app.py

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.Interface.load("models/Gustavosta/MagicPrompt-Stable-Diffusion")
proc1 = gr.Interface.load("models/openskyml/midjourney-v4-xl")

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.") 

import random

import random
import time

# ... (existing code)

import random
import time

# ... (existing code)

def get_prompts(prompt_text):
    if not prompt_text:
        return "Please enter text before generating prompts.رجاء ادخل النص اولا" 
        raise gr.Error("Please enter text before generating prompts.رجاء ادخل النص اولا")
    else:
        global request_counter
        request_counter += 1
        timestamp = f"{time.time()}_{request_counter}"

    options = [
        "Cyberpunk android",
        "2060",
        "newyork",
        ", style of laurie greasley" , "studio ghibli" , "akira toriyama" , "james gilleard" , "genshin impact" , "trending pixiv fanbox" , "acrylic palette knife, 4k, vibrant colors, devinart, trending on artstation, low details"
        ", Editorial Photography, Shot on 70mm lens, Depth of Field, Bokeh, DOF, Tilt Blur, Shutter Speed 1/1000, F/22,  32k, Super-Resolution, award winning,", 
         ", high detail, warm lighting, godrays, vivid, beautiful, trending on artstation, by jordan grimmer, huge scene, grass, art greg rutkowski ", 
         ", highly detailed, digital painting, artstation, illustration, art by artgerm and greg rutkowski and alphonse mucha.", 
         ", Charlie Bowater, stanley artgerm lau, a character portrait, sots art, sharp focus, smooth, aesthetic, extremely detailed, octane render,solo, dark industrial background, rtx, rock clothes, cinematic light, intricate detail, highly detailed, high res, detailed facial features", 
        ", portrait photograph" , "realistic" , "concept art" , "elegant, highly detailed" , "intricate, sharp focus, depth of field, f/1. 8, 85mm, medium shot, mid shot, (((professionally color graded)))" ," sharp focus, bright soft diffused light" , "(volumetric fog),", 
        ",Cinematic film still" ," (dark city street:1.2)" , "(cold colors), damp, moist, intricate details" ,"shallow depth of field, [volumetric fog]" , "cinematic lighting, reflections, photographed on a Canon EOS R5, 50mm lens, F/2.8, HDR, 8k resolution" , "cinematic film still from cyberpunk movie" , "volumetric fog,  (RAW, analog, masterpiece, best quality, soft particles, 8k, flawless perfect face, intricate details" , "trending on artstation, trending on cgsociety, dlsr, ultra sharp, hdr, rtx, antialiasing, canon 5d foto))" , "((skin details, high detailed skin texture))" , "(((perfect face))), (perfect eyes)))", 
        "facinating and imposing" , "fantasy digital art, octane render, beautiful composition" ," trending on artstation, award-winning photograph, masterpiece", 

"portrait  elf", "intricate, elegant", "highly detailed" , "digital painting" , "artstation", "concept art, smooth, sharp focus" , "illustration, art by artgerm and greg rutkowski and alphonse mucha, 8k", 

" intricate, elegant, highly detailed" , "digital painting, artstation, concept art, smooth, sharp focus" ," illustration, art by artgerm and greg rutkowski and alphonse mucha, 8k", 
" matte painting, highly detailed, dynamic lighting, cinematic, realism, realistic" , "photo real, sunset,detailed, high contrast, denoised, centered, michael whelan", 


 "cyborg| full-length portrait", "detailed face", "symmetric| steampunk", "cyberpunk| cyborg| intricate detailed| to scale", "hyperrealistic", "cinematic lighting| digital art| concept art", 

"photo of a ultra realistic" ," dramatic light, pale sunrise, cinematic lighting" , "battered, low angle, trending on artstation, 4k, hyper realistic" , "focused, extreme details" , "unreal engine 5, cinematic, masterpiece, art by studio ghibli, intricate artwork by john william turner", 
"street| old town| old city| winter| heavy snow", "| comprehensive cinematic", "| Atmosphere| Masterpiece", 
"fantasy, intricate, elegant, highly detailed" , "digital painting, artstation, concept art, matte, sharp focus, illustration, hearthstone, art by artgerm and greg rutkowski and alphonse mucha, hdr 4k, 8k", 

" (((wild west))) environment, Utah landscape, ultra realistic" , "concept art, elegant, ((intricate)), ((highly detailed)), depth of field, ((professionally color graded)), soft ambient lighting, dusk, 8k, art by artgerm and greg rutkowski and alphonse mucha", 

"Incredibly detailed technical diagram, split into complex geometric shapes and flowers growing from the shapes" ," Chiaroscuro lighting, fine intricate details –q 2 –upbeta –v 4 –v 4", 
" : concept art::1 cyberpunk::1 splatter paint::1 wide angle lens::2 Zdzislaw Beksinski style" , "winter storm, ultra detailed| 4k –v 4", 
"photo of a ultra realistic, dramatic light, pale sunrise" , "cinematic lighting, battered" , "low angle, trending on artstation" , "4k, hyper realistic, focused, extreme details, unreal engine 5, cinematic, masterpiece" , "art by studio ghibli, intricate artwork by john william turner", 


"mdjrny-v4 style, incredible highly detailed space ship" , "space background, perfect composition" , "beautiful detailed, intricate, insanely detailed, octane render" , "trending on artstation, artistic, photorealistic, concept art, soft natural volumetric cinematic perfect light, chiaroscuro" , "award winning photograph, masterpiece, oil on canvas, raphael, caravaggio, greg rutkowski, beeple, beksinski, giger style", 

"japanese style shrine on top of a misty mountain overgrown" , "hyper realistic, lush gnarly plants, 8 k, denoised, by greg rutkowski" , "tom bagshaw, james gurney cinematic lighting", 

"insanely detailed and intricate digital illustration by Hayao Miyazaki, Ismail Inceoglu, M.W. Kaluta and Yoshitaka Amano"," a masterpiece, close-up, 8k resolution, trending on artstation, delicate, watercolor, soft,", 



"neon light sign in design of face", "| precise lineart", "| intricate | realistic | studio quality | cinematic | luminescence", "| character design | concept art", "| highly detailed", "| illustration", "| digital art | digital painting", 


        # Add other prompt options here...
    
    ]

    if prompt_text:
        chosen_option = random.choice(options)
        return text_gen(f"{prompt_text}, {chosen_option} - {timestamp}")
    else:
        return text_gen("", timestamp)



# Existing code...

# Existing code...

with gr.Blocks(css=".gradio-container {background-color: #F5F5F5;} .dark .gradio-container {background-color: #003333;} footer{display:none !important;}",) as demo:


    with gr.Column(elem_id="col-container"):
        with gr.Row(variant="compact"):
            input_text = gr.Textbox(
                lines=8,
                label="Short Prompt",
                show_label=False,
                max_lines=10,
                placeholder="Enter a basic idea and click 'Magic Prompt'. Got no ideas? No problem, Simply just hit the magic button!",
            ).style(
                container=False,
                textarea={'height': '400px'}
            )
            see_prompts = gr.Button("✨ Magic Prompt ✨").style(full_width=False)

        with gr.Row(variant="compact"):
            prompt = gr.Textbox(
                lines=8,
                label="Enter your prompt",
                show_label=False,
                max_lines=10,
                placeholder="Full Prompt",
            ).style(
                container=False,
                textarea={'height': '400px'}
            )
            run = gr.Button("Generate Images").style(full_width=False)

        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)

        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])
        
        
        
    demo.launch(enable_queue=True, inline=True)