Update app.py

app.py

@@ -1,63 +1,247 @@
 import gradio as gr
+import requests
+import time
+import json
+from contextlib import closing
+from websocket import create_connection
+from deep_translator import GoogleTranslator
+from langdetect import detect
+import os
+from PIL import Image
+import io
+from io import BytesIO
+import base64
+import re
+from gradio_client import Client
+from fake_useragent import UserAgent
+import random
+from theme import theme
+from fastapi import FastAPI
 
-#----------Start of theme----------
-theme = gr.themes.Ocean(
-    primary_hue="zinc",
-    secondary_hue="slate",
-    neutral_hue="neutral",
-    font=[gr.themes.GoogleFont('Kavivanar'), gr.themes.GoogleFont('Kavivanar'), 'system-ui', 'sans-serif'],
-    font_mono=[gr.themes.GoogleFont('Source Code Pro'), gr.themes.GoogleFont('Inconsolata'), gr.themes.GoogleFont('Inconsolata'), 'monospace'],
-).set(
-    #Body Settings
-    body_background_fill='linear-gradient(10deg, *primary_200, *secondary_50)',
-    body_text_color='secondary_600',
-    body_text_color_subdued='*primary_500',
-    body_text_weight='500',
-
-    #Background Settings
-    background_fill_primary='*primary_100',
-    background_fill_secondary='*secondary_200',
+app = FastAPI()
+
+
+def query(prompt, negative_prompt, task, steps, sampler, cfg_scale, seed, width, height):
+    result = {"prompt": prompt,"negative_prompt": negative_prompt,"task": task,"steps": steps,"sampler": sampler,"cfg_scale": cfg_scale,"seed": seed, "width": width, "height": height}
+    print(result)
+    try:
+        language = detect(prompt)
+        if language == 'ru':
+            prompt = GoogleTranslator(source='ru', target='en').translate(prompt)
+            print(prompt)
+    except:
+        pass
+
+    prompt = re.sub(r'[^a-zA-Zа-яА-Я\s]', '', prompt)
     
