set",
+              "oversized shirt-and-cargo outfit",
+              "cropped jacket and wide denim outfit",
+              "clean athleisure set",
+              "utility vest and trouser outfit",
+              "layered tee and open-shirt outfit"
+            ],
+            "texture_detail": [
+              "washed cotton texture",
+              "soft fleece texture",
+              "matte nylon fabric",
+              "structured denim seams",
+              "subtle ribbed knit trim",
+              "smooth leather accents",
+              "canvas strap details",
+              "creased everyday fabric"
+            ],
+            "top": [
+              "fitted white tee",
+              "cropped tank top",
+              "graphic tee",
+              "ribbed long-sleeve top",
+              "simple black tee",
+              "slim turtleneck",
+              "soft henley shirt",
+              "cropped sweatshirt",
+              "mesh-layered tee",
+              "clean sleeveless top"
+            ]
+          },
           "scenes": [
             {
               "slug": "city_crosswalk",
@@ -34,20 +157,166 @@
           "poses": [
             "standing with one hand in a pocket",
             "leaning against a wall with relaxed confidence",
-            "walking forward with a casual runway stride"
+            "walking forward with a casual runway stride",
+            "looking over one shoulder while stepping off a curb",
+            "sitting on a low concrete wall with one knee raised",
+            "adjusting sunglasses with a relaxed half-smile",
+            "hands in jacket pockets with a slight hip shift",
+            "turning mid-step as fabric layers move naturally"
           ]
         },
         {
           "name": "Summer casual",
           "slug": "summer_casual",
           "weight": 1.0,
-          "items": [
+          "scene_pools": ["casual_summer_scenes"],
-            "light cotton sundress with simple sandals",
+          "items": ["summer casual outfit generator"],
-            "linen shorts with a tucked-in sleeveless blouse",
+          "item_templates": [
-            "soft camp-collar shirt with relaxed trousers",
+            "{dress} with {footwear}, {accessory}, and {fabric_detail}",
-            "ribbed tank top with a flowing midi skirt",
+            "{top} with {bottom}, {footwear}, {bag}, and {color_mood}",
-            "breathable linen two-piece in pale summer colors"
+            "{layer} over {top}, with {bottom}, {accessory}, and {texture_detail}",
+            "{two_piece} with {footwear}, {jewelry}, and {fabric_detail}",
+            "{top} tucked into {bottom}, paired with {bag}, {footwear}, and {detail}",
+            "{dress} under {layer}, with {accessory}, {jewelry}, and {color_mood}",
+            "{two_piece} styled with {bag}, {footwear}, {texture_detail}, and {detail}",
+            "{top} with {bottom}, {layer}, {accessory}, and {fabric_detail}"
           ],
+          "item_axes": {
+            "accessory": [
+              "wide sunglasses",
+              "a straw sunhat",
+              "a silk hair scarf",
+              "a woven belt",
+              "thin oval sunglasses",
+              "a cotton bandana",
+              "a simple sun visor",
+              "a lightweight shawl"
+            ],
+            "bag": [
+              "a woven tote",
+              "a small raffia bag",
+              "a canvas beach bag",
+              "a soft shoulder bag",
+              "a compact basket purse",
+              "a linen drawstring bag",
+              "a minimal crossbody pouch",
+              "a straw clutch"
+            ],
+            "bottom": [
+              "linen shorts",
+              "relaxed cropped trousers",
+              "a flowing midi skirt",
+              "high-waist cotton shorts",
+              "a breezy wrap skirt",
+              "wide-leg linen pants",
+              "a soft pleated skirt",
+              "light denim shorts",
+              "paperbag-waist trousers",
+              "a calf-length summer skirt"
+            ],
+            "color_mood": [
+              "pale summer colors",
+              "sun-washed white and blue",
+              "coral and cream accents",
+              "sage green and ivory tones",
+              "soft yellow and denim blue",
+              "warm terracotta details",
+              "fresh white and citrus accents",
+              "muted sea-glass colors"
+            ],
+            "detail": [
+              "rolled hems",
+              "a loose tucked waist",
+              "wind-lifted fabric edges",
+              "open collar styling",
+              "a relaxed vacation fit",
+              "thin shoulder straps",
+              "a clean high-waist line",
+              "softly draped fabric"
+            ],
+            "dress": [
+              "light cotton sundress",
+              "button-front linen dress",
+              "soft wrap dress",
+              "ribbed tank dress",
+              "flowing midi sundress",
+              "simple slip dress",
+              "tiered cotton dress",
+              "halter summer dress"
+            ],
+            "fabric_detail": [
+              "breathable linen texture",
+              "soft cotton folds",
+              "light gauze fabric",
+              "fine ribbed cotton",
+              "sunlit woven texture",
+              "thin summer knit texture",
+              "crisp poplin folds",
+              "airy voile fabric"
+            ],
+            "footwear": [
+              "simple sandals",
+              "flat leather sandals",
+              "white canvas sneakers",
+              "espadrilles",
+              "strappy sandals",
+              "woven slides",
+              "minimal mule sandals",
+              "low platform sandals"
+            ],
+            "jewelry": [
+              "small gold hoops",
+              "a shell necklace",
+              "a delicate anklet",
+              "thin stacked bracelets",
+              "a small pendant necklace",
+              "pearl stud earrings",
+              "a beaded bracelet",
+              "a fine waist chain over fabric"
+            ],
+            "layer": [
+              "soft camp-collar shirt",
+              "open linen shirt",
+              "light cotton overshirt",
+              "cropped denim jacket",
+              "sheer beach shirt",
+              "loose short-sleeve cardigan",
+              "thin knit wrap",
+              "unbuttoned chambray shirt"
+            ],
+            "texture_detail": [
+              "natural linen slubs",
+              "matte cotton finish",
+              "subtle woven stripes",
+              "soft wrinkled fabric",
+              "delicate eyelet texture",
+              "smooth summer poplin",
+              "sunlit thread texture",
+              "lightweight ribbing"
+            ],
+            "top": [
+              "tucked-in sleeveless blouse",
+              "ribbed tank top",
+              "cropped cotton tee",
+              "linen camisole",
+              "halter knit top",
+              "soft bandeau under a shirt",
+              "square-neck tank",
+              "thin-strapped summer top",
+              "buttoned linen vest",
+              "loose cotton blouse"
+            ],
+            "two_piece": [
+              "breathable linen two-piece",
+              "matching crop top and skirt set",
+              "soft resort shirt-and-short set",
+              "ribbed tank and midi skirt set",
+              "cotton co-ord set",
+              "linen vest and trouser set",
+              "open shirt and wrap-skirt set",
+              "minimal summer knit set"
+            ]
+          },
           "scenes": [
             {
               "slug": "sunny_market",
@@ -61,20 +330,148 @@
           "poses": [
             "turning slightly with fabric moving in the breeze",
             "standing in warm sunlight with relaxed shoulders",
-            "sitting on a low wall with one knee bent"
+            "sitting on a low wall with one knee bent",
+            "walking with one hand holding a sunhat",
+            "leaning on a promenade railing with a soft smile",
+            "lifting sunglasses while looking toward the light",
+            "standing barefoot near warm paving stones",
+            "mid-step with loose fabric trailing behind"
           ]
         },
         {
           "name": "Cozy lounge",
           "slug": "cozy_lounge",
           "weight": 1.0,
-          "items": [
+          "scene_pools": ["casual_lounge_scenes"],
-            "soft knit cardigan with a fitted tee and lounge trousers",
+          "items": ["cozy lounge outfit generator"],
-            "oversized sweater with leggings and wool socks",
+          "item_templates": [
-            "relaxed sweatshirt with drawstring joggers",
+            "{layer} over {top}, with {bottom}, {footwear}, and {texture_detail}",
-            "ribbed lounge set with a long open cardigan",
+            "{set_piece} with {layer}, {accessory}, and {color_mood}",
-            "simple cotton tee with loose pajama-style trousers"
+            "{top} with {bottom}, {footwear}, {prop}, and {detail}",
+            "{layer} wrapped around {top}, with {bottom}, {jewelry}, and {texture_detail}",
+            "{set_piece} styled with {footwear}, {prop}, and {detail}",
+            "{top} tucked loosely into {bottom}, with {layer}, {accessory}, and {color_mood}",
+            "{layer} slipping off one shoulder over {top}, with {bottom}, {footwear}, and {texture_detail}",
+            "{set_piece} with {accessory}, {jewelry}, {prop}, and {detail}"
           ],
+          "item_axes": {
+            "accessory": [
+              "a soft hair clip",
+              "thin reading glasses",
+              "a scrunchie at the wrist",
+              "a loose blanket scarf",
+              "a simple headband",
+              "a warm knit beanie",
+              "a delicate sleep mask pushed up",
+              "a cotton bandana"
+            ],
+            "bottom": [
+              "lounge trousers",
+              "soft leggings",
+              "drawstring joggers",
+              "loose pajama-style trousers",
+              "ribbed lounge pants",
+              "wide knit pants",
+              "cotton sleep shorts",
+              "thermal leggings",
+              "slouchy sweatpants",
+              "soft waffle-knit pants"
+            ],
+            "color_mood": [
+              "warm oatmeal and grey tones",
+              "soft rose and cream colors",
+              "muted sage and ivory",
+              "heather grey and white",
+              "warm mocha neutrals",
+              "powder blue and cream",
+              "charcoal and blush accents",
+              "soft lavender and warm beige"
+            ],
+            "detail": [
+              "relaxed draped proportions",
+              "rolled sleeves",
+              "softly rumpled fabric",
+              "a loose off-duty silhouette",
+              "visible cozy layering",
+              "a slightly oversized fit",
+              "bare ankle styling",
+              "a gentle high-waist line"
+            ],
+            "footwear": [
+              "wool socks",
+              "soft house slippers",
+              "bare feet",
+              "fuzzy socks",
+              "knit ankle socks",
+              "shearling slippers",
+              "simple cotton socks",
+              "ribbed knee socks"
+            ],
+            "jewelry": [
+              "tiny hoop earrings",
+              "a simple pendant necklace",
+              "a thin bracelet",
+              "small stud earrings",
+              "a delicate ring",
+              "a minimal chain necklace",
+              "a soft fabric wristband",
+              "a subtle ankle chain"
+            ],
+            "layer": [
+              "soft knit cardigan",
+              "long open cardigan",
+              "oversized sweater",
+              "relaxed sweatshirt",
+              "chunky cable-knit cardigan",
+              "brushed fleece hoodie",
+              "thin robe cardigan",
+              "cropped lounge hoodie",
+              "slouchy wrap sweater",
+              "soft waffle-knit cardigan"
+            ],
+            "prop": [
+              "a casual magazine nearby",
+              "a warm mug in one hand",
+              "a paperback book nearby",
+              "a folded blanket at the hip",
+              "a phone resting on the sofa",
+              "a small tray on a side table",
+              "a pillow tucked against the waist",
+              "a half-open notebook nearby"
+            ],
+            "set_piece": [
+              "ribbed lounge set",
+              "matching sweatshirt and jogger set",
+              "soft knit co-ord set",
+              "cotton tee and pajama trouser set",
+              "waffle-knit lounge set",
+              "brushed fleece lounge set",
+              "cardigan and knit pant set",
+              "simple sleepwear-inspired set"
+            ],
+            "texture_detail": [
+              "soft knit texture",
+              "brushed fleece texture",
+              "ribbed cotton texture",
+              "waffle-knit fabric",
+              "warm wool fibers",
+              "smooth jersey folds",
+              "plush cardigan texture",
+              "softly worn cotton"
+            ],
+            "top": [
+              "fitted tee",
+              "simple cotton tee",
+              "ribbed tank top",
+              "soft long-sleeve top",
+              "thin camisole",
+              "slouchy henley shirt",
+              "cropped lounge tee",
+              "thermal knit top",
+              "light sleep tank",
+              "soft V-neck tee"
+            ]
+          },
           "scenes": [
             {
               "slug": "sunny_apartment",
@@ -88,7 +485,12 @@
           "poses": [
             "curled comfortably on a sofa",
             "standing barefoot near a window with a relaxed smile",
-            "sitting cross-legged with a casual magazine nearby"
+            "sitting cross-legged with a casual magazine nearby",
+            "leaning into a couch corner with one knee raised",
+            "stretching lazily with sleeves falling over the hands",
+            "kneeling on a rug while reaching for a warm mug",
+            "standing in profile near soft curtains",
+            "reclining with one arm draped over a pillow"
           ]
         }
       ]

