from __future__ import annotations

from dataclasses import dataclass
from typing import Any

try:
    from . import category_library as category_policy
    from . import row_expression as row_expression_policy
    from . import row_item as row_item_policy
    from . import row_pools as row_pool_policy
    from . import pov_policy
    from .hardcore_text_cleanup import sanitize_hardcore_environment_anchors
except ImportError:  # Allows local smoke tests from the repository root.
    import category_library as category_policy
    import row_expression as row_expression_policy
    import row_item as row_item_policy
    import row_pools as row_pool_policy
    import pov_policy
    from hardcore_text_cleanup import sanitize_hardcore_environment_anchors


@dataclass(frozen=True)
class PromptAxesRoute:
    scene_slug: str
    scene: str
    pose: str
    expression: str
    shared_expression: str
    character_expressions: list[str]
    character_expression_text: str
    source_composition: str
    composition: str

    def as_dict(self) -> dict[str, Any]:
        return {
            "scene_slug": self.scene_slug,
            "scene": self.scene,
            "pose": self.pose,
            "expression": self.expression,
            "shared_expression": self.shared_expression,
            "character_expressions": list(self.character_expressions),
            "character_expression_text": self.character_expression_text,
            "source_composition": self.source_composition,
            "composition": self.composition,
        }


def resolve_prompt_axes_result(
    *,
    category: dict[str, Any],
    subcategory: dict[str, Any],
    item: Any,
    subject_type: str,
    context: dict[str, Any],
    poses: str,
    women_count: int,
    men_count: int,
    scene_rng: Any,
    pose_rng: Any,
    expression_rng: Any,
    composition_rng: Any,
    expression_disabled: bool,
    expression_intensity: float,
    character_slots: list[dict[str, Any]] | None = None,
    character_slot_map: dict[str, dict[str, Any]] | None = None,
    expression_phase: str = "",
    source_role_graph: Any = "",
    item_axis_values: dict[str, Any] | None = None,
    is_pose_category: bool = False,
    pov_character_labels: list[str] | None = None,
    location_config: dict[str, Any] | None = None,
    composition_config: dict[str, Any] | None = None,
) -> PromptAxesRoute:
    character_slots = character_slots or []
    character_slot_map = character_slot_map or {}
    pov_character_labels = pov_character_labels or []

    scene_slug, scene = row_item_policy.choose_pair(
        scene_rng,
        category_policy.compatible_entries(
            row_pool_policy.scene_pool(category, subcategory, item, subject_type, location_config),
            women_count,
            men_count,
        ),
    )
    pose = str(
        category_policy.merged_field(category, subcategory, item, "pose", "")
        or context.get("fallback_pose")
        or row_item_policy.choose_text(
            pose_rng,
            category_policy.compatible_entries(
                row_pool_policy.pose_pool(category, subcategory, item, subject_type, poses),
                women_count,
                men_count,
            ),
        )
    )
    if is_pose_category:
        pose = sanitize_hardcore_environment_anchors(pose)

    expression_pool = row_pool_policy.expression_pool(category, subcategory, item)
    if expression_disabled:
        expression = ""
    else:
        expression_entries = category_policy.compatible_entries(
            row_expression_policy.expression_entries_for_intensity(expression_pool, expression_intensity),
            women_count,
            men_count,
        )
        expression = row_item_policy.choose_text(expression_rng, expression_entries)
        if subject_type in ("couple", "group") and ";" not in expression:
            secondary_expression = row_item_policy.choose_distinct_text(expression_rng, expression_entries, expression)
            if secondary_expression:
                expression = f"{expression}; {secondary_expression}"

    shared_expression = expression
    character_expressions: list[str] = []
    character_expression_text = ""
    if not expression_disabled and subject_type == "configured_cast" and character_slots:
        character_expressions = row_expression_policy.character_expression_entries(
            expression_rng,
            expression_pool,
            expression_intensity,
            character_slot_map,
            women_count,
            men_count,
            expression_phase,
        )
        character_expression_text = "; ".join(character_expressions)
        character_expression_text = row_expression_policy.sanitize_character_expression_text_for_action(
            character_expression_text,
            source_role_graph,
            item,
            item_axis_values or {},
        )
        character_expressions = [part.strip() for part in character_expression_text.split(";") if part.strip()]
        if character_expression_text:
            expression = character_expression_text

    source_composition = row_item_policy.choose_text(
        composition_rng,
        category_policy.compatible_entries(
            row_pool_policy.composition_pool(category, subcategory, item, subject_type, composition_config),
            women_count,
            men_count,
        ),
    )
    if is_pose_category:
        source_composition = sanitize_hardcore_environment_anchors(source_composition)
    composition = pov_policy.pov_composition_prompt(source_composition, pov_character_labels)

    return PromptAxesRoute(
        scene_slug=scene_slug,
        scene=scene,
        pose=pose,
        expression=expression,
        shared_expression=shared_expression,
        character_expressions=character_expressions,
        character_expression_text=character_expression_text,
        source_composition=source_composition,
        composition=composition,
    )


def resolve_prompt_axes(
    *,
    category: dict[str, Any],
    subcategory: dict[str, Any],
    item: Any,
    subject_type: str,
    context: dict[str, Any],
    poses: str,
    women_count: int,
    men_count: int,
    scene_rng: Any,
    pose_rng: Any,
    expression_rng: Any,
    composition_rng: Any,
    expression_disabled: bool,
    expression_intensity: float,
    character_slots: list[dict[str, Any]] | None = None,
    character_slot_map: dict[str, dict[str, Any]] | None = None,
    expression_phase: str = "",
    source_role_graph: Any = "",
    item_axis_values: dict[str, Any] | None = None,
    is_pose_category: bool = False,
    pov_character_labels: list[str] | None = None,
    location_config: dict[str, Any] | None = None,
    composition_config: dict[str, Any] | None = None,
) -> dict[str, Any]:
    return resolve_prompt_axes_result(
        category=category,
        subcategory=subcategory,
        item=item,
        subject_type=subject_type,
        context=context,
        poses=poses,
        women_count=women_count,
        men_count=men_count,
        scene_rng=scene_rng,
        pose_rng=pose_rng,
        expression_rng=expression_rng,
        composition_rng=composition_rng,
        expression_disabled=expression_disabled,
        expression_intensity=expression_intensity,
        character_slots=character_slots,
        character_slot_map=character_slot_map,
        expression_phase=expression_phase,
        source_role_graph=source_role_graph,
        item_axis_values=item_axis_values,
        is_pose_category=is_pose_category,
        pov_character_labels=pov_character_labels,
        location_config=location_config,
        composition_config=composition_config,
    ).as_dict()