from __future__ import annotations

import json
import re
from typing import Any


TRIGGER_CANDIDATES = (
    "sxcpinup_coloredpencil",
    "sxcppnl7",
)

PROMPT_FIELD_LABELS = (
    "Ages",
    "Body types",
    "Cast",
    "Cast descriptors",
    "Characters",
    "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 _with_indefinite_article(text: str) -> str:
    text = _clean(text)
    if not text or text.lower().startswith(("a ", "an ")):
        return text
    article = "an" if text[:1].lower() in "aeiou" else "a"
    return f"{article} {text}"


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 _body_phrase(body: Any, figure_note: Any = "") -> str:
    body = _clean(body)
    figure_note = _clean(figure_note)
    if not body:
        return figure_note
    if not figure_note:
        return f"{body} figure"
    if "figure" in figure_note.lower():
        return f"{body} build and {figure_note}"
    return f"{body} figure with {figure_note}"


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 = _body_phrase(body_type, figure)
    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 _prompt_cast_descriptors(text: str) -> str:
    return _clean(text).replace("Woman A / primary creator:", "Woman A:")


def _cast_entries(text: str) -> list[tuple[str, str]]:
    text = _prompt_cast_descriptors(text)
    entries: list[tuple[str, str]] = []
    for part in text.split(";"):
        part = _clean(part)
        match = re.match(r"^((?:Woman|Man) [A-Z]):\s*(.+)$", part)
        if match:
            entries.append((match.group(1), _clean(match.group(2))))
    return entries


def _label_join(labels: list[str]) -> str:
    labels = [_clean(label) for label in labels if _clean(label)]
    if not labels:
        return "the named adults"
    if set(labels) == {"Woman A", "Man A"}:
        return "the woman and man"
    if len(labels) == 1:
        if labels[0] == "Woman A":
            return "the woman"
        if labels[0] == "Man A":
            return "the man"
        return labels[0]
    if len(labels) == 2:
        return f"{labels[0]} and {labels[1]}"
    return f"{', '.join(labels[:-1])}, and {labels[-1]}"


def _natural_label_text(text: Any, labels: list[str]) -> str:
    text = _clean(text)
    if not text:
        return ""
    if set(labels) == {"Woman A", "Man A"}:
        text = re.sub(r"\bWoman A\b", "the woman", text)
        text = re.sub(r"\bMan A\b", "the man", text)
    elif labels == ["Woman A"]:
        text = re.sub(r"\bWoman A\b", "the woman", text)
    elif labels == ["Man A"]:
        text = re.sub(r"\bMan A\b", "the man", text)
    return text


def _cast_prose(text: str, central_label: str = "Woman A") -> tuple[str, list[str]]:
    entries = _cast_entries(text)
    if not entries:
        return (f"{central_label} is {_clean(text)}" if _clean(text) else "", [])
    labels = [label for label, _descriptor in entries]
    if labels == ["Woman A"]:
        return _with_indefinite_article(entries[0][1]), labels
    if labels == ["Man A"]:
        return _with_indefinite_article(entries[0][1]), labels
    if set(labels) == {"Woman A", "Man A"} and len(labels) == 2:
        by_label = {label: descriptor for label, descriptor in entries}
        return f"{_with_indefinite_article(by_label['Woman A'])} alongside {_with_indefinite_article(by_label['Man A'])}", labels
    sentences = []
    for label, descriptor in entries:
        sentences.append(f"{label} is {descriptor}.")
    if central_label in labels:
        sentences.append(f"{central_label} is the central subject.")
    return " ".join(sentences), labels


def _sanitize_scene_text_for_cast(text: Any, labels: list[str]) -> str:
    text = _clean(text)
    if not text:
        return ""
    if len(labels) < 3:
        text = re.sub(r"\s*(?:while|as)\s+another partner watches\b", "", text, flags=re.IGNORECASE)
        text = re.sub(r"\banother partner watches\b", "", text, flags=re.IGNORECASE)
        text = re.sub(r",?\s*\bone partner held between two bodies\b", "", text, flags=re.IGNORECASE)
        text = re.sub(r",?\s*\bthree bodies locked together\b", "", text, flags=re.IGNORECASE)
        text = re.sub(r",?\s*\bthree bodies\b", "", text, flags=re.IGNORECASE)
        text = re.sub(r"\bwith\s*,\s*", "with ", text, flags=re.IGNORECASE)
    text = re.sub(r"\bwhile blowjob\b", "during a blowjob", text, flags=re.IGNORECASE)
    text = re.sub(r"\bfeaturing blowjob\b", "featuring a blowjob", text, flags=re.IGNORECASE)
    text = re.sub(r"\s+,", ",", text)
    text = re.sub(r",\s*,", ",", text)
    text = re.sub(r"\s{2,}", " ", text).strip(" ,")
    return text


def _natural_clothing_state(text: Any) -> str:
    text = _clean(text)
    if not text:
        return ""
    text = re.sub(r"^Clothing state:\s*", "", text, flags=re.IGNORECASE)
    match = re.match(
        r"^(.*?)\b(?:softcore|teaser) outfit is (.*?)(?: for the (?:hardcore|sex) scene)?;\s*(?:softcore visual reference|teaser outfit detail):\s*(.*?)\.?$",
        text,
        flags=re.IGNORECASE,
    )
    if match:
        owner = _natural_label_text(match.group(1).strip(" 's"), ["Woman A", "Man A"]).strip() or "the woman"
        state = _clean(match.group(2)).lower()
        outfit = _clean(match.group(3)).rstrip(".")
        if "fully nude" in state:
            return f"{owner.capitalize()} is fully nude, with the removed {outfit} visible nearby"
        if "nude-adjacent" in state:
            return f"{owner.capitalize()} is partly nude, with the {outfit} slipping off and no abstract clothing-reference wording"
        if "partially removed" in state or "pushed aside" in state:
            return f"{owner.capitalize()}'s {outfit} is pushed aside and partly removed, exposing the sexual contact clearly"
        if "keeps" in state:
            return f"{owner.capitalize()} keeps the {outfit} on while the sexual contact stays visible"
    text = re.sub(r";\s*(?:softcore visual reference|teaser outfit detail):\s*", ". Visual clothing state: ", text, flags=re.IGNORECASE)
    text = text.replace("softcore outfit", "outfit")
    text = text.replace("teaser outfit", "outfit")
    text = text.replace("hardcore scene", "sex scene")
    return text