categories/erotic_clothes.json

@@ -10,6 +10,7 @@
       "style": "explicit adult erotic fashion illustration, sensual pin-up coloured-pencil comic style, adults only",
       "positive_suffix": "Use crisp clean comic linework, detailed hatching, soft skin shading, tactile fabric texture, warm intimate lighting, and textured paper.",
       "negative_prompt": "minors, childlike appearance, schoolgirl, childlike costume, non-consensual, coercion, violence, injury, watermark",
+      "scene_pools": ["softcore_creator_scenes", "mirror_scenes"],
       "expressions": [
         "heavy-lidded seductive gaze",
         "direct erotic stare",
@@ -47,6 +48,7 @@
           "name": "Provocative lingerie",
           "slug": "provocative_lingerie",
           "weight": 1.0,
+          "scene_pools": ["boudoir_bedroom_scenes"],
           "item_templates": [
             "{color} {fabric} {bra_style} with {bottom_style}, {garter_detail}, {stocking_style}, and {shoe_style}",
             "{color} {bodywear} with {neckline}, {hip_cut}, {back_detail}, and {trim_detail}",
@@ -306,6 +308,7 @@
           "name": "Sheer exposed",
           "slug": "sheer_exposed",
           "weight": 1.0,
+          "scene_pools": ["softcore_creator_scenes", "mirror_scenes"],
           "item_templates": [
             "{color} {sheer_fabric} {sheer_garment} with {exposed_breast_detail}, {hip_detail}, and {shoe_style}",
             "{color} open sheer robe exposing {exposed_breast_detail}, {lower_exposure}, and {jewelry}",
@@ -549,6 +552,7 @@
           "name": "Fetish inspired",
           "slug": "fetish_inspired",
           "weight": 1.0,
+          "scene_pools": ["fetish_studio_scenes"],
           "item_templates": [
             "{color} {material} {latex_piece} with {zipper_detail}, {boot_style}, and {glove_style}",
             "{color} {harness_style} over {breast_exposure} with {bottom_detail}, {hardware}, and {shoe_style}",
@@ -808,6 +812,7 @@
           "name": "Nude accessories",
           "slug": "nude_accessories",
           "weight": 1.0,
+          "scene_pools": ["boudoir_bedroom_scenes", "mirror_scenes"],
           "item_templates": [
             "fully nude body styled only with {stocking_style}, {shoe_style}, and {jewelry}",
             "bare breasts and bare hips framed by {accessory_set}, {stocking_style}, and {shoe_style}",
@@ -971,6 +976,7 @@
           "name": "Microwear and body tape",
           "slug": "microwear_body_tape",
           "weight": 1.0,
+          "scene_pools": ["softcore_creator_scenes", "fetish_studio_scenes"],
           "item_templates": [
             "{color} micro bikini with {top_detail}, {bottom_detail}, {body_tape}, and {shoe_style}",
             "{color} body tape design covering only {tape_coverage}, with {bottom_detail}, {jewelry}, and {shoe_style}",
@@ -1160,6 +1166,7 @@
           "name": "Erotic costumes",
           "slug": "erotic_costumes",
           "weight": 1.0,
+          "scene_pools": ["costume_backstage_scenes", "softcore_creator_scenes"],
           "item_templates": [
             "{color} adult {costume_role} look with {top_detail}, {bottom_detail}, {stocking_style}, and {shoe_style}",
             "{color} fantasy {costume_role} costume with {corset_detail}, {exposure_detail}, {accessory}, and {shoe_style}",

