import gradio as gr
import os
import sys
import random
import string
import time
from queue import Queue
from threading import Thread



text_gen = gr.load(name="spaces/Ashrafb/MagicPrompt-Stable-Diffusiongust")
proc1 = gr.Interface.load("models/runwayml/stable-diffusion-v1-5")

def get_prompts(prompt_text):
    return text_gen(prompt_text)
    
def restart_script_periodically():
    while True:
        random_time = random.randint(540, 600)
        time.sleep(random_time)
        os.execl(sys.executable, sys.executable, *sys.argv)

restart_thread = Thread(target=restart_script_periodically, daemon=True)
restart_thread.start()

queue = Queue()
queue_threshold = 100

def add_random_noise(prompt, noise_level=0.00):
    if noise_level == 0:
        noise_level = 0.00
    percentage_noise = noise_level * 5
    num_noise_chars = int(len(prompt) * (percentage_noise / 100))
    noise_indices = random.sample(range(len(prompt)), num_noise_chars)
    prompt_list = list(prompt)
    noise_chars = list(string.ascii_letters + string.punctuation + ' ' + string.digits)
    noise_chars.extend(['😍', '💩', '😂', '🤔', '😊', '🤗', '😭', '🙄', '😷', '🤯', '🤫', '🥴', '😴', '🤩', '🥳', '😔', '😩', '🤪', '😇', '🤢', '😈', '👹', '👻', '🤖', '👽', '💀', '🎃', '🎅', '🎄', '🎁', '🎂', '🎉', '🎈', '🎊', '🎮', '❤️', '💔', '💕', '💖', '💗', '🐶', '🐱', '🐭', '🐹', '🦊', '🐻', '🐨', '🐯', '🦁', '🐘', '🔥', '🌧️', '🌞', '🌈', '💥', '🌴', '🌊', '🌺', '🌻', '🌸', '🎨', '🌅', '🌌', '☁️', '⛈️', '❄️', '☀️', '🌤️', '⛅️', '🌥️', '🌦️', '🌧️', '🌩️', '🌨️', '🌫️', '☔️', '🌬️', '💨', '🌪️', '🌈'])
    for index in noise_indices:
        prompt_list[index] = random.choice(noise_chars)
    return "".join(prompt_list)

# Existing code...

import uuid  # Import the UUID library

# Existing code...

# Existing code...

request_counter = 0  # Global counter to track requests

def send_it1(inputs, noise_level, proc=proc1):
    global request_counter
    request_counter += 1
    timestamp = f"{time.time()}_{request_counter}"
    prompt_with_noise = add_random_noise(inputs, noise_level) + f" - {timestamp}"
    
    try:
        while queue.qsize() >= queue_threshold:
            time.sleep(2)
        queue.put(prompt_with_noise)
        output = proc(prompt_with_noise)
        return output
    except Exception as e:
        # Display a generic error message to the user
        raise gr.Error("Experiencing high demand. Please retry shortly. Thank you for your patience.")




with gr.Blocks(css="footer{display:none !important;}",) as demo:
    gr.HTML("""<div style="text-align: center; max-width: 700px; margin: 0 auto;">
            <div
            style="
                display: inline-flex;
                align-items: center;
                gap: 0.8rem;
                font-size: 1.75rem;
            "
            >
            <h1 style="font-weight: 900; margin-bottom: 7px; margin-top: 5px;">
                Magic Diffusion 🪄
            </h1>
            </div>
            <p style="margin-bottom: 10px; font-size: 94%">
            This Space prettifies your prompt using MagicPrompt
            and then runs it through Stable Diffusion to create aesthetically pleasing images. Simply enter a few concepts and let it improve your prompt. You can then diffuse the prompt.
            </p>
        </div>""")

    with gr.Column(elem_id="col-container"):
        with gr.Row(variant="compact"):
            input_text = gr.Textbox(
                lines=4,
                label="Short text prompt",
                
                max_lines=8,
                placeholder="",
            ).style(
                
                textarea={'height': '400px'}
            )
            see_prompts = gr.Button("✨ Feed in your text! ✨")

        with gr.Row(variant="compact"):
            prompt = gr.Textbox(
                lines=4,
                label="Prettified text prompt",
                
                max_lines=10,
                placeholder="Full Prompt",
            ).style(
                
                textarea={'height': '400px'}
            )
            run = gr.Button("Diffuse the Prompt!")

        with gr.Row():
            with gr.Row():
                noise_level = gr.Slider(minimum=0.0, maximum=3, step=0.1, label="Noise Level")

        with gr.Row():
            with gr.Row():
                output1 = gr.Image(label="Dreamlike Diffusion 1.0", show_label=False, show_share_button=False)
                output2 = gr.Image(label="Dreamlike Diffusion 1.0", show_label=False, show_share_button=False)
                output3 = gr.Image(label="Dreamlike Diffusion 1.0", show_label=False, show_share_button=False)


        see_prompts.click(get_prompts, inputs=[input_text], outputs=[prompt], queue=False)
        run.click(send_it1, inputs=[prompt, noise_level], outputs=[output1])
        run.click(send_it1, inputs=[prompt, noise_level], outputs=[output2])
        run.click(send_it1, inputs=[prompt, noise_level], outputs=[output3])
        
        
        
    demo.launch(enable_queue=True, inline=True)