def _axis_values_text(axis_values: Any) -> str:
    if not isinstance(axis_values, dict):
        return ""
    priority = (
        "position",
        "body_position",
        "body_arrangement",
        "arrangement",
        "angle",
        "surface",
        "body_contact",
        "leg_detail",
        "oral_act",
        "oral_detail",
        "penetration_act",
        "penetration_detail",
        "anal_act",
        "double_act",
        "threesome_act",
        "group_act",
    )
    parts = [_clean(axis_values.get(key)) for key in priority if _clean(axis_values.get(key))]
    return " ".join(parts)


def _position_context_text(role_graph: str, hard_item: str, composition: str = "", axis_values: Any = None) -> str:
    return " ".join(
        _clean(part).lower()
        for part in (role_graph, hard_item, composition, _axis_values_text(axis_values))
        if _clean(part)
    )


def _mentions_ass(text: str) -> bool:
    return bool(
        re.search(
            r"\bass\b|ass[- ](?:up|raised|exposed|lifted)|spread cheeks|lower back and ass|cum (?:on|dripping from) ass|pussy, ass|ass and",
            text,
        )
    )


def _mentions_rear_entry(text: str) -> bool:
    return bool(
        re.search(
            r"ass[- ](?:up|raised|exposed|lifted|stretched)|penis entering ass|cum (?:on|dripping from) ass|spread cheeks|lower back and ass|pussy, ass|rear[- ]entry",
            text,
        )
    )


def _hardcore_pose_anchor(role_graph: str, hard_item: str, composition: str = "", axis_values: Any = None) -> str:
    text = _position_context_text(role_graph, hard_item, composition, axis_values)
    item_text = " ".join(part for part in (_clean(hard_item).lower(), _axis_values_text(axis_values).lower()) if part)
    if not text:
        return ""
    if "double penetration" in text or "vaginal and anal penetration" in text or "front-and-back" in text:
        if "face-down ass-up" in text:
            return "face-down rear-entry double-penetration pose"
        if "doggy style" in text or "doggy-style" in text:
            return "doggy-style double-penetration pose"
        if "bent-over" in text:
            return "bent-over double-penetration pose"
        if "spooning anal" in text or "side-lying anal" in text:
            return "side-lying double-penetration pose"
        if "bed-edge" in text or "edge-of-bed" in text:
            return "bed-edge front-and-back double-penetration pose"
        if "standing anal" in text or "standing supported" in text:
            return "standing supported front-and-back double-penetration pose"
        if "kneeling anal" in text:
            return "kneeling rear-entry double-penetration pose"
        if "standing supported" in text:
            return "standing supported front-and-back double-penetration pose"
        if "kneeling" in text:
            return "kneeling front-and-back double-penetration pose"
        return "front-and-back double-penetration pose"
    if "sixty-nine" in text:
        return "sixty-nine oral pose"
    if "face-sitting" in text:
        return "face-sitting oral pose"
    if "cunnilingus" in text or "pussy licking" in text or "mouth on her pussy" in text:
        if "reclining" in text:
            return "reclining cunnilingus pose"
        if "straddled" in text:
            return "straddled cunnilingus pose"
        return "open-thigh cunnilingus pose"
    if "oral" in text or "blowjob" in text or "penis in her mouth" in text or "penis in mouth" in text:
        if "side-lying oral position" in item_text:
            return "side-lying oral pose"
        if "spread-leg oral position" in item_text:
            return "spread-leg oral pose"
        if "edge-of-bed oral position" in item_text:
            return "edge-of-bed oral pose"
        if "standing oral position" in item_text:
            return "standing oral pose"
        if "chair oral position" in item_text:
            return "chair oral pose"
        if "kneeling oral position" in item_text or "kneeling" in text:
            return "kneeling oral pose"
        if "standing" in text:
            return "standing oral pose"
        if "side-lying" in text:
            return "side-lying oral pose"
        if "edge-of-bed" in text or "bed-edge" in text:
            return "edge-of-bed oral pose"
        if "spread-leg" in text:
            return "spread-leg oral pose"
        if "chair oral" in text:
            return "chair oral pose"
        return "mouth-to-genitals oral pose"
    if "anal" in text or _mentions_rear_entry(text) or "rear-entry" in text:
        if "face-down ass-up" in text:
            return "face-down ass-up rear-entry anal pose"
        if "doggy style" in text or "doggy-style" in text:
            return "doggy-style anal pose"
        if "bed-edge" in text or "edge-of-bed" in text:
            return "bed-edge rear-entry anal pose"
        if "bent-over" in text:
            return "bent-over rear-entry anal pose"
        if "spooning anal" in text or "side-lying anal" in text:
            return "side-lying rear-entry anal pose"
        if "kneeling anal" in text:
            return "kneeling rear-entry anal pose"
        if "standing anal" in text:
            return "standing rear-entry anal pose"
        if "doggy" in text:
            return "doggy-style anal pose"
        return "rear-entry anal pose"
    positions = (
        "missionary",
        "reverse cowgirl",
        "cowgirl",
        "doggy style",
        "standing sex",
        "spooning sex",
        "edge-of-bed",
        "kneeling straddle",
        "lotus",
        "bent-over",
    )
    for position in positions:
        if position in text:
            return f"{position.replace('doggy style', 'doggy-style')} pose"
    if "threesome" in text or "three-body" in text:
        return "three-body explicit sex pose"
    if "group" in text or "orgy" in text:
        return "multi-body explicit sex pose"
    if "penetrat" in text or "thrust" in text:
        return "hip-aligned penetrative sex pose"
    return ""


