app.py

import gradio as gr
import random
from PIL import Image
import numpy as np
from datetime import datetime, timedelta
import pandas as pd
import plotly.graph_objects as go
from plotly.subplots import make_subplots

# 食物營養資料庫
food_nutrition = {
    "米飯": {
        "calories": 130, "protein": 2.7, "carbs": 28.7, "fat": 0.3, "fiber": 0.4,
        "category": "主食", "glycemic_index": "高", "allergens": [],
        "vitamins": {"B1": 0.02, "B2": 0.01, "B3": 0.4},
        "minerals": {"鐵": 0.2, "鎂": 12, "鋅": 0.4}
    },
    "牛肉": {
        "calories": 250, "protein": 26, "carbs": 0, "fat": 17, "fiber": 0,
        "category": "蛋白質", "glycemic_index": "低", "allergens": [],
        "vitamins": {"B12": 2.1, "B6": 0.3, "D": 0.1},
        "minerals": {"鐵": 2.7, "鋅": 4.8, "硒": 33.2}
    },
    "麵包": {
        "calories": 265, "protein": 9, "carbs": 49, "fat": 3.2, "fiber": 2.5,
        "category": "主食", "glycemic_index": "高", "allergens": ["麩質"],
        "vitamins": {"B1": 0.1, "B3": 1.3, "葉酸": 0.04},
        "minerals": {"鎂": 26, "磷": 86, "鐵": 1.4}
    },
    "蔬菜": {
        "calories": 25, "protein": 1.5, "carbs": 5, "fat": 0.2, "fiber": 2.5,
        "category": "蔬菜", "glycemic_index": "低", "allergens": [],
        "vitamins": {"A": 0.5, "C": 10, "K": 0.1},
        "minerals": {"鉀": 290, "鈣": 40, "鎂": 15}
    },
    "番茄": {
        "calories": 18, "protein": 0.9, "carbs": 3.9, "fat": 0.2, "fiber": 1.2,
        "category": "蔬果", "glycemic_index": "低", "allergens": [],
        "vitamins": {"C": 13.7, "A": 0.8, "K": 0.07},
        "minerals": {"鉀": 237, "鎂": 11, "鈣": 10}
    },
    "雞蛋": {
        "calories": 155, "protein": 13, "carbs": 0.6, "fat": 11, "fiber": 0,
        "category": "蛋白質", "glycemic_index": "低", "allergens": ["蛋"],
        "vitamins": {"D": 1.1, "B12": 0.6, "B2": 0.3},
        "minerals": {"硒": 20, "鋅": 1.3, "鐵": 1.8}
    },
    "豬肉": {
            "calories": 242, "protein": 22.5, "carbs": 0, "fat": 17, "fiber": 0,
            "category": "蛋白質", "glycemic_index": "低", "allergens": [],
            "vitamins": {"B1": 0.6, "B6": 0.4, "B12": 0.7},
            "minerals": {"鋅": 4.5, "鐵": 1.2, "硒": 35.3}
    },
    "三文魚": {
            "calories": 208, "protein": 22, "carbs": 0, "fat": 13, "fiber": 0,
            "category": "蛋白質", "glycemic_index": "低", "allergens": ["魚"],
            "vitamins": {"D": 9.5, "B12": 3.2, "B6": 0.6},
            "minerals": {"硒": 40.2, "鋅": 0.5, "鐵": 0.5}
    },
    "青菜": {
            "calories": 16, "protein": 1.3, "carbs": 2.9, "fat": 0.2, "fiber": 2.1,
            "category": "蔬菜", "glycemic_index": "低", "allergens": [],
            "vitamins": {"A": 0.3, "C": 35, "K": 0.2},
            "minerals": {"鈣": 105, "鎂": 22, "鉀": 370}
    },
    "水果": {
            "calories": 52, "protein": 0.5, "carbs": 14, "fat": 0.2, "fiber": 2.4,
            "category": "蔬果", "glycemic_index": "中", "allergens": [],
            "vitamins": {"C": 8.5, "A": 0.2, "葉酸": 0.02},
            "minerals": {"鉀": 200, "鎂": 10, "鈣": 20}
    },
    "土豆": {
            "calories": 77, "protein": 2, "carbs": 17, "fat": 0.1, "fiber": 2.2,
            "category": "主食", "glycemic_index": "高", "allergens": [],
            "vitamins": {"C": 10, "B6": 0.3, "葉酸": 0.01},
            "minerals": {"鉀": 421, "鎂": 23, "磷": 57}
    },
    "豆腐": {
            "calories": 84, "protein": 9, "carbs": 2, "fat": 5, "fiber": 0.5,
            "category": "蛋白質", "glycemic_index": "低", "allergens": ["大豆"],
            "vitamins": {"A": 0.1, "葉酸": 0.02, "K": 0.02},
            "minerals": {"鈣": 350, "鐵": 2.1, "鎂": 37}
    },
    "花生": {
            "calories": 567, "protein": 25.8, "carbs": 16.1, "fat": 49.2, "fiber": 8.5,
            "category": "脂肪", "glycemic_index": "低", "allergens": ["花生"],
            "vitamins": {"E": 8.3, "B3": 14.4, "葉酸": 0.24},
            "minerals": {"鎂": 168, "磷": 376, "鋅": 3.3}
    },
    "牛奶": {
            "calories": 42, "protein": 3.4, "carbs": 4.8, "fat": 1.0, "fiber": 0,
            "category": "乳製品", "glycemic_index": "低", "allergens": ["乳製品"],
            "vitamins": {"B12": 0.4, "B2": 0.2, "D": 0.1},
            "minerals": {"鈣": 120, "磷": 93, "鉀": 150}
    },
    "香蕉": {
            "calories": 89, "protein": 1.1, "carbs": 22.8, "fat": 0.3, "fiber": 2.6,
            "category": "蔬果", "glycemic_index": "中", "allergens": [],
            "vitamins": {"C": 8.7, "B6": 0.4, "A": 0.1},
            "minerals": {"鉀": 358, "鎂": 27, "鐵": 0.3}
    },
    "雞肉": {
            "calories": 239, "protein": 27, "carbs": 0, "fat": 14, "fiber": 0,
            "category": "蛋白質", "glycemic_index": "低", "allergens": [],
            "vitamins": {"B6": 0.5, "B12": 0.3, "A": 0.02},
            "minerals": {"鋅": 2.7, "鐵": 0.9, "硒": 24.5}
    }
    