categories/location_pools.json

@@ -0,0 +1,181 @@
+{
+  "version": 1,
+  "scene_pools": {
+    "casual_urban_scenes": [
+      {"slug": "city_crosswalk_phone_snap", "prompt": "sunlit city crosswalk with storefront reflections and a casual phone-snapshot angle"},
+      {"slug": "subway_tile_selfie_corner", "prompt": "clean subway platform with tiled walls, overhead lights, and a quiet selfie corner"},
+      {"slug": "parking_rooftop_streetwear", "prompt": "parking garage rooftop with painted lines, city haze, and late-afternoon light"},
+      {"slug": "record_shop_mirror_wall", "prompt": "record shop aisle with warm neon, poster walls, and a small mirror behind the counter"},
+      {"slug": "coffee_window_counter", "prompt": "coffee shop window counter with street reflections and soft morning light"},
+      {"slug": "brick_alley_fire_escape", "prompt": "brick alley beside a fire escape with clean pavement and reflected city light"},
+      {"slug": "boutique_changing_mirror", "prompt": "boutique changing-room mirror with clothing hooks, soft bulbs, and a candid outfit-check angle"},
+      {"slug": "streetwear_elevator_lobby", "prompt": "modern apartment elevator lobby with brushed metal doors and a full-length mirror"}
+    ],
+    "casual_summer_scenes": [
+      {"slug": "seaside_prom_phone_photo", "prompt": "seaside promenade with bright sky, warm paving stones, and casual phone-photo framing"},
+      {"slug": "weekend_market_canvas_awning", "prompt": "open-air weekend market with fruit stands, canvas awnings, and sunlit walkway space"},
+      {"slug": "rooftop_day_terrace", "prompt": "daytime rooftop terrace with potted plants, white chairs, and clear summer light"},
+      {"slug": "beach_cafe_table", "prompt": "beach cafe table with woven chairs, linen shade, and ocean light in the background"},
+      {"slug": "poolside_daybed_casual", "prompt": "poolside daybed with white towels, glass railings, and soft resort sunlight"},
+      {"slug": "garden_wall_summer", "prompt": "garden wall with climbing flowers, pale stone, and warm afternoon shadows"},
+      {"slug": "lake_boardwalk_summer", "prompt": "wooden lakeside boardwalk with reeds, clean sky, and relaxed vacation light"},
+      {"slug": "sunny_balcony_outfit_check", "prompt": "sunny apartment balcony with plants, city rooftops, and a casual outfit-check composition"}
+    ],
+    "casual_lounge_scenes": [
+      {"slug": "sunny_apartment_phone_tripod", "prompt": "sunny apartment corner with bookshelves, a warm rug, and a phone on a small tripod"},
+      {"slug": "window_seat_soft_curtains", "prompt": "comfortable window seat with soft curtains, pillows, and afternoon light"},
+      {"slug": "bedroom_floor_lounge", "prompt": "cozy bedroom floor with folded blankets, low shelves, and soft window light"},
+      {"slug": "sofa_ring_light_corner", "prompt": "living-room sofa corner with a ring light stand, plants, and warm lamps"},
+      {"slug": "loft_kitchen_lounge", "prompt": "open loft kitchen with a breakfast counter, wood floor, and relaxed home light"},
+      {"slug": "reading_nook_phone_snap", "prompt": "reading nook with stacked books, a small mirror, and candid phone-snapshot framing"},
+      {"slug": "hotel_morning_lounge", "prompt": "hotel room lounge chair with rumpled travel bags, curtains, and soft morning sun"},
+      {"slug": "studio_apartment_mirror", "prompt": "small studio apartment with a full-length mirror, neutral bedding, and warm lamp light"}
+    ],
+    "softcore_creator_scenes": [
+      {"slug": "creator_bedroom_ring_light", "prompt": "private creator bedroom with a ring light, phone tripod, rumpled bedding, and warm lamps"},
+      {"slug": "onlyfans_mirror_bedroom", "prompt": "bedroom mirror selfie setup with a visible phone, messy sheets, and soft amber light"},
+      {"slug": "walk_in_closet_tryon", "prompt": "mirrored walk-in closet with open drawers, hanging outfits, and warm boutique bulbs"},
+      {"slug": "hotel_bed_phone_tripod", "prompt": "hotel bed content setup with a phone on a mini tripod, city lights, and satin bedding"},
+      {"slug": "bathroom_counter_selfie", "prompt": "private bathroom counter with mirror haze, phone reflection, towels, and warm vanity lights"},
+      {"slug": "vanity_ring_light_close", "prompt": "vanity corner with makeup lights, perfume bottles, silk fabric, and close creator-shot framing"},
+      {"slug": "apartment_floor_content", "prompt": "apartment floor content setup with a low mirror, pillows, and soft practical lamps"},
+      {"slug": "balcony_phone_selfie", "prompt": "private balcony with city lights, glass railing, and handheld phone-selfie perspective"},
+      {"slug": "car_interior_creator_selfie", "prompt": "parked car interior with seat reflections, dashboard glow, and close phone-selfie framing"},
+      {"slug": "shower_steam_phone_reflection", "prompt": "steamy private shower room with wet tile, glass reflections, and implied phone-shot framing"},
+      {"slug": "studio_bedroom_backdrop", "prompt": "small creator studio with a bed, seamless backdrop, ring light, and visible phone stand"},
+      {"slug": "couch_lamp_creator_clip", "prompt": "private couch corner with scattered clothes, warm lamp glow, and vertical creator-video framing"}
+    ],
+    "mirror_scenes": [
+      {"slug": "large_bedroom_mirror_selfie", "prompt": "large bedroom mirror with the phone visible, bed behind the subject, and warm side lamps"},
+      {"slug": "antique_mirror_boudoir", "prompt": "antique mirror corner with dark wood, perfume bottles, and golden lamplight"},
+      {"slug": "bathroom_mirror_haze", "prompt": "bathroom mirror selfie setup with steam haze, marble tile, and warm vanity bulbs"},
+      {"slug": "closet_full_length_mirror", "prompt": "full-length closet mirror with outfit racks, shoe shelves, and soft boutique lighting"},
+      {"slug": "hotel_mirror_city_view", "prompt": "hotel suite mirror reflecting city lights, satin bedding, and a phone in hand"},
+      {"slug": "neon_mirror_wall", "prompt": "neon mirror wall with glossy floor reflections and saturated magenta-blue edge light"},
+      {"slug": "gold_vanity_mirror", "prompt": "gold-framed vanity mirror with makeup lights, silk fabric, and close reflected framing"},
+      {"slug": "black_lacquer_mirror_room", "prompt": "black lacquer mirror room with glossy furniture, velvet curtains, and sharp rim light"}
+    ],
+    "hardcore_mirror_scenes": [
+      {"slug": "hardcore_bedroom_mirror_pair", "prompt": "large bedroom mirror placed beside a rumpled bed, reflecting explicit adult body contact and the phone-camera angle", "min_people": 2, "max_people": 3},
+      {"slug": "hardcore_hotel_mirror_pair", "prompt": "hotel suite mirror facing a messy bed, city lights behind it, and enough space for explicit adult positioning", "min_people": 2, "max_people": 3},
+      {"slug": "hardcore_floor_mirror_set", "prompt": "floor mattress beside a full-length mirror with reflected bodies, warm lamps, and close creator-shot framing", "min_people": 2, "max_people": 3},
+      {"slug": "hardcore_shower_mirror_pair", "prompt": "private shower room with a fogged mirror wall, wet tile, and reflected explicit adult contact", "min_people": 2, "max_people": 3},
+      {"slug": "hardcore_vanity_mirror_floor", "prompt": "vanity mirror floor setup with bulbs, scattered clothing, low phone-camera angle, and reflected adult bodies", "min_people": 2, "max_people": 3},
+      {"slug": "hardcore_lacquer_mirror_bed", "prompt": "black lacquer mirror bedroom with glossy reflections, a low bed, and warm rim light around explicit adult contact", "min_people": 2, "max_people": 3},
+      {"slug": "hardcore_tripod_mirror_bed", "prompt": "creator bedroom mirror setup with a phone on tripod, bed sheets, reflected bodies, and clear adult-only framing", "min_people": 2, "max_people": 3},
+      {"slug": "hardcore_threesome_mirror_suite", "prompt": "wide mirror-wall suite arranged for three adults, with a bed, floor cushions, and all bodies visible in direct and reflected views", "min_people": 3, "max_people": 3}
+    ],
+    "boudoir_bedroom_scenes": [
+      {"slug": "warm_boudoir_canopy_bed", "prompt": "warm boudoir bedroom with satin sheets, canopy curtains, low lamplight, and bedside phone framing"},
+      {"slug": "silk_bed_close_creator", "prompt": "silk-sheet bed with pillows, a phone on the nightstand, and intimate creator-shot light"},
+      {"slug": "velvet_headboard_bedroom", "prompt": "velvet headboard bedroom with gold lamps, rumpled bedding, and close sensual framing"},
+      {"slug": "four_poster_lingerie_room", "prompt": "four-poster bed with sheer drapes, warm lamps, and soft floor shadows"},
+      {"slug": "hotel_satin_bedroom", "prompt": "luxury hotel bedroom with satin bedding, city glow, and a visible mirror near the bed"},
+      {"slug": "rose_lamp_bedroom", "prompt": "intimate bedroom with rose-colored lamps, silk sheets, and soft shadows"}
+    ],
+    "fetish_studio_scenes": [
+      {"slug": "black_latex_studio_floor", "prompt": "dark private studio with glossy black floor reflections, rim light, and a phone tripod"},
+      {"slug": "red_velvet_lacquer_room", "prompt": "red velvet room with black lacquer furniture, low spotlights, and reflective surfaces"},
+      {"slug": "industrial_loft_private_set", "prompt": "private industrial loft with brick walls, metal beams, chains, and dramatic light"},
+      {"slug": "neon_lacquer_private_room", "prompt": "private neon-lit lacquer room with magenta highlights, mirrors, and glossy floor"},
+      {"slug": "harness_wall_studio", "prompt": "private harness-wall studio with leather props, matte black backdrop, and controlled rim light"},
+      {"slug": "chrome_fetish_set", "prompt": "chrome studio set with reflective panels, black curtains, and hard-edged erotic lighting"}
+    ],
+    "costume_backstage_scenes": [
+      {"slug": "costume_dressing_room_phone", "prompt": "private costume dressing room with racks, warm mirror bulbs, velvet curtains, and a phone selfie angle"},
+      {"slug": "burlesque_stage_close", "prompt": "small private burlesque stage with red curtains, warm spotlights, and close audience-level framing"},
+      {"slug": "cabaret_backstage_vanity", "prompt": "cabaret backstage corner with feather props, vanity mirrors, and dark wood"},
+      {"slug": "after_dark_private_office", "prompt": "stylized private office after dark with blinds, desk lamp, and city glow"},
