729 lines
33 KiB
Python
729 lines
33 KiB
Python
"""
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智能食物数据库和热量估算模块
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简化用户数据录入过程
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"""
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from typing import Dict, List, Optional, Tuple
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import json
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from pathlib import Path
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class SmartFoodDatabase:
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"""智能食物数据库"""
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def __init__(self):
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self.food_database = self._load_food_database()
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self.portion_sizes = self._load_portion_sizes()
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self.calorie_estimates = self._load_calorie_estimates()
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# 添加缓存
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self.ai_cache = {} # AI分析结果缓存
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self.calorie_cache = {} # 热量估算缓存
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self.search_cache = {} # 搜索结果缓存
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# 预计算常用食物
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self._precompute_common_foods()
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def _load_food_database(self) -> Dict[str, Dict]:
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"""加载食物数据库"""
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return {
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# 主食类
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"米饭": {"category": "主食", "calories_per_100g": 130, "protein": 2.7, "carbs": 28, "fat": 0.3},
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"面条": {"category": "主食", "calories_per_100g": 131, "protein": 5, "carbs": 25, "fat": 1.1},
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"馒头": {"category": "主食", "calories_per_100g": 221, "protein": 7, "carbs": 47, "fat": 1.1},
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"包子": {"category": "主食", "calories_per_100g": 227, "protein": 7.3, "carbs": 45, "fat": 2.6},
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"饺子": {"category": "主食", "calories_per_100g": 250, "protein": 11, "carbs": 35, "fat": 8},
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"粥": {"category": "主食", "calories_per_100g": 50, "protein": 1.1, "carbs": 10, "fat": 0.3},
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"燕麦": {"category": "主食", "calories_per_100g": 389, "protein": 17, "carbs": 66, "fat": 7},
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"面包": {"category": "主食", "calories_per_100g": 265, "protein": 9, "carbs": 49, "fat": 3.2},
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"饼干": {"category": "主食", "calories_per_100g": 433, "protein": 9, "carbs": 71, "fat": 12},
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"薯条": {"category": "主食", "calories_per_100g": 319, "protein": 4, "carbs": 41, "fat": 15},
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"玉米": {"category": "主食", "calories_per_100g": 86, "protein": 3.4, "carbs": 19, "fat": 1.2},
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"红薯": {"category": "主食", "calories_per_100g": 86, "protein": 1.6, "carbs": 20, "fat": 0.1},
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# 蛋白质类
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"鸡蛋": {"category": "蛋白质", "calories_per_100g": 155, "protein": 13, "carbs": 1.1, "fat": 11},
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"鸡肉": {"category": "蛋白质", "calories_per_100g": 165, "protein": 31, "carbs": 0, "fat": 3.6},
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"猪肉": {"category": "蛋白质", "calories_per_100g": 143, "protein": 20, "carbs": 0, "fat": 6.2},
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"牛肉": {"category": "蛋白质", "calories_per_100g": 250, "protein": 26, "carbs": 0, "fat": 15},
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"鱼肉": {"category": "蛋白质", "calories_per_100g": 206, "protein": 22, "carbs": 0, "fat": 12},
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"豆腐": {"category": "蛋白质", "calories_per_100g": 76, "protein": 8, "carbs": 2, "fat": 4.8},
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"牛奶": {"category": "蛋白质", "calories_per_100g": 42, "protein": 3.4, "carbs": 5, "fat": 1},
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"酸奶": {"category": "蛋白质", "calories_per_100g": 59, "protein": 3.3, "carbs": 4.7, "fat": 3.2},