def _hardcore_pose_arrangement(anchor: str, role_graph: str, hard_item: str, composition: str = "", axis_values: Any = None) -> str:
    text = _position_context_text(anchor, f"{role_graph} {hard_item}", composition, axis_values)
    if not text:
        return ""
    mixed_woman_man = "the woman" in text and "the man" in text
    is_double = "double-penetration" in text or "double penetration" in text

    def cast_phrase(mixed: str, generic: str) -> str:
        return mixed if mixed_woman_man else generic

    def double_tail() -> str:
        return ", with the toy aligned at the second penetration point" if "toy" in text else ", with the second penetration point aligned"

    if "sixty-nine" in text:
        return cast_phrase(
            "with the woman and man inverted head-to-hips so both mouths align with genitals",
            "with both bodies inverted head-to-hips so both mouths align with genitals",
        )
    if "face-sitting" in text:
        return cast_phrase(
            "with the man lying back while the woman straddles his face",
            "with one partner lying back while the other straddles the face",
        )
    if "reclining cunnilingus" in text or "spread-leg oral" in text:
        if "takes the man's penis" in text or "penis in her mouth" in text:
            return cast_phrase(
                "with the man seated with legs apart and the woman positioned at his hips",
                "with the receiver seated with legs apart and the giver positioned at the hips",
            )
        return cast_phrase(
            "with the woman lying back, thighs spread, and the man positioned between her legs",
            "with the receiving partner lying back, thighs spread, and the giver positioned between the legs",
        )
    if "straddled cunnilingus" in text or "straddled oral" in text:
        return cast_phrase(
            "with the woman straddling above the man's mouth and her thighs framing his face",
            "with the receiver straddling above the giver's mouth",
        )
    if "edge-of-bed oral" in text:
        if "takes the man's penis" in text or "penis in her mouth" in text:
            return cast_phrase(
                "with the man at the bed edge and the woman kneeling at his hips",
                "with the receiver at the bed edge and the giver positioned at hip height",
            )
        return cast_phrase(
            "with the woman lying at the bed edge and the man positioned between her open thighs",
            "with the receiver lying at the bed edge and the giver positioned between open thighs",
        )
    if "standing oral" in text:
        if "takes the man's penis" in text or "penis in her mouth" in text:
            return cast_phrase(
                "with the man standing and the woman kneeling in front of his hips",
                "with the receiver standing and the giver kneeling at hip height",
            )
        return cast_phrase(
            "with the woman standing braced and the man kneeling between her thighs",
            "with the receiver standing braced and the giver kneeling between the thighs",
        )
    if "chair oral" in text:
        if "takes the man's penis" in text or "penis in her mouth" in text:
            return cast_phrase(
                "with the man seated in the chair and the woman kneeling between his legs at hip level",
                "with the receiver seated in the chair and the giver kneeling between the legs at hip level",
            )
        return cast_phrase(
            "with one partner seated in a chair and the other kneeling between the open thighs",
            "with the receiver seated in a chair and the giver kneeling between the open thighs",
        )
    if "side-lying oral" in text:
        return "with both bodies lying on their sides and mouth aligned to genitals"
    if "kneeling oral" in text:
        if "takes the man's penis" in text or "penis in her mouth" in text:
            return cast_phrase(
                "with the woman kneeling in front of the man's hips, her mouth at penis level",
                "with the giver kneeling in front of the receiver's hips",
            )
        if "mouth on her pussy" in text or "uses his mouth on" in text:
            return cast_phrase(
                "with the man kneeling between the woman's open thighs, his mouth at her pussy",
                "with the giver kneeling between the receiver's open thighs",
            )
        return "with the giver kneeling at the receiver's hips"
    if "reverse cowgirl" in text:
        return cast_phrase(
            "with the man lying on his back under the woman while she straddles his hips facing away",
            "with the lower partner lying on their back while the upper partner straddles them facing away",
        )
    if "cowgirl" in text:
        return cast_phrase(
            "with the man lying on his back under the woman while she straddles his hips on top",
            "with the lower partner lying on their back while the upper partner straddles their hips on top",
        )
    if "missionary" in text:
        return cast_phrase(
            "with the woman lying on her back under the man, legs open around his hips",
            "with the receiving partner lying on their back under the penetrating partner, legs open around the hips",
        )
    if "lotus" in text:
        return cast_phrase(
            "with the man seated upright and the woman seated in his lap facing him, legs wrapped around his hips",
            "with one partner seated upright and the other seated in their lap facing them, legs wrapped around the hips",
        )
    if "kneeling straddle" in text:
        return cast_phrase(
            "with the woman straddling the man's kneeling lap, both torsos upright and hips pressed together",
            "with one partner straddling the other's kneeling lap, torsos upright and hips pressed together",
        )
    if "doggy-style" in text:
        return cast_phrase(
            f"with the woman on all fours and the man positioned behind her at hip level{double_tail() if is_double else ''}",
            f"with the receiving partner on all fours and the penetrating partner positioned behind at hip level{double_tail() if is_double else ''}",
        )
    if "face-down" in text:
        return cast_phrase(
            f"with the woman face-down, hips raised, and the man positioned behind her{double_tail() if is_double else ''}",
            f"with the receiving partner face-down, hips raised, and the penetrating partner positioned behind{double_tail() if is_double else ''}",
        )
    if "bent-over" in text:
        return cast_phrase(
            f"with the woman bent forward at the waist and the man positioned behind her{double_tail() if is_double else ''}",
            f"with the receiving partner bent forward at the waist and the penetrating partner positioned behind{double_tail() if is_double else ''}",
        )
    if "spooning" in text or ("side-lying" in text and "oral" not in text):
        return cast_phrase(
            f"with both lying on their sides and the man positioned behind the woman{double_tail() if is_double else ''}",
            f"with both bodies lying on their sides and the penetrating partner positioned behind{double_tail() if is_double else ''}",
        )
    if "edge-of-bed" in text or "bed-edge" in text:
        return cast_phrase(
            f"with the woman lying at the bed edge, hips at the edge, and the man kneeling between her legs{double_tail() if is_double else ''}",
            f"with the receiver lying at the bed edge, hips at the edge, and the penetrating partner kneeling between the legs{double_tail() if is_double else ''}",
        )
    if "standing" in text:
        return cast_phrase(
            f"with the woman braced standing and the man aligned at her hips{double_tail() if is_double else ''}",
            f"with both partners standing and the penetrating partner aligned at the receiver's hips{double_tail() if is_double else ''}",
        )
    if "kneeling" in text and ("anal" in text or "rear-entry" in text):
        return cast_phrase(
            f"with the woman kneeling forward and the man positioned behind her{double_tail() if is_double else ''}",
            f"with the receiving partner kneeling forward and the penetrating partner positioned behind{double_tail() if is_double else ''}",
        )
    if "double-penetration" in text or "double penetration" in text:
        if "toy" in text:
            return cast_phrase(
                "with the woman on all fours, the man behind her, and the toy aligned at the second penetration point",
                "with the receiving body on all fours and the toy aligned at the second penetration point",
            )
        if "from the front" in text:
            return cast_phrase(
                "with the woman held between the man behind her and a second partner in front",
                "with the receiving body held between one partner behind and a second partner in front",
            )
        return cast_phrase(
            "with the woman held in a front-and-back position so both contact points are visible",
            "with the central body held in a front-and-back position so both contact points are visible",
        )
    if "anal" in text or _mentions_rear_entry(text) or "rear-entry" in text:
        return cast_phrase(
            "with the woman's hips raised, ass exposed, and the man positioned behind her",
            "with the receiving partner's hips raised and the penetrating partner positioned behind",
        )
    if "cunnilingus" in text or "mouth on her pussy" in text or "pussy licking" in text:
        return cast_phrase(
            "with the woman's thighs open and the man's mouth pressed to her pussy",
            "with the receiver's thighs open and the giver's mouth pressed to genitals",
        )
    if "oral" in text or "blowjob" in text or "penis in her mouth" in text or "penis in mouth" in text:
        if "takes the man's penis in her mouth" in text or "penis in her mouth" in text:
            return cast_phrase(
                "with the woman's mouth at the man's hips",
                "with the giver's mouth positioned at the receiver's hips",
            )
        return "with mouth and genitals aligned clearly"
    if "threesome" in text or "three-body" in text:
        return "with all three adult bodies clearly placed around the central subject"
    if "group" in text or "orgy" in text:
        return "with each adult body readable in the shared sex act"
    if "penetrat" in text or "thrust" in text:
        return "with hips aligned and legs open around the contact point"
    return ""