+      {"slug": "fantasy_parlor_content_set", "prompt": "dark fantasy parlor with velvet chair, candlelight, antique wallpaper, and creator-shot framing"},
+      {"slug": "cosplay_hotel_mirror", "prompt": "hotel mirror cosplay try-on setup with costume pieces on chairs and warm vanity bulbs"}
+    ],
+    "hardcore_private_scenes": [
+      {"slug": "hardcore_bedroom_phone_tripod", "prompt": "private bedroom sex-content setup with a phone tripod, rumpled sheets, pillows, and warm lamps"},
+      {"slug": "hardcore_hotel_bed_city", "prompt": "luxury hotel suite with city lights, messy satin bedding, floor clothes, and low amber light"},
+      {"slug": "hardcore_mirror_bedroom", "prompt": "bedroom with a large mirror reflecting the explicit adult scene and a visible phone angle"},
+      {"slug": "hardcore_low_mattress_studio", "prompt": "private photo studio with a low mattress, fabric drapes, phone tripod, and controlled warm spotlighting"},
+      {"slug": "hardcore_velvet_room", "prompt": "private velvet room with dark curtains, soft cushions, scattered clothes, and warm red light"},
+      {"slug": "hardcore_shower_room", "prompt": "large private shower room with steam, wet tile, glass reflections, and warm reflected light"},
+      {"slug": "hardcore_lounge_couch", "prompt": "dim private lounge with a wide couch, scattered clothing, side lamps, and soft golden shadows"},
+      {"slug": "hardcore_floor_cushion_room", "prompt": "intimate room with floor cushions, silk sheets, low candles, and close vertical camera framing"},
+      {"slug": "hardcore_ring_light_bed", "prompt": "creator bedroom with ring light reflection, phone on tripod, bed sheets, and visible content setup"},
+      {"slug": "hardcore_bathroom_counter", "prompt": "private bathroom with counter mirror, wet towels, steam, and explicit creator-shot framing"},
+      {"slug": "hardcore_walk_in_closet_floor", "prompt": "mirrored walk-in closet floor with clothes scattered, warm bulbs, and a phone reflection"},
+      {"slug": "hardcore_car_backseat", "prompt": "parked private car backseat with tinted windows, dashboard glow, and tight phone-camera framing"}
+    ],
+    "hardcore_bed_scenes": [
+      {"slug": "bed_edge_close_contact", "prompt": "edge of a rumpled bed with pillows pushed aside, sheets pulled tight, and close phone-camera framing"},
+      {"slug": "low_bed_mirror_angle", "prompt": "low bed beside a full-length mirror with visible reflected bodies and warm lamps"},
+      {"slug": "hotel_bed_overhead", "prompt": "hotel bed arranged for an overhead phone shot with satin sheets and city light"},
+      {"slug": "floor_mattress_creator_set", "prompt": "floor mattress content setup with fabric drapes, ring light shadow, and scattered clothes"},
+      {"slug": "canopy_bed_explicit_set", "prompt": "canopy bed with sheer curtains, warm bedside light, and intimate full-body framing"},
+      {"slug": "velvet_bedroom_wide", "prompt": "velvet bedroom with wide bed, dark curtains, soft cushions, and warm red side light"}
+    ],
+    "hardcore_penetrative_scenes": [
+      {"slug": "penetration_mirror_bedroom", "prompt": "mirror-facing bedroom setup designed to show explicit body contact and the phone angle"},
+      {"slug": "penetration_edge_of_bed", "prompt": "edge-of-bed setup with hips near the camera, rumpled sheets, and warm lamp light"},
+      {"slug": "penetration_low_mattress", "prompt": "low mattress studio with side lighting, fabric drapes, and all bodies visible"},
+      {"slug": "penetration_couch_lounge", "prompt": "wide private couch with pillows pushed aside, scattered clothes, and golden shadows"},
+      {"slug": "penetration_shower_bench", "prompt": "wet shower bench with steam, tile reflections, and close explicit framing"},
+      {"slug": "penetration_floor_cushions", "prompt": "floor cushions and silk sheets arranged for full-body explicit contact"}
+    ],
+    "hardcore_oral_scenes": [
+      {"slug": "oral_bed_kneeling_close", "prompt": "bedside kneeling setup with pillows, warm lamps, and close mouth-level camera framing"},
+      {"slug": "oral_mirror_floor", "prompt": "mirror-facing floor setup with bodies reflected and phone held low"},
+      {"slug": "oral_couch_front_view", "prompt": "private couch arranged for front-view oral contact with soft side lamps"},
+      {"slug": "oral_shower_steam", "prompt": "steamy shower room with wet tile, glass reflections, and close explicit framing"},
+      {"slug": "oral_vanity_floor", "prompt": "vanity-room floor with mirror bulbs, scattered lingerie, and low phone-camera angle"},
+      {"slug": "oral_hotel_bed_close", "prompt": "hotel bed close-up setup with satin sheets, city light, and tight vertical framing"}
+    ],
+    "hardcore_anal_scenes": [
+      {"slug": "anal_rear_mirror_bed", "prompt": "bedroom mirror setup emphasizing rear-view body alignment and explicit contact"},
+      {"slug": "anal_bent_over_couch", "prompt": "wide private couch arranged for bent-over explicit contact and low camera angle"},
+      {"slug": "anal_edge_bed_low_angle", "prompt": "edge-of-bed low-angle setup with sheets pulled aside and hips near the lens"},
+      {"slug": "anal_shower_wall", "prompt": "wet shower wall with steam, tile reflections, and hard side lighting"},
+      {"slug": "anal_velvet_bench", "prompt": "private velvet bench with dark curtains, red light, and clear full-body framing"},
+      {"slug": "anal_floor_mattress_mirror", "prompt": "floor mattress beside a full-length mirror with both direct and reflected views"}
+    ],
+    "hardcore_threesome_scenes": [
+      {"slug": "threesome_wide_bedroom", "prompt": "wide bedroom setup with a large bed, mirror wall, phone tripod, and all three bodies visible"},
+      {"slug": "threesome_hotel_suite", "prompt": "hotel suite bed and couch area arranged for three adults and city-window light"},
+      {"slug": "threesome_floor_cushions", "prompt": "floor cushion room with silk sheets, low lamps, and enough space for three bodies"},
+      {"slug": "threesome_studio_mattress", "prompt": "private studio mattress with fabric drapes, ring light shadow, and three-person framing"},
+      {"slug": "threesome_shower_room", "prompt": "large shower room with wet tile, steam, glass reflections, and three-person spacing"},
+      {"slug": "threesome_velvet_lounge", "prompt": "private velvet lounge with wide couch, cushions, and warm red-gold light"}
+    ],
+    "hardcore_group_scenes": [
+      {"slug": "group_suite_wide_bed", "prompt": "large private suite with a wide bed, couch area, scattered clothes, and all participants visible"},
+      {"slug": "group_studio_mattress_room", "prompt": "private studio with multiple low mattresses, fabric drapes, ring lights, and full group visibility"},
+      {"slug": "group_velvet_orgy_room", "prompt": "private velvet orgy room with dark curtains, floor cushions, soft lamps, and open floor space"},
+      {"slug": "group_lounge_couches", "prompt": "dim private lounge with multiple couches, pillows, warm side lamps, and wide group framing"},
+      {"slug": "group_floor_pillow_room", "prompt": "large floor-pillow room with silk sheets, low candles, and overhead camera possibility"},
+      {"slug": "group_shower_spa_room", "prompt": "large private shower spa with wet tile, steam, benches, and space for multiple adults"},
+      {"slug": "group_rooftop_private_party", "prompt": "private rooftop after-party suite with glass railings, couches, and city lights"},
+      {"slug": "group_hotel_party_bedroom", "prompt": "messy hotel party bedroom with a king bed, side couch, bottles, and warm practical lights"},
+      {"slug": "group_backstage_private_room", "prompt": "private backstage green room with costume racks, couches, mirror bulbs, and scattered clothes"},
+      {"slug": "group_neon_loft_room", "prompt": "private neon loft with mattresses, glossy floor reflections, and wide explicit group composition"},
+      {"slug": "group_mirror_wall_suite", "prompt": "large mirror-wall suite with a wide bed, floor cushions, phone tripod, and enough space to reflect a full adult group"},
+      {"slug": "group_lacquer_mirror_lounge", "prompt": "wide black-lacquer mirror lounge with multiple couches, glossy reflections, warm rim light, and all participants visible"}
+    ],
+    "hardcore_climax_scenes": [
+      {"slug": "climax_bed_close_flash", "prompt": "rumpled bed close-up setup with direct phone flash, sheets, and visible fluid detail"},
+      {"slug": "climax_mirror_counter", "prompt": "mirror-facing vanity counter setup with phone reflection and explicit aftermath framing"},
+      {"slug": "climax_floor_sheets", "prompt": "floor sheets with pillows pushed aside, low lamp light, and close body-detail framing"},
+      {"slug": "climax_hotel_bed_flash", "prompt": "hotel bed with phone-flash lighting, messy satin sheets, and city light behind"},
+      {"slug": "climax_shower_tile", "prompt": "wet shower tile scene with steam, reflected light, and visible fluid detail"},
+      {"slug": "climax_velvet_couch", "prompt": "velvet couch with dark curtains, warm red light, and close explicit aftermath framing"}
+    ]
+  },
+  "pool_extensions": {
+    "group_scenes": [
+      {"slug": "private_suite_group_party", "prompt": "large private suite with a wide bed, couch area, scattered clothes, and warm party lighting"},
+      {"slug": "private_studio_group_mattresses", "prompt": "private studio with multiple low mattresses, fabric drapes, and wide group visibility"},
+      {"slug": "velvet_lounge_group_couches", "prompt": "private velvet lounge with multiple couches, pillows, and low red-gold light"},
+      {"slug": "rooftop_afterparty_suite", "prompt": "private rooftop after-party suite with glass railings, couches, and city lights"},
+      {"slug": "hotel_party_bedroom_group", "prompt": "messy hotel party bedroom with a king bed, side couch, bottles, and warm practical lights"},
+      {"slug": "neon_loft_group_room", "prompt": "private neon loft with glossy floor reflections, mattresses, and wide group composition"},
+      {"slug": "backstage_green_room_group", "prompt": "private backstage green room with costume racks, mirror bulbs, couches, and scattered clothes"},
+      {"slug": "shower_spa_group_room", "prompt": "large private shower spa room with benches, steam, wet tile, and multiple adults"}
+    ]
+  }
+}