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"虾": {"category": "蛋白质", "calories_per_100g": 99, "protein": 24, "carbs": 0, "fat": 0.2},
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"蟹": {"category": "蛋白质", "calories_per_100g": 97, "protein": 20, "carbs": 0, "fat": 1.5},
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"鸭肉": {"category": "蛋白质", "calories_per_100g": 183, "protein": 25, "carbs": 0, "fat": 9},
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"羊肉": {"category": "蛋白质", "calories_per_100g": 203, "protein": 25, "carbs": 0, "fat": 11},
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"火腿": {"category": "蛋白质", "calories_per_100g": 145, "protein": 18, "carbs": 1.5, "fat": 7.5},
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"香肠": {"category": "蛋白质", "calories_per_100g": 301, "protein": 13, "carbs": 2, "fat": 25},
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# 蔬菜类
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"白菜": {"category": "蔬菜", "calories_per_100g": 17, "protein": 1.5, "carbs": 3.2, "fat": 0.1},
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"菠菜": {"category": "蔬菜", "calories_per_100g": 23, "protein": 2.9, "carbs": 3.6, "fat": 0.4},
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"西兰花": {"category": "蔬菜", "calories_per_100g": 34, "protein": 2.8, "carbs": 7, "fat": 0.4},
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"胡萝卜": {"category": "蔬菜", "calories_per_100g": 41, "protein": 0.9, "carbs": 10, "fat": 0.2},
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"土豆": {"category": "蔬菜", "calories_per_100g": 77, "protein": 2, "carbs": 17, "fat": 0.1},
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"西红柿": {"category": "蔬菜", "calories_per_100g": 18, "protein": 0.9, "carbs": 3.9, "fat": 0.2},
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"黄瓜": {"category": "蔬菜", "calories_per_100g": 16, "protein": 0.7, "carbs": 4, "fat": 0.1},
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"茄子": {"category": "蔬菜", "calories_per_100g": 25, "protein": 1.1, "carbs": 6, "fat": 0.2},
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"豆角": {"category": "蔬菜", "calories_per_100g": 31, "protein": 2.1, "carbs": 7, "fat": 0.2},
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"韭菜": {"category": "蔬菜", "calories_per_100g": 25, "protein": 2.4, "carbs": 4, "fat": 0.4},
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"芹菜": {"category": "蔬菜", "calories_per_100g": 16, "protein": 0.7, "carbs": 4, "fat": 0.1},
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"洋葱": {"category": "蔬菜", "calories_per_100g": 40, "protein": 1.1, "carbs": 9, "fat": 0.1},
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"大蒜": {"category": "蔬菜", "calories_per_100g": 149, "protein": 6.4, "carbs": 33, "fat": 0.5},
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"生姜": {"category": "蔬菜", "calories_per_100g": 80, "protein": 1.8, "carbs": 18, "fat": 0.8},
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# 水果类
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"苹果": {"category": "水果", "calories_per_100g": 52, "protein": 0.3, "carbs": 14, "fat": 0.2},
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"香蕉": {"category": "水果", "calories_per_100g": 89, "protein": 1.1, "carbs": 23, "fat": 0.3},
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"橙子": {"category": "水果", "calories_per_100g": 47, "protein": 0.9, "carbs": 12, "fat": 0.1},
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"葡萄": {"category": "水果", "calories_per_100g": 44, "protein": 0.2, "carbs": 11, "fat": 0.2},
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"草莓": {"category": "水果", "calories_per_100g": 32, "protein": 0.7, "carbs": 8, "fat": 0.3},
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"西瓜": {"category": "水果", "calories_per_100g": 30, "protein": 0.6, "carbs": 8, "fat": 0.1},
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"梨": {"category": "水果", "calories_per_100g": 57, "protein": 0.4, "carbs": 15, "fat": 0.1},
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"桃子": {"category": "水果", "calories_per_100g": 39, "protein": 0.9, "carbs": 10, "fat": 0.3},
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"樱桃": {"category": "水果", "calories_per_100g": 63, "protein": 1.1, "carbs": 16, "fat": 0.2},
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"柠檬": {"category": "水果", "calories_per_100g": 29, "protein": 1.1, "carbs": 9, "fat": 0.3},
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"芒果": {"category": "水果", "calories_per_100g": 60, "protein": 0.8, "carbs": 15, "fat": 0.4},
