app.py

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

queue = Queue()
queue_threshold = 15

text_gen=gr.Interface.load("spaces/Omnibus/MagicPrompt-Stable-Diffusion")
proc1=gr.Interface.load("models/dreamlike-art/dreamlike-diffusion-1.0")


def add_random_noise(prompt, noise_level=0.07):
    # Get the percentage of characters to add as noise
    percentage_noise = noise_level * 5
    # Get the number of characters to add as noise
    num_noise_chars = int(len(prompt) * (percentage_noise/100))
    # Get the indices of the characters to add noise to
    noise_indices = random.sample(range(len(prompt)), num_noise_chars)
    # Add noise to the selected characters
    prompt_list = list(prompt)
    noise_chars = string.ascii_letters + string.punctuation + ' '
    for index in noise_indices:
        prompt_list[index] = random.choice(noise_chars)
    return "".join(prompt_list)


def send_it1(inputs, noise_level, proc1=proc1):
    global queue
    prompt_with_noise = add_random_noise(inputs, noise_level)
    queue.put(prompt_with_noise)
    while queue.qsize() > queue_threshold:
        time.sleep(1)
    output1 = proc1(queue.get())
    return output1

def send_it2(inputs, noise_level, proc1=proc1):
    global queue
    prompt_with_noise = add_random_noise(inputs, noise_level)
    queue.put(prompt_with_noise)
    while queue.qsize() > queue_threshold:
        time.sleep(1)
    output2 = proc1(queue.get())
    return output2

def send_it3(inputs, noise_level, proc1=proc1):
    global queue
    prompt_with_noise = add_random_noise(inputs, noise_level)
    queue.put(prompt_with_noise)
    while queue.qsize() > queue_threshold:
        time.sleep(1)
    output3 = proc1(queue.get())
    return output3

def send_it4(inputs, noise_level, proc1=proc1):
    global queue
    prompt_with_noise = add_random_noise(inputs, noise_level)
    queue.put(prompt_with_noise)
    while queue.qsize() > queue_threshold:
        time.sleep(1)
    output4 = proc1(queue.get())
    return output4

def send_it5(inputs, noise_level, proc1=proc1):
    global queue
    prompt_with_noise = add_random_noise(inputs, noise_level)
    queue.put(prompt_with_noise)
    while queue.qsize() > queue_threshold:
        time.sleep(1)
    output5 = proc1(queue.get())
    return output5

def send_it6(inputs, noise_level, proc1=proc1):
    global queue
    prompt_with_noise = add_random_noise(inputs, noise_level)
    queue.put(prompt_with_noise)
    while queue.qsize() > queue_threshold:
        time.sleep(1)
    output6 = proc1(queue.get())
    return output6

def send_it7(inputs, noise_level, proc1=proc1):
    global queue
    prompt_with_noise = add_random_noise(inputs, noise_level)
    queue.put(prompt_with_noise)
    while queue.qsize() > queue_threshold:
        time.sleep(1)
    output7 = proc1(queue.get())
    return output7

def send_it8(inputs, noise_level, proc1=proc1):
    global queue
    prompt_with_noise = add_random_noise(inputs, noise_level)
    queue.put(prompt_with_noise)
    while queue.qsize() > queue_threshold:
        time.sleep(1)
    output8 = proc1(queue.get())
    return output8


def get_prompts(prompt_text):
    global queue
    queue.put(prompt_text)
    while queue.qsize() > queue_threshold:
        time.sleep(1)
    output = text_gen(queue.get())
    return output


with gr.Blocks() as myface:
    with gr.Row():

        input_text=gr.Textbox(label="Short Prompt")
        see_prompts=gr.Button("Magic Prompt")
    with gr.Row():

        prompt=gr.Textbox(label="Enter Prompt")
        noise_level=gr.Slider(minimum=0.1, maximum=3, step=0.1, label="Noise Level: Controls how much randomness is added to the input before it is sent to the model. Higher noise level produces more diverse outputs, while lower noise level produces similar outputs.")
        run=gr.Button("Generate")

    with gr.Row():
        like_message = gr.Button("❤️ Press the Like Button if you enjoy my space! ❤️")
    with gr.Row():
        output1=gr.Image(label="Dreamlike Diffusion 1.0")
        output2=gr.Image(label="Dreamlike Diffusion 1.0")
    with gr.Row():
        output3=gr.Image(label="Dreamlike Diffusion 1.0")
        output4=gr.Image(label="Dreamlike Diffusion 1.0")
    with gr.Row():
        output5=gr.Image(label="Dreamlike Diffusion 1.0")
        output6=gr.Image(label="Dreamlike Diffusion 1.0")
    with gr.Row():
        output7=gr.Image(label="Dreamlike Diffusion 1.0")
        output8=gr.Image(label="Dreamlike Diffusion 1.0")

    
    run.click(send_it1, inputs=[prompt, noise_level], outputs=[output1])
    run.click(send_it2, inputs=[prompt, noise_level], outputs=[output2])
    run.click(send_it3, inputs=[prompt, noise_level], outputs=[output3])
    run.click(send_it4, inputs=[prompt, noise_level], outputs=[output4])
    run.click(send_it5, inputs=[prompt, noise_level], outputs=[output5])
    run.click(send_it6, inputs=[prompt, noise_level], outputs=[output6])
    run.click(send_it7, inputs=[prompt, noise_level], outputs=[output7])
    run.click(send_it8, inputs=[prompt, noise_level], outputs=[output8])
    see_prompts.click(get_prompts, inputs=[input_text], outputs=[prompt])

myface.queue(concurrency_count=15)

def reset_queue_periodically():
    start_time = time.time()
    while True:
        if time.time() - start_time > 150: # 150 seconds
            queue.queue.clear()
            start_time = time.time()

reset_queue_thread = Thread(target=reset_queue_periodically)
reset_queue_thread.start()
myface.launch(enable_queue=True, inline=True)
reset_queue_thread.join()