categories/sexual_poses.json

@@ -10,6 +10,7 @@
       "style": "explicit consensual adult hardcore sex illustration, anatomically clear erotic comic pin-up style, adults only",
       "positive_suffix": "Use clear adult anatomy, visible sexual contact, intense body language, crisp comic linework, detailed hatching, warm erotic lighting, and tactile textured paper.",
       "negative_prompt": "minors, childlike appearance, teen, schoolgirl, incest, bestiality, non-consensual, coercion, rape, violence, injury, blood, gore, watermark",
+      "scene_pools": ["hardcore_private_scenes"],
       "prompt_template": "{subject_phrase}, all 21+ consenting adults: {style}. Cast: {cast_summary}. Role graph: {role_graph} Sexual pose: {item}. Setting: {scene}. Composition: {composition}. Facial expressions: {expression}. Make the scene explicit, hardcore, and anatomically clear, with visible genital contact and adult bodies only. {positive_suffix} Avoid: {negative_prompt}.",
       "caption_template": "{trigger}, {scene_kind}, {cast_summary}, {role_graph}, {item}, {scene}, {composition}, explicit consensual adult hardcore sex illustration",
       "expressions": [
@@ -84,6 +85,7 @@
           "slug": "penetrative_sex",
           "min_people": 2,
           "weight": 1.0,
+          "scene_pools": ["hardcore_penetrative_scenes", "hardcore_bed_scenes", "hardcore_mirror_scenes"],
           "item_templates": [
             "{penetration_act} in {position}, with {body_contact}, {intensity}, and {visibility}",
             "{position} while {penetration_act}, {hand_detail}, {mouth_detail}, and {visibility}",
@@ -248,6 +250,7 @@
           "slug": "oral_sex",
           "min_people": 2,
           "weight": 1.0,
+          "scene_pools": ["hardcore_oral_scenes", "hardcore_bed_scenes", "hardcore_mirror_scenes"],
           "item_templates": [
             "{oral_act} in {position}, with {hand_detail}, {expression_detail}, and {visibility}",
             "{position} featuring {oral_act}, {body_contact}, {saliva_detail}, and {climax_hint}",
@@ -380,6 +383,7 @@
           "slug": "anal_double_penetration",
           "min_people": 2,
           "weight": 1.0,
+          "scene_pools": ["hardcore_anal_scenes", "hardcore_bed_scenes", "hardcore_mirror_scenes"],
           "item_templates": [
             "{anal_act} in {position}, with {leg_detail}, {hand_detail}, and {visibility}",
             "{double_act} with {body_arrangement}, {intensity}, {mouth_detail}, and {visibility}",
@@ -584,6 +588,7 @@
           "slug": "threesomes",
           "min_people": 3,
           "weight": 1.0,
+          "scene_pools": ["hardcore_threesome_scenes", "hardcore_group_scenes", "hardcore_mirror_scenes"],
           "item_templates": [
             "{threesome_act} with {body_arrangement}, {oral_detail}, {penetration_detail}, and {visibility}",
             "{body_arrangement} while {threesome_act}, with {hand_detail}, {mouth_detail}, and {climax_hint}",
@@ -760,7 +765,9 @@
           "name": "Group sex and orgy",
           "slug": "group_sex_orgy",
           "min_people": 4,
+          "inherit_scenes": false,
           "weight": 1.0,
+          "scene_pools": ["hardcore_group_scenes"],
           "item_templates": [
             "{group_act} with {arrangement}, {contact_detail}, {fluid_detail}, and {visibility}",
             "{arrangement} featuring {group_act}, {oral_detail}, {penetration_detail}, and {intensity}",
@@ -928,6 +935,7 @@
           "slug": "cumshot_climax",
           "min_people": 1,
           "weight": 1.0,
+          "scene_pools": ["hardcore_climax_scenes", "hardcore_bed_scenes", "hardcore_mirror_scenes"],
           "item_templates": [
             "{climax_act} with {fluid_location}, {body_position}, {expression_detail}, and {visibility}",
             "{body_position} during {climax_act}, with {hand_detail}, {fluid_location}, and {fluid_detail}",

generate_prompt_batches.py

@@ -1331,9 +1331,10 @@ def _expand_scenes() -> list[tuple[str, str]]:
     additions: list[tuple[str, str]] = []
     for base_slug, base_description in bases:
         for mood_slug, mood_description in moods:
+            separator = ", " if mood_description.startswith("with ") else " "
             additions.append((
                 _scene_slug(f"{base_slug}_{mood_slug}"),
-                f"{base_description} {mood_description}",
+                f"{base_description}{separator}{mood_description}",
             ))
     additions.extend(
         [