-    color_accent='*primary_300',
+    cfg = int(cfg_scale)
+    steps = int(steps)
+    seed = int(seed)
+
+    width = 896
+    height = 1152
+
+    if task == "Playground v2":
+        ua = UserAgent()
+        headers = {
+            'user-agent': f'{ua.random}'
+        }
+        client = Client("https://ashrafb-arpr.hf.space/", headers=headers)
+        result = client.predict(prompt, fn_index=0)
+        return result
+            
+    if task == "Artigen v3":
+        ua = UserAgent()
+        headers = {
+            'user-agent': f'{ua.random}'
+        }
+        client = Client("https://ashrafb-arv3s.hf.space/", headers=headers)
+        result = client.predict(prompt,0,"Cinematic", fn_index=0)
+        return result
+    try:
+        with closing(create_connection("wss://google-sdxl.hf.space/queue/join")) as conn:
+            conn.send('{"fn_index":3,"session_hash":""}')
+            conn.send(f'{{"data":["{prompt}, 4k photo","[deformed | disfigured], poorly drawn, [bad : wrong] anatomy, [extra | missing | floating | disconnected] limb, (mutated hands and fingers), blurry",7.5,"(No style)"],"event_data":null,"fn_index":3,"session_hash":""}}')
+            c = 0
+            while c < 60:
+                status = json.loads(conn.recv())['msg']
+                if status == 'estimation':
+                    c += 1
+                    time.sleep(1)
+                    continue
+                if status == 'process_starts':
+                    break
+            photo = json.loads(conn.recv())['output']['data'][0][0]
+            photo = photo.replace('data:image/jpeg;base64,', '').replace('data:image/png;base64,', '')
+            photo = Image.open(io.BytesIO(base64.decodebytes(bytes(photo, "utf-8"))))
+            return photo
+    except:
+        try:
+            ua = UserAgent()
+            headers = {
+                'authority': 'ehristoforu-dalle-3-xl-lora-v2.hf.space',
+                'accept': 'text/event-stream',
+                'accept-language': 'ru,en;q=0.9,la;q=0.8,ja;q=0.7',
+                'cache-control': 'no-cache',
+                'referer': 'https://ehristoforu-dalle-3-xl-lora-v2.hf.space/?__theme=light',
+                'sec-ch-ua': '"Not_A Brand";v="8", "Chromium";v="120", "YaBrowser";v="24.1", "Yowser";v="2.5"',
+                'sec-ch-ua-mobile': '?0',
+                'sec-ch-ua-platform': '"Windows"',
+                'sec-fetch-dest': 'empty',
+                'sec-fetch-mode': 'cors',
+                'sec-fetch-site': 'same-origin',
+                'user-agent': f'{ua.random}'
+            }
+            client = Client("ehristoforu/dalle-3-xl-lora-v2", headers=headers)
+            result = client.predict(prompt,"(deformed, distorted, disfigured:1.3), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, (mutated hands and fingers:1.4), disconnected limbs, mutation, mutated, ugly, disgusting, blurry, amputation",True,0,1024,1024,6,True, api_name='/run')
+            return result[0][0]['image']
+        except:
+            try:
+                ua = UserAgent()
+                headers = {
+                    'authority': 'nymbo-sd-xl.hf.space',
+                    'accept': 'text/event-stream',
+                    'accept-language': 'ru,en;q=0.9,la;q=0.8,ja;q=0.7',
+                    'cache-control': 'no-cache',
+                    'referer': 'https://nymbo-sd-xl.hf.space/?__theme=light',
+                    'sec-ch-ua': '"Not_A Brand";v="8", "Chromium";v="120", "YaBrowser";v="24.1", "Yowser";v="2.5"',
+                    'sec-ch-ua-mobile': '?0',
+                    'sec-ch-ua-platform': '"Windows"',
+                    'sec-fetch-dest': 'empty',
+                    'sec-fetch-mode': 'cors',
+                    'sec-fetch-site': 'same-origin',
+                    'user-agent': f'{ua.random}'
+                }
+                client = Client("Nymbo/SD-XL", headers=headers)
+                result = client.predict(prompt,negative_prompt,"","",True,False,False,0,896,1152,7,1,25,25,False,api_name="/run")
+                return result
+            except:
+                try:
+                    ua = UserAgent()
+                    headers = {
+                        'authority': 'radames-real-time-text-to-image-sdxl-lightning.hf.space',
+                        'accept': 'text/event-stream',
+                        'accept-language': 'ru,en;q=0.9,la;q=0.8,ja;q=0.7',
+                        'cache-control': 'no-cache',
+                        'referer': 'https://radames-real-time-text-to-image-sdxl-lightning.hf.space/?__theme=light',
+                        'sec-ch-ua': '"Not_A Brand";v="8", "Chromium";v="120", "YaBrowser";v="24.1", "Yowser";v="2.5"',
+                        'sec-ch-ua-mobile': '?0',
+                        'sec-ch-ua-platform': '"Windows"',
+                        'sec-fetch-dest': 'empty',
+                        'sec-fetch-mode': 'cors',
+                        'sec-fetch-site': 'same-origin',
+                        'user-agent': f'{ua.random}'
+                    }
+                    client = Client("radames/Real-Time-Text-to-Image-SDXL-Lightning", headers=headers)
+                    result = client.predict(prompt, [], 0, random.randint(1, 999999), fn_index=0)
+                    return result
+                except:
+                    try:
+                        ua = UserAgent()
+                        headers = {
+                            'user-agent': f'{ua.random}'
+                        }
+                        client = Client("https://ashrafb-arpr.hf.space/", headers=headers)
+                        result = client.predict(prompt, fn_index=0)
+                        return result
+                    except:
+                        ua = UserAgent()
+                        headers = {
+                            'user-agent': f'{ua.random}'
+                        }
+                        client = Client("https://ashrafb-arv3s.hf.space/", headers=headers)
+                        result = client.predict(prompt,0,"Cinematic", fn_index=0)
+                        return result
+                        
+
+
+def mirror(image_output, scale_by, method, gfpgan, codeformer):
+
+    url_up = "https://darkstorm2150-protogen-web-ui.hf.space/run/predict/"
+    url_up_f = "https://darkstorm2150-protogen-web-ui.hf.space/file="
 