def _hardcore_item_detail(hard_item: str) -> str:
    text = _clean(hard_item).rstrip(".")
    if not text:
        return ""
    text = re.sub(r"^hardcore\s+", "", text, flags=re.IGNORECASE)
    text = re.sub(r"^explicit\s+", "", text, flags=re.IGNORECASE)
    text = re.sub(r"^(?:orgasm|climax)\s+scene:\s*", "", text, flags=re.IGNORECASE)
    text = re.sub(r"^(?:mouth-to-genitals|double-contact sex|adult group pile|sex pile)\s+pose:\s*", "", text, flags=re.IGNORECASE)
    text = re.sub(r"^(?:oral|threesome|orgy)\s+scene\s+with\s+", "", text, flags=re.IGNORECASE)
    text = re.sub(r"^(?:threesome|orgy)\s+pose:\s*", "", text, flags=re.IGNORECASE)
    act_patterns = (
        r"(?:penis and toy|toy and strap-on|toy-assisted|front-and-back|hardcore|deep|kneeling|standing supported)?\s*double penetration",
        r"toy-assisted vaginal and anal penetration at the same time",
        r"vaginal and anal penetration at the same time",
        r"one penis in pussy and one penis in ass",
        r"anal penetration with visible genital contact",
        r"rear-entry anal penetration",
        r"anal sex with spread cheeks",
        r"ass stretched around a penis",
        r"penis entering ass",
        r"deep anal sex",
        r"bent-over anal sex",
        r"hardcore anal thrusting",
        r"vaginal penetration with visible genital contact",
        r"penis entering pussy",
        r"pussy stretched around a penis",
        r"deep vaginal sex",
        r"explicit penetrative sex",
        r"penetrative sex",
        r"hardcore vaginal thrusting",
        r"full-body penetrative sex",
        r"close-contact vaginal sex",
        r"fellatio with penis in mouth",
        r"deepthroat blowjob",
        r"blowjob",
        r"penis sucking with visible saliva",
        r"cunnilingus with tongue on pussy",
        r"face-sitting cunnilingus",
        r"pussy licking with thighs spread",
        r"oral sex with tongue and fingers",
        r"mouth on genitals with explicit contact",
        r"sixty-nine oral sex",
    )
    act_pattern = "|".join(act_patterns)
    position_pattern = (
        r"missionary position|cowgirl position|reverse cowgirl position|doggy style position|"
        r"standing sex position|spooning sex position|edge-of-bed position|kneeling straddle position|"
        r"lotus sex position|bent-over position|kneeling oral position|face-sitting position|"
        r"sixty-nine position|edge-of-bed oral position|standing oral position|reclining cunnilingus position|"
        r"straddled oral position|side-lying oral position|spread-leg oral position|chair oral position"
    )
    text = re.sub(
        rf"^({position_pattern})\s+(?:while|with|featuring)\s+(?:{act_pattern})\s*,?\s*",
        r"\1, ",
        text,
        flags=re.IGNORECASE,
    )
    text = re.sub(
        rf"^(?:{act_pattern})\s*(?:in|from|on|with|while|featuring)?\s*",
        "",
        text,
        flags=re.IGNORECASE,
    )
    text = re.sub(r"^(?:position|pose)\s+", "", text, flags=re.IGNORECASE)
    text = re.sub(r"^with\s+", "", text, flags=re.IGNORECASE)
    text = re.sub(r"\bwith with\b", "with", text, flags=re.IGNORECASE)
    text = re.sub(r",\s*with\s+", ", ", text, flags=re.IGNORECASE)
    text = re.sub(r",\s+and\s+", ", ", text)
    text = re.sub(r"\s*,\s*", ", ", text).strip(" ,;")
    return _clean(text)