    
}

class UserProfile:
    # 初始化用戶資料
    def __init__(self, age, gender, height, weight, activity_level):
        # 身高與體重範圍檢查
        if not (50 <= height <= 250):
            raise ValueError("身高應在50到250公分之間")
        if not (20 <= weight <= 300):
            raise ValueError("體重應在20到300公斤之間")
        
        self.age = age
        self.gender = gender
        self.height = height
        self.weight = weight
        self.activity_level = activity_level

    def calculate_bmr(self):
        # 計算基礎代謢率（BMR）
        if self.gender == "男":
            return 88.362 + (13.397 * self.weight) + (4.799 * self.height) - (5.677 * self.age)
        else:
            return 447.593 + (9.247 * self.weight) + (3.098 * self.height) - (4.330 * self.age)

    def calculate_tdee(self):
        # 計算每日總能量消耗（TDEE）
        activity_factors = {
            "久坐": 1.2,
            "輕度活動": 1.375,
            "中度活動": 1.55,
            "重度活動": 1.725,
            "極重度活動": 1.9
        }
        return self.calculate_bmr() * activity_factors[self.activity_level]

def create_nutrition_charts(total_nutrients, recommended_nutrients, total_calories):
    """創建優化後的營養圖表"""
    # 創建子圖布局
    fig = make_subplots(
        rows=2, cols=2,
        specs=[
            [{"colspan": 2}, None],
            [{"type": "pie"}, {"type": "bar"}]
        ],
        subplot_titles=(
            '每日營養素攝入比較',
            '熱量來源分布',
            '營養素達標率'
        ),
        vertical_spacing=0.12,
        horizontal_spacing=0.1
    )

