migration to gradio 4.4.0

small changes to make it work on gradio 4.4.0

app.py

@@ -1,4 +1,3 @@
-import numpy as np
 import gradio as gr
 import requests
 import time
@@ -6,12 +5,11 @@ import json
 import base64
 import os
 from io import BytesIO
-import PIL
-from PIL.ExifTags import TAGS
 import html
 import re
 
 
+
 class Prodia:
     def __init__(self, api_key, base=None):
         self.base = base or "https://api.prodia.com/v1"
@@ -83,6 +81,7 @@ def image_to_base64(image):
 
     return img_str.decode('utf-8')  # Convert bytes to string
 
+
 def remove_id_and_ext(text):
     text = re.sub(r'\[.*\]$', '', text)
     extension = text[-12:].strip()
@@ -92,6 +91,7 @@ def remove_id_and_ext(text):
         text = text[:-4]
     return text
 
+
 def get_data(text):
     results = {}
     patterns = {
@@ -119,9 +119,10 @@ def get_data(text):
         results['h'] = None
     return results
 
+
 def send_to_txt2img(image):
-    
-    result = {tabs: gr.Tabs.update(selected="t2i")}
+
+    result = {tabs: gr.update(selected="t2i")}
 
     try:
         text = image.info['parameters']
@@ -142,15 +143,6 @@ def send_to_txt2img(image):
 
     except Exception as e:
         print(e)
-        result[prompt] = gr.update()
-        result[negative_prompt] = gr.update()
-        result[steps] = gr.update()
-        result[seed] = gr.update()
-        result[cfg_scale] = gr.update()
-        result[width] = gr.update()
-        result[height] = gr.update()
-        result[sampler] = gr.update()
-        result[model] = gr.update()
 
         return result
 
@@ -163,6 +155,7 @@ for model_name in model_list:
     name_without_ext = remove_id_and_ext(model_name)
     model_names[name_without_ext] = model_name
 
+
 def txt2img(prompt, negative_prompt, model, steps, sampler, cfg_scale, width, height, seed):
     result = prodia_client.generate({
         "prompt": prompt,
@@ -180,6 +173,7 @@ def txt2img(prompt, negative_prompt, model, steps, sampler, cfg_scale, width, he
 
     return job["imageUrl"]
 
+
 def img2img(input_image, denoising, prompt, negative_prompt, model, steps, sampler, cfg_scale, width, height, seed):
     result = prodia_client.transform({
         "imageData": image_to_base64(input_image),
@@ -214,7 +208,6 @@ with gr.Blocks(css=css) as demo:
         with gr.Column(scale=1):
             gr.Markdown(elem_id="powered-by-prodia", value="AUTOMATIC1111 Stable Diffusion Web UI.<br>Powered by [Prodia](https://prodia.com).<br>For more features and faster generation times check out our [API Docs](https://docs.prodia.com/reference/getting-started-guide).")
 
-
     with gr.Tabs() as tabs:
         with gr.Tab("txt2img", id='t2i'):
             with gr.Row():
@@ -245,12 +238,12 @@ with gr.Blocks(css=css) as demo:
     
                         cfg_scale = gr.Slider(label="CFG Scale", minimum=1, maximum=20, value=7, step=1)
                         seed = gr.Number(label="Seed", value=-1)
-    
-                    
+
                 with gr.Column(scale=2):
                     image_output = gr.Image(value="https://images.prodia.xyz/8ede1a7c-c0ee-4ded-987d-6ffed35fc477.png")
     
-            text_button.click(txt2img, inputs=[prompt, negative_prompt, model, steps, sampler, cfg_scale, width, height, seed], outputs=image_output)
+            text_button.click(txt2img, inputs=[prompt, negative_prompt, model, steps, sampler, cfg_scale, width, height,
+                                               seed], outputs=image_output, concurrency_limit=64)
         
         with gr.Tab("img2img", id='i2i'):
             with gr.Row():
@@ -271,7 +264,7 @@ with gr.Blocks(css=css) as demo:
                                 
                             with gr.Column(scale=1):
                                 i2i_steps = gr.Slider(label="Sampling Steps", minimum=1, maximum=30, value=25, step=1)
-    
+
                         with gr.Row():
                             with gr.Column(scale=1):
                                 i2i_width = gr.Slider(label="Width", maximum=1024, value=512, step=8)
@@ -284,12 +277,13 @@ with gr.Blocks(css=css) as demo:
                         i2i_cfg_scale = gr.Slider(label="CFG Scale", minimum=1, maximum=20, value=7, step=1)
                         i2i_denoising = gr.Slider(label="Denoising Strength", minimum=0, maximum=1, value=0.7, step=0.1)
                         i2i_seed = gr.Number(label="Seed", value=-1)
-    
-                    
+
                 with gr.Column(scale=2):
                     i2i_image_output = gr.Image(value="https://images.prodia.xyz/8ede1a7c-c0ee-4ded-987d-6ffed35fc477.png")
     
-            i2i_text_button.click(img2img, inputs=[i2i_image_input, i2i_denoising, i2i_prompt, i2i_negative_prompt, model, i2i_steps, i2i_sampler, i2i_cfg_scale, i2i_width, i2i_height, i2i_seed], outputs=i2i_image_output)
+            i2i_text_button.click(img2img, inputs=[i2i_image_input, i2i_denoising, i2i_prompt, i2i_negative_prompt,
+                                                   model, i2i_steps, i2i_sampler, i2i_cfg_scale, i2i_width, i2i_height,
+                                                   i2i_seed], outputs=i2i_image_output, concurrency_limit=64)
         
         with gr.Tab("PNG Info"):
             def plaintext_to_html(text, classname=None):
@@ -325,7 +319,9 @@ with gr.Blocks(css=css) as demo:
                     send_to_txt2img_btn = gr.Button("Send to txt2img")
     
             image_input.upload(get_exif_data, inputs=[image_input], outputs=exif_output)
-            send_to_txt2img_btn.click(send_to_txt2img, inputs=[image_input], outputs=[tabs, prompt, negative_prompt, steps, seed,
-                                                                                          model, sampler, width, height, cfg_scale])
+            send_to_txt2img_btn.click(send_to_txt2img, inputs=[image_input], outputs=[tabs, prompt, negative_prompt,
+                                                                                      steps, seed, model, sampler,
+                                                                                      width, height, cfg_scale],
+                                      concurrency_limit=64)
 
-demo.queue(concurrency_count=64, max_size=80, api_open=False).launch(max_threads=256)
+demo.queue(max_size=80, api_open=False).launch(max_threads=256, show_api=False)