krea_formatter.py

@@ -0,0 +1,380 @@
+from __future__ import annotations
+
+import json
+import re
+from typing import Any
+
+
+TRIGGER_CANDIDATES = (
+    "sxcpinup_coloredpencil",
+    "sxcppnl7",
+)
+
+PROMPT_FIELD_LABELS = (
+    "Ages",
+    "Body types",
+    "Cast",
+    "Scene",
+    "Setting",
+    "Pose",
+    "Sexual pose",
+    "Facial expression",
+    "Facial expressions",
+    "Clothing",
+    "Erotic outfit",
+    "Prop/detail",
+    "Composition",
+    "Role graph",
+    "Use",
+    "Avoid",
+)
+
+
+def _clean(value: Any) -> str:
+    text = "" if value is None else str(value)
+    text = text.replace("\n", " ")
+    text = re.sub(r"\s+", " ", text).strip()
+    text = re.sub(r"\s+([,.;:])", r"\1", text)
+    return text
+
+
+def _sentence(text: str) -> str:
+    text = _clean(text).strip(" ,;")
+    if not text:
+        return ""
+    text = text[:1].upper() + text[1:]
+    if text[-1] not in ".!?":
+        text += "."
+    return text
+
+
+def _paragraph(parts: list[str]) -> str:
+    return " ".join(part for part in (_sentence(part) for part in parts) if part)
+
+
+def _maybe_json(text: str) -> dict[str, Any] | None:
+    text = _clean(text)
+    if not text.startswith("{"):
+        return None
+    try:
+        value = json.loads(text)
+    except json.JSONDecodeError:
+        return None
+    return value if isinstance(value, dict) else None
+
+
+def _row_from_inputs(source_text: str, metadata_json: str, input_hint: str) -> tuple[dict[str, Any] | None, str]:
+    candidates: list[tuple[str, str]] = []
+    if input_hint in ("auto", "metadata_json"):
+        candidates.append((metadata_json, "metadata_json"))
+        candidates.append((source_text, "source_json"))
+    for text, method in candidates:
+        row = _maybe_json(text)
+        if row is not None:
+            return row, method
+    return None, "text"
+
+
+def _strip_trigger(text: str, preserve_trigger: bool) -> str:
+    text = _clean(text)
+    if preserve_trigger:
+        return text
+    for trigger in TRIGGER_CANDIDATES:
+        if text.lower().startswith(trigger.lower() + ","):
+            return text[len(trigger) + 1 :].strip(" ,")
+        if text.lower().startswith(trigger.lower() + "."):
+            return text[len(trigger) + 1 :].strip(" ,")
+    return text
+
+
+def _split_avoid(text: str) -> tuple[str, str]:
+    match = re.search(r"\bAvoid:\s*(.*)$", text)
+    if not match:
+        return text, ""
+    return text[: match.start()].strip(" ."), match.group(1).strip(" .")
+
+
+def _prompt_field(text: str, label: str) -> str:
+    text = _clean(text)
+    if not text:
+        return ""
+    labels = "|".join(re.escape(name) for name in PROMPT_FIELD_LABELS)
+    pattern = rf"{re.escape(label)}:\s*(.*?)(?=\. (?:{labels}):|\. Use\b|\. Avoid\b|$)"
+    match = re.search(pattern, text)
+    if not match:
+        return ""
+    return _clean(match.group(1)).rstrip(".")
+
+
+def _row_value(row: dict[str, Any], key: str, labels: tuple[str, ...] = ()) -> str:
+    value = _clean(row.get(key, ""))
+    if value:
+        return value
+    prompt = _clean(row.get("prompt", ""))
+    for label in labels:
+        value = _prompt_field(prompt, label)
+        if value:
+            return value
+    return ""
+
+
+def _single_caption_front(row: dict[str, Any]) -> dict[str, str]:
+    caption = _strip_trigger(_clean(row.get("caption")), False)
+    if not caption:
+        return {}
+    subject = _clean(row.get("primary_subject"))
+    age = _clean(row.get("age_band") or row.get("age"))
+    body = _clean(row.get("body_phrase"))
+    if not body:
+        body_type = _clean(row.get("body_type") or row.get("body"))
+        figure = _clean(row.get("figure"))
+        body = f"{body_type} figure with {figure}" if body_type and figure else f"{body_type} figure".strip()
+    front = f"{subject}, {age}, {body}, "
+    if subject in ("woman", "man") and age and body and caption.startswith(front):
+        try:
+            skin, hair, eyes, _rest = caption[len(front) :].split(", ", 3)
+        except ValueError:
+            return {}
+        return {"body_phrase": body, "skin": skin, "hair": hair, "eyes": eyes}
+    return {}
+
+
+def _combine_negative(*parts: str) -> str:
+    cleaned = [_clean(part).strip(" ,.") for part in parts if _clean(part).strip(" ,.")]
+    return ", ".join(cleaned)
+
+
+def _clean_age(age: Any) -> str:
+    return _clean(age)
+
+
+def _age_subject(row: dict[str, Any], fallback_subject: str = "adult person") -> str:
+    subject = _clean(row.get("subject_phrase") or row.get("primary_subject") or row.get("subject") or fallback_subject)
+    age = _clean_age(row.get("age_band") or row.get("age"))
+    if row.get("subject_type") == "configured_cast":
+        return _clean(row.get("subject_phrase") or subject)
+    if subject in ("woman", "man"):
+        if age:
+            return f"{age} {subject}" if "adult" in age.lower() else f"{age} adult {subject}"
+        return f"adult {subject}"
+    if age and "adult" not in subject.lower():
+        return f"{age} {subject}"
+    return subject or fallback_subject
+
+
+def _appearance_phrase(row: dict[str, Any]) -> str:
+    front = _single_caption_front(row)
+    parts = [
+        _row_value(row, "body_phrase") or front.get("body_phrase"),
+        _row_value(row, "skin") or front.get("skin"),
+        _row_value(row, "hair") or front.get("hair"),
+        _row_value(row, "eyes") or front.get("eyes"),
+    ]
+    return ", ".join(_clean(part) for part in parts if _clean(part))
+
+
+def _camera_phrase(row: dict[str, Any]) -> str:
+    directive = _clean(row.get("camera_directive"))
+    if directive:
+        return directive
+    config = row.get("camera_config")
+    if isinstance(config, dict):
+        mode = _clean(config.get("camera_mode")).replace("_", " ")
+        shot = _clean(config.get("shot_size")).replace("_", " ")
+        angle = _clean(config.get("angle")).replace("_", " ")
+        pieces = [piece for piece in (mode, shot, angle) if piece and piece != "auto" and piece != "standard"]
+        if pieces:
+            return "Camera framing uses " + ", ".join(pieces)
+    return ""
+
+
+def _style_phrase(row: dict[str, Any], style_mode: str) -> str:
+    if style_mode == "minimal":
+        return ""
+    if style_mode == "photographic":
+        return "realistic creator-shot photography with natural lighting, tactile skin and fabric detail, and clean social-media composition"
+    style = _clean(row.get("style"))
+    suffix = _clean(row.get("positive_suffix")) or _prompt_field(_clean(row.get("prompt")), "Use")
+    if style and suffix:
+        return f"{style}; {suffix}"
+    return style or suffix
+
+
+def _normal_row_to_krea(row: dict[str, Any], detail_level: str, style_mode: str) -> tuple[str, str]:
+    subject_type = _clean(row.get("subject_type"))
+    primary = _clean(row.get("primary_subject"))
+    item = _row_value(row, "item", ("Sexual pose", "Erotic outfit", "Clothing")) or _clean(row.get("custom_item"))
+    item = re.sub(r",?\s*(fashion editorial|resort) styling$", "", item, flags=re.IGNORECASE)
+    scene = _row_value(row, "scene_text", ("Setting", "Scene")) or _clean(row.get("scene"))
+    pose = _row_value(row, "pose", ("Sexual pose", "Pose"))
+    expression = _row_value(row, "expression", ("Facial expressions", "Facial expression"))
+    composition = re.sub(r"^vertical\s+", "", _row_value(row, "composition", ("Composition",)), flags=re.IGNORECASE)
+    camera = _camera_phrase(row)
+    style = _style_phrase(row, style_mode)
+
+    if subject_type == "configured_cast" or _clean(row.get("cast_summary")):
+        subject = _clean(row.get("subject_phrase") or primary or "adult sexual scene")
+        cast = _clean(row.get("cast_summary"))
+        role_graph = _clean(row.get("role_graph"))
+        parts = [
+            f"A consensual explicit adult scene with {subject}, all participants 21+ and visibly adult",