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"菠萝": {"category": "水果", "calories_per_100g": 50, "protein": 0.5, "carbs": 13, "fat": 0.1},
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"猕猴桃": {"category": "水果", "calories_per_100g": 61, "protein": 1.1, "carbs": 15, "fat": 0.5},
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# 坚果类
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"花生": {"category": "坚果", "calories_per_100g": 567, "protein": 25, "carbs": 16, "fat": 49},
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"核桃": {"category": "坚果", "calories_per_100g": 654, "protein": 15, "carbs": 14, "fat": 65},
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"杏仁": {"category": "坚果", "calories_per_100g": 579, "protein": 21, "carbs": 22, "fat": 50},
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"腰果": {"category": "坚果", "calories_per_100g": 553, "protein": 18, "carbs": 30, "fat": 44},
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"开心果": {"category": "坚果", "calories_per_100g": 560, "protein": 20, "carbs": 28, "fat": 45},
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"瓜子": {"category": "坚果", "calories_per_100g": 606, "protein": 19, "carbs": 20, "fat": 53},
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# 饮料类
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"水": {"category": "饮料", "calories_per_100g": 0, "protein": 0, "carbs": 0, "fat": 0},
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"茶": {"category": "饮料", "calories_per_100g": 1, "protein": 0.1, "carbs": 0.3, "fat": 0},
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"咖啡": {"category": "饮料", "calories_per_100g": 2, "protein": 0.1, "carbs": 0.3, "fat": 0},
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"果汁": {"category": "饮料", "calories_per_100g": 45, "protein": 0.3, "carbs": 11, "fat": 0.1},
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"可乐": {"category": "饮料", "calories_per_100g": 42, "protein": 0, "carbs": 10.6, "fat": 0},
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"雪碧": {"category": "饮料", "calories_per_100g": 40, "protein": 0, "carbs": 10, "fat": 0},
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"啤酒": {"category": "饮料", "calories_per_100g": 43, "protein": 0.5, "carbs": 3.6, "fat": 0},
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"红酒": {"category": "饮料", "calories_per_100g": 83, "protein": 0.1, "carbs": 2.6, "fat": 0},
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"白酒": {"category": "饮料", "calories_per_100g": 298, "protein": 0, "carbs": 0, "fat": 0},
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# 调料类
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"盐": {"category": "调料", "calories_per_100g": 0, "protein": 0, "carbs": 0, "fat": 0},
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"糖": {"category": "调料", "calories_per_100g": 387, "protein": 0, "carbs": 100, "fat": 0},
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"酱油": {"category": "调料", "calories_per_100g": 63, "protein": 7, "carbs": 7, "fat": 0},
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"醋": {"category": "调料", "calories_per_100g": 31, "protein": 0.1, "carbs": 7, "fat": 0},
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"油": {"category": "调料", "calories_per_100g": 884, "protein": 0, "carbs": 0, "fat": 100},
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"辣椒": {"category": "调料", "calories_per_100g": 40, "protein": 1.9, "carbs": 9, "fat": 0.4},
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"胡椒": {"category": "调料", "calories_per_100g": 251, "protein": 10, "carbs": 64, "fat": 3.3},
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"花椒": {"category": "调料", "calories_per_100g": 258, "protein": 6, "carbs": 37, "fat": 8.9},
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}
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def _load_portion_sizes(self) -> Dict[str, List[str]]:
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"""加载分量选项"""
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return {
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"主食": ["1小碗", "1中碗", "1大碗", "1个", "2个", "3个", "半份", "1份", "2份"],
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"蛋白质": ["1个", "2个", "3个", "1小块", "2小块", "1片", "2片", "1杯", "2杯", "适量"],
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"蔬菜": ["1小份", "1中份", "1大份", "1把", "2把", "1根", "2根", "适量", "很多"],
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"水果": ["1个", "2个", "3个", "1小个", "1大个", "1片", "2片", "适量"],
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"坚果": ["1小把", "1把", "2把", "1颗", "2颗", "3颗", "适量"],
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"饮料": ["1杯", "2杯", "3杯", "1小杯", "1大杯", "1瓶", "2瓶", "适量"],
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"调料": ["1小勺", "1勺", "2勺", "1小匙", "1匙", "2匙", "适量", "少许"]
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}
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def _load_calorie_estimates(self) -> Dict[str, Dict]:
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"""加载热量估算"""
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return {
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"1小碗": {"米饭": 130, "面条": 131, "粥": 50},
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"1中碗": {"米饭": 195, "面条": 196, "粥": 75},
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"1大碗": {"米饭": 260, "面条": 262, "粥": 100},
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"1个": {"鸡蛋": 77, "苹果": 52, "香蕉": 89, "馒头": 221, "包子": 227},
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"2个": {"鸡蛋": 154, "苹果": 104, "香蕉": 178, "馒头": 442, "包子": 454},
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"1小块": {"鸡肉": 50, "猪肉": 50, "牛肉": 50, "豆腐": 50},
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"2小块": {"鸡肉": 100, "猪肉": 100, "牛肉": 100, "豆腐": 100},
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"1杯": {"牛奶": 150, "酸奶": 150, "水": 0, "茶": 0, "咖啡": 0},
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"2杯": {"牛奶": 300, "酸奶": 300, "水": 0, "茶": 0, "咖啡": 0},
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"1小份": {"白菜": 50, "菠菜": 50, "西兰花": 50, "胡萝卜": 50},
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"1中份": {"白菜": 100, "菠菜": 100, "西兰花": 100, "胡萝卜": 100},
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"1大份": {"白菜": 150, "菠菜": 150, "西兰花": 150, "胡萝卜": 150},
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"1小把": {"花生": 30, "核桃": 30, "杏仁": 30},
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"1把": {"花生": 60, "核桃": 60, "杏仁": 60},
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"适量": {"default": 50}, # 默认适量为50卡路里
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"很多": {"default": 150}, # 默认很多为150卡路里
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"1小勺": {"盐": 0, "糖": 16, "酱油": 3, "醋": 2, "油": 44, "辣椒": 2, "胡椒": 13, "花椒": 13},
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"1勺": {"盐": 0, "糖": 32, "酱油": 6, "醋": 4, "油": 88, "辣椒": 4, "胡椒": 25, "花椒": 26},
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"2勺": {"盐": 0, "糖": 64, "酱油": 12, "醋": 8, "油": 176, "辣椒": 8, "胡椒": 50, "花椒": 52},
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"1小匙": {"盐": 0, "糖": 8, "酱油": 1.5, "醋": 1, "油": 22, "辣椒": 1, "胡椒": 6, "花椒": 6},
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"1匙": {"盐": 0, "糖": 16, "酱油": 3, "醋": 2, "油": 44, "辣椒": 2, "胡椒": 13, "花椒": 13},
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"2匙": {"盐": 0, "糖": 32, "酱油": 6, "醋": 4, "油": 88, "辣椒": 4, "胡椒": 25, "花椒": 26},
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"少许": {"default": 5}, # 默认少许为5卡路里
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}
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def search_foods(self, query: str) -> List[Dict]:
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"""搜索食物（优化版本）"""
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query = query.lower().strip()
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# 检查缓存
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if query in self.search_cache:
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return self.search_cache[query]
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results = []
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# 精确匹配优先
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for food_name, food_info in self.food_database.items():
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if query == food_name.lower():
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results.insert(0, {
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"name": food_name,
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"category": food_info["category"],
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"calories_per_100g": food_info["calories_per_100g"],
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"match_type": "exact"
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})
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# 包含匹配
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for food_name, food_info in self.food_database.items():
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if query in food_name.lower() and query != food_name.lower():
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results.append({
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"name": food_name,
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"category": food_info["category"],
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"calories_per_100g": food_info["calories_per_100g"],
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"match_type": "contains"
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})
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# 关键词匹配
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if len(results) < 5:
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keywords = query.split()
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for food_name, food_info in self.food_database.items():
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if any(keyword in food_name.lower() for keyword in keywords):
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if not any(r["name"] == food_name for r in results):
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results.append({
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"name": food_name,
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"category": food_info["category"],
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"calories_per_100g": food_info["calories_per_100g"],
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"match_type": "keyword"
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})
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# 限制结果数量并缓存
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results = results[:10]
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self.search_cache[query] = results
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return results
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def get_food_info(self, food_name: str) -> Optional[Dict]:
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"""获取食物信息"""
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return self.food_database.get(food_name)
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def get_portion_options(self, food_name: str) -> List[str]:
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"""获取分量选项"""
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food_info = self.get_food_info(food_name)
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if not food_info:
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return ["适量"]
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category = food_info["category"]
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return self.portion_sizes.get(category, ["适量"])
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def estimate_calories(self, food_name: str, portion: str) -> int:
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"""估算热量（优化版本）"""
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# 检查缓存
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cache_key = f"{food_name}_{portion}"
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if cache_key in self.calorie_cache:
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return self.calorie_cache[cache_key]
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# 首先尝试精确匹配
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if portion in self.calorie_estimates:
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portion_data = self.calorie_estimates[portion]
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if food_name in portion_data:
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calories = portion_data[food_name]
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self.calorie_cache[cache_key] = calories
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return calories
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elif "default" in portion_data:
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calories = portion_data["default"]
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self.calorie_cache[cache_key] = calories
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return calories
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# 使用快速估算
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calories = self._calculate_calories_fast(food_name, portion)
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self.calorie_cache[cache_key] = calories
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return calories
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def _estimate_weight(self, portion: str, category: str) -> int:
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"""估算重量（克）"""
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weight_estimates = {
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"1小碗": 100, "1中碗": 150, "1大碗": 200,
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"1个": 50, "2个": 100, "3个": 150,
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"1小块": 30, "2小块": 60,
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"1片": 20, "2片": 40,
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"1杯": 150, "2杯": 300,
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"1小份": 50, "1中份": 100, "1大份": 150,
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"1把": 30, "2把": 60,
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"1根": 100, "2根": 200,
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"1小把": 15, "1把": 30, "2把": 60,
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"1颗": 10, "2颗": 20, "3颗": 30,
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"1小勺": 5, "1勺": 10, "2勺": 20,
|
||
"1小匙": 3, "1匙": 5, "2匙": 10,
|
||
"适量": 50, "很多": 150, "少许": 2
|
||
}
|
||
|
||
return weight_estimates.get(portion, 50)
|
||
|
||
def _precompute_common_foods(self):
|
||
"""预计算常用食物的热量"""
|
||
common_foods = [
|
||
"米饭", "面条", "馒头", "包子", "饺子", "粥", "面包",
|
||
"鸡蛋", "鸡肉", "猪肉", "牛肉", "鱼肉", "豆腐", "牛奶", "酸奶",
|
||
"白菜", "菠菜", "西兰花", "胡萝卜", "土豆", "西红柿", "黄瓜",
|
||
"苹果", "香蕉", "橙子", "葡萄", "草莓", "西瓜"
|
||
]
|
||
|
||
common_portions = ["1小碗", "1中碗", "1大碗", "1个", "2个", "1小块", "2小块", "1杯", "2杯"]
|
||
|
||
for food in common_foods:
|
||
for portion in common_portions:
|
||
cache_key = f"{food}_{portion}"
|
||
if cache_key not in self.calorie_cache:
|
||
calories = self._calculate_calories_fast(food, portion)
|
||
self.calorie_cache[cache_key] = calories
|
||
|
||
def _calculate_calories_fast(self, food_name: str, portion: str) -> int:
|
||
"""快速计算热量（不使用AI）"""
|
||
# 首先尝试精确匹配
|
||
if portion in self.calorie_estimates:
|
||
portion_data = self.calorie_estimates[portion]
|
||
if food_name in portion_data:
|
||
return portion_data[food_name]
|
||
elif "default" in portion_data:
|
||
return portion_data["default"]
|
||
|
||
# 使用食物数据库估算
|
||
food_info = self.get_food_info(food_name)
|
||
if food_info:
|
||
weight_estimate = self._estimate_weight(portion, food_info["category"])
|
||
calories = int(food_info["calories_per_100g"] * weight_estimate / 100)
|
||
return max(calories, 10)
|
||
|
||
# 基于食物名称的快速估算
|
||
return self._quick_estimate_by_name(food_name, portion)
|
||
|
||
def _quick_estimate_by_name(self, food_name: str, portion: str) -> int:
|
||
"""基于食物名称的快速估算"""
|
||
# 食物类型快速估算
|
||
if any(keyword in food_name for keyword in ["米饭", "面条", "馒头", "包子", "饺子", "粥", "面包"]):
|
||
base_calories = 200 # 主食基础热量
|
||
elif any(keyword in food_name for keyword in ["鸡蛋", "鸡肉", "猪肉", "牛肉", "鱼肉", "豆腐", "牛奶", "酸奶"]):
|
||
base_calories = 150 # 蛋白质基础热量
|
||
elif any(keyword in food_name for keyword in ["白菜", "菠菜", "西兰花", "胡萝卜", "土豆", "西红柿", "黄瓜"]):
|
||
base_calories = 50 # 蔬菜基础热量
|
||
elif any(keyword in food_name for keyword in ["苹果", "香蕉", "橙子", "葡萄", "草莓", "西瓜"]):
|
||
base_calories = 80 # 水果基础热量
|
||
else:
|
||
base_calories = 100 # 默认基础热量
|
||
|
||
# 根据分量调整
|
||
portion_multiplier = {
|
||
"1小碗": 0.8, "1中碗": 1.0, "1大碗": 1.5,
|
||
"1个": 0.6, "2个": 1.2, "3个": 1.8,
|
||
"1小块": 0.4, "2小块": 0.8,
|
||
"1杯": 1.0, "2杯": 2.0,
|
||
"适量": 0.8, "很多": 1.5
|
||
}
|
||
|
||
multiplier = portion_multiplier.get(portion, 1.0)
|
||
return int(base_calories * multiplier)
|
||
|
||
def _estimate_calories_with_ai(self, food_name: str, portion: str) -> int:
|
||
"""使用AI估算食物热量"""
|
||
try:
|
||
from llm_integration.qwen_client import get_qwen_client
|
||
|
||
client = get_qwen_client()
|
||
|
||
# 构建AI提示词
|
||
system_prompt = """
|
||
你是一个专业的营养师，擅长估算食物的热量和营养成分。
|
||
|
||
你的任务是：
|
||
1. 根据食物名称和分量估算热量
|
||
2. 提供准确的营养信息
|
||
3. 考虑食物的常见制作方式
|
||
|
||
请以JSON格式返回结果，包含以下字段：
|
||
- calories: 估算的热量值（整数）
|
||
- category: 食物分类
|
||
- confidence: 置信度(0-1)
|
||
- reasoning: 估算理由
|
||
|
||
注意：
|
||
- 热量值应该是整数
|
||
- 考虑食物的常见分量
|
||
- 基于科学的营养学知识
|
||
- 如果不确定，给出保守估算
|
||
"""
|
||
|
||
user_prompt = f"""
|
||
请估算以下食物的热量：
|
||
|
||
食物名称: {food_name}
|
||
分量: {portion}
|
||
|
||
请提供：
|
||
1. 估算的热量值（卡路里）
|
||
2. 食物分类
|
||
3. 估算理由
|
||
4. 置信度
|
||
|
||
请以JSON格式返回结果。
|
||
"""
|
||
|
||
messages = [
|
||
{"role": "system", "content": system_prompt},
|
||
{"role": "user", "content": user_prompt}
|
||
]
|
||
|
||
response = client.chat_completion(messages, temperature=0.2, max_tokens=500)
|
||
|
||
if response and 'choices' in response:
|
||
content = response['choices'][0]['message']['content']
|
||
result = self._parse_ai_calorie_result(content)
|
||
|
||
if result.get('success'):
|
||
calories = result.get('calories', 50)
|
||
# 将AI估算的食物添加到缓存
|
||
self._cache_ai_food_info(food_name, result)
|
||
return max(calories, 10)
|
||
else:
|
||
print(f"AI解析失败: {result}")
|
||
return 50
|
||
|
||
except Exception as e:
|
||
print(f"AI热量估算失败: {e}")
|
||
|
||
# 如果AI估算失败，返回默认值
|
||
return 50
|
||
|
||
def _parse_ai_calorie_result(self, content: str) -> Dict:
|
||
"""解析AI热量估算结果"""
|
||
try:
|
||
import json
|
||
|
||
# 尝试提取JSON部分
|
||
start_idx = content.find('{')
|
||
end_idx = content.rfind('}') + 1
|
||
|
||
if start_idx != -1 and end_idx != -1:
|
||
json_str = content[start_idx:end_idx]
|
||
result_dict = json.loads(json_str)
|
||
|
||
return {
|
||
'success': True,
|
||
'calories': int(result_dict.get('calories', 50)),
|
||
'category': result_dict.get('category', '其他'),
|
||
'confidence': float(result_dict.get('confidence', 0.5)),
|
||
'reasoning': result_dict.get('reasoning', 'AI估算')
|
||
}
|
||
except Exception as e:
|
||
print(f"解析AI结果失败: {e}")
|
||
|
||
return {'success': False, 'calories': 50}
|
||
|
||
def _cache_ai_food_info(self, food_name: str, ai_result: Dict):
|
||
"""缓存AI估算的食物信息"""
|
||
try:
|
||
# 将AI估算的食物添加到内存数据库
|
||
self.food_database[food_name] = {
|
||
"category": ai_result.get('category', '其他'),
|
||
"calories_per_100g": ai_result.get('calories', 50),
|
||
"protein": 0, # AI暂时不提供详细营养成分
|
||
"carbs": 0,
|
||
"fat": 0,
|
||
"ai_estimated": True, # 标记为AI估算
|
||
"confidence": ai_result.get('confidence', 0.5)
|
||
}
|
||
except Exception as e:
|
||
print(f"缓存AI食物信息失败: {e}")
|
||
|
||
def get_food_categories(self) -> List[str]:
|
||
"""获取食物分类"""
|
||
return ["主食", "蛋白质", "蔬菜", "水果", "坚果", "饮料", "调料"]
|
||
|
||
def get_foods_by_category(self, category: str) -> List[str]:
|
||
"""根据分类获取食物列表"""
|
||
foods = []
|
||
for food_name, food_info in self.food_database.items():
|
||
if food_info["category"] == category:
|
||
foods.append(food_name)
|
||
return foods
|
||
|
||
def analyze_food_with_ai(self, food_name: str, portion: str) -> Dict:
|
||
"""使用AI分析食物详细信息"""
|
||
try:
|
||
from llm_integration.qwen_client import get_qwen_client
|
||
|
||
client = get_qwen_client()
|
||
|
||
# 构建AI提示词
|
||
system_prompt = """
|
||
你是一个专业的营养师和食物分析专家，擅长分析食物的营养成分和健康价值。
|
||
|
||
你的任务是：
|
||
1. 分析食物的详细营养成分
|
||
2. 估算热量和主要营养素含量
|
||
3. 提供健康建议
|
||
4. 考虑食物的制作方式
|
||
|
||
请以JSON格式返回结果，包含以下字段：
|
||
- calories: 热量值（整数）
|
||
- protein: 蛋白质含量（克）
|
||
- carbs: 碳水化合物含量（克）
|
||
- fat: 脂肪含量（克）
|
||
- fiber: 纤维含量（克）
|
||
- category: 食物分类
|
||
- health_tips: 健康建议列表
|
||
- cooking_suggestions: 制作建议列表
|
||
- confidence: 置信度(0-1)
|
||
- reasoning: 分析理由
|
||
|
||
注意：
|
||
- 所有数值应该是数字
|
||
- 基于科学的营养学知识
|
||
- 考虑食物的常见制作方式
|
||
- 提供实用的健康建议
|
||
"""
|
||
|
||
user_prompt = f"""
|
||
请详细分析以下食物：
|
||
|
||
食物名称: {food_name}
|
||
分量: {portion}
|
||
|
||
请提供：
|
||
1. 详细的营养成分分析
|
||
2. 热量和主要营养素含量
|
||
3. 食物分类
|
||
4. 健康建议
|
||
5. 制作建议
|
||
6. 分析理由
|
||
|
||
请以JSON格式返回结果。
|
||
"""
|
||
|
||
messages = [
|
||
{"role": "system", "content": system_prompt},
|
||
{"role": "user", "content": user_prompt}
|
||
]
|
||
|
||
response = client.chat_completion(messages, temperature=0.2, max_tokens=800)
|
||
|
||
if response and 'choices' in response:
|
||
content = response['choices'][0]['message']['content']
|
||
result = self._parse_ai_food_analysis(content)
|
||
|
||
if result.get('success'):
|
||
# 缓存AI分析结果
|
||
self._cache_ai_food_analysis(food_name, result)
|
||
return result
|
||
else:
|
||
print(f"AI食物分析解析失败: {result}")
|
||
return self._get_fallback_food_analysis(food_name, portion)
|
||
|
||
except Exception as e:
|
||
print(f"AI食物分析失败: {e}")
|
||
|
||
# 如果AI分析失败，返回基础估算
|
||
return self._get_fallback_food_analysis(food_name, portion)
|
||
|
||
def _get_fallback_food_analysis(self, food_name: str, portion: str) -> Dict:
|
||
"""获取备用食物分析结果"""
|
||
return {
|
||
'success': False,
|
||
'calories': self.estimate_calories(food_name, portion),
|
||
'protein': 0,
|
||
'carbs': 0,
|
||
'fat': 0,
|
||
'fiber': 0,
|
||
'category': '其他',
|
||
'health_tips': ['保持均衡饮食'],
|
||
'cooking_suggestions': ['简单烹饪'],
|
||
'confidence': 0.3,
|
||
'reasoning': '基础估算'
|
||
}
|
||
|
||
def _parse_ai_food_analysis(self, content: str) -> Dict:
|
||
"""解析AI食物分析结果"""
|
||
try:
|
||
import json
|
||
|
||
# 尝试提取JSON部分
|
||
start_idx = content.find('{')
|
||
end_idx = content.rfind('}') + 1
|
||
|
||
if start_idx != -1 and end_idx != -1:
|
||
json_str = content[start_idx:end_idx]
|
||
result_dict = json.loads(json_str)
|
||
|
||
return {
|
||
'success': True,
|
||
'calories': int(result_dict.get('calories', 50)),
|
||
'protein': float(result_dict.get('protein', 0)),
|
||
'carbs': float(result_dict.get('carbs', 0)),
|
||
'fat': float(result_dict.get('fat', 0)),
|
||
'fiber': float(result_dict.get('fiber', 0)),
|
||
'category': result_dict.get('category', '其他'),
|
||
'health_tips': result_dict.get('health_tips', ['保持均衡饮食']),
|
||
'cooking_suggestions': result_dict.get('cooking_suggestions', ['简单烹饪']),
|
||
'confidence': float(result_dict.get('confidence', 0.5)),
|
||
'reasoning': result_dict.get('reasoning', 'AI分析')
|
||
}
|
||
except Exception as e:
|
||
print(f"解析AI食物分析结果失败: {e}")
|
||
|
||
return {'success': False}
|
||
|
||
def _cache_ai_food_analysis(self, food_name: str, analysis_result: Dict):
|
||
"""缓存AI食物分析结果"""
|
||
try:
|
||
# 将AI分析的食物添加到内存数据库
|
||
self.food_database[food_name] = {
|
||
"category": analysis_result.get('category', '其他'),
|
||
"calories_per_100g": analysis_result.get('calories', 50),
|
||
"protein": analysis_result.get('protein', 0),
|
||
"carbs": analysis_result.get('carbs', 0),
|
||
"fat": analysis_result.get('fat', 0),
|
||
"fiber": analysis_result.get('fiber', 0),
|
||
"ai_estimated": True,
|
||
"confidence": analysis_result.get('confidence', 0.5),
|
||
"health_tips": analysis_result.get('health_tips', []),
|
||
"cooking_suggestions": analysis_result.get('cooking_suggestions', [])
|
||
}
|
||
except Exception as e:
|
||
print(f"缓存AI食物分析结果失败: {e}")
|
||
|
||
|
||
class SmartMealRecorder:
|
||
"""智能餐食记录器"""
|
||
|
||
def __init__(self):
|
||
self.food_db = SmartFoodDatabase()
|
||
|
||
def record_meal_smart(self, user_id: str, meal_data: Dict) -> bool:
|
||
"""智能记录餐食"""
|
||
try:
|
||
# 自动估算热量
|
||
total_calories = 0
|
||
for food_item in meal_data.get("foods", []):
|
||
food_name = food_item.get("name", "")
|
||
portion = food_item.get("portion", "适量")
|
||
calories = self.food_db.estimate_calories(food_name, portion)
|
||
total_calories += calories
|
||
food_item["estimated_calories"] = calories
|
||
|
||
# 更新总热量
|
||
meal_data["total_calories"] = total_calories
|
||
|
||
# 保存到数据库
|
||
from modules.data_collection import record_meal
|
||
return record_meal(user_id, meal_data)
|
||
|
||
except Exception as e:
|
||
print(f"智能记录餐食失败: {e}")
|
||
return False
|
||
|
||
def suggest_foods(self, category: str = None) -> List[str]:
|
||
"""建议食物"""
|
||
if category:
|
||
return self.food_db.get_foods_by_category(category)
|
||
else:
|
||
# 返回所有食物
|
||
return list(self.food_db.food_database.keys())
|
||
|
||
def search_foods(self, query: str) -> List[Dict]:
|
||
"""搜索食物"""
|
||
return self.food_db.search_foods(query)
|
||
|
||
|
||
# 全局实例
|
||
smart_meal_recorder = SmartMealRecorder()
|
||
|
||
|
||
# 便捷函数
|
||
def search_foods(query: str) -> List[Dict]:
|
||
"""搜索食物"""
|
||
return smart_meal_recorder.search_foods(query)
|
||
|
||
|
||
def get_food_categories() -> List[str]:
|
||
"""获取食物分类"""
|
||
return smart_meal_recorder.food_db.get_food_categories()
|
||
|
||
|
||
def get_foods_by_category(category: str) -> List[str]:
|
||
"""根据分类获取食物"""
|
||
return smart_meal_recorder.food_db.get_foods_by_category(category)
|
||
|
||
|
||
def get_portion_options(food_name: str) -> List[str]:
|
||
"""获取分量选项"""
|
||
return smart_meal_recorder.food_db.get_portion_options(food_name)
|
||
|
||
|
||
def estimate_calories(food_name: str, portion: str) -> int:
|
||
"""估算热量"""
|
||
return smart_meal_recorder.food_db.estimate_calories(food_name, portion)
|
||
|
||
|
||
def record_meal_smart(user_id: str, meal_data: Dict) -> bool:
|
||
"""智能记录餐食"""
|
||
return smart_meal_recorder.record_meal_smart(user_id, meal_data)
|
||
|
||
|
||
def analyze_food_with_ai(food_name: str, portion: str) -> Dict:
|
||
"""使用AI分析食物详细信息"""
|
||
return smart_meal_recorder.food_db.analyze_food_with_ai(food_name, portion)
|
||
|
||
|
||
def get_food_ai_suggestions(food_name: str) -> Dict:
|
||
"""获取食物的AI建议"""
|
||
try:
|
||
food_info = smart_meal_recorder.food_db.get_food_info(food_name)
|
||
if food_info and food_info.get('ai_estimated'):
|
||
return {
|
||
'health_tips': food_info.get('health_tips', ['保持均衡饮食']),
|
||
'cooking_suggestions': food_info.get('cooking_suggestions', ['简单烹饪']),
|
||
'confidence': food_info.get('confidence', 0.5)
|
||
}
|
||
else:
|
||
# 如果数据库中没有AI分析结果，进行AI分析
|
||
analysis = analyze_food_with_ai(food_name, "适量")
|
||
return {
|
||
'health_tips': analysis.get('health_tips', ['保持均衡饮食']),
|
||
'cooking_suggestions': analysis.get('cooking_suggestions', ['简单烹饪']),
|
||
'confidence': analysis.get('confidence', 0.5)
|
||
}
|
||
except Exception as e:
|
||
print(f"获取AI建议失败: {e}")
|
||
return {
|
||
'health_tips': ['保持均衡饮食'],
|
||
'cooking_suggestions': ['简单烹饪'],
|
||
'confidence': 0.3
|
||
}
|
||
|
||
|
||
if __name__ == "__main__":
|
||
# 测试智能食物数据库
|
||
print("测试智能食物数据库...")
|
||
|
||
# 测试搜索
|
||
results = search_foods("鸡")
|
||
print(f"搜索'鸡'的结果: {results}")
|
||
|
||
# 测试分类
|
||
categories = get_food_categories()
|
||
print(f"食物分类: {categories}")
|
||
|
||
# 测试分量选项
|
||
portions = get_portion_options("鸡肉")
|
||
print(f"鸡肉的分量选项: {portions}")
|
||
|
||
# 测试热量估算
|
||
calories = estimate_calories("鸡肉", "1小块")
|
||
print(f"1小块鸡肉的热量: {calories}卡路里")
|
||
|
||
print("智能食物数据库测试完成！")
|