from __future__ import annotations

import re
from typing import Any

try:
    from . import caption_metadata_routes
    from . import caption_policy
    from . import formatter_input as input_policy
    from . import krea_cast as cast_policy
    from . import route_metadata as route_metadata_policy
    from .prompt_hygiene import sanitize_prose_text
except ImportError:  # Allows local smoke tests with `python -c`.
    import caption_metadata_routes
    import caption_policy
    import formatter_input as input_policy
    import krea_cast as cast_policy
    import route_metadata as route_metadata_policy
    from prompt_hygiene import sanitize_prose_text


OLD_TRIGGER = caption_policy.OLD_TRIGGER
DEFAULT_TRIGGER = caption_policy.DEFAULT_TRIGGER
STYLE_TAILS = caption_policy.STYLE_TAILS

PROMPT_FIELD_LABELS = input_policy.prompt_field_labels()

ITEM_LABELS = caption_policy.ITEM_LABELS
ACTION_FAMILY_CAPTION_LABELS = caption_policy.ACTION_FAMILY_CAPTION_LABELS
POSITION_FAMILY_CAPTION_LABELS = caption_policy.POSITION_FAMILY_CAPTION_LABELS


def _clean_text(value: Any) -> str:
    return input_policy.clean_text(value)


def _is_false(value: Any) -> bool:
    if isinstance(value, bool):
        return value is False
    if isinstance(value, str):
        return value.strip().lower() in ("false", "0", "no", "off")
    return False


def _expression_disabled(row: dict[str, Any]) -> bool:
    return bool(row.get("expression_disabled")) or _is_false(row.get("expression_enabled", True))


def _cap_first(text: str) -> str:
    text = _clean_text(text).strip(" ,")
    return text[:1].upper() + text[1:] if text else ""


def _article(noun_phrase: str) -> str:
    word = noun_phrase.lstrip().lower()
    if word.startswith("hour") or word[:1] in "aeiou":
        return "an"
    return "a"


def _sentence(text: str) -> str:
    text = _clean_text(text).strip(" ,;")
    if not text:
        return ""
    if text[-1] not in ".!?":
        text += "."
    return _cap_first(text)


def _join_sentences(parts: list[str]) -> str:
    return " ".join(part for part in (_sentence(part) for part in parts) if part)


def _formatter_hint_parts(row: dict[str, Any]) -> list[str]:
    hints: list[str] = []
    if not isinstance(row, dict):
        return hints
    for hint in route_metadata_policy.row_formatter_hints(row, "caption"):
        hint = _clean_text(hint).strip(" .")
        if hint and hint not in hints:
            hints.append(hint)
    return hints


def _append_formatter_hints(prose: str, row: dict[str, Any]) -> str:
    hints = _formatter_hint_parts(row)
    if not hints:
        return prose
    return _join_sentences([prose, *hints])


def _human_join(parts: list[str]) -> str:
    parts = [part for part in (_clean_text(part) for part in parts) if part]
    if len(parts) <= 1:
        return "".join(parts)
    if len(parts) == 2:
        return f"{parts[0]} and {parts[1]}"
    return f"{', '.join(parts[:-1])}, and {parts[-1]}"


def _metadata_action_label(row: dict[str, Any], default: str = "sexual pose") -> str:
    return caption_policy.metadata_action_label(row, default)


def _prompt_cast_descriptors(text: str) -> str:
    return cast_policy.prompt_cast_descriptors(text)


def _cast_entries(text: str) -> list[tuple[str, str]]:
    return cast_policy.cast_entries(text)


def _natural_cast_descriptor_text(text: str) -> str:
    return cast_policy.natural_cast_descriptor_text(text)


def _cast_labels(text: str) -> list[str]:
    return cast_policy.cast_labels(text)


def _natural_label_text(text: Any, labels: list[str]) -> str:
    return cast_policy.natural_label_text(text, labels, capitalize_sentence_starts=False)


def _strip_style_tail(text: str) -> str:
    return caption_policy.strip_style_tail(text)


def _remove_trigger(text: str, trigger: str) -> str:
    return input_policy.strip_trigger_prefix(
        text,
        (trigger, OLD_TRIGGER, DEFAULT_TRIGGER),
        remove_exact=True,
    )


def _with_trigger(text: str, trigger: str, include_trigger: bool) -> str:
    text = _join_sentences([text]) if "." not in text else _clean_text(text)
    trigger = _clean_text(trigger or DEFAULT_TRIGGER)
    if not include_trigger or not trigger:
        return text
    if text.lower().startswith(trigger.lower() + "."):
        return text
    return f"{trigger}. {text}"