def _dedupe_hardcore_detail(detail: str, anchor: str) -> str:
    detail = _clean(detail)
    anchor_lower = anchor.lower()
    duplicate_phrases = {
        "front-and-back": (r"front-and-back contact",),
        "side-lying oral": (r"side-lying oral position",),
        "kneeling oral": (r"kneeling oral position",),
        "face-sitting": (r"face-sitting position",),
        "sixty-nine": (
            r"sixty-nine position",
            r"sixty-nine oral sex",
            r"kneeling oral position",
            r"face-sitting position",
            r"edge-of-bed oral position",
            r"standing oral position",
            r"reclining cunnilingus position",
            r"straddled oral position",
            r"side-lying oral position",
            r"spread-leg oral position",
            r"chair oral position",
        ),
        "edge-of-bed oral": (r"edge-of-bed oral position",),
        "standing oral": (r"standing oral position",),
        "spread-leg oral": (r"spread-leg oral position",),
        "chair oral": (r"chair oral position",),
        "reclining cunnilingus": (r"reclining cunnilingus position",),
        "straddled cunnilingus": (r"straddled oral position", r"straddled cunnilingus position"),
        "open-thigh cunnilingus": (r"reclining cunnilingus position", r"straddled cunnilingus position"),
        "bent-over": (r"bent-over position",),
        "face-down": (r"face-down ass-up position",),
        "missionary": (r"missionary position",),
        "reverse cowgirl": (r"reverse cowgirl position",),
        "cowgirl": (r"cowgirl position",),
        "doggy-style": (r"doggy style position",),
        "edge-of-bed": (r"edge-of-bed position",),
        "lotus": (r"lotus sex position",),
        "standing sex": (r"standing sex position",),
        "spooning": (r"spooning sex position", r"spooning anal position"),
    }
    for anchor_token, phrases in duplicate_phrases.items():
        if anchor_token in anchor_lower:
            for phrase in phrases:
                detail = re.sub(rf"\b{phrase}\b,?\s*", "", detail, flags=re.IGNORECASE)
    detail = re.sub(r"^\s*,\s*", "", detail)
    detail = re.sub(r",\s*,", ",", detail)
    return _clean(detail).strip(" ,;")


def _is_climax_text(*parts: str) -> bool:
    text = " ".join(_clean(part).lower() for part in parts if _clean(part))
    return any(
        token in text
        for token in (
            "cumshot",
            "ejaculation",
            "post-orgasm",
            "post-climax",
            "orgasm aftermath",
            "orgasm scene",
            "orgasm during",
            "shared climax",
            "hardcore climax",
            "external cumshot",
            "visible external ejaculation",
            "climaxes on",
            "climax lands",
        )
    )