-    #Border Settings
-    border_color_accent_subdued='*primary_400',
-    border_color_primary='*primary_400',
+    scale_by = int(scale_by)
+    gfpgan = int(gfpgan)
+    codeformer = int(codeformer)
     
-    #Block Settings
-    block_radius='*radius_md',
-    block_background_fill='*primary_200',
-    block_border_color='*primary_500',
-    block_border_width='*panel_border_width',
-    block_info_text_color='*primary_700',
-    block_info_text_size='*text_md',
+    with open(image_output, "rb") as image_file:
+        encoded_string2 = base64.b64encode(image_file.read())
+        encoded_string2 = str(encoded_string2).replace("b'", '')
+
+    encoded_string2 = "data:image/png;base64," + encoded_string2
+    data = {"fn_index":81,"data":[0,0,encoded_string2,None,"","",True,gfpgan,codeformer,0,scale_by,896,1152,None,method,"None",1,False,[],"",""],"session_hash":""}
+    r = requests.post(url_up, json=data, timeout=100)
+    print(r.text)
+    print(r.json()['data'][0][0]['name'])
+    ph = "https://darkstorm2150-protogen-web-ui.hf.space/file=" + str(r.json()['data'][0][0]['name'])
+    print(ph)
+    response2 = requests.get(ph)
+    img = Image.open(BytesIO(response2.content))
+    return img
+
+css = """
+.gradio-container {background-color: MediumAquaMarine}
+footer{display:none !important}
+#generate {
+    width: 100%;
+}
+#image_output {
+height: 100% !important;
+}
+"""
+
+with gr.Blocks(css=css, theme=theme) as app:
+
+    with gr.Tab("Basic Settings"):
+        with gr.Row():
+            prompt = gr.Textbox(placeholder="Enter the image description...", show_label=True, label='Image Prompt ✍️', lines=3, show_copy_button = True)
+        with gr.Row():
+            task = gr.Radio(interactive=True, value="Stable Diffusion XL 1.0", show_label=True, label="Model of neural network 🧠 ", choices=['Stable Diffusion XL 1.0', 'Crystal Clear XL', 
+                                                                                                              'Juggernaut XL', 'DreamShaper XL',
+                                                                                                              'SDXL Niji', 'Cinemax SDXL', 'NightVision XL'])
+    with gr.Tab("Extended settings"):
+        with gr.Row():
+            negative_prompt = gr.Textbox(placeholder="Negative Prompt", show_label=True, label='Negative Prompt:', lines=3, value="[deformed | disfigured], poorly drawn, [bad : wrong] anatomy, [extra | missing | floating | disconnected] limb, (mutated hands and fingers), blurry")
+        with gr.Row():
+            sampler = gr.Dropdown(value="DPM++ 2M Karras", show_label=True, label="Sampling Method:", choices=[
+                "DPM++ 2M Karras", "DPM++ 2S a Karras", "DPM2 a Karras", "DPM2 Karras", "DPM++ SDE Karras", "DEIS", "LMS", "DPM Adaptive", "DPM++ 2M", "DPM2 Ancestral", "DPM++ S", "DPM++ SDE", "DDPM", "DPM Fast", "dpmpp_2s_ancestral", "Euler", "Euler CFG PP", "Euler a", "Euler Ancestral", "Euler+beta", "Heun", "Heun PP2", "DDIM", "LMS Karras", "PLMS", "UniPC", "UniPC BH2"])
+        with gr.Row():
+            steps = gr.Slider(show_label=True, label="Sampling Steps:", minimum=1, maximum=50, value=35, step=1)
+        with gr.Row():
+            cfg_scale = gr.Slider(show_label=True, label="CFG Scale:", minimum=1, maximum=20, value=7, step=1)
+        with gr.Row():
+            seed = gr.Number(show_label=True, label="Seed:", minimum=-1, maximum=1000000, value=-1, step=1)
+        with gr.Row():
+            width = gr.Slider(label="Width", minimum=512, maximum=2048, step=8, value=896, interactive=True,)
+        with gr.Row():
+            height = gr.Slider(label="Height", minimum=512, maximum=2048, step=8, value=1152,interactive=True,)
     