    # 1. 營養素對比條形圖（上方大圖）
    nutrients = ['蛋白質', '碳水化合物', '脂肪', '膳食纖維']

    fig.add_trace(
        go.Bar(
            name='實際攝入',
            x=nutrients,
            y=[total_nutrients[n] for n in nutrients],
            marker_color='rgb(55, 83, 109)'
        ),
        row=1, col=1
    )

    fig.add_trace(
        go.Bar(
            name='建議攝入',
            x=nutrients,
            y=[recommended_nutrients[n] for n in nutrients],
            marker_color='rgb(26, 118, 255)'
        ),
        row=1, col=1
    )

    # 2. 熱量來源分布圓餅圖（左下）
    calorie_values = [
        total_nutrients['蛋白質'] * 4,
        total_nutrients['碳水化合物'] * 4,
        total_nutrients['脂肪'] * 9
    ]

    fig.add_trace(
        go.Pie(
            labels=['蛋白質', '碳水化合物', '脂肪'],
            values=calorie_values,
            hole=0.4,
            marker=dict(colors=['rgb(55, 83, 109)', 'rgb(26, 118, 255)', 'rgb(95, 70, 144)'])
        ),
        row=2, col=1
    )

    # 3. 營養素達標率（右下）
    achievement_rates = [
        (total_nutrients[n] / recommended_nutrients[n] * 100)
        if recommended_nutrients[n] > 0 else 0
        for n in nutrients
    ]

    fig.add_trace(
        go.Bar(
            x=nutrients,
            y=achievement_rates,
            marker_color='rgb(158, 202, 225)',
            text=[f"{rate:.1f}%" for rate in achievement_rates],
            textposition='auto',
        ),
        row=2, col=2
    )

    # 更新布局
    fig.update_layout(
        height=800,  # 增加圖表高度
        width=900,   # 適當的寬度
        showlegend=True,
        legend=dict(
            orientation="h",
            yanchor="bottom",
            y=1.02,
            xanchor="right",
            x=1
        ),
        title_text="營養分析總覽",
        title_x=0.5,
        font=dict(size=12),
    )

    # 更新y軸標題
    fig.update_yaxes(title_text="克", row=1, col=1)
    fig.update_yaxes(title_text="達標率(%)", row=2, col=2)

    return fig

def analyze_meals_advanced(
    images, age, gender, height, weight,
    activity_level, diet_preference, health_goal,
    allergies, medical_conditions
):
    try:
        # 新增的輸入驗證
        if not all([age, gender, height, weight, activity_level]):
            return "請填寫所有必要的個人信息", "", "", None, ""

        # 檢查過敏原
        if "無" in allergies and len(allergies) > 1:
            return "過敏原不能同時選擇「無」和其他選項", "", "", None, ""

        # 檢查醫療狀況
        if "無" in medical_conditions and len(medical_conditions) > 1:
            return "醫療狀況不能同時選擇「無」和其他選項", "", "", None, ""

        # 嘗試建立UserProfile並檢查身高體重範圍
        user = UserProfile(age, gender, height, weight, activity_level)
        tdee = user.calculate_tdee()

        # 模擬食物識別
        recognized_foods = []
        for img in images:
            foods = random.sample(list(food_nutrition.keys()), k=random.randint(1, 3))
            recognized_foods.extend(foods)

        # 計算營養總量
        total_nutrients = {
            "蛋白質": sum(food_nutrition[food]["protein"] for food in recognized_foods),
            "碳水化合物": sum(food_nutrition[food]["carbs"] for food in recognized_foods),
            "脂肪": sum(food_nutrition[food]["fat"] for food in recognized_foods),
            "膳食纖維": sum(food_nutrition[food]["fiber"] for food in recognized_foods)
        }

        # 計算建議攝入量
        recommended_nutrients = {
            "蛋白質": weight * 1.2,
            "碳水化合物": tdee * 0.5 / 4,
            "脂肪": tdee * 0.3 / 9,
            "膳食纖維": 25
        }

        total_calories = sum(food_nutrition[food]["calories"] for food in recognized_foods)

        # 創建優化後的圖表
        charts = create_nutrition_charts(total_nutrients, recommended_nutrients, total_calories)

        # 生成更簡潔的報告
        report = f"""📊 營養攝入概要
--------------------------------
⚡ 每日能量需求：{tdee:.0f} 大卡
🍽️ 實際攝入：{total_calories:.0f} 大卡
🥩 蛋白質：{total_nutrients['蛋白質']:.1f}g
🍚 碳水化合物：{total_nutrients['碳水化合物']:.1f}g
🥑 脂肪：{total_nutrients['脂肪']:.1f}g
🥬 膳食纖維：{total_nutrients['膳食纖維']:.1f}g"""

