700 lines
29 KiB
Python
700 lines
29 KiB
Python
from __future__ import annotations
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import re
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from typing import Any
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try:
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from . import formatter_input as input_policy
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from . import route_metadata as route_metadata_policy
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from .krea_action_context import (
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is_close_foreplay_text as _is_close_foreplay_text,
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is_outercourse_text as _is_outercourse_text,
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normalize_hardcore_detail_density as _normalize_hardcore_detail_density,
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)
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from . import krea_configured_cast_formatter
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from . import krea_pair_formatter
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from .hardcore_text_cleanup import (
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sanitize_hardcore_axis_values as _sanitize_hardcore_axis_values,
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sanitize_hardcore_environment_anchors as _sanitize_hardcore_environment_anchors,
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)
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from .krea_cast import (
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cast_prose as _cast_prose,
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label_join as _label_join,
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lowercase_for_inline_join as _lowercase_for_inline_join,
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natural_label_text as _natural_label_text,
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prompt_cast_descriptors as _prompt_cast_descriptors,
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)
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from .krea_clothing import natural_clothing_state as _natural_clothing_state
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from .krea_action_positions import action_position_phrase as _action_position_phrase
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from .krea_actions import hardcore_action_sentence as _hardcore_action_sentence
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from .krea_pov import (
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filter_pov_labeled_clauses as _filter_pov_labeled_clauses,
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merge_labels as _merge_labels,
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pov_camera_phrase as _pov_camera_phrase,
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pov_composition_text as _pov_composition_text,
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pov_labels_from_value as _pov_labels_from_value,
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)
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from .krea_pov_actions import pov_action_phrase as _pov_action_phrase
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from .prompt_hygiene import sanitize_negative_text, sanitize_prose_text
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except ImportError: # Allows local smoke tests with `python -c`.
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import formatter_input as input_policy
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import route_metadata as route_metadata_policy
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from krea_action_context import (
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is_close_foreplay_text as _is_close_foreplay_text,
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is_outercourse_text as _is_outercourse_text,
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normalize_hardcore_detail_density as _normalize_hardcore_detail_density,
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)
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import krea_configured_cast_formatter
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import krea_pair_formatter
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from hardcore_text_cleanup import (
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sanitize_hardcore_axis_values as _sanitize_hardcore_axis_values,
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sanitize_hardcore_environment_anchors as _sanitize_hardcore_environment_anchors,
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)
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from krea_cast import (
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cast_prose as _cast_prose,
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label_join as _label_join,
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lowercase_for_inline_join as _lowercase_for_inline_join,
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natural_label_text as _natural_label_text,
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prompt_cast_descriptors as _prompt_cast_descriptors,
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)
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from krea_clothing import natural_clothing_state as _natural_clothing_state
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from krea_action_positions import action_position_phrase as _action_position_phrase
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from krea_actions import hardcore_action_sentence as _hardcore_action_sentence
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from krea_pov import (
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filter_pov_labeled_clauses as _filter_pov_labeled_clauses,
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merge_labels as _merge_labels,
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pov_camera_phrase as _pov_camera_phrase,
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pov_composition_text as _pov_composition_text,
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pov_labels_from_value as _pov_labels_from_value,
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)
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from krea_pov_actions import pov_action_phrase as _pov_action_phrase
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from prompt_hygiene import sanitize_negative_text, sanitize_prose_text
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TRIGGER_CANDIDATES = (
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"sxcpinup_coloredpencil",
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"sxcppnl7",
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)
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PROMPT_FIELD_LABELS = input_policy.prompt_field_labels()
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def _clean(value: Any) -> str:
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return input_policy.clean_text(value)
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def _is_false(value: Any) -> bool:
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if isinstance(value, bool):
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return value is False
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if isinstance(value, str):
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return value.strip().lower() in ("false", "0", "no", "off")
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return False
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def _expression_disabled(row: dict[str, Any]) -> bool:
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return bool(row.get("expression_disabled")) or _is_false(row.get("expression_enabled", True))
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def _sentence(text: str) -> str:
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text = _clean(text).strip(" ,;")
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if not text:
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return ""
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text = text[:1].upper() + text[1:]
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if text[-1] not in ".!?":
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text += "."