def _maybe_json(text: str) -> dict[str, Any] | None:
    return input_policy.maybe_json(text)


def _row_from_inputs(source_text: str, metadata_json: str, input_hint: str) -> tuple[dict[str, Any] | None, str]:
    return input_policy.row_from_inputs(source_text, metadata_json, input_hint)


def _prompt_field(text: str, label: str) -> str:
    return input_policy.prompt_field(text, label, field_labels=PROMPT_FIELD_LABELS)


def _row_value(row: dict[str, Any], key: str, labels: tuple[str, ...] = ()) -> str:
    return input_policy.row_value(row, key, labels, field_labels=PROMPT_FIELD_LABELS)


def _field_from_any_prompt(text: str, labels: tuple[str, ...]) -> str:
    for label in labels:
        value = input_policy.prompt_field(text, label, field_labels=PROMPT_FIELD_LABELS)
        if value:
            return value
    return ""


def _normalize_composition(text: str) -> str:
    return caption_policy.normalize_composition(text)


def _clean_clothing(text: str) -> str:
    return caption_policy.clean_clothing(text)


def _body_phrase(body: Any, figure_note: Any = "") -> str:
    body = _clean_text(body)
    figure_note = _clean_text(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 = _clean_text(row.get("caption"))
    if not caption:
        return {}
    caption = _remove_trigger(_strip_style_tail(caption), _clean_text(row.get("trigger")) or DEFAULT_TRIGGER)
    caption = _remove_trigger(caption, OLD_TRIGGER)
    subject = _clean_text(row.get("primary_subject"))
    age = _clean_text(row.get("age_band") or row.get("age"))
    body_phrase = _clean_text(row.get("body_phrase"))
    if not body_phrase:
        body = _clean_text(row.get("body_type") or row.get("body"))
        figure = _clean_text(row.get("figure"))
        body_phrase = _body_phrase(body, figure)
    front = f"{subject}, {age}, {body_phrase}, "
    if subject in ("woman", "man") and age and body_phrase and caption.startswith(front):
        try:
            skin, hair, eyes, _rest = caption[len(front) :].split(", ", 3)
        except ValueError:
            return {}
    else:
        pieces = [piece.strip() for piece in caption.split(", ", 6)]
        if len(pieces) < 7:
            return {}
        subject, age, body_phrase, skin, hair, eyes, _rest = pieces
    if subject not in ("woman", "man"):
        return {}
    return {
        "caption_subject": subject,
        "caption_age": age,
        "caption_body_phrase": body_phrase,
        "caption_skin": skin,
        "caption_hair": hair,
        "caption_eyes": eyes,
    }


def _pose_clause(pose: str) -> str:
    pose = _clean_text(pose)
    if not pose:
        return ""
    first = pose.split(None, 1)[0].lower()
    if first.endswith("ing") or first in ("seated", "reclined", "posed"):
        return pose
    return f"posing in {pose}"


def _age_subject(age: str, subject: str) -> str:
    age = _clean_text(age)
    subject = _clean_text(subject) or "person"
    if not age:
        return f"An adult {subject}"
    clean_age = re.sub(r"\s+adults?$", "", age).strip()
    if "year-old" in clean_age:
        return f"A {clean_age} adult {subject}"
    if re.search(r"\d", clean_age):
        poss = "her" if subject == "woman" else "his"
        return f"An adult {subject} in {poss} {clean_age}"
    return f"An adult {clean_age} {subject}"


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


def _subject_phrase_from_counts(row: dict[str, Any]) -> str:
    subject = _clean_text(row.get("subject_phrase"))
    if subject:
        return subject
    try:
        women = int(row.get("women_count") or 0)
        men = int(row.get("men_count") or 0)
    except (TypeError, ValueError):
        return _clean_text(row.get("primary_subject")) or "adult scene"
    parts = []
    if women:
        parts.append(f"{women} adult {'woman' if women == 1 else 'women'}")
    if men:
        parts.append(f"{men} adult {'man' if men == 1 else 'men'}")
    if not parts:
        return _clean_text(row.get("primary_subject")) or "adult scene"
    return " and ".join(parts)


def _verb_for_row(row: dict[str, Any]) -> str:
    try:
        return "is" if int(row.get("person_count") or 0) == 1 else "are"
    except (TypeError, ValueError):
        return "are"


