import os
import random
import io
from PIL import Image
from deep_translator import GoogleTranslator
import aiohttp
from quart import Quart, request, jsonify, send_file, render_template_string
from flask_caching import Cache  # flask-cachingを使用

# アプリケーションの設定
app = Quart(__name__)

# キャッシュの設定
cache_config = {
    "CACHE_TYPE": "SimpleCache",  # メモリベースのシンプルなキャッシュ
    "CACHE_DEFAULT_TIMEOUT": 60 * 60 * 24  # 24時間
}
app.config.from_mapping(cache_config)
cache = Cache(app)

API_URL = "https://api-inference.huggingface.co/models/black-forest-labs/FLUX.1-dev"
API_TOKEN = os.getenv("HF_READ_TOKEN")
headers = {"Authorization": f"Bearer {API_TOKEN}"}
timeout = 50000  # タイムアウトを300秒に設定

# 非同期APIリクエストの実行関数
async def query_async(prompt, negative_prompt="", steps=35, cfg_scale=7, sampler="DPM++ 2M Karras", seed=-1, strength=0.7, width=1024, height=1024, num_inference_steps=30, guidance_scale=7.5, top_k=50, top_p=0.9, eta=0.1):
    if not prompt:
        return None, "Prompt is required"

    key = random.randint(0, 999)

    # Translate the prompt from Russian to English if necessary
    prompt = GoogleTranslator(source='ru', target='en').translate(prompt)
    print(f'Generation {key} translation: {prompt}')

    prompt = f"{prompt} | ultra detail, ultra elaboration, ultra quality, perfect."
    print(f'Generation {key}: {prompt}')
    
    payload = {
        "inputs": prompt,
        "is_negative": False,
        "steps": steps,
        "cfg_scale": cfg_scale,
        "seed": seed if seed != -1 else random.randint(1, 1000000000),
        "strength": strength,
        "negative_prompt": negative_prompt,
        "top_k": top_k,
        "top_p": top_p,
        "eta": eta,
        "parameters": {
            "width": width,
            "height": height,
            "num_inference_steps": num_inference_steps,
            "guidance_scale": guidance_scale
        }
    }

    async with aiohttp.ClientSession() as session:
        try:
            async with session.post(API_URL, json=payload, headers=headers, timeout=timeout) as response:
                if response.status != 200:
                    return None, f"Error: Failed to get image. Status code: {response.status}, Details: {await response.text()}"

                image_bytes = await response.read()
                image = Image.open(io.BytesIO(image_bytes))
                return image, None
        except asyncio.TimeoutError:
            return None, "Error: The request timed out. Please try again."
        except Exception as e:
            return None, f"Request Exception: {str(e)}"


# Content-Security-Policyヘッダーを設定するための関数
@app.after_request
async def add_security_headers(response):
    response.headers['Content-Security-Policy'] = (
        "default-src 'self'; "
        "connect-src 'self' ^https?:\/\/[\w.-]+\.[\w.-]+(\/[\w.-]*)*(\?[^\s]*)?$"
        "img-src 'self' data:; "
        "style-src 'self' 'unsafe-inline'; "
        "script-src 'self' 'unsafe-inline'; "
    )
    return response

# HTMLテンプレート
index_html = """
<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <title>Image Generator</title>
</head>
<body>
    <h1>Welcome to the Image Generator</h1>
    <form action="/generate" method="get">
        <input type="text" name="prompt" placeholder="Enter prompt" required>
        <input type="submit" value="Generate">
    </form>
</body>
</html>
"""

@app.route('/')
async def index():
    return await render_template_string(index_html)

@app.route('/generate', methods=['GET'])
async def generate_image():
    prompt = request.args.get("prompt", "")
    negative_prompt = request.args.get("negative_prompt", "")
    steps = int(request.args.get("steps", 35))
    cfg_scale = float(request.args.get("cfgs", 7))
    sampler = request.args.get("sampler", "DPM++ 2M Karras")
    strength = float(request.args.get("strength", 0.7))
    seed = int(request.args.get("seed", -1))
    width = int(request.args.get("width", 1024))
    height = int(request.args.get("height", 1024))
    num_inference_steps = int(request.args.get("num_inference_steps", 30))
    guidance_scale = float(request.args.get("guidance_scale", 7.5))
    top_k = int(request.args.get("top_k", 50))
    top_p = float(request.args.get("top_p", 0.9))
    eta = float(request.args.get("eta", 0.1))

    # キャッシュを確認
    cached_image = cache.get(prompt)
    if cached_image:
        return await send_file(io.BytesIO(cached_image), mimetype='image/png')

    image, error = await query_async(prompt, negative_prompt, steps, cfg_scale, sampler, seed, strength, width, height, num_inference_steps, guidance_scale, top_k, top_p, eta)

    if error:
        return jsonify({"error": error}), 400

    img_bytes = io.BytesIO()
    image.save(img_bytes, format='PNG')
    img_bytes.seek(0)

    # 画像をキャッシュに保存
    cache.set(prompt, img_bytes.getvalue())

    return await send_file(img_bytes, mimetype='image/png')

if __name__ == "__main__":
    app.run(host='0.0.0.0', port=7860)