import gradio as gr
import requests
import io
import random
import os
import time
from PIL import Image
from deep_translator import GoogleTranslator
import json
from themes import IndonesiaTheme  # Import custom IndonesiaTheme

# Project by Nymbo
API_URL = "https://api-inference.huggingface.co/models/black-forest-labs/FLUX.1-schnell"
API_TOKEN = os.getenv("HF_READ_TOKEN")
headers = {"Authorization": f"Bearer {API_TOKEN}"}
timeout = 100

# Function to query the API and return the generated image
def query(prompt, is_negative=False, steps=30, cfg_scale=7, sampler="DPM++ 2M Karras", seed=-1, strength=0.7, width=1024, height=1024):
    if prompt == "" or prompt is None:
        return None

    key = random.randint(0, 999)
    
    API_TOKEN = random.choice([os.getenv("HF_READ_TOKEN")])
    headers = {"Authorization": f"Bearer {API_TOKEN}"}
    
    # Translate the prompt from Russian to English if necessary
    prompt = GoogleTranslator(source='ru', target='en').translate(prompt)
    print(f'\033[1mGeneration {key} translation:\033[0m {prompt}')

    # Add some extra flair to the prompt
    prompt = f"{prompt} | ultra detail, ultra elaboration, ultra quality, perfect."
    print(f'\033[1mGeneration {key}:\033[0m {prompt}')
    
    # Prepare the payload for the API call, including width and height
    payload = {
        "inputs": prompt,
        "is_negative": is_negative,
        "steps": steps,
        "cfg_scale": cfg_scale,
        "seed": seed if seed != -1 else random.randint(1, 1000000000),
        "strength": strength,
        "parameters": {
            "width": width,  # Pass the width to the API
            "height": height  # Pass the height to the API
        }
    }

    # Send the request to the API and handle the response
    response = requests.post(API_URL, headers=headers, json=payload, timeout=timeout)
    if response.status_code != 200:
        print(f"Error: Failed to get image. Response status: {response.status_code}")
        print(f"Response content: {response.text}")
        if response.status_code == 503:
            raise gr.Error(f"{response.status_code} : The model is being loaded")
        raise gr.Error(f"{response.status_code}")
    
    try:
        # Convert the response content into an image
        image_bytes = response.content
        image = Image.open(io.BytesIO(image_bytes))
        print(f'\033[1mGeneration {key} completed!\033[0m ({prompt})')
        return image
    except Exception as e:
        print(f"Error when trying to open the image: {e}")
        return None

# CSS to style the app
css = """
#app-container {
    max-width: 800px;
    margin-left: auto;
    margin-right: auto;
    padding: 20px;
    background-color: #2b2b2b;
    border-radius: 15px;
    box-shadow: 0 4px 10px rgba(0, 0, 0, 0.4);
}

h1 {
    font-size: 2.5rem;
    text-align: center;
    color: #ffa500;
    margin-bottom: 10px;
    font-weight: bold;
    text-shadow: 2px 2px 4px rgba(0, 0, 0, 0.3);
}

.description {
    text-align: center;
    font-size: 1.2rem;
    color: black;
    margin-bottom: 20px;
    font-style: italic;
}

#gen-button {
    background-color: #ff9800;
    color: white;
    font-weight: bold;
    border-radius: 10px;
    padding: 15px;
    transition: background-color 0.3s ease;
}

#gen-button:hover {
    background-color: #e67e22;
    transform: scale(1.05);
}

#gallery {
    border: 2px solid #ff9800;
    border-radius: 15px;
}

#prompt-text-input, #negative-prompt-text-input {
    background-color: #444444;
    color: white;
    border-radius: 8px;
    border: 1px solid #ffa500;
}

label {
    color: #ffffff;
}
"""

# Build the Gradio UI with Blocks
with gr.Blocks(theme=IndonesiaTheme(), css=css) as app:
    # Add a title to the app with an emoji and large header
    gr.HTML("<h1>🔥 Unlimited FLUX Schnell - V1.3 🔥</h1>")
    
    # Description below the title in Indonesian
    gr.HTML("<p class='description'>🚀 Generator gambar AI berkualitas tinggi dengan kontrol penuh atas detail dan opsi lanjutan. Buat karya seni spektakuler dengan mudah! 🎨</p>")
    
    # Container for all the UI elements
    with gr.Column(elem_id="app-container"):
        # Add a text input for the main prompt
        with gr.Row():
            with gr.Column(elem_id="prompt-container"):
                with gr.Row():
                    text_prompt = gr.Textbox(label="🎨 Prompt", placeholder="Masukkan deskripsi gambar di sini", lines=2, elem_id="prompt-text-input")
                
                # Accordion for advanced settings
                with gr.Row():
                    with gr.Accordion("⚙️ Pengaturan Lanjutan", open=False):
                        negative_prompt = gr.Textbox(label="❌ Prompt Negatif", placeholder="Elemen yang tidak diinginkan dalam gambar", value="(deformed, distorted, disfigured), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, (mutated hands and fingers), disconnected limbs, mutation, mutated, ugly, disgusting, blurry, amputation, misspellings, typos", lines=3, elem_id="negative-prompt-text-input")
                        with gr.Row():
                            width = gr.Slider(label="Lebar", value=1024, minimum=64, maximum=1216, step=32)
                            height = gr.Slider(label="Tinggi", value=768, minimum=64, maximum=1216, step=32)
                        steps = gr.Slider(label="Langkah Sampling", value=4, minimum=1, maximum=100, step=1)
                        cfg = gr.Slider(label="Skala CFG", value=7, minimum=1, maximum=20, step=1)
                        strength = gr.Slider(label="Kekuatan", value=0.7, minimum=0, maximum=1, step=0.001)
                        seed = gr.Slider(label="Seed", value=-1, minimum=-1, maximum=1000000000, step=1)  # -1 for random
                        method = gr.Radio(label="Metode Sampling", value="DPM++ 2M Karras", choices=["DPM++ 2M Karras", "DPM++ SDE Karras", "Euler", "Euler a", "Heun", "DDIM"])

        # Add a button to trigger the image generation
        with gr.Row():
            text_button = gr.Button("🚀 Buat Gambar", variant='primary', elem_id="gen-button")
        
        # Image output area to display the generated image
        with gr.Row():
            image_output = gr.Image(type="pil", label="Hasil Gambar", elem_id="gallery")
        
        # Bind the button to the query function with the added width and height inputs
        text_button.click(query, inputs=[text_prompt, negative_prompt, steps, cfg, method, seed, strength, width, height], outputs=image_output)

# Launch the Gradio app
app.launch(show_api=False, share=False)