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return text
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def _paragraph(parts: list[str]) -> str:
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return " ".join(part for part in (_sentence(part) for part in parts) if part)
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def _formatter_hint_parts(*rows: dict[str, Any]) -> list[str]:
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hints: list[str] = []
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for row in rows:
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if not isinstance(row, dict):
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continue
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for hint in route_metadata_policy.row_formatter_hints(row, "krea"):
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hint = _clean(hint).strip(" .")
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if hint and hint not in hints:
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hints.append(hint)
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return hints
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def _append_formatter_hints(prompt: str, *rows: dict[str, Any]) -> str:
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hints = _formatter_hint_parts(*rows)
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if not hints:
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return prompt
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return _paragraph([prompt, *hints])
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def _with_indefinite_article(text: str) -> str:
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text = _clean(text)
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if not text or text.lower().startswith(("a ", "an ")):
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return text
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article = "an" if text[:1].lower() in "aeiou" else "a"
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return f"{article} {text}"
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def _maybe_json(text: str) -> dict[str, Any] | None:
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return input_policy.maybe_json(text)
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def _row_from_inputs(source_text: str, metadata_json: str, input_hint: str) -> tuple[dict[str, Any] | None, str]:
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return input_policy.row_from_inputs(source_text, metadata_json, input_hint)
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def _strip_trigger(text: str, preserve_trigger: bool) -> str:
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return input_policy.strip_trigger_prefix(text, TRIGGER_CANDIDATES, preserve_trigger=preserve_trigger)
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def _split_avoid(text: str) -> tuple[str, str]:
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return input_policy.split_avoid(text)
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def _prompt_field(text: str, label: str) -> str:
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return input_policy.prompt_field(text, label, field_labels=PROMPT_FIELD_LABELS)
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def _row_value(row: dict[str, Any], key: str, labels: tuple[str, ...] = ()) -> str:
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return input_policy.row_value(row, key, labels, field_labels=PROMPT_FIELD_LABELS)
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def _body_phrase(body: Any, figure_note: Any = "") -> str:
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body = _clean(body)
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figure_note = _clean(figure_note)
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if not body:
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return figure_note
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if not figure_note:
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return f"{body} figure"
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if "figure" in figure_note.lower():
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return f"{body} build and {figure_note}"
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return f"{body} figure with {figure_note}"
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def _single_caption_front(row: dict[str, Any]) -> dict[str, str]:
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caption = _strip_trigger(_clean(row.get("caption")), False)
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if not caption:
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return {}
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subject = _clean(row.get("primary_subject"))
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age = _clean(row.get("age_band") or row.get("age"))
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body = _clean(row.get("body_phrase"))
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if not body:
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body_type = _clean(row.get("body_type") or row.get("body"))
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figure = _clean(row.get("figure"))
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body = _body_phrase(body_type, figure)
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front = f"{subject}, {age}, {body}, "
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if subject in ("woman", "man") and age and body and caption.startswith(front):
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try:
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skin, hair, eyes, _rest = caption[len(front) :].split(", ", 3)
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except ValueError:
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return {}
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return {"body_phrase": body, "skin": skin, "hair": hair, "eyes": eyes}
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return {}
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def _combine_negative(*parts: str) -> str:
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cleaned = [_clean(part).strip(" ,.") for part in parts if _clean(part).strip(" ,.")]
