"""AR Optimizer Node for ComfyUI Reality."""

from typing import Any

import torch

from ..exceptions import AROptimizationError
from .base import BaseARNode


class AROptimizer(BaseARNode):
    """Optimize 3D assets for mobile AR performance.

    This node applies various optimization techniques including texture compression,
    LOD generation, polygon reduction, and mobile-specific performance tuning.
    """

    @classmethod
    def INPUT_TYPES(cls) -> dict[str, Any]:
        """Define the input parameters for the node."""
        return {
            "required": {
                "image": ("IMAGE",),
                "target_platform": (
                    ["ios", "android", "universal"],
                    {"default": "universal"},
                ),
                "optimization_level": (
                    ["aggressive", "balanced", "conservative"],
                    {"default": "balanced"},
                ),
                "max_texture_size": (
                    [256, 512, 1024, 2048],
                    {"default": 1024},
                ),
                "compression_format": (
                    ["auto", "astc", "etc2", "pvrtc", "dxt"],
                    {"default": "auto"},
                ),
            },
            "optional": {
                "geometry": ("GEOMETRY",),
                "target_fps": (
                    "INT",
                    {"default": 60, "min": 30, "max": 120, "step": 1},
                ),
                "memory_budget_mb": (
                    "INT",
                    {"default": 100, "min": 10, "max": 500, "step": 10},
                ),
                "lod_levels": (
                    "INT",
                    {"default": 3, "min": 1, "max": 5, "step": 1},
                ),
                "quality_threshold": (
                    "FLOAT",
                    {"default": 0.8, "min": 0.1, "max": 1.0, "step": 0.1},
                ),
            },
        }

    RETURN_TYPES = ("IMAGE", "GEOMETRY", "OPTIMIZATION_REPORT")
    RETURN_NAMES = ("optimized_texture", "optimized_geometry", "performance_report")
    FUNCTION = "optimize_for_ar"
    CATEGORY = "🔧 ComfyReality/Optimization"
    DESCRIPTION = "Optimize 3D assets for mobile AR performance"

    def optimize_for_ar(
        self,
        image: torch.Tensor,
        target_platform: str,
        optimization_level: str,
        max_texture_size: int,
        compression_format: str,
        geometry=None,
        target_fps: int = 60,
        memory_budget_mb: int = 100,
        lod_levels: int = 3,
        quality_threshold: float = 0.8,
    ):
        """Optimize assets for AR performance."""
        try:
            # Input validation using base class methods
            self.validate_image_tensor(image, "image", channels=(3, 4))
            self.validate_string_parameter(
                target_platform,
                "target_platform",
                valid_values=["ios", "android", "universal"],
            )
            self.validate_string_parameter(
                optimization_level,
                "optimization_level",
                valid_values=["aggressive", "balanced", "conservative"],
            )
            self.validate_numeric_parameter(
                max_texture_size,
                "max_texture_size",
                valid_values=[256, 512, 1024, 2048],
            )
            self.validate_string_parameter(
                compression_format,
                "compression_format",
                valid_values=["auto", "astc", "etc2", "pvrtc", "dxt"],
            )
            self.validate_numeric_parameter(target_fps, "target_fps", min_val=30, max_val=120)
            self.validate_numeric_parameter(memory_budget_mb, "memory_budget_mb", min_val=10, max_val=500)
            self.validate_numeric_parameter(lod_levels, "lod_levels", min_val=1, max_val=5)
            self.validate_numeric_parameter(quality_threshold, "quality_threshold", min_val=0.1, max_val=1.0)

            self.log_processing_info(
                "AR Optimization",
                platform=target_platform,
                level=optimization_level,
                texture_size=max_texture_size,
            )

            # Placeholder implementation - texture optimization
            optimized_texture = self._optimize_texture(image, max_texture_size, compression_format, target_platform)

            # Placeholder implementation - geometry optimization
            optimized_geometry = self._optimize_geometry(geometry, lod_levels, quality_threshold) if geometry is not None else None

            # Generate performance report
            report = {
                "platform": target_platform,
                "optimization_level": optimization_level,
                "texture_compression_ratio": 0.7,  # Placeholder
                "geometry_reduction": 0.3,  # Placeholder
                "estimated_memory_mb": memory_budget_mb * 0.8,  # Placeholder
                "estimated_fps": target_fps,
            }

            result = (optimized_texture, optimized_geometry, report)
            self.validate_return_types(result, self.RETURN_TYPES)

            self.log_result_info("AR Optimization", success=True, platform=target_platform)
            return result

        except Exception as e:
            self.log_result_info("AR Optimization", success=False, error=str(e))
            raise AROptimizationError(f"Optimization failed: {e}") from e

    def _optimize_texture(self, image, max_size, format_type, platform):
        """Optimize texture for mobile performance."""
        # Placeholder: resize and compress texture
        return image  # TODO: Implement texture optimization

    def _optimize_geometry(self, geometry, lod_levels, quality_threshold):
        """Generate LOD levels for geometry."""
        # Placeholder: generate multiple LOD levels
        return geometry  # TODO: Implement geometry optimization
