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 def reset_script_periodically(): start_time = time.time() while True: if time.time() - start_time > 60: # 300 seconds = 5 minutes os.system("python app.py") 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 reset_queue_periodically(): start_time = time.time() while True: if time.time() - start_time > 300: # 300 seconds = 5 minutes queue.queue.clear() start_time = time.time() 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) for index in noise_indices: prompt_list[index] = random.choice(string.ascii_letters + string.punctuation) 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) myface.launch(enable_queue=True, inline=True) def queue_monitor(): while True: if queue.qsize() >= 15: queue.queue.clear() time.sleep(30) monitor_thread = Thread(target=queue_monitor) monitor_thread.start() myface.launch(enable_queue=True, inline=True)