# -*- coding: utf-8 -*-
"""
以图搜图 API - CLIP Vision Embedding + pgvector 余弦距离检索
"""

import os
import uuid
import json
from flask import Blueprint, request, jsonify
from sqlalchemy import text
from app.extensions import db
from app.utils.ai_vision import load_clip_model, get_image_embedding

# 注册蓝图
image_search_bp = Blueprint('image_search', __name__)


# ============================================================================
# POST /api/v1/common/image-search
# 以图搜图：上传图片 → CLIP embedding → pgvector 余弦相似度检索
# ============================================================================

@image_search_bp.route('/image-search', methods=['POST'])
def image_search():
    # ---------------------------------------------------------
    # 1. 检查文件
    # ---------------------------------------------------------
    if 'file' not in request.files:
        return jsonify({"code": 400, "msg": "未找到图片文件"}), 400

    file = request.files['file']
    if file.filename == '':
        return jsonify({"code": 400, "msg": "未选择文件"}), 400

    # ---------------------------------------------------------
    # 2. 安全保存临时文件
    # ---------------------------------------------------------
    ext = file.filename.rsplit('.', 1)[-1].lower()
    if ext not in {'png', 'jpg', 'jpeg', 'gif', 'bmp', 'webp'}:
        return jsonify({"code": 400, "msg": "不支持的图片格式"}), 400

    tmp_filename = f"{uuid.uuid4().hex}.{ext}"
    tmp_dir = os.path.join(os.path.dirname(__file__), '..', '..', '..', 'uploads')
    os.makedirs(tmp_dir, exist_ok=True)
    tmp_path = os.path.join(tmp_dir, tmp_filename)

    try:
        file.save(tmp_path)
        print(f"💾 [ImageSearch] 临时文件已保存: {tmp_path}")

        # ---------------------------------------------------------
        # 3. 提取 CLIP embedding
        # ---------------------------------------------------------
        load_clip_model()
        embedding = get_image_embedding(tmp_path)
        print(f"✅ [ImageSearch] Embedding 提取成功，维度: {len(embedding)}")

    except Exception as e:
        print(f"❌ [ImageSearch] 图像处理失败: {e}")
        return jsonify({"code": 500, "msg": f"图像处理失败: {str(e)}"}), 500

    finally:
        # ---------------------------------------------------------
        # 4. 无论成功与否，都删除临时文件
        # ---------------------------------------------------------
        if os.path.exists(tmp_path):
            try:
                os.remove(tmp_path)
                print(f"🗑️ [ImageSearch] 临时文件已清理: {tmp_path}")
            except Exception as e:
                print(f"⚠️ [ImageSearch] 临时文件删除失败: {e}")

    # ---------------------------------------------------------
    # 5. pgvector 余弦相似度检索（跨表联合检索）
    # ---------------------------------------------------------
    try:
        query_vector_str = '[' + ','.join(str(v) for v in embedding) + ']'

        sql = text("""
            SELECT id, name, spec_model, image_url,
                   (1 - (vec <=> :query_vector)) AS similarity
            FROM (
                SELECT id,
                       COALESCE(name, '') AS name,
                       COALESCE(spec, '') AS spec_model,
                       COALESCE(product_image, '') AS image_url,
                       img_embedding AS vec
                FROM material_base
                WHERE img_embedding IS NOT NULL

                UNION ALL

                SELECT id,
                       '采购入库' AS name,
                       '到货照片' AS spec_model,
                       COALESCE(arrival_photo, '') AS image_url,
                       arrival_image_embedding AS vec
                FROM stock_buy
                WHERE arrival_image_embedding IS NOT NULL

                UNION ALL

                SELECT id,
                       '采购入库' AS name,
                       '质检报告' AS spec_model,
                       COALESCE(qc_report, '') AS image_url,
                       qc_report_image_embedding AS vec
                FROM stock_buy
                WHERE qc_report_image_embedding IS NOT NULL
            ) AS combined
            ORDER BY vec <=> :query_vector
            LIMIT 10
        """)

        result = db.session.execute(sql, {"query_vector": query_vector_str})
        rows = result.fetchall()

        results = []
        for row in rows:
            item_id = row[0]
            item_name = row[1] or ""
            spec_model = row[2] or ""
            raw_image = row[3]

            # 解析图片 URL 列表，取第一张
            image_url = ""
            if raw_image:
                try:
                    image_list = json.loads(raw_image)
                    if image_list and len(image_list) > 0:
                        image_url = image_list[0]
                except Exception:
                    # 纯字符串直接使用
                    image_url = str(raw_image)

            results.append({
                "id": item_id,
                "name": item_name,
                "spec_model": spec_model,
                "image_url": image_url,
                "similarity": round(float(row[4]), 4)
            })

        print(f"✅ [ImageSearch] 跨表检索完成，命中 {len(results)} 条结果")
        return jsonify({
            "code": 200,
            "msg": "检索成功",
            "data": results
        })

    except Exception as e:
        print(f"❌ [ImageSearch] 数据库检索失败: {e}")
        return jsonify({"code": 500, "msg": f"检索失败: {str(e)}"}), 500