def _climax_role_graph(role_graph: str, hard_item: str, axis_values: Any = None) -> str:
    role_graph = _clean(role_graph).rstrip(".")
    text = " ".join(part.lower() for part in (role_graph, _clean(hard_item), _axis_values_text(axis_values)) if part)
    if "the woman" not in text or "the man" not in text:
        return role_graph
    if "lying between two partners" in text or "lies between" in text:
        return "the woman lies between two partners, the man under her hips and another partner over her torso as visible semen lands on her body"
    if "held between front-and-back partners" in text:
        return "the woman is held between the man behind her and another partner in front of her as visible semen lands across her body"
    if "kneeling between standing partners" in text:
        return "the woman kneels between standing partners gathered around her face and torso for visible ejaculation"
    if "side-lying with thighs parted" in text:
        return "the woman lies on her side with thighs parted while the man kneels beside her hips and ejaculates semen across her thighs and pussy"
    if "sitting on the edge of the bed" in text:
        return "the woman sits on the edge of the bed with knees spread while the man stands close between her legs and ejaculates semen across her body"
    if "lying at the bed edge with thighs open" in text:
        return "the woman lies at the bed edge with thighs open while the man kneels between her legs and ejaculates semen across her pussy and thighs"
    if "reclining with thighs open" in text or "lying on the back with legs spread" in text:
        return "the woman lies on her back with thighs open while the man kneels between her legs and ejaculates semen across her pussy and thighs"
    if "on all fours with hips raised" in text:
        return "the woman is on all fours with hips raised while the man is positioned behind her and ejaculates semen across her ass, thighs, and lower back"
    if "face-down ass-up" in text:
        return "the woman lies face-down with ass raised while the man is positioned behind her and ejaculates semen across her lower back and ass"
    if "bent over with ass raised" in text or "bent over" in text:
        return "the woman bends forward with hips raised while the man stands behind her with visible semen across her lower back, ass, and thighs"
    if "kneeling with mouth open" in text:
        return "the woman kneels in front of the man at hip height as he ejaculates semen onto her face, lips, and chest"
    if "kneeling in front of a standing partner" in text:
        return "the woman kneels in front of the man at hip height while he stands over her for visible ejaculation"
    if "standing with cum on the body" in text:
        return "the woman stands braced in front of the man while he stands close at hip level and ejaculates semen across her body"
    if "squatting on top of a partner" in text:
        return "the woman squats over the man's hips while the man lies on his back under her and ejaculates semen onto her body"
    if "reverse cowgirl over a partner's hips" in text:
        return "the woman straddles the man's hips facing away while the man lies on his back under her and ejaculates semen onto her body"
    if "straddles" in text or "straddling a partner" in text or "straddling a partner's hips" in text or "shared climax after penetration" in text:
        return "the woman straddles the man's hips while the man lies on his back under her and ejaculates semen onto her body"
    if "seated in a partner's lap facing them" in text:
        return "the woman sits in the man's lap facing him, legs wrapped around his hips as he ejaculates semen across her body"
    if "lower back" in text or "cum dripping from ass" in text or "cum on lower back" in text or _mentions_rear_entry(text):
        return "the woman bends forward with hips raised while the man stands behind her with visible semen across her lower back, ass, and thighs"
    if "cum on face" in text or "cum on tongue" in text or "cum on lips" in text or "cum on tongue and chin" in text:
        return "the woman kneels in front of the man at hip height as he ejaculates semen onto her face, lips, and chest"
    if (
        "cum dripping from pussy" in text
        or "arousal dripping from pussy" in text
        or "open thighs" in text
    ):
        return "the woman lies on her back with thighs open while the man kneels between her legs and ejaculates semen across her pussy and thighs"
    if role_graph:
        return role_graph
    return "the woman lies on her back with thighs open while the man kneels between her legs and ejaculates semen across her body"


def _dedupe_climax_detail(detail: str, role_graph: str) -> str:
    detail = _clean(detail)
    lower = role_graph.lower()
    patterns: list[str] = []
    if "lies on her back" in lower:
        patterns.extend((r"lying on the back with legs spread and hips lifted", r"reclining with thighs open", r"lying on the back with legs spread"))
        detail = re.sub(r"\bcum on lower back and ass\b", "cum across thighs and pussy", detail, flags=re.IGNORECASE)
        detail = re.sub(r"\bcum (?:on|dripping from) ass\b", "cum across thighs and pussy", detail, flags=re.IGNORECASE)
    if "straddles" in lower:
        patterns.extend(
            (
                r"straddling a partner's hips in cowgirl position",
                r"reverse cowgirl over a partner's hips",
                r"straddling a partner",
                r"squatting on top of a partner",
            )
        )
    if "squats over" in lower:
        patterns.append(r"squatting on top of a partner")
    if "sits in the man's lap" in lower:
        patterns.append(r"seated in a partner's lap facing them")
    if "bends forward" in lower:
        patterns.append(r"bent over with ass raised")
    if "on all fours" in lower:
        patterns.append(r"on all fours with hips raised")
    if "face-down" in lower:
        patterns.append(r"face-down ass-up on the mattress")
    if "lies on her side" in lower:
        patterns.append(r"side-lying with thighs parted")
    if "sits on the edge" in lower:
        patterns.append(r"sitting on the edge of the bed")
    if "bed edge" in lower:
        patterns.append(r"lying at the bed edge with thighs open")
    if "kneels in front" in lower:
        patterns.extend((r"kneeling with mouth open", r"kneeling in front of a standing partner"))
    if "stands braced" in lower:
        patterns.append(r"standing with cum on the body")
    for pattern in patterns:
        detail = re.sub(rf"\b{pattern}\b,?\s*", "", detail, flags=re.IGNORECASE)
    if not any(token in lower for token in ("face", "mouth", "lips", "tongue")):
        detail = re.sub(r"\bsaliva and cum mixed on the mouth\b", "visible semen on skin", detail, flags=re.IGNORECASE)
        detail = re.sub(r"\bcum on tongue and chin\b", "visible semen on skin", detail, flags=re.IGNORECASE)
        detail = re.sub(r"\bcum on face and lips\b", "visible semen on skin", detail, flags=re.IGNORECASE)
    detail = re.sub(r",\s*,", ",", detail)
    detail = re.sub(r"\bwith\s*,\s*", "with ", detail, flags=re.IGNORECASE)
    detail = re.sub(r"^with\s+", "", detail, flags=re.IGNORECASE)
    detail = re.sub(r"^and\s+", "", detail, flags=re.IGNORECASE)
    return _clean(detail).strip(" ,;")


