File size: 2,253 Bytes
7a1db81 e39414c 7a1db81 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 | import gradio as gr
import os
import sys
import random
import string
import time
from queue import Queue
from threading import Thread
proc1 = gr.Interface.load("models/playgroundai/playground-v2-1024px-aesthetic")
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
import uuid # Import the UUID library
# Existing code...
# Existing code...
request_counter = 0 # Global counter to track requests
# Modify your send_it1 function to handle any errors generically
def send_it1(inputs, proc=proc1):
global request_counter
request_counter += 1
timestamp = f"{time.time()}_{request_counter}"
prompt_with_noise = (inputs) + 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=".gradio-container {background-color: #FDF5E6;} .dark .gradio-container {background-color: black;} 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="Enter your prompt",
show_label=False,
max_lines=10,
placeholder="Enter your text prompt here",
).style(
container=False,
textarea={'height': '400px'}
)
run = gr.Button("Generate Image").style(full_width=False)
with gr.Row():
with gr.Row():
output1 = gr.Image(label="", show_label=False, show_share_button=False)
run.click(send_it1, inputs=[input_text], outputs=[output1])
demo.launch(enable_queue=True, inline=True)
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