Update app.py

app.py

@@ -132,162 +132,6 @@ with gr.Blocks(theme=theme, fill_width=True, css=css) as app:
                                         - **film-noir**: in the style of FLMNR
                                         - **flux-lora-pro-headshot**: PROHEADSHOT
                             		""")
-                        with gr.Row():
-                            custom_lora = 
-FLUX.Dev-LORA
-/ app.py
-DigiP-AI's picture
-DigiP-AI
-Update app.py
-9026664
-verified
-1 day ago
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-11.8 kB
-#!/usr/bin/env python
-import gradio as gr
-import requests
-import io
-import random
-import os
-import time
-import numpy as np
-import subprocess
-import torch
-import json
-import uuid
-import spaces
-from typing import Tuple
-from transformers import AutoProcessor, AutoModelForCausalLM
-from PIL import Image
-from deep_translator import GoogleTranslator
-from datetime import datetime
-from theme import theme
-from typing import Tuple
-from fastapi import FastAPI
-
-app = FastAPI()
-
-
-
-API_TOKEN = os.getenv("HF_READ_TOKEN")
-headers = {"Authorization": f"Bearer {API_TOKEN}"}
-timeout = 100
-
-def flip_image(x):
-    return np.fliplr(x)
-
-def clear():
-  return None    
-
-def query(lora_id, prompt, is_negative=False, steps=28, cfg_scale=3.5, sampler="DPM++ 2M Karras", seed=-1, strength=100, width=896, height=1152):
-    if prompt == "" or prompt == None:
-        return None
-
-    if lora_id.strip() == "" or lora_id == None:
-        lora_id = "black-forest-labs/FLUX.1-dev"
-
-    key = random.randint(0, 999)
-
-    API_URL = "https://api-inference.huggingface.co/models/"+ lora_id.strip()
-
-    API_TOKEN = random.choice([os.getenv("HF_READ_TOKEN")])
-    headers = {"Authorization": f"Bearer {API_TOKEN}"}
-    
-    # prompt = GoogleTranslator(source='ru', target='en').translate(prompt)
-    # print(f'\033[1mGeneration {key} translation:\033[0m {prompt}')
-    prompt = GoogleTranslator(source='ru', target='en').translate(prompt)
-    print(f'\033[1mGeneration {key} translation:\033[0m {prompt}')
-
-    prompt = f"{prompt} | ultra detail, ultra elaboration, ultra quality, perfect."
-    print(f'\033[1mGeneration {key}:\033[0m {prompt}')
-
-    # If seed is -1, generate a random seed and use it
-    if seed == -1:
-        seed = random.randint(1, 1000000000)
-
-    # Prepare the payload for the API call, including width and height
-    payload = {
-        "inputs": prompt,
-        "is_negative": is_negative,
-        "steps": steps,
-        "cfg_scale": cfg_scale,
-        "seed": seed if seed != -1 else random.randint(1, 1000000000),
-        "strength": strength,
-        "parameters": {
-            "width": width,  # Pass the width to the API
-            "height": height  # Pass the height to the API
-        }
-    }
-
-    response = requests.post(API_URL, headers=headers, json=payload, timeout=timeout)
-    if response.status_code != 200:
-        print(f"Error: Failed to get image. Response status: {response.status_code}")
-        print(f"Response content: {response.text}")
-        if response.status_code == 503:
-            raise gr.Error(f"{response.status_code} : The model is being loaded")
-        raise gr.Error(f"{response.status_code}")
-
-    try:
-        image_bytes = response.content
-        image = Image.open(io.BytesIO(image_bytes))
-        print(f'\033[1mGeneration {key} completed!\033[0m ({prompt})')
-        return image, seed
-    except Exception as e:
-        print(f"Error when trying to open the image: {e}")
-        return None
-
-examples = [
-    "a beautiful woman with blonde hair and blue eyes",
-    "a beautiful woman with brown hair and grey eyes",
-    "a beautiful woman with black hair and brown eyes",
-]
-
-css = """
-#app-container {
-    max-width: 930px;
-    margin-left: auto;
-    margin-right: auto;
-}
-".gradio-container {background: url('file=abstract.jpg')}
-   
-"""
-with gr.Blocks(theme=theme, css=css, elem_id="app-container") as app:
-    gr.HTML("<center><h6>🎨 FLUX.1-Dev with LoRA 🇬🇧</h6></center>")
-    with gr.Tab("Text to Image"):
-        with gr.Column(elem_id="app-container"):
-            with gr.Row():
-                with gr.Column(elem_id="prompt-container"):
-                    with gr.Group():
-                        with gr.Row():
-                            text_prompt = gr.Textbox(label="Image Prompt ✍️", placeholder="Enter a prompt here", lines=2, show_copy_button = True, elem_id="prompt-text-input")
-                        with gr.Row():
-                            with gr.Accordion("🎨 Lora trigger words", open=False):
-                            		gr.Markdown("""
-                                        - **Canopus-Pencil-Art-LoRA**: Pencil Art
-                                        - **Flux-Realism-FineDetailed**: Fine Detailed
-                                        - **Fashion-Hut-Modeling-LoRA**: Modeling
-                                        - **SD3.5-Large-Turbo-HyperRealistic-LoRA**: hyper realistic
-                                        - **Flux-Fine-Detail-LoRA**: Super Detail
-                                        - **SD3.5-Turbo-Realism-2.0-LoRA**: Turbo Realism
-                                        - **Canopus-LoRA-Flux-UltraRealism-2.0**: Ultra realistic 
-                                        - **Canopus-Pencil-Art-LoRA**: Pencil Art
-                                        - **SD3.5-Large-Photorealistic-LoRA**: photorealistic
-                                        - **Flux.1-Dev-LoRA-HDR-Realism**: HDR
-                                        - **prithivMLmods/Ton618-Epic-Realism-Flux-LoRA**: Epic Realism
-                                        - **john-singer-sargent-style**: John Singer Sargent Style
-                                        - **alphonse-mucha-style**: Alphonse Mucha Style
-                                        - **ultra-realistic-illustration**: ultra realistic illustration
-                                        - **eye-catching**: eye-catching
-                                        - **john-constable-style**: John Constable Style
-                                        - **film-noir**: in the style of FLMNR
-                                        - **flux-lora-pro-headshot**: PROHEADSHOT
-                            		""")                       
-                                
                         with gr.Row():
                             custom_lora = gr.Dropdown([" ", "prithivMLmods/Canopus-Pencil-Art-LoRA", "prithivMLmods/Flux-Realism-FineDetailed", "prithivMLmods/Fashion-Hut-Modeling-LoRA", "prithivMLmods/SD3.5-Large-Turbo-HyperRealistic-LoRA", "prithivMLmods/Flux-Fine-