+            f"The cast includes {cast}" if cast else "",
+            role_graph,
+            f"The sexual action is {item}" if item else "",
+            f"The setting is {scene}" if scene else "",
+            f"Facial expressions are {expression}" if expression else "",
+            f"The image is framed as {composition}" if composition else "",
+            camera,
+            style if detail_level != "concise" else "",
+        ]
+        return _paragraph(parts), "metadata(configured_cast)"
+
+    if primary in ("woman", "man") or subject_type in ("woman", "man", "single_any"):
+        subject = _age_subject(row, "adult woman")
+        appearance = _appearance_phrase(row)
+        parts = [
+            f"A {subject}" if not subject.lower().startswith(("a ", "an ")) else subject,
+            f"with {appearance}" if appearance else "",
+            f"wearing {item}" if item else "",
+            f"{pose}" if pose else "",
+            f"with {expression}" if expression else "",
+            f"in {scene}" if scene else "",
+            f"framed as {composition}" if composition else "",
+            camera,
+            style if detail_level != "concise" else "",
+        ]
+        return _paragraph([", ".join(part for part in parts[:6] if part), *parts[6:]]), "metadata(single)"
+
+    subject = _age_subject(row, primary or "adult scene")
+    parts = [
+        f"{subject}",
+        f"featuring {item}" if item else "",
+        f"in {scene}" if scene else "",
+        f"with {expression}" if expression else "",
+        f"framed as {composition}" if composition else "",
+        camera,
+        style if detail_level != "concise" else "",
+    ]
+    return _paragraph(parts), "metadata(generic)"
+
+
+def _insta_pair_to_krea(row: dict[str, Any], detail_level: str, style_mode: str) -> tuple[str, str, str, str]:
+    descriptor = _clean(row.get("shared_descriptor"))
+    soft = row.get("softcore_row") if isinstance(row.get("softcore_row"), dict) else {}
+    hard = row.get("hardcore_row") if isinstance(row.get("hardcore_row"), dict) else {}
+    soft_camera = _clean(row.get("softcore_camera_directive")) or _camera_phrase(soft)
+    hard_camera = _clean(row.get("hardcore_camera_directive")) or _camera_phrase(hard)
+    soft_style = _style_phrase(soft, style_mode)
+    hard_style = _style_phrase(hard, style_mode)
+    options = row.get("options") if isinstance(row.get("options"), dict) else {}
+    soft_level = _clean(options.get("softcore_level")).replace("_", " ")
+    hard_level = _clean(options.get("hardcore_level")).replace("_", " ")
+    hard_cast = _clean(row.get("hardcore_women_count"))
+    hard_men = _clean(row.get("hardcore_men_count"))
+    hard_cast_text = _clean(hard.get("cast_summary")) or (
+        f"{hard_cast} adult women and {hard_men} adult men" if hard_cast or hard_men else ""
+    )
+
+    soft_parts = [
+        f"A visibly adult creator, {descriptor}",
+        f"shown in a {soft_level or 'softcore'} Insta/OF creator image",
+        f"wearing {soft.get('item')}" if soft.get("item") else "",
+        f"{soft.get('pose')}" if soft.get("pose") else "",
+        f"with {soft.get('expression')}" if soft.get("expression") else "",
+        f"in {soft.get('scene_text')}" if soft.get("scene_text") else "",
+        f"framed as {soft.get('composition')}" if soft.get("composition") else "",
+        soft_camera,
+        soft_style if detail_level != "concise" else "",
+    ]
+    hard_parts = [
+        f"The same visibly adult creator, {descriptor}, is the visually central woman in a consensual explicit adult {hard_level or 'hardcore'} scene",
+        f"all participants are 21+ and visibly adult; the cast includes {hard_cast_text}" if hard_cast_text else "all participants are 21+ and visibly adult",
+        _clean(hard.get("role_graph")),
+        f"The sexual action is {hard.get('item')}" if hard.get("item") else "",
+        f"set in {row.get('hardcore_row', {}).get('scene_text') or hard.get('scene_text')}" if hard.get("scene_text") else "",
+        f"with {hard.get('expression')}" if hard.get("expression") else "",
+        f"framed as {hard.get('composition')}" if hard.get("composition") else "",
+        hard_camera,
+        hard_style if detail_level != "concise" else "",
+    ]
+    return (
+        _paragraph(soft_parts),
+        _combine_negative(row.get("softcore_negative_prompt")),
+        _paragraph(hard_parts),
+        _combine_negative(row.get("hardcore_negative_prompt")),
+    )
+
+
+def _fallback_text_to_krea(
+    source_text: str,
+    preserve_trigger: bool,
+    detail_level: str,
+    style_mode: str,
+) -> tuple[str, str, str]:
+    positive, negative = _split_avoid(_strip_trigger(source_text, preserve_trigger))
+    positive = re.sub(r"\b(?:Scene|Setting):", "The setting is", positive)
+    positive = re.sub(r"\b(?:Pose|Sexual pose):", "The pose is", positive)
+    positive = re.sub(r"\bFacial expressions?:", "The facial expression is", positive)
+    positive = re.sub(r"\bComposition:", "The composition is", positive)
+    positive = re.sub(r"\bRole graph:", "The role choreography is", positive)
+    positive = re.sub(r"\bUse\b", "Use", positive)
+    positive = _clean(positive)
+    return _paragraph([positive]), negative, "text(fallback)"
+
+
+def format_krea2_prompt(
+    source_text: str,
+    metadata_json: str = "",
+    negative_prompt: str = "",
+    input_hint: str = "auto",
+    target: str = "auto",
+    detail_level: str = "balanced",
+    style_mode: str = "preserve",
+    preserve_trigger: bool = False,
+    extra_positive: str = "",
+    extra_negative: str = "",
+) -> dict[str, str]:
+    detail_level = detail_level if detail_level in ("concise", "balanced", "dense") else "balanced"
+    style_mode = style_mode if style_mode in ("preserve", "photographic", "minimal") else "preserve"
+    target = target if target in ("auto", "single", "softcore", "hardcore") else "auto"
+    row, method = _row_from_inputs(source_text, metadata_json, input_hint)
+    extracted_negative = ""
+
+    if row and row.get("mode") == "Insta/OF":
+        soft_prompt, soft_negative, hard_prompt, hard_negative = _insta_pair_to_krea(row, detail_level, style_mode)
+        selected = hard_prompt if target == "hardcore" else soft_prompt if target == "softcore" else soft_prompt
+        selected_negative = hard_negative if target == "hardcore" else soft_negative
+        if extra_positive.strip():
+            selected = f"{selected.rstrip()} {extra_positive.strip()}"
+            soft_prompt = f"{soft_prompt.rstrip()} {extra_positive.strip()}"
+            hard_prompt = f"{hard_prompt.rstrip()} {extra_positive.strip()}"
+        negative = _combine_negative(selected_negative, negative_prompt, extra_negative)
+        return {
+            "krea_prompt": selected,
+            "negative_prompt": negative,
+            "krea_softcore_prompt": soft_prompt,
+            "krea_hardcore_prompt": hard_prompt,
+            "softcore_negative_prompt": _combine_negative(soft_negative, extra_negative),
+            "hardcore_negative_prompt": _combine_negative(hard_negative, extra_negative),
+            "method": f"{method}:krea2(insta_of_pair)",
+        }
+
+    if row:
+        prompt, kind = _normal_row_to_krea(row, detail_level, style_mode)
+        extracted_negative = _clean(row.get("negative_prompt"))
+        method = f"{method}:krea2({kind})"
+    else:
+        prompt, extracted_negative, method = _fallback_text_to_krea(source_text, preserve_trigger, detail_level, style_mode)
+
+    if extra_positive.strip():
+        prompt = f"{prompt.rstrip()} {extra_positive.strip()}"
+    negative = _combine_negative(extracted_negative, negative_prompt, extra_negative)
+    return {
+        "krea_prompt": prompt,
+        "negative_prompt": negative,
+        "krea_softcore_prompt": "",
+        "krea_hardcore_prompt": "",
+        "softcore_negative_prompt": "",
+        "hardcore_negative_prompt": "",
+        "method": method,
+    }