-    container_radius='*radius_xl',
-    panel_background_fill='*primary_200',
-    accordion_text_color='*primary_600',
-    checkbox_border_radius='*radius_xl',
-    #slider_color='*primary_600',
-    table_text_color='*primary_600',
-    input_background_fill='*primary_50',
-    input_background_fill_focus='*primary_100',
-
-    #Button Settings
-    button_border_width='1px',
-    button_transform_hover='scale(1.01)',
-    button_transition='all 0.1s ease-in-out',
-    button_transform_active='Scale(0.9)',
-    button_large_radius='*radius_xl',
-    button_small_radius='*radius_xl',
-    button_primary_border_color='*primary_500',
-    button_secondary_border_color='*primary_400',
-    button_primary_background_fill_hover='linear-gradient(90deg, *primary_400, *secondary_200, *primary_400)',
-    button_primary_background_fill='linear-gradient(90deg,*secondary_300 , *primary_500, *secondary_300)',
-    button_primary_text_color='*primary_100',
-    button_primary_text_color_hover='*primary_700',
-    button_cancel_background_fill='*primary_500',
-    button_cancel_background_fill_hover='*primary_400',
-
-    loader_color="#800000",
-    slider_color="#708090"
-)
-#----------End of theme----------
+    with gr.Tab("Upscaling Settings"):
+        with gr.Column():
+            with gr.Row():
+                scale_by = gr.Number(show_label=True, label="How many times to increase:", minimum=1, maximum=2, value=2, step=1)
+            with gr.Row():
+                method = gr.Dropdown(show_label=True, value="ESRGAN_4x", label="Increasing algorithm", choices=["ScuNET GAN", "SwinIR 4x", "ESRGAN_4x", "R-ESRGAN 4x+", "R-ESRGAN 4x+ Anime6B"])
+        with gr.Column():
+            with gr.Row():
+                gfpgan = gr.Slider(show_label=True, label="Effect GFPGAN (For facial improvement)", minimum=0, maximum=1, value=0, step=0.1)
+            with gr.Row():
+                codeformer = gr.Slider(show_label=True, label="Effect CodeFormer (Improve the face)", minimum=0, maximum=1, value=0, step=0.1)
+    
+    with gr.Column():
+        text_button = gr.Button("Generate image", variant="primary", interactive=True, elem_id="generate")
+    with gr.Column():
+        image_output = gr.Image(show_download_button=True, interactive=False, label='Generated Image 🌄', show_share_button=False, format="png", type="filepath", elem_id="gallery")
+        
+        text_button.click(query, inputs=[prompt, negative_prompt, task, steps, sampler, cfg_scale, seed, width, height], outputs=image_output, concurrency_limit=48)
+        clear_prompt =gr.Button("Clear 🗑️",variant="primary", elem_id="clear_button")
+        clear_prompt.click(lambda: (None, None), None, [prompt, image_output], queue=False, show_api=False)
+        
+        img2img_b = gr.Button("Increase the image", variant='secondary')
+        image_i2i = gr.Image(show_label=True, label='Increased image:')
+        img2img_b.click(mirror, inputs=[image_output, scale_by, method, gfpgan, codeformer], outputs=image_i2i, concurrency_limit=48)
+    
+
+app.queue(default_concurrency_limit=200, max_size=200)  # <-- Sets up a queue with default parameters
+if __name__ == "__main__":
+    app.launch()