        # 過敏警告
        allergy_warnings = "⚠️ 過敏原警告：\n"
        if allergies and "無" not in allergies:
            found_allergens = []
            for food in recognized_foods:
                food_allergens = food_nutrition[food].get("allergens", [])
                found_allergens.extend([a for a in allergies if a in food_allergens])

            if found_allergens:
                allergy_warnings += "\n".join(f"- 發現含有{allergen}的食物" for allergen in set(found_allergens))
            else:
                allergy_warnings += "未發現任何過敏原"
        else:
            allergy_warnings += "未設置過敏原信息"

        # 醫療建議
        medical_advice = "👨‍⚕️ 健康建議：\n"
        if medical_conditions:
            for condition in medical_conditions:
                if condition == "糖尿病":
                    if total_nutrients['碳水化合物'] > recommended_nutrients['碳水化合物']:
                        medical_advice += "- 碳水化合物攝入偏高，建議調整\n"
                elif condition == "高血壓":
                    medical_advice += "- 建議選擇低鈉食物，控制鹽分攝入\n"
        else:
            medical_advice += "無特殊醫療注意事項"

        return report, allergy_warnings, recognized_foods, charts, medical_advice

    except ValueError as e:
        return f"錯誤：{str(e)}", "", "", None, ""  # 返回錯誤訊息
    except Exception as e:
        return f"分析過程出錯：{str(e)}", "", "", None, ""

def create_interface():
    with gr.Blocks(theme=gr.themes.Soft()) as iface:
        gr.Markdown("# 🥗 智能營養分析系統")

        with gr.Row():
            with gr.Column(scale=1):
                images = gr.Gallery(label="上傳一日三餐的照片", height=200)

                with gr.Row():
                    with gr.Column(scale=1):
                        age = gr.Number(label="年齡", minimum=1, maximum=120)
                        height = gr.Number(label="身高(cm)", minimum=50, maximum=250)
                    with gr.Column(scale=1):
                        gender = gr.Radio(["男", "女"], label="性別")
                        weight = gr.Number(label="體重(kg)", minimum=20, maximum=200)

                activity_level = gr.Dropdown(
                    ["久坐", "輕度活動", "中度活動", "重度活動", "極重度活動"],
                    label="活動程度"
                )

                with gr.Row():
                    with gr.Column(scale=1):
                        diet_preference = gr.Radio(
                            ["一般", "素食", "低碳", "高蛋白", "低脂", "無糖"],
                            label="飲食偏好"
                        )
                        health_goal = gr.Radio(
                            ["減肥", "增肌", "維持健康", "改善消化"],
                            label="健康目標"
                        )

                    with gr.Column(scale=1):
                        allergies = gr.Radio(
                            ["無", "花生", "海鮮", "乳製品", "麩質", "蛋", "豆類"],
                            label="過敏原",
                            type="value"  # 新增這個參數
                        )
                        medical_conditions = gr.Radio(
                            ["無", "糖尿病", "高血壓", "高血脂", "腎臟病"],
                            label="醫療狀況",
                            type="value"  # 新增這個參數
                        )

            with gr.Column(scale=1):
                charts_output = gr.Plot(label="營養分析圖表")
                report_output = gr.Textbox(label="營養分析報告", lines=6)
                with gr.Row():
                    allergy_warning_output = gr.Textbox(label="過敏警告", lines=3)
                    medical_advice_output = gr.Textbox(label="醫療建議", lines=3)
                suggestions_output = gr.Textbox(label="個人化建議", lines=8)

        analyze_btn = gr.Button("開始分析", variant="primary")
        analyze_btn.click(
            fn=analyze_meals_advanced,
            inputs=[images, age, gender, height, weight,
                    activity_level, diet_preference, health_goal,
                    allergies, medical_conditions],
            outputs=[report_output, allergy_warning_output,
                     medical_advice_output, charts_output, suggestions_output]
        )

    return iface

if __name__ == "__main__":
    iface = create_interface()
    iface.launch()