import gradio as gr
import requests
import os

# 使用 Dreamlike 模型來生成圖像
API_URL = "https://api-inference.huggingface.co/models/dreamlike-art/dreamlike-photoreal-2.0"
HF_API_TOKEN = os.getenv("HF_API_TOKEN")
headers = {"Authorization": f"Bearer {HF_API_TOKEN}"}

def query(payload):
    response = requests.post(API_URL, headers=headers, json=payload)
    
    if response.status_code != 200:
        print(f"Request failed with status code {response.status_code}")
        print(f"Error details: {response.text}")
        return f"Error: {response.status_code}, {response.text}"
    
    return response.content  # 返回圖片的二進位數據

def generate_dinner_image(hint):
    # 使用繁體中文提示對應的晚餐描述
    dinner_hints = {
        "這是一個有很多起司的東西，通常切成片狀。": "a pizza with lots of cheese",
        "這是一道義大利麵，通常搭配奶油醬。": "a plate of creamy spaghetti",
        "這是一個烤的東西，有些人喜歡加上烤肉醬。": "grilled chicken with barbecue sauce",
        "這通常在一個麵包中，裡面有生菜和番茄。": "a hamburger with lettuce and tomato",
        "這是亞洲常見的食物，通常搭配醬油。": "sushi with soy sauce"
    }
    
    description = dinner_hints.get(hint, "delicious food")
    
    # 調用 API 生成圖像
    output = query({"inputs": description})
    
    if isinstance(output, str) and output.startswith("Error:"):
        return output  # 返回錯誤訊息
    
    # 保存生成的圖像到文件
    with open("generated_dinner.png", "wb") as f:
        f.write(output)
    
    return "generated_dinner.png"

# 創建 Gradio 介面
interface = gr.Interface(
    fn=generate_dinner_image,
    inputs=gr.Textbox(lines=2, placeholder="輸入提示內容來生成晚餐圖片...（例如：這是一個有很多起司的東西，通常切成片狀。）"),
    outputs="image",
    title="最強第一組",
    description="根據您的描述生成晚餐圖片！"
)

# 啟動 Gradio 應用
interface.launch()