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return ", ".join(cleaned)
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def _sanitize_scene_text_for_cast(text: Any, labels: list[str]) -> str:
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text = _clean(text)
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if not text:
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return ""
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if len(labels) < 3:
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text = re.sub(r"\s*(?:while|as)\s+another partner watches\b", "", text, flags=re.IGNORECASE)
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text = re.sub(r"\banother partner watches\b", "", text, flags=re.IGNORECASE)
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text = re.sub(r",?\s*\bone partner held between two bodies\b", "", text, flags=re.IGNORECASE)
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text = re.sub(r",?\s*\bthree bodies locked together\b", "", text, flags=re.IGNORECASE)
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text = re.sub(r",?\s*\bthree bodies\b", "", text, flags=re.IGNORECASE)
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text = re.sub(r"\bwith\s*,\s*", "with ", text, flags=re.IGNORECASE)
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text = re.sub(r"\bwhile blowjob\b", "during a blowjob", text, flags=re.IGNORECASE)
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text = re.sub(r"\bfeaturing blowjob\b", "featuring a blowjob", text, flags=re.IGNORECASE)
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text = re.sub(r"\s+,", ",", text)
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text = re.sub(r",\s*,", ",", text)
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text = re.sub(r"\s{2,}", " ", text).strip(" ,")
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return text
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def _composition_phrase(
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composition: Any,
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action: str = "",
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prefix: str = "framed as",
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detail_density: str = "balanced",
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) -> str:
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composition = _clean(composition)
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if not composition:
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return ""
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action_lower = _clean(action).lower()
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composition_lower = composition.lower()
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detail_density = _normalize_hardcore_detail_density(detail_density)
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if "first-person underview" in action_lower or "straddling the viewer's face" in action_lower:
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if any(token in composition_lower for token in ("mirror-reflected", "oral scene", "face and body visible")):
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return (
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f"{prefix} close first-person underview with the woman's thighs framing the camera and the oral contact centered"
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)
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if "pov viewer" in action_lower and any(
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token in action_lower
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for token in ("ass raised", "seen from behind", "on all fours", "bent forward", "face-down")
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):
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return (
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f"{prefix} first-person rear-view frame looking down at the woman's raised ass, with foreground hands and rear-entry contact readable"
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)
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oral_pose_tokens = (
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"kneeling oral",
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"side-lying oral",
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"spread-leg oral",
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"standing oral",
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"edge-of-bed oral",
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"face-sitting",
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"sixty-nine",
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"reclining cunnilingus",
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"straddled oral",
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"chair oral",
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)
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if "oral" in action_lower:
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composition_oral_tokens = [token for token in oral_pose_tokens if token in composition_lower]
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if composition_oral_tokens and not any(token in action_lower for token in composition_oral_tokens):
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match = re.search(r"\bwith\s+(.+)$", composition, flags=re.IGNORECASE)
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return f"framed with {match.group(1)}" if match else ""
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if _is_outercourse_text(action_lower):
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return f"{prefix} {composition}"
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position = _action_position_phrase(action)
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close_or_aftermath = any(
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token in composition_lower
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for token in ("close-up", "close crop", "tight", "direct-flash", "subscriber-view", "post-ejaculation", "aftermath")
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)
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if _is_close_foreplay_text(action_lower) and close_or_aftermath:
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return f"{prefix} {composition}, in one continuous first-person close-body frame"
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if position and close_or_aftermath:
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if detail_density == "compact":
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return f"{prefix} {composition}, with the {position} still readable"
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return f"{prefix} {composition}, keeping the {position} and action geography readable"
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return f"{prefix} {composition}"
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def _clean_age(age: Any) -> str:
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return _clean(age)
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def _age_detail_phrase(age: Any) -> str:
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text = _clean(age)
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text = re.sub(r"\s+adults?$", "", text).strip()
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return text.replace("-year-old", " years old")
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def _age_subject(row: dict[str, Any], fallback_subject: str = "adult person") -> str:
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subject = _clean(row.get("subject_phrase") or row.get("primary_subject") or row.get("subject") or fallback_subject)
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age = _clean_age(row.get("age_band") or row.get("age"))
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if row.get("subject_type") == "configured_cast":
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return _clean(row.get("subject_phrase") or subject)
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if subject in ("woman", "man"):
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if age:
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return f"{age} {subject}" if "adult" in age.lower() else f"{age} adult {subject}"
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return f"adult {subject}"
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if age and "adult" not in subject.lower():
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return f"{age} {subject}"
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return subject or fallback_subject
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def _appearance_phrase(row: dict[str, Any]) -> str:
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front = _single_caption_front(row)
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parts = [
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_row_value(row, "body_phrase") or front.get("body_phrase"),
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_row_value(row, "skin") or front.get("skin"),
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_row_value(row, "hair") or front.get("hair"),
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_row_value(row, "eyes") or front.get("eyes"),
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]
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return ", ".join(_clean(part) for part in parts if _clean(part))
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def _expression_phrase(expression: Any) -> str:
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expression = _clean(expression)
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if not expression:
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return ""
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if ";" in expression or re.search(
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r"\b(?:Woman|Man) [A-Z] has\b|\bthe (?:woman|man) has\b",
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expression,
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flags=re.IGNORECASE,
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):
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return f"Expressions: {expression}"
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return f"with {expression}"
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def _camera_phrase(row: dict[str, Any]) -> str:
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directive = _clean(row.get("camera_directive"))
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if directive:
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return directive
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config = row.get("camera_config")
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if isinstance(config, dict):
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detail = _clean(config.get("camera_detail"))
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if detail == "off" or _clean(config.get("camera_mode")) == "disabled":
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return ""
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custom = _clean(config.get("custom_camera_prompt"))
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if custom:
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base = _clean(config.get("camera_mode")).replace("_", " ")
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pieces = [piece for piece in (base, custom) if piece and piece != "standard"]
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return "Camera: " + ", ".join(pieces)
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mode = _clean(config.get("camera_mode")).replace("_", " ")
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shot = _clean(config.get("shot_size")).replace("_", " ")
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angle = _clean(config.get("angle")).replace("_", " ")
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pieces = [piece for piece in (mode, shot, angle) if piece and piece != "auto" and piece != "standard"]
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if pieces:
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return "Camera: " + ", ".join(pieces)
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return ""
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def _camera_scene_phrase(row: dict[str, Any]) -> str:
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return _clean(row.get("camera_scene_directive"))
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def _camera_phrase_from_config(config: Any) -> str:
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if not isinstance(config, dict):
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return ""
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detail = _clean(config.get("camera_detail"))
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if detail == "off" or _clean(config.get("camera_mode")) == "disabled":
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return ""
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custom = _clean(config.get("custom_camera_prompt"))
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if custom:
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base = _clean(config.get("camera_mode")).replace("_", " ")
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pieces = [piece for piece in (base, custom) if piece and piece != "standard"]
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return "Camera: " + ", ".join(pieces)
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values = [
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_clean(config.get("camera_mode")).replace("_", " "),
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_clean(config.get("shot_size")).replace("_", " "),
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_clean(config.get("angle")).replace("_", " "),
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_clean(config.get("lens")).replace("_", " "),
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_clean(config.get("distance")).replace("_", " "),
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_clean(config.get("orientation")).replace("_", " "),
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_clean(config.get("phone_visibility")).replace("_", " "),
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]
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pieces = [value for value in values if value and value not in ("auto", "standard")]
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if not pieces:
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return ""
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return "Camera: " + ", ".join(pieces)
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def _pair_camera_phrase(directive: Any, config: Any, row: dict[str, Any]) -> str:
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directive_text = _clean(directive)
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if directive_text:
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return directive_text
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if isinstance(config, dict) and (
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_clean(config.get("camera_detail")) == "off" or _clean(config.get("camera_mode")) == "disabled"
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):
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return ""
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return _camera_phrase_from_config(config) or _camera_phrase(row)
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def _style_phrase(row: dict[str, Any], style_mode: str) -> str:
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if style_mode == "minimal":
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return ""
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if style_mode == "photographic":
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return "realistic creator-shot photography with natural lighting, tactile skin and fabric detail, and clean social-media composition"
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style = _clean(row.get("style"))
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suffix = _clean(row.get("positive_suffix")) or _prompt_field(_clean(row.get("prompt")), "Use")
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if style and suffix:
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return f"{style}; {suffix}"
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return style or suffix
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def _couple_clothing_phrase(item: str) -> str:
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item = _clean(item)
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lower = item.lower()
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partner_text = re.sub(r"\bPartner ([AB]) wears\b", r"Partner \1 wearing", item)
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partner_text = re.sub(r"\bPartner ([AB]) has\b", r"Partner \1 with", partner_text)
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if lower.startswith("partner a "):
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return f"The outfits show {partner_text}"
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if lower.startswith(("two ", "paired ", "coordinated ")):
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return f"The outfits are {partner_text}"
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return f"The couple wears {item}"
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def _krea_configured_cast_dependencies() -> krea_configured_cast_formatter.KreaConfiguredCastDependencies:
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return krea_configured_cast_formatter.KreaConfiguredCastDependencies(
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clean=_clean,
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prompt_field=_prompt_field,
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sanitize_hardcore_environment_anchors=_sanitize_hardcore_environment_anchors,
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sanitize_hardcore_axis_values=_sanitize_hardcore_axis_values,
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sanitize_scene_text_for_cast=_sanitize_scene_text_for_cast,
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normalize_hardcore_detail_density=_normalize_hardcore_detail_density,
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row_action_family=route_metadata_policy.row_action_family,
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hardcore_action_sentence=_hardcore_action_sentence,
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pov_action_phrase=_pov_action_phrase,
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pov_labels_from_value=_pov_labels_from_value,
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merge_labels=_merge_labels,
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cast_prose_omit=lambda text, omit_labels: _cast_prose(text, omit_labels=omit_labels),
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filter_pov_labeled_clauses=_filter_pov_labeled_clauses,
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natural_label_text=_natural_label_text,
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pov_composition_text=_pov_composition_text,
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pov_camera_phrase=lambda labels: _pov_camera_phrase(labels),
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expression_phrase=_expression_phrase,