def _detail_allows(level: str, dense_only: bool = False) -> bool:
    return caption_policy.detail_allows(level, dense_only=dense_only)


def _caption_metadata_route_dependencies() -> caption_metadata_routes.CaptionMetadataRouteDependencies:
    return caption_metadata_routes.CaptionMetadataRouteDependencies(
        item_labels=ITEM_LABELS,
        clean_text=_clean_text,
        row_value=_row_value,
        field_row_value=lambda row, key: _row_value(row, key),
        clean_clothing=_clean_clothing,
        normalize_composition=_normalize_composition,
        expression_disabled=_expression_disabled,
        detail_allows=_detail_allows,
        join_sentences=_join_sentences,
        human_join=_human_join,
        article=_article,
        cap_first=_cap_first,
        body_phrase=_body_phrase,
        single_caption_front=_single_caption_front,
        pose_clause=_pose_clause,
        age_subject=_age_subject,
        clean_age_phrase=_clean_age_phrase,
        subject_phrase_from_counts=_subject_phrase_from_counts,
        verb_for_row=_verb_for_row,
        metadata_action_label=_metadata_action_label,
        natural_cast_descriptor_text=_natural_cast_descriptor_text,
        cast_labels=_cast_labels,
        natural_label_text=_natural_label_text,
        metadata_to_prose=_metadata_to_prose,
    )


def _caption_metadata_route_request(
    row: dict[str, Any],
    detail_level: str,
    keep_style: bool,
) -> caption_metadata_routes.CaptionMetadataRouteRequest:
    return caption_metadata_routes.CaptionMetadataRouteRequest(
        row=row,
        detail_level=detail_level,
        keep_style=keep_style,
    )


def _single_from_row(row: dict[str, Any], detail_level: str, keep_style: bool) -> tuple[str, str] | None:
    return caption_metadata_routes.single_from_row(
        _caption_metadata_route_request(row, detail_level, keep_style),
        _caption_metadata_route_dependencies(),
    )


def pronoun(subject: str) -> str:
    return caption_metadata_routes.pronoun(subject)


def possessive_pronoun(subject: str) -> str:
    return caption_metadata_routes.possessive_pronoun(subject)


def _couple_clothing_sentence(clothing: str) -> str:
    return caption_metadata_routes.couple_clothing_sentence(clothing, _clean_text)


def _couple_from_row(row: dict[str, Any], detail_level: str, keep_style: bool) -> tuple[str, str] | None:
    return caption_metadata_routes.couple_from_row(
        _caption_metadata_route_request(row, detail_level, keep_style),
        _caption_metadata_route_dependencies(),
    )


def _configured_cast_from_row(row: dict[str, Any], detail_level: str, keep_style: bool) -> tuple[str, str] | None:
    return caption_metadata_routes.configured_cast_from_row(
        _caption_metadata_route_request(row, detail_level, keep_style),
        _caption_metadata_route_dependencies(),
    )


def _group_or_layout_from_row(row: dict[str, Any], detail_level: str, keep_style: bool) -> tuple[str, str] | None:
    return caption_metadata_routes.group_or_layout_from_row(
        _caption_metadata_route_request(row, detail_level, keep_style),
        _caption_metadata_route_dependencies(),
    )


def _insta_of_pair_from_row(row: dict[str, Any], detail_level: str, keep_style: bool) -> tuple[str, str] | None:
    return caption_metadata_routes.insta_of_pair_from_row(
        _caption_metadata_route_request(row, detail_level, keep_style),
        _caption_metadata_route_dependencies(),
    )


def _metadata_to_prose(row: dict[str, Any], detail_level: str, keep_style: bool) -> tuple[str, str]:
    for builder in (
        _insta_of_pair_from_row,
        _configured_cast_from_row,
        _single_from_row,
        _couple_from_row,
        _group_or_layout_from_row,
    ):
        result = builder(row, detail_level, keep_style)
        if result:
            prose, method = result
            return _append_formatter_hints(prose, row), method
    prose, method = _text_to_prose(_clean_text(row.get("caption") or row.get("prompt")), detail_level, keep_style)
    return _append_formatter_hints(prose, row), method


