Extract character appearance policy
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@@ -0,0 +1,268 @@
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from __future__ import annotations
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import random
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from typing import Any
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try:
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from . import character_config as character_policy
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from . import character_profile as character_profile_policy
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from . import character_slot as character_slot_policy
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from . import generate_prompt_batches as g
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from . import seed_config as seed_policy
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except ImportError: # Allows local smoke tests with top-level imports.
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import character_config as character_policy
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import character_profile as character_profile_policy
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import character_slot as character_slot_policy
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import generate_prompt_batches as g
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import seed_config as seed_policy
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def _choose(rng: random.Random, items: list[Any]) -> Any:
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return items[rng.randrange(len(items))]
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def slot_softcore_outfit(slot: dict[str, Any] | None, rng: random.Random | None = None) -> str:
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if not slot:
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return ""
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outfit = character_policy.slot_value(slot.get("softcore_outfit"))
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if outfit:
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return outfit
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if rng is None:
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return ""
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return character_policy.characteristic_choice(
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character_policy.parse_characteristics_config(slot.get("characteristics")),
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"softcore_outfits",
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rng,
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)
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def slot_hardcore_clothing(slot: dict[str, Any] | None, rng: random.Random | None = None) -> str:
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if not slot:
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return ""
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clothing = character_policy.slot_value(slot.get("hardcore_clothing"))
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if clothing:
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return clothing
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if rng is None:
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return ""
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return character_policy.characteristic_choice(
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character_policy.parse_characteristics_config(slot.get("characteristics")),
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"hardcore_clothing",
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rng,
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)
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def hair_descriptor_from_slot(base_hair: Any, slot: dict[str, Any], rng: random.Random) -> str:
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hair_config = character_policy.parse_hair_config(slot.get("hair_config"))
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color_choice = character_policy.normalize_hair_choice(slot.get("hair_color"), character_policy.CHARACTER_HAIR_COLOR_CHOICES)
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length_choice = character_policy.normalize_hair_choice(slot.get("hair_length"), character_policy.CHARACTER_HAIR_LENGTH_CHOICES)
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style_choice = character_policy.normalize_hair_choice(slot.get("hair_style"), character_policy.CHARACTER_HAIR_STYLE_CHOICES)
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color_options = hair_config.get("colors") or []
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length_options = hair_config.get("lengths") or []
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style_options = hair_config.get("styles") or []
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if (
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color_choice == "random"
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and length_choice == "random"
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and style_choice == "random"
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and not color_options
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and not length_options
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and not style_options
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):
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return ""
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if color_choice != "random":
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color_key = color_choice
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elif color_options:
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color_key = _choose(rng, color_options)
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else:
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color_key = character_policy.infer_hair_color_key(base_hair)
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if length_choice != "random":
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length_key = length_choice
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elif length_options:
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length_key = _choose(rng, length_options)
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else:
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length_key = character_policy.infer_hair_length_key(base_hair)
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if style_choice != "random":
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style_key = style_choice
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elif style_options:
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style_key = _choose(rng, style_options)
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else:
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style_key = character_policy.infer_hair_style_key(base_hair)
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if color_key == "random":
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color_key = character_policy.choose_hair_key(rng, character_policy.CHARACTER_HAIR_COLOR_CHOICES)
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if length_key == "random":
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length_key = character_policy.choose_hair_key(rng, character_policy.CHARACTER_HAIR_LENGTH_CHOICES)
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if style_key == "random":
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style_key = character_policy.choose_hair_key(rng, character_policy.CHARACTER_HAIR_STYLE_CHOICES)
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if length_key == "updo" and style_key not in ("ponytail", "braid", "braids", "bun", "messy_bun", "locs", "twists"):
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style_key = _choose(rng, ["ponytail", "braid", "bun", "messy_bun"])
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return character_policy.hair_phrase_from_parts(color_key, length_key, style_key)
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def appearance_for_subject(
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rng: random.Random,
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subject_type: str,
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ethnicity: str,
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figure: str,
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no_plus_women: bool,
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no_black: bool,
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) -> dict[str, str]:
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if subject_type == "single_any":
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subject_type = "woman" if rng.random() < 0.82 else "man"
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if subject_type == "man":
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men_ethnicity = ethnicity if ethnicity else "any"
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subject, age, body, skin, hair, eyes = g.choose(rng, g.by_ethnicity(g.MEN, men_ethnicity))
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return {
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"subject_type": "man",
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"subject": subject,
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"subject_phrase": subject,
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"age": age,
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"body": body,
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"skin": skin,
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"hair": hair,
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"eyes": eyes,
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"body_phrase": f"{body} figure",
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}
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subject, age, body, skin, hair, eyes = g.choose_woman(rng, ethnicity, no_plus_women, no_black)
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figure_note = g.choose(rng, g.figure_pool(figure))
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return {
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"subject_type": "woman",
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"subject": subject,
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"subject_phrase": subject,
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"age": age,
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"body": body,
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"skin": skin,