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composition_phrase=_composition_phrase,
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paragraph=_paragraph,
|
|
)
|
|
|
|
|
|
def _krea_configured_cast_request(
|
|
row: dict[str, Any],
|
|
detail_level: str,
|
|
style_mode: str,
|
|
primary: str,
|
|
item: str,
|
|
scene: str,
|
|
expression: str,
|
|
composition: str,
|
|
source_composition: str,
|
|
camera: str,
|
|
camera_scene: str,
|
|
style: str,
|
|
) -> krea_configured_cast_formatter.KreaConfiguredCastRequest:
|
|
return krea_configured_cast_formatter.KreaConfiguredCastRequest(
|
|
row=row,
|
|
detail_level=detail_level,
|
|
style_mode=style_mode,
|
|
primary=primary,
|
|
item=item,
|
|
scene=scene,
|
|
expression=expression,
|
|
composition=composition,
|
|
source_composition=source_composition,
|
|
camera=camera,
|
|
camera_scene=camera_scene,
|
|
style=style,
|
|
)
|
|
|
|
|
|
def _krea_configured_cast_request_from_row(
|
|
row: dict[str, Any],
|
|
detail_level: str,
|
|
style_mode: str,
|
|
) -> krea_configured_cast_formatter.KreaConfiguredCastRequest:
|
|
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$", "", item, flags=re.IGNORECASE)
|
|
scene = _row_value(row, "scene_text", ("Setting", "Scene")) or _clean(row.get("scene"))
|
|
expression = ""
|
|
if not _expression_disabled(row):
|
|
expression = _row_value(row, "character_expression_text") or _row_value(row, "expression", ("Facial expressions", "Facial expression"))
|
|
composition = re.sub(r"^vertical\s+", "", _row_value(row, "composition", ("Composition",)), flags=re.IGNORECASE)
|
|
source_composition = re.sub(
|
|
r"^vertical\s+",
|
|
"",
|
|
_clean(row.get("source_composition")) or composition,
|
|
flags=re.IGNORECASE,
|
|
)
|
|
camera = _camera_phrase(row)
|
|
camera_scene = _camera_scene_phrase(row)
|
|
style = _style_phrase(row, style_mode)
|
|
return _krea_configured_cast_request(
|
|
row,
|
|
detail_level,
|
|
style_mode,
|
|
primary,
|
|
item,
|
|
scene,
|
|
expression,
|
|
composition,
|
|
source_composition,
|
|
camera,
|
|
camera_scene,
|
|
style,
|
|
)
|
|
|
|
|
|
def _normal_row_to_krea(row: dict[str, Any], detail_level: str, style_mode: str) -> tuple[str, str]:
|
|
subject_type = _clean(row.get("subject_type"))
|
|
if subject_type == "configured_cast" or _clean(row.get("cast_summary")):
|
|
return krea_configured_cast_formatter.format_configured_cast(
|
|
_krea_configured_cast_request_from_row(row, detail_level, style_mode),
|
|
_krea_configured_cast_dependencies(),
|
|
)
|
|
|
|
primary = _clean(row.get("primary_subject"))
|
|
item = _row_value(row, "item", ("Sexual pose", "Erotic outfit", "Clothing")) or _clean(row.get("custom_item"))
|
|
item = re.sub(r",?\s*(fashion editorial|resort) styling$", "", 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 = ""
|
|
if not _expression_disabled(row):
|
|
expression = _row_value(row, "character_expression_text") or _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)
|
|
camera_scene = _camera_scene_phrase(row)
|
|
style = _style_phrase(row, style_mode)
|
|
|
|
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 "",
|
|
camera_scene,
|
|
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 "",
|
|
camera_scene,
|
|
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 "",
|
|
camera_scene,
|
|
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 _krea_pair_format_dependencies() -> krea_pair_formatter.KreaPairFormatDependencies:
|
|
return krea_pair_formatter.KreaPairFormatDependencies(
|
|
clean=_clean,
|
|
prompt_cast_descriptors=_prompt_cast_descriptors,
|
|
pair_camera_phrase=_pair_camera_phrase,
|
|
camera_scene_phrase=_camera_scene_phrase,
|
|
style_phrase=_style_phrase,
|
|
sanitize_hardcore_environment_anchors=_sanitize_hardcore_environment_anchors,
|
|
sanitize_hardcore_axis_values=_sanitize_hardcore_axis_values,
|
|
sanitize_scene_text_for_cast=_sanitize_scene_text_for_cast,
|
|
normalize_hardcore_detail_density=_normalize_hardcore_detail_density,
|
|
row_action_family=route_metadata_policy.row_action_family,
|
|
hardcore_action_sentence=_hardcore_action_sentence,
|
|
pov_action_phrase=_pov_action_phrase,
|
|
pov_labels_from_value=_pov_labels_from_value,
|
|
merge_labels=_merge_labels,
|
|
cast_prose_omit=lambda text, omit_labels: _cast_prose(text, omit_labels=omit_labels),
|
|
label_join=_label_join,
|
|
filter_pov_labeled_clauses=_filter_pov_labeled_clauses,
|
|
natural_label_text=_natural_label_text,
|
|
expression_disabled=_expression_disabled,
|
|
expression_phrase=_expression_phrase,
|
|
pov_camera_phrase=lambda labels: _pov_camera_phrase(labels),
|
|
pov_soft_camera_phrase=lambda labels: _pov_camera_phrase(labels, softcore=True),
|
|
pov_composition_text=_pov_composition_text,
|
|
natural_clothing_state=_natural_clothing_state,
|
|
composition_phrase=_composition_phrase,
|
|
paragraph=_paragraph,
|
|
combine_negative=_combine_negative,
|
|
)
|
|
|
|
|
|
def _insta_pair_to_krea(row: dict[str, Any], detail_level: str, style_mode: str) -> tuple[str, str, str, str]:
|
|
return krea_pair_formatter.format_insta_pair(
|
|
krea_pair_formatter.KreaPairFormatRequest(
|
|
row=row,
|
|
detail_level=detail_level,
|
|
style_mode=style_mode,
|
|
),
|
|
_krea_pair_format_dependencies(),
|
|
)
|
|
|
|
|
|
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)
|
|
soft_row = row.get("softcore_row") if isinstance(row.get("softcore_row"), dict) else {}
|
|
hard_row = row.get("hardcore_row") if isinstance(row.get("hardcore_row"), dict) else {}
|
|
soft_prompt = _append_formatter_hints(soft_prompt, row, soft_row)
|
|
hard_prompt = _append_formatter_hints(hard_prompt, row, hard_row)
|
|
if extra_positive.strip():
|
|
soft_prompt = f"{soft_prompt.rstrip()} {extra_positive.strip()}"
|
|
hard_prompt = f"{hard_prompt.rstrip()} {extra_positive.strip()}"
|
|
soft_prompt = sanitize_prose_text(soft_prompt, triggers=TRIGGER_CANDIDATES)
|
|
hard_prompt = sanitize_prose_text(hard_prompt, triggers=TRIGGER_CANDIDATES)
|
|
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
|
|
negative = sanitize_negative_text(_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": sanitize_negative_text(_combine_negative(soft_negative, extra_negative)),
|
|
"hardcore_negative_prompt": sanitize_negative_text(_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)
|
|
prompt = _append_formatter_hints(prompt, row)
|
|
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()}"
|
|
prompt = sanitize_prose_text(prompt, triggers=TRIGGER_CANDIDATES)
|
|
negative = sanitize_negative_text(_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,
|
|
}
|