prompt_builder.py

@@ -202,6 +202,14 @@ def _list_from(value: Any) -> list[Any]:
     return [value]
 
 
+def _is_false(value: Any) -> bool:
+    if isinstance(value, bool):
+        return value is False
+    if isinstance(value, str):
+        return value.strip().lower() in ("false", "0", "no", "off")
+    return False
+
+
 def _unique_extend(target: list[Any], additions: list[Any]) -> None:
     seen = set()
     for item in target:
@@ -554,6 +562,24 @@ def load_category_library() -> list[dict[str, Any]]:
     return categories
 
 
+def load_scene_pool_library() -> dict[str, list[Any]]:
+    pools: dict[str, list[Any]] = {}
+    for path in _json_files():
+        data = _read_json(path)
+        raw_pools = data.get("scene_pools", {})
+        if not raw_pools:
+            continue
+        if not isinstance(raw_pools, dict):
+            raise ValueError(f"scene_pools in {path} must be an object")
+        for name, entries in raw_pools.items():
+            pool_name = str(name).strip()
+            if not pool_name:
+                continue
+            pools.setdefault(pool_name, [])
+            _unique_extend(pools[pool_name], _list_from(entries))
+    return pools
+
+
 def _extension_targets() -> dict[str, tuple[list[Any], bool]]:
     return {
         "women_clothes": (g.WOMEN_CLOTHES, False),
@@ -1335,7 +1361,27 @@ def _subject_context(
 
 def _scene_pool(category: dict[str, Any], subcategory: dict[str, Any], item: Any, subject_type: str) -> list[Any]:
     fallback = g.GROUP_SCENES if subject_type in ("group", "configured_cast") else g.SCENES
-    return _list_from(_merged_field(category, subcategory, item, "scenes", fallback))
+    scene_entries: list[Any] = []
+    scene_pools = load_scene_pool_library()
+    item_source = item if isinstance(item, dict) else None
+    if item_source is not None and _is_false(item_source.get("inherit_scenes")):
+        sources = (item_source,)
+    elif _is_false(subcategory.get("inherit_scenes")):
+        sources = (subcategory, item_source)
+    else:
+        sources = (category, subcategory, item_source)
+    for source in sources:
+        if not isinstance(source, dict):
+            continue
+        if "scenes" in source:
+            _unique_extend(scene_entries, _list_from(source["scenes"]))
+        refs = _list_from(source.get("scene_pool")) + _list_from(source.get("scene_pools"))
+        for ref in refs:
+            ref_name = str(ref).strip()
+            if ref_name not in scene_pools:
+                raise ValueError(f"Unknown scene pool '{ref_name}'")
+            _unique_extend(scene_entries, scene_pools[ref_name])
+    return scene_entries or fallback
 
 
 def _pose_pool(category: dict[str, Any], subcategory: dict[str, Any], item: Any, subject_type: str, poses: str) -> list[Any]: