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recommend/smart_food/smart_database.py

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Initial commit: 个性化饮食推荐助手 - 包含OCR识别、AI分析、现代化界面等功能
2025-09-25 14:20:11 +01:00
"""
智能食物数据库和热量估算模块
简化用户数据录入过程
"""
from typing import Dict, List, Optional, Tuple
import json
from pathlib import Path
class SmartFoodDatabase:
"""智能食物数据库"""
def __init__(self):
self.food_database = self._load_food_database()
self.portion_sizes = self._load_portion_sizes()
self.calorie_estimates = self._load_calorie_estimates()
# 添加缓存
self.ai_cache = {} # AI分析结果缓存
self.calorie_cache = {} # 热量估算缓存
self.search_cache = {} # 搜索结果缓存
# 预计算常用食物
self._precompute_common_foods()
def _load_food_database(self) -> Dict[str, Dict]:
"""加载食物数据库"""
return {
# 主食类
"米饭": {"category": "主食", "calories_per_100g": 130, "protein": 2.7, "carbs": 28, "fat": 0.3},
"面条": {"category": "主食", "calories_per_100g": 131, "protein": 5, "carbs": 25, "fat": 1.1},
"馒头": {"category": "主食", "calories_per_100g": 221, "protein": 7, "carbs": 47, "fat": 1.1},
"包子": {"category": "主食", "calories_per_100g": 227, "protein": 7.3, "carbs": 45, "fat": 2.6},
"饺子": {"category": "主食", "calories_per_100g": 250, "protein": 11, "carbs": 35, "fat": 8},
"粥": {"category": "主食", "calories_per_100g": 50, "protein": 1.1, "carbs": 10, "fat": 0.3},
"燕麦": {"category": "主食", "calories_per_100g": 389, "protein": 17, "carbs": 66, "fat": 7},
"面包": {"category": "主食", "calories_per_100g": 265, "protein": 9, "carbs": 49, "fat": 3.2},
"饼干": {"category": "主食", "calories_per_100g": 433, "protein": 9, "carbs": 71, "fat": 12},
"薯条": {"category": "主食", "calories_per_100g": 319, "protein": 4, "carbs": 41, "fat": 15},
"玉米": {"category": "主食", "calories_per_100g": 86, "protein": 3.4, "carbs": 19, "fat": 1.2},
"红薯": {"category": "主食", "calories_per_100g": 86, "protein": 1.6, "carbs": 20, "fat": 0.1},
# 蛋白质类
"鸡蛋": {"category": "蛋白质", "calories_per_100g": 155, "protein": 13, "carbs": 1.1, "fat": 11},
"鸡肉": {"category": "蛋白质", "calories_per_100g": 165, "protein": 31, "carbs": 0, "fat": 3.6},
"猪肉": {"category": "蛋白质", "calories_per_100g": 143, "protein": 20, "carbs": 0, "fat": 6.2},
"牛肉": {"category": "蛋白质", "calories_per_100g": 250, "protein": 26, "carbs": 0, "fat": 15},
"鱼肉": {"category": "蛋白质", "calories_per_100g": 206, "protein": 22, "carbs": 0, "fat": 12},
"豆腐": {"category": "蛋白质", "calories_per_100g": 76, "protein": 8, "carbs": 2, "fat": 4.8},
"牛奶": {"category": "蛋白质", "calories_per_100g": 42, "protein": 3.4, "carbs": 5, "fat": 1},
"酸奶": {"category": "蛋白质", "calories_per_100g": 59, "protein": 3.3, "carbs": 4.7, "fat": 3.2},
"虾": {"category": "蛋白质", "calories_per_100g": 99, "protein": 24, "carbs": 0, "fat": 0.2},
"蟹": {"category": "蛋白质", "calories_per_100g": 97, "protein": 20, "carbs": 0, "fat": 1.5},
"鸭肉": {"category": "蛋白质", "calories_per_100g": 183, "protein": 25, "carbs": 0, "fat": 9},
"羊肉": {"category": "蛋白质", "calories_per_100g": 203, "protein": 25, "carbs": 0, "fat": 11},
"火腿": {"category": "蛋白质", "calories_per_100g": 145, "protein": 18, "carbs": 1.5, "fat": 7.5},
"香肠": {"category": "蛋白质", "calories_per_100g": 301, "protein": 13, "carbs": 2, "fat": 25},
# 蔬菜类
"白菜": {"category": "蔬菜", "calories_per_100g": 17, "protein": 1.5, "carbs": 3.2, "fat": 0.1},
"菠菜": {"category": "蔬菜", "calories_per_100g": 23, "protein": 2.9, "carbs": 3.6, "fat": 0.4},
"西兰花": {"category": "蔬菜", "calories_per_100g": 34, "protein": 2.8, "carbs": 7, "fat": 0.4},
"胡萝卜": {"category": "蔬菜", "calories_per_100g": 41, "protein": 0.9, "carbs": 10, "fat": 0.2},
"土豆": {"category": "蔬菜", "calories_per_100g": 77, "protein": 2, "carbs": 17, "fat": 0.1},
"西红柿": {"category": "蔬菜", "calories_per_100g": 18, "protein": 0.9, "carbs": 3.9, "fat": 0.2},
"黄瓜": {"category": "蔬菜", "calories_per_100g": 16, "protein": 0.7, "carbs": 4, "fat": 0.1},
"茄子": {"category": "蔬菜", "calories_per_100g": 25, "protein": 1.1, "carbs": 6, "fat": 0.2},
"豆角": {"category": "蔬菜", "calories_per_100g": 31, "protein": 2.1, "carbs": 7, "fat": 0.2},
"韭菜": {"category": "蔬菜", "calories_per_100g": 25, "protein": 2.4, "carbs": 4, "fat": 0.4},
"芹菜": {"category": "蔬菜", "calories_per_100g": 16, "protein": 0.7, "carbs": 4, "fat": 0.1},
"洋葱": {"category": "蔬菜", "calories_per_100g": 40, "protein": 1.1, "carbs": 9, "fat": 0.1},
"大蒜": {"category": "蔬菜", "calories_per_100g": 149, "protein": 6.4, "carbs": 33, "fat": 0.5},
"生姜": {"category": "蔬菜", "calories_per_100g": 80, "protein": 1.8, "carbs": 18, "fat": 0.8},
# 水果类
"苹果": {"category": "水果", "calories_per_100g": 52, "protein": 0.3, "carbs": 14, "fat": 0.2},
"香蕉": {"category": "水果", "calories_per_100g": 89, "protein": 1.1, "carbs": 23, "fat": 0.3},
"橙子": {"category": "水果", "calories_per_100g": 47, "protein": 0.9, "carbs": 12, "fat": 0.1},
"葡萄": {"category": "水果", "calories_per_100g": 44, "protein": 0.2, "carbs": 11, "fat": 0.2},
"草莓": {"category": "水果", "calories_per_100g": 32, "protein": 0.7, "carbs": 8, "fat": 0.3},
"西瓜": {"category": "水果", "calories_per_100g": 30, "protein": 0.6, "carbs": 8, "fat": 0.1},
"梨": {"category": "水果", "calories_per_100g": 57, "protein": 0.4, "carbs": 15, "fat": 0.1},
"桃子": {"category": "水果", "calories_per_100g": 39, "protein": 0.9, "carbs": 10, "fat": 0.3},
"樱桃": {"category": "水果", "calories_per_100g": 63, "protein": 1.1, "carbs": 16, "fat": 0.2},
"柠檬": {"category": "水果", "calories_per_100g": 29, "protein": 1.1, "carbs": 9, "fat": 0.3},
"芒果": {"category": "水果", "calories_per_100g": 60, "protein": 0.8, "carbs": 15, "fat": 0.4},
"菠萝": {"category": "水果", "calories_per_100g": 50, "protein": 0.5, "carbs": 13, "fat": 0.1},
"猕猴桃": {"category": "水果", "calories_per_100g": 61, "protein": 1.1, "carbs": 15, "fat": 0.5},
# 坚果类
"花生": {"category": "坚果", "calories_per_100g": 567, "protein": 25, "carbs": 16, "fat": 49},
"核桃": {"category": "坚果", "calories_per_100g": 654, "protein": 15, "carbs": 14, "fat": 65},
"杏仁": {"category": "坚果", "calories_per_100g": 579, "protein": 21, "carbs": 22, "fat": 50},
"腰果": {"category": "坚果", "calories_per_100g": 553, "protein": 18, "carbs": 30, "fat": 44},
"开心果": {"category": "坚果", "calories_per_100g": 560, "protein": 20, "carbs": 28, "fat": 45},
"瓜子": {"category": "坚果", "calories_per_100g": 606, "protein": 19, "carbs": 20, "fat": 53},
# 饮料类
"水": {"category": "饮料", "calories_per_100g": 0, "protein": 0, "carbs": 0, "fat": 0},
"茶": {"category": "饮料", "calories_per_100g": 1, "protein": 0.1, "carbs": 0.3, "fat": 0},
"咖啡": {"category": "饮料", "calories_per_100g": 2, "protein": 0.1, "carbs": 0.3, "fat": 0},
"果汁": {"category": "饮料", "calories_per_100g": 45, "protein": 0.3, "carbs": 11, "fat": 0.1},
"可乐": {"category": "饮料", "calories_per_100g": 42, "protein": 0, "carbs": 10.6, "fat": 0},
"雪碧": {"category": "饮料", "calories_per_100g": 40, "protein": 0, "carbs": 10, "fat": 0},
"啤酒": {"category": "饮料", "calories_per_100g": 43, "protein": 0.5, "carbs": 3.6, "fat": 0},
"红酒": {"category": "饮料", "calories_per_100g": 83, "protein": 0.1, "carbs": 2.6, "fat": 0},
"白酒": {"category": "饮料", "calories_per_100g": 298, "protein": 0, "carbs": 0, "fat": 0},
# 调料类
"盐": {"category": "调料", "calories_per_100g": 0, "protein": 0, "carbs": 0, "fat": 0},
"糖": {"category": "调料", "calories_per_100g": 387, "protein": 0, "carbs": 100, "fat": 0},
"酱油": {"category": "调料", "calories_per_100g": 63, "protein": 7, "carbs": 7, "fat": 0},
"醋": {"category": "调料", "calories_per_100g": 31, "protein": 0.1, "carbs": 7, "fat": 0},
"油": {"category": "调料", "calories_per_100g": 884, "protein": 0, "carbs": 0, "fat": 100},
"辣椒": {"category": "调料", "calories_per_100g": 40, "protein": 1.9, "carbs": 9, "fat": 0.4},
"胡椒": {"category": "调料", "calories_per_100g": 251, "protein": 10, "carbs": 64, "fat": 3.3},
"花椒": {"category": "调料", "calories_per_100g": 258, "protein": 6, "carbs": 37, "fat": 8.9},
}
def _load_portion_sizes(self) -> Dict[str, List[str]]:
"""加载分量选项"""
return {
"主食": ["1小碗", "1中碗", "1大碗", "1个", "2个", "3个", "半份", "1份", "2份"],
"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"],
"蔬菜": ["1小份", "1中份", "1大份", "1把", "2把", "1根", "2根", "适量", "很多"],
"水果": ["1个", "2个", "3个", "1小个", "1大个", "1片", "2片", "适量"],
"坚果": ["1小把", "1把", "2把", "1颗", "2颗", "3颗", "适量"],
"饮料": ["1杯", "2杯", "3杯", "1小杯", "1大杯", "1瓶", "2瓶", "适量"],
"调料": ["1小勺", "1勺", "2勺", "1小匙", "1匙", "2匙", "适量", "少许"]
}
def _load_calorie_estimates(self) -> Dict[str, Dict]:
"""加载热量估算"""
return {
"1小碗": {"米饭": 130, "面条": 131, "粥": 50},
"1中碗": {"米饭": 195, "面条": 196, "粥": 75},
"1大碗": {"米饭": 260, "面条": 262, "粥": 100},
"1个": {"鸡蛋": 77, "苹果": 52, "香蕉": 89, "馒头": 221, "包子": 227},
"2个": {"鸡蛋": 154, "苹果": 104, "香蕉": 178, "馒头": 442, "包子": 454},
"1小块": {"鸡肉": 50, "猪肉": 50, "牛肉": 50, "豆腐": 50},
"2小块": {"鸡肉": 100, "猪肉": 100, "牛肉": 100, "豆腐": 100},
"1杯": {"牛奶": 150, "酸奶": 150, "水": 0, "茶": 0, "咖啡": 0},
"2杯": {"牛奶": 300, "酸奶": 300, "水": 0, "茶": 0, "咖啡": 0},
"1小份": {"白菜": 50, "菠菜": 50, "西兰花": 50, "胡萝卜": 50},
"1中份": {"白菜": 100, "菠菜": 100, "西兰花": 100, "胡萝卜": 100},
"1大份": {"白菜": 150, "菠菜": 150, "西兰花": 150, "胡萝卜": 150},
"1小把": {"花生": 30, "核桃": 30, "杏仁": 30},
"1把": {"花生": 60, "核桃": 60, "杏仁": 60},
"适量": {"default": 50}, # 默认适量为50卡路里
"很多": {"default": 150}, # 默认很多为150卡路里
"1小勺": {"盐": 0, "糖": 16, "酱油": 3, "醋": 2, "油": 44, "辣椒": 2, "胡椒": 13, "花椒": 13},