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"hair": hair,
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"eyes": eyes,
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"body_phrase": character_profile_policy.body_phrase(body, figure_note),
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"figure": figure_note,
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}
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def context_from_character_slot(
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rng: random.Random,
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slot: dict[str, Any],
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subject_type: str,
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ethnicity: str,
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figure: str,
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no_plus_women: bool,
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no_black: bool,
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) -> dict[str, Any]:
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slot_ethnicity = character_policy.slot_value(slot.get("ethnicity"))
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slot_body = character_policy.slot_value(slot.get("body"))
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effective_ethnicity = slot_ethnicity or ethnicity
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effective_figure = character_slot_policy.slot_effective_figure(slot, subject_type, figure)
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effective_no_plus = bool(no_plus_women) and not slot_body
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effective_no_black = bool(no_black) and not slot_ethnicity
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appearance_rng = character_slot_policy.slot_context_rng(slot, rng)
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context = appearance_for_subject(
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appearance_rng,
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subject_type,
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effective_ethnicity,
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effective_figure,
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effective_no_plus,
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effective_no_black,
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)
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characteristics = character_policy.parse_characteristics_config(slot.get("characteristics"))
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age = character_policy.slot_value(slot.get("age")) or character_policy.characteristic_choice(characteristics, "ages", appearance_rng)
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body_phrase = character_policy.slot_value(slot.get("body_phrase"))
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if not slot_body:
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slot_body = character_policy.characteristic_choice(characteristics, "bodies", appearance_rng)
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if age:
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context["age"] = age
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if slot_body:
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context["body"] = slot_body
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if subject_type == "woman":
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context["body_phrase"] = character_profile_policy.body_phrase(slot_body, context.get("figure", ""))
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else:
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context["body_phrase"] = f"{slot_body} figure"
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if body_phrase:
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context["body_phrase"] = body_phrase
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skin_value = character_policy.slot_value(slot.get("skin"))
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if skin_value:
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context["skin"] = skin_value
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eyes_value = character_policy.slot_value(slot.get("eyes"))
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if not eyes_value:
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eyes_value = character_policy.eye_phrase_from_key(character_policy.characteristic_choice(characteristics, "eyes", appearance_rng))
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if eyes_value:
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context["eyes"] = eyes_value
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hair_value = character_policy.slot_value(slot.get("hair"))
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if hair_value:
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context["hair"] = hair_value
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else:
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hair_descriptor = hair_descriptor_from_slot(context.get("hair"), slot, appearance_rng)
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if hair_descriptor:
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context["hair"] = hair_descriptor
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context["descriptor_detail"] = character_policy.normalize_descriptor_detail(slot.get("descriptor_detail"))
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context["presence_mode"] = character_policy.normalize_presence_mode(slot.get("presence_mode"), subject_type)
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context["expression_enabled"] = character_slot_policy.slot_expression_enabled(slot)
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expression_intensity = character_slot_policy.slot_expression_intensity(slot)
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if expression_intensity is not None:
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context["expression_intensity"] = expression_intensity
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context["subject_type"] = subject_type
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context["subject"] = subject_type
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context["subject_phrase"] = subject_type
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return context
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def character_context_for_label(
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label: str,
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label_map: dict[str, dict[str, Any]],
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rng: random.Random,
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ethnicity: str,
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figure: str,
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no_plus_women: bool,
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no_black: bool,
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) -> tuple[dict[str, Any], dict[str, Any] | None]:
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subject_type = "man" if label.startswith("Man ") else "woman"
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slot = label_map.get(label)
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if slot:
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return context_from_character_slot(rng, slot, subject_type, ethnicity, figure, no_plus_women, no_black), slot
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return appearance_for_subject(rng, subject_type, ethnicity, figure, no_plus_women, no_black), None
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def apply_character_context_to_row(row: dict[str, Any], context: dict[str, Any]) -> dict[str, Any]:
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for key in (
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"subject_type",
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"subject",
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"subject_phrase",
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"age",
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"body",
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"body_phrase",
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"skin",
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"hair",
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"eyes",
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"figure",
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"descriptor_detail",
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"presence_mode",
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"expression_enabled",
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"expression_intensity",
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):
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value = context.get(key)
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if value is not None and value != "":
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row[key] = value
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if context.get("age"):
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row["age_band"] = context["age"]
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return row
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def row_from_character_slot(character_slot: str | dict[str, Any] | None) -> dict[str, Any]:
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slots = character_slot_policy.parse_character_cast(character_slot)
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if not slots:
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return {}
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slot = slots[-1]
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if character_slot_policy.slot_seed(slot) >= 0:
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subject_type = str(slot.get("subject_type") or "woman")
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return context_from_character_slot(
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random.Random(seed_policy.row_seed(character_slot_policy.slot_seed(slot), 1, 719)),
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slot,
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subject_type,
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"any",
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"curvy",
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False,
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False,
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)
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return slot
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