def _hardcore_action_sentence(role_graph: str, hard_item: str, composition: str = "", axis_values: Any = None) -> str:
    role_graph = _clean(role_graph).rstrip(".")
    hard_item = _clean(hard_item).rstrip(".")
    role_graph = re.sub(
        r"\bthe man penetrates the woman while a toy adds a second point of contact\b",
        "the man's penis thrusts into the woman while a toy adds a second penetration point",
        role_graph,
        flags=re.IGNORECASE,
    )
    role_graph = re.sub(
        r"\bthe man thrusts his penis into the woman while a toy adds a second penetration point\b",
        "the man's penis thrusts into the woman while a toy adds the second penetration point",
        role_graph,
        flags=re.IGNORECASE,
    )
    role_graph = re.sub(
        r"\bthe man thrusts his penis into the woman\b",
        "the man's penis thrusts into the woman",
        role_graph,
        flags=re.IGNORECASE,
    )
    role_graph = re.sub(
        r"\bthe man penetrates the woman anally\b",
        "the man's penis thrusts into the woman's ass",
        role_graph,
        flags=re.IGNORECASE,
    )
    role_graph = re.sub(
        r"\bthe man thrusts his penis into the woman's ass\b",
        "the man's penis thrusts into the woman's ass",
        role_graph,
        flags=re.IGNORECASE,
    )
    role_graph = re.sub(
        r"\bthe man penetrates the woman\b",
        "the man's penis thrusts into the woman",
        role_graph,
        flags=re.IGNORECASE,
    )
    role_graph = re.sub(
        r"\bthe woman and the man are in mutual oral contact with mouth-to-genital contact visible\b",
        "the woman has the man's penis in her mouth while the man uses his mouth on her pussy",
        role_graph,
        flags=re.IGNORECASE,
    )
    role_graph = re.sub(
        r"\bthe woman gives oral to the man\b",
        "the woman takes the man's penis in her mouth",
        role_graph,
        flags=re.IGNORECASE,
    )
    is_climax = _is_climax_text(role_graph, hard_item, composition, _axis_values_text(axis_values))
    if is_climax:
        role_graph = _climax_role_graph(role_graph, hard_item, axis_values)
    detail = _hardcore_item_detail(hard_item)
    anchor = _hardcore_pose_anchor(role_graph, hard_item, composition, axis_values)
    if "double-penetration" in anchor.lower() and "toy" in role_graph.lower():
        role_graph = re.sub(
            r"\s+while a toy adds (?:the|a) second penetration point\b",
            "",
            role_graph,
            flags=re.IGNORECASE,
        )
    if is_climax:
        anchor = ""
        detail = _dedupe_climax_detail(detail, role_graph)
    else:
        detail = _dedupe_hardcore_detail(detail, anchor) if anchor else detail
    arrangement = _hardcore_pose_arrangement(anchor, role_graph, hard_item, composition, axis_values)
    anchor_phrase = _with_indefinite_article(anchor) if anchor else ""
    if arrangement and anchor_phrase:
        anchor_phrase = f"{anchor_phrase} {arrangement}"
    if role_graph and anchor_phrase:
        sentence = f"In {anchor_phrase}, {role_graph}"
    elif role_graph:
        sentence = role_graph
    elif detail and anchor_phrase:
        sentence = f"In {anchor_phrase}, {detail}"
        detail = ""
    else:
        sentence = detail or hard_item
        detail = ""
    if detail:
        sentence = f"{sentence}; {detail}"
    return sentence


def _composition_phrase(composition: Any, action: str = "", prefix: str = "framed as") -> str:
    composition = _clean(composition)
    if not composition:
        return ""
    action_lower = _clean(action).lower()
    composition_lower = composition.lower()
    oral_pose_tokens = (
        "kneeling oral",
        "side-lying oral",
        "spread-leg oral",
        "standing oral",
        "edge-of-bed oral",
        "face-sitting",
        "sixty-nine",
        "reclining cunnilingus",
        "straddled oral",
        "chair oral",
    )
    if "oral" in action_lower:
        composition_oral_tokens = [token for token in oral_pose_tokens if token in composition_lower]
        if composition_oral_tokens and not any(token in action_lower for token in composition_oral_tokens):
            match = re.search(r"\bwith\s+(.+)$", composition, flags=re.IGNORECASE)
            return f"framed with {match.group(1)}" if match else ""
    return f"{prefix} {composition}"


def _clean_age(age: Any) -> str:
    return _clean(age)


def _age_detail_phrase(age: Any) -> str:
    text = _clean(age)
    text = re.sub(r"\s+adults?$", "", text).strip()
    return text.replace("-year-old", " years old")


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):
        detail = _clean(config.get("camera_detail"))
        if detail == "off" or _clean(config.get("camera_mode")) == "disabled":
            return ""
        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: " + ", ".join(pieces)
    return ""


def _camera_phrase_from_config(config: Any) -> str:
    if not isinstance(config, dict):
        return ""
    detail = _clean(config.get("camera_detail"))
    if detail == "off" or _clean(config.get("camera_mode")) == "disabled":
        return ""
    values = [
        _clean(config.get("camera_mode")).replace("_", " "),
        _clean(config.get("shot_size")).replace("_", " "),
        _clean(config.get("angle")).replace("_", " "),
        _clean(config.get("lens")).replace("_", " "),
        _clean(config.get("distance")).replace("_", " "),
        _clean(config.get("orientation")).replace("_", " "),
        _clean(config.get("phone_visibility")).replace("_", " "),
    ]
    pieces = [value for value in values if value and value not in ("auto", "standard")]
    if not pieces:
        return ""
    return "Camera: " + ", ".join(pieces)


def _pair_camera_phrase(directive: Any, config: Any, row: dict[str, Any]) -> str:
    directive_text = _clean(directive)
    if directive_text:
        return directive_text
    if isinstance(config, dict) and (
        _clean(config.get("camera_detail")) == "off" or _clean(config.get("camera_mode")) == "disabled"
    ):
        return ""
    return _camera_phrase_from_config(config) or _camera_phrase(row)


