import gradio as gr
import requests
import random
from geopy.geocoders import Nominatim
import os
from huggingface_hub import InferenceClient

HF_TOKEN = os.environ.get("HF_TOKEN")
client = InferenceClient(api_key=HF_TOKEN)

# 餐點推薦資料庫（根據情緒和天氣）
meal_recommendations = {
    "開心": {
        "cold": ["小籠包", "燉牛肉", "泡麵", "玉米濃湯"],
        "hot": ["雪花冰", "氣水", "涼麵", "西瓜"],
        "normal": ["炸雞配汽水", "壽喜燒", "韓式烤肉"]
    },
    "羞愧": {
        "cold": ["抹茶", "清淡的米粥", "唐心蛋"],
        "hot": ["蔬菜沙拉", "冷飲", "玉米餅"],
        "normal": ["全麥麵包", "藍莓、草莓、橙子", "蒸包子"]
    },
    "憤怒": {
        "cold": ["暖呼呼的火鍋", "熱可可", "麻辣湯"],
        "hot": ["冰沙", "涼拌黃瓜", "水果"],
        "normal": ["炸雞", "巧克力", "薰衣草茶"]
    },
    "悲傷": {
        "cold": ["雞湯", "清淡的米粥", "餅乾"],
        "hot": ["冷湯", "冰棒", "三明治"],
        "normal": ["牛排", "雞蛋", "波士頓派"]
    },
    "忌妒": {
        "cold": ["熱狗","拉麵","泡麵"],
        "hot": ["蔬菜沙拉", "冷飲",],
        "normal": ["奶酥麵包","橙子","pizza"]
    },
    "恐懼": {
        "cold": ["湯泡飯", "泡麵", "湯麵"],
        "hot": ["涼麵", "飲料", "冰淇淋"],
        "normal": ["爆米花", "薯片", "牛排"]
    }
}

# 主功能函式
def recommend_meal(emotion, city):
    temp, weather_info = get_weather(city)
    
    if temp is None:
        return "Unable to fetch weather details. Please check if the city name is correct.", "", ""

    # 根據情緒和氣候選擇餐點
    # 請自行完成挑選餐點的邏輯
    if temp < 15:
       climate = "cold"
    elif temp > 28:
       climate = "hot"
    else:
       climate = "normal"

    meals = meal_recommendations.get(emotion, {}).get(climate, ["隨意料理"])
    meal= random.choice(meals)

    # 生成暖心話語
    comforting_message = generate_comforting_message(emotion)

    recommendation = f"Today's Top Pick: {meal}"

    return f"Current Weather：\n{weather_info}", recommendation, comforting_message

def get_weather(city):
    geolocator = Nominatim(user_agent="geoapi")
    location = geolocator.geocode(city)

    if location:
        lat, lon = location.latitude, location.longitude
        # 使用 Open-Meteo API 取得天氣數據
        weather_url = f"https://api.open-meteo.com/v1/forecast?latitude={lat}&longitude={lon}&current_weather=true"
        weather_response = requests.get(weather_url)
        if weather_response.status_code == 200:
            weather_data = weather_response.json()
            temp, temp_unit = weather_data['current_weather']['temperature'], weather_data['current_weather_units']['temperature']
            windspeed, windspeed_unit = weather_data['current_weather']['windspeed'], weather_data['current_weather_units']['windspeed']
            weather_desc = f"{temp}{temp_unit}，Wind speed: {windspeed} {windspeed_unit}"
            return temp, weather_desc
    else:
        return None, None

# 生成暖心話語的函式
def generate_comforting_message(emotion):
    temperature, top_p = random.uniform(0.6, 0.75), random.uniform(0.7, 1.0)
    completion = client.chat.completions.create(
        model="mistralai/Mistral-Nemo-Instruct-2407",
        messages=[{
            "role": "system",
            "content": "你是一位善解人意且富有同理心的 AI 助理，專門為人們提供鼓勵和安慰。無論使用者的情緒如何，你都能給予真摯、溫暖且鼓舞人心的話語，讓他們感到被理解和支持。請用溫柔、真誠且富有啟發性的語氣回應，並確保所有回覆都以**繁體中文**撰寫。"
        }, {
            "role": "user",
            "content": f"我現在感到{emotion}，請給我一句鼓勵的話。\n"
        }],
        temperature=temperature,
        max_tokens=2048,
        top_p=top_p,
    )

    return completion.choices[0].message.content

# Gradio 介面
with gr.Blocks() as app:
    gr.Markdown("## 🌤️🍽️ Meal Matchmaker: Food for Your Mood and Weather! 🍽️🌤️")

    with gr.Row():
        with gr.Column():
            emotion = gr.Dropdown(
                ["開心", "羞愧", "憤怒", "悲傷", "忌妒", "恐懼"],
                label="🎭 Pick Your Mood "
            )
        with gr.Column():
            city = gr.Textbox(label="📍 Enter Your Location (e.g., 台北、Okinawa)")

    submit_btn = gr.Button("Serve Me a Meal! ✨")

    with gr.Row():
            weather_output = gr.Textbox(label="☁️ Weather Check", interactive=False)
            meal_output = gr.Textbox(label="🎉 Your Perfect Meal", interactive=False)
            message_output = gr.Textbox(label="💖 A Little Boost of Encouragement", interactive=False)

    submit_btn.click(
        recommend_meal,
        inputs=[emotion, city],
        outputs=[weather_output, meal_output, message_output]
    )

# 啟動應用
app.launch(debug=False)