/**
 * Room Photo Analyzer using OpenAI GPT-4 Vision
 * Analyzes room photos to extract dimensions, detect doors/windows, and suggest wardrobe placement
 */
import OpenAI from 'openai';

// Lazy initialization to avoid errors when API key is not set
let openaiClient = null;

function getOpenAIClient() {
  if (!openaiClient) {
    if (!process.env.OPENAI_API_KEY) {
      throw new Error('OPENAI_API_KEY is not configured. Add it to server/.env');
    }
    openaiClient = new OpenAI({
      apiKey: process.env.OPENAI_API_KEY
    });
  }
  return openaiClient;
}

/**
 * Prompt for GPT-4 Vision to analyze room photos
 */
const ROOM_ANALYSIS_PROMPT = `You are a professional interior designer and architect specializing in custom wardrobe installations. Analyze this room photo with a STRONG FOCUS on the visible wall surfaces (parois) and ceiling (plafond).

PRIORITY: Carefully examine every visible wall and the ceiling. Detect their exact colors, materials, and textures as they appear in the photo. This is critical for accurate 3D room reconstruction.

Return a JSON object with the following structure:
{
  "roomDimensions": {
    "widthM": <estimated width in meters, e.g., 4.2>,
    "lengthM": <estimated length/depth in meters, e.g., 3.8>,
    "heightM": <estimated ceiling height in meters, typically 2.4-2.7>
  },
  "walls": [
    {
      "side": "back" | "left" | "right",
      "visible": <boolean - is this wall clearly visible in the photo?>,
      "color": "<EXACT hex color code sampled from the wall surface, e.g., #f5f5f0>",
      "material": "paint" | "wallpaper" | "brick" | "wood_panel" | "concrete" | "plaster" | "stone" | "tile",
      "texture": "smooth" | "textured" | "patterned" | "rough" | "glossy",
      "hasWindow": <boolean>,
      "hasDoor": <boolean>,
      "surfaceArea": <approximate visible surface area percentage 0-100, accounting for windows/doors>
    }
  ],
  "windows": [
    {
      "wall": "back" | "left" | "right",
      "xPercent": <horizontal position from left edge, 0-100>,
      "yPercent": <vertical position from floor, 0-100>,
      "widthPercent": <width as percentage of wall, e.g., 25>,
      "heightPercent": <height as percentage of wall, e.g., 40>,
      "type": "window" | "french_window" | "skylight" | "bay_window"
    }
  ],
  "doors": [
    {
      "wall": "back" | "left" | "right",
      "xPercent": <horizontal position from left edge, 0-100>,
      "widthPercent": <width as percentage of wall, typically 15-25>,
      "heightPercent": <height as percentage of wall, typically 80-90>,
      "type": "door" | "double_door" | "opening" | "closet" | "sliding_door"
    }
  ],
  "floor": {
    "color": "<exact hex color code>",
    "material": "wood" | "tile" | "carpet" | "concrete" | "laminate" | "vinyl" | "parquet"
  },
  "ceiling": {
    "visible": <boolean - is the ceiling visible in the photo?>,
    "color": "<EXACT hex color code detected from the ceiling surface>",
    "type": "flat" | "sloped" | "beamed" | "coffered" | "vaulted",
    "material": "paint" | "plaster" | "wood" | "concrete",
    "slopeAngleDeg": <angle in degrees if sloped, 0 for flat, null if not applicable>,
    "slopeDirection": "front_to_back" | "left_to_right" | null
  },
  "lighting": {
    "natural": "bright" | "moderate" | "dim",
    "windowSide": "left" | "right" | "back" | "front" | null
  },
  "suggestedWardrobeWall": "back" | "left" | "right",
  "suggestedWardrobePosition": {
    "xPercent": <start position from left, 0-100>,
    "widthPercent": <suggested width as percentage of wall, e.g., 50>,
    "reason": "<brief explanation of why this position is recommended>"
  },
  "roomType": "bedroom" | "living_room" | "hallway" | "dressing" | "other",
  "confidence": <confidence score 0-100>
}

IMPORTANT GUIDELINES FOR WALL AND CEILING DETECTION:
- ALWAYS include all three walls (back, left, right). Set visible=false only if a wall is truly not visible at all.
- Sample the EXACT hex color from the dominant area of each wall surface — do NOT default to #f5f5f0.
- Pay close attention to paint color nuances: beige vs cream vs off-white vs warm grey etc.
- Detect the wall material: painted plaster, wallpaper, exposed brick, wood paneling, etc.
- For the ceiling: detect its actual color (it may not be pure white), its type, and material.
- If the ceiling is sloped (mansarde/sous-pente), estimate the slope angle and direction.
- Estimate dimensions based on standard furniture sizes if visible (beds, doors, windows).
- Standard door height is ~2.1m, standard door width is ~0.8-0.9m.
- Standard ceiling height is 2.4-2.7m in residential.
- For wardrobe placement, prefer walls without windows/doors and with enough clear space.
- Return ONLY valid JSON, no additional text.`;