def _prompt_to_prose(text: str, detail_level: str, keep_style: bool) -> tuple[str, str] | None:
    if ":" not in text:
        return None
    cast = _field_from_any_prompt(text, ("Cast",))
    item = _field_from_any_prompt(text, ITEM_LABELS)
    scene = _field_from_any_prompt(text, ("Setting", "Scene"))
    pose = _field_from_any_prompt(text, ("Pose",))
    role_graph = _field_from_any_prompt(text, ("Role graph",))
    expression = _field_from_any_prompt(text, ("Facial expressions", "Facial expression"))
    composition = _normalize_composition(_field_from_any_prompt(text, ("Composition",)))
    if not any((cast, item, scene, pose, role_graph, expression, composition)):
        return None

    subject = _clean_text(text.split(":", 1)[0])
    parts = []
    if subject:
        parts.append(f"{_cap_first(subject)}")
    if cast:
        parts.append(f"The cast is {cast}")
    if role_graph:
        parts.append(role_graph)
    if item:
        item_label = "sexual pose" if _field_from_any_prompt(text, ("Sexual pose",)) else "key detail"
        parts.append(f"The {item_label} is {item}")
    elif pose:
        parts.append(f"The pose is {pose}")
    scene_bits = []
    if scene:
        scene_bits.append(f"set in {scene}")
    if expression:
        scene_bits.append(f"with {expression}")
    if composition:
        scene_bits.append(f"framed as {composition}")
    if scene_bits and _detail_allows(detail_level):
        parts.append(", ".join(scene_bits))
    if keep_style:
        style = _clean_text(text.split(":", 1)[1].split(".", 1)[0])
        if style:
            parts.append(f"The visual style is {style}")
    return _join_sentences(parts), "prompt(labels)"


def _parts_to_sentence(parts: list[str], detail_level: str) -> str:
    parts = [part for part in (_clean_text(part).strip(" ,.") for part in parts) if part]
    if not parts:
        return ""
    if len(parts) == 1:
        return _sentence(parts[0])
    subject = parts[0]
    trailing_style = ""
    if parts[-1].lower().endswith("illustration"):
        trailing_style = parts.pop()
    composition = parts[-1] if len(parts) >= 2 else ""
    scene = parts[-2] if len(parts) >= 3 else ""
    details = parts[1:-2] if len(parts) >= 3 else parts[1:]
    sentences = [f"{_cap_first(subject)} includes {', '.join(details)}" if details else _cap_first(subject)]
    if _detail_allows(detail_level) and scene:
        sentences.append(f"The setting is {scene}")
    if _detail_allows(detail_level) and composition:
        sentences.append(f"The composition is {composition}")
    if trailing_style and _detail_allows(detail_level, dense_only=True):
        sentences.append(f"The visual style is {trailing_style}")
    return _join_sentences(sentences)


def _text_to_prose(text: str, detail_level: str, keep_style: bool) -> tuple[str, str]:
    text = _clean_text(text)
    prompt_result = _prompt_to_prose(text, detail_level, keep_style)
    if prompt_result:
        return prompt_result
    text = _remove_trigger(_strip_style_tail(text), DEFAULT_TRIGGER)
    text = _remove_trigger(text, OLD_TRIGGER)
    parts = [part.strip() for part in text.split(",")]
    prose = _parts_to_sentence(parts, detail_level)
    return prose or _sentence(text), "text(fallback)"


def naturalize_caption(
    source_text: str,
    metadata_json: str = "",
    input_hint: str = "auto",
    trigger: str = DEFAULT_TRIGGER,
    include_trigger: bool = True,
    detail_level: str = "balanced",
    style_policy: str = "drop_style_tail",
    caption_profile: str = caption_policy.CAPTION_PROFILE_DEFAULT,
) -> tuple[str, str]:
    """Rewrite tag-style prompt/caption text into compact natural language."""
    input_hint = input_hint if input_hint in ("auto", "metadata_json", "caption_or_prompt") else "auto"
    detail_level, style_policy, include_trigger = caption_policy.apply_caption_profile(
        caption_profile,
        detail_level=detail_level,
        style_policy=style_policy,
        include_trigger=include_trigger,
    )
    keep_style = caption_policy.keep_style_terms(style_policy)
    row, row_method = _row_from_inputs(source_text, metadata_json, input_hint)
    if row is not None:
        prose, method = _metadata_to_prose(row, detail_level, keep_style)
        caption = sanitize_prose_text(_with_trigger(prose, trigger, include_trigger), triggers=(trigger,))
        return caption, f"{row_method}:{method}"
    prose, method = _text_to_prose(source_text, detail_level, keep_style)
    caption = sanitize_prose_text(_with_trigger(prose, trigger, include_trigger), triggers=(trigger,))
    return caption, method