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 _couple_clothing_phrase(item: str) -> str:
    item = _clean(item)
    lower = item.lower()
    partner_text = re.sub(r"\bPartner ([AB]) wears\b", r"Partner \1 wearing", item)
    partner_text = re.sub(r"\bPartner ([AB]) has\b", r"Partner \1 with", partner_text)
    if lower.startswith("partner a "):
        return f"The outfits show {partner_text}"
    if lower.startswith(("two ", "paired ", "coordinated ")):
        return f"The outfits are {partner_text}"
    return f"The couple wears {item}"


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"))
        try:
            women_count = int(row.get("women_count") or 0)
            men_count = int(row.get("men_count") or 0)
        except (TypeError, ValueError):
            women_count = men_count = 0
        cast_descriptor_text = (
            _clean(row.get("cast_descriptor_text"))
            or _prompt_field(_clean(row.get("prompt")), "Characters")
            or _prompt_field(_clean(row.get("prompt")), "Cast descriptors")
        )
        cast_prose, cast_labels = _cast_prose(cast_descriptor_text)
        if not cast_labels and women_count == 1 and men_count == 1:
            cast_labels = ["Woman A", "Man A"]
        role_graph = _sanitize_scene_text_for_cast(row.get("role_graph"), cast_labels)
        item = _sanitize_scene_text_for_cast(item, cast_labels)
        role_graph = _natural_label_text(role_graph, cast_labels)
        item = _natural_label_text(item, cast_labels)
        axis_values = row.get("item_axis_values") if isinstance(row.get("item_axis_values"), dict) else {}
        action = _hardcore_action_sentence(role_graph, item, composition, axis_values)
        parts = [
            action,
            cast_prose,
            f"A consensual explicit adult scene with {subject}" if not action else "",
            f"The cast includes {cast}" if cast and not cast_prose and not (women_count == 1 and men_count == 1) else "",
            f"The setting is {scene}" if scene else "",
            f"Facial expressions are {expression}" if expression else "",
            _composition_phrase(composition, action, "The image is framed as"),
            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 = [
            _with_indefinite_article(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)"

    if subject_type == "couple" or primary in ("two women", "two men", "a woman and a man"):
        subject = _clean(row.get("subject_phrase") or primary or "adult couple")
        if subject == "woman and man":
            subject = "a woman and a man"
        ages = _age_detail_phrase(_row_value(row, "age", ("Ages",)) or row.get("age_band"))
        body = _row_value(row, "body", ("Body types",)) or _clean(row.get("body_type"))
        parts = [
            f"An adult couple: {subject}, all visibly adult",
            f"Age detail: {ages}" if ages else "",
            f"Body types: {body}" if body else "",
            _couple_clothing_phrase(item) if item else "",
            f"The pose is {pose}" if pose 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(couple)"

    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"))
    cast_descriptors = row.get("shared_cast_descriptors")
    if isinstance(cast_descriptors, list):
        cast_descriptor_text = "; ".join(_clean(item) for item in cast_descriptors if _clean(item))
    else:
        cast_descriptor_text = _clean(cast_descriptors)
    cast_descriptor_text = _prompt_cast_descriptors(cast_descriptor_text)
    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 = _pair_camera_phrase(row.get("softcore_camera_directive"), row.get("softcore_camera_config"), soft)
    hard_camera = _pair_camera_phrase(row.get("hardcore_camera_directive"), row.get("hardcore_camera_config"), 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("_", " ")
    same_room = options.get("continuity") == "same_creator_same_room"
    hard_scene = soft.get("scene_text") if same_room and soft.get("scene_text") else hard.get("scene_text")
    hard_composition = hard.get("composition")
    soft_cast_descriptor_text = (
        cast_descriptor_text
        if options.get("softcore_cast") == "same_as_hardcore"
        else f"Woman A: {descriptor}"
    )
    soft_cast_prose, soft_labels = _cast_prose(soft_cast_descriptor_text)
    hard_cast_prose, hard_labels = _cast_prose(cast_descriptor_text)
    hard_item = _sanitize_scene_text_for_cast(hard.get("item"), hard_labels)
    hard_role_graph = _sanitize_scene_text_for_cast(hard.get("role_graph"), hard_labels)
    hard_item = _natural_label_text(hard_item, hard_labels)
    hard_role_graph = _natural_label_text(hard_role_graph, hard_labels)
    hard_axis_values = hard.get("item_axis_values") if isinstance(hard.get("item_axis_values"), dict) else {}
    hard_action = _hardcore_action_sentence(hard_role_graph, hard_item, hard_composition, hard_axis_values)
    same_soft_cast = options.get("softcore_cast") == "same_as_hardcore"
    soft_cast_presence = (
        f"{_label_join(soft_labels)} are together in a non-explicit teaser pose, with no sex act or genital contact"
        if same_soft_cast
        else "The image focuses on the woman alone"
    )
    partner_styling = row.get("softcore_partner_styling")
    if isinstance(partner_styling, dict):
        outfits = partner_styling.get("outfits")
        partner_outfit_text = "; ".join(_clean(item) for item in outfits if _clean(item)) if isinstance(outfits, list) else ""
        partner_pose = _clean(partner_styling.get("pose"))
    else:
        partner_outfit_text = ""
        partner_pose = ""
    partner_outfit_text = _natural_label_text(partner_outfit_text, soft_labels)

    soft_parts = [
        soft_cast_prose,
        soft_cast_presence,
        partner_outfit_text,
        partner_pose,
        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 = [
        hard_action,
        _natural_clothing_state(row.get("hardcore_clothing_state")),
        hard_cast_prose,
        f"set in {hard_scene}" if hard_scene else "",
        f"with {hard.get('expression')}" if hard.get("expression") else "",
        _composition_phrase(hard_composition, hard_action),
        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,
    }