/**
 * Analyze a room photo using GPT-4 Vision
 * @param {string} imageBase64 - Base64 encoded image data
 * @param {string} mimeType - Image MIME type (image/jpeg, image/png, etc.)
 * @returns {Object} Room analysis result
 */
export async function analyzeRoomPhoto(imageBase64, mimeType = 'image/jpeg') {
  const openai = getOpenAIClient();

  try {
    const response = await openai.chat.completions.create({
      model: 'gpt-4o',
      messages: [
        {
          role: 'user',
          content: [
            { type: 'text', text: ROOM_ANALYSIS_PROMPT },
            {
              type: 'image_url',
              image_url: {
                url: `data:${mimeType};base64,${imageBase64}`,
                detail: 'high'
              }
            }
          ]
        }
      ],
      max_tokens: 2000,
      response_format: { type: 'json_object' }
    });

    const content = response.choices[0]?.message?.content;
    if (!content) {
      throw new Error('No response from OpenAI');
    }

    const analysis = JSON.parse(content);
    
    // Validate required fields
    if (!analysis.roomDimensions || !analysis.suggestedWardrobeWall) {
      throw new Error('Incomplete room analysis');
    }

    return {
      success: true,
      analysis,
      tokensUsed: response.usage?.total_tokens || 0
    };

  } catch (error) {
    console.error('Room analysis error:', error);
    
    if (error.code === 'invalid_api_key') {
      throw new Error('Invalid OpenAI API key');
    }
    
    if (error.code === 'rate_limit_exceeded') {
      throw new Error('API rate limit exceeded. Please try again later.');
    }

    throw error;
  }
}

/**
 * Convert analysis to 3D room configuration for Three.js
 * @param {Object} analysis - Room analysis from GPT-4 Vision
 * @returns {Object} 3D room configuration
 */
export function analysisTo3DConfig(analysis) {
  const { roomDimensions, walls, windows, doors, floor, ceiling, suggestedWardrobeWall, suggestedWardrobePosition } = analysis;
  
  return {
    // Room dimensions in meters
    width: roomDimensions.widthM || 4,
    length: roomDimensions.lengthM || 4,
    height: roomDimensions.heightM || 2.5,
    
    // Wall configurations with material info
    walls: {
      back: (() => {
        const w = walls?.find(w => w.side === 'back');
        return w ? { color: w.color || '#f5f5f0', visible: w.visible !== false, material: w.material || 'paint', texture: w.texture || 'smooth' }
               : { color: '#f5f5f0', visible: true, material: 'paint', texture: 'smooth' };
      })(),
      left: (() => {
        const w = walls?.find(w => w.side === 'left');
        return w ? { color: w.color || '#f5f5f0', visible: w.visible !== false, material: w.material || 'paint', texture: w.texture || 'smooth' }
               : { color: '#f5f5f0', visible: true, material: 'paint', texture: 'smooth' };
      })(),
      right: (() => {
        const w = walls?.find(w => w.side === 'right');
        return w ? { color: w.color || '#f5f5f0', visible: w.visible !== false, material: w.material || 'paint', texture: w.texture || 'smooth' }
               : { color: '#f5f5f0', visible: true, material: 'paint', texture: 'smooth' };
      })()
    },
    
    // Windows for each wall
    windows: (windows || []).map(w => ({
      wall: w.wall,
      x: (w.xPercent || 50) / 100,
      y: (w.yPercent || 30) / 100,
      width: (w.widthPercent || 25) / 100,
      height: (w.heightPercent || 40) / 100,
      type: w.type || 'window'
    })),
    
    // Doors for each wall
    doors: (doors || []).map(d => ({
      wall: d.wall,
      x: (d.xPercent || 10) / 100,
      width: (d.widthPercent || 20) / 100,
      height: (d.heightPercent || 85) / 100,
      type: d.type || 'door'
    })),
    
    // Floor and ceiling
    floor: {
      color: floor?.color || '#c4a574',
      material: floor?.material || 'wood'
    },
    ceiling: {
      color: ceiling?.color || '#ffffff',
      type: ceiling?.type || 'flat',
      visible: ceiling?.visible !== false,
      material: ceiling?.material || 'paint',
      slopeAngleDeg: ceiling?.slopeAngleDeg || 0,
      slopeDirection: ceiling?.slopeDirection || null
    },
    
    // Wardrobe placement
    wardrobePlacement: {
      wall: suggestedWardrobeWall || 'back',
      xPercent: suggestedWardrobePosition?.xPercent || 25,
      widthPercent: suggestedWardrobePosition?.widthPercent || 50
    }
  };
}

export default { analyzeRoomPhoto, analysisTo3DConfig };