"1勺": {"盐": 0, "糖": 32, "酱油": 6, "醋": 4, "油": 88, "辣椒": 4, "胡椒": 25, "花椒": 26},
"2勺": {"盐": 0, "糖": 64, "酱油": 12, "醋": 8, "油": 176, "辣椒": 8, "胡椒": 50, "花椒": 52},
"1小匙": {"盐": 0, "糖": 8, "酱油": 1.5, "醋": 1, "油": 22, "辣椒": 1, "胡椒": 6, "花椒": 6},
"1匙": {"盐": 0, "糖": 16, "酱油": 3, "醋": 2, "油": 44, "辣椒": 2, "胡椒": 13, "花椒": 13},
"2匙": {"盐": 0, "糖": 32, "酱油": 6, "醋": 4, "油": 88, "辣椒": 4, "胡椒": 25, "花椒": 26},
"少许": {"default": 5}, # 默认少许为5卡路里
}
def search_foods(self, query: str) -> List[Dict]:
"""搜索食物（优化版本）"""
query = query.lower().strip()
# 检查缓存
if query in self.search_cache:
return self.search_cache[query]
results = []
# 精确匹配优先
for food_name, food_info in self.food_database.items():
if query == food_name.lower():
results.insert(0, {
"name": food_name,
"category": food_info["category"],
"calories_per_100g": food_info["calories_per_100g"],
"match_type": "exact"
})
# 包含匹配
for food_name, food_info in self.food_database.items():
if query in food_name.lower() and query != food_name.lower():
results.append({
"name": food_name,
"category": food_info["category"],
"calories_per_100g": food_info["calories_per_100g"],
"match_type": "contains"
})
# 关键词匹配
if len(results) < 5:
keywords = query.split()
for food_name, food_info in self.food_database.items():
if any(keyword in food_name.lower() for keyword in keywords):
if not any(r["name"] == food_name for r in results):
results.append({
"name": food_name,
"category": food_info["category"],
"calories_per_100g": food_info["calories_per_100g"],
"match_type": "keyword"
})
# 限制结果数量并缓存
results = results[:10]
self.search_cache[query] = results
return results
def get_food_info(self, food_name: str) -> Optional[Dict]:
"""获取食物信息"""
return self.food_database.get(food_name)
def get_portion_options(self, food_name: str) -> List[str]:
"""获取分量选项"""
food_info = self.get_food_info(food_name)
if not food_info:
return ["适量"]
category = food_info["category"]
return self.portion_sizes.get(category, ["适量"])
def estimate_calories(self, food_name: str, portion: str) -> int:
"""估算热量（优化版本）"""
# 检查缓存
cache_key = f"{food_name}_{portion}"
if cache_key in self.calorie_cache:
return self.calorie_cache[cache_key]
# 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:
calories = portion_data[food_name]
self.calorie_cache[cache_key] = calories
return calories
elif "default" in portion_data:
calories = portion_data["default"]
self.calorie_cache[cache_key] = calories
return calories
# 使用快速估算
calories = self._calculate_calories_fast(food_name, portion)
self.calorie_cache[cache_key] = calories
return calories
def _estimate_weight(self, portion: str, category: str) -> int:
"""估算重量（克）"""
weight_estimates = {
"1小碗": 100, "1中碗": 150, "1大碗": 200,
"1个": 50, "2个": 100, "3个": 150,
"1小块": 30, "2小块": 60,
"1片": 20, "2片": 40,
"1杯": 150, "2杯": 300,
"1小份": 50, "1中份": 100, "1大份": 150,
"1把": 30, "2把": 60,
"1根": 100, "2根": 200,
"1小把": 15, "1把": 30, "2把": 60,
"1颗": 10, "2颗": 20, "3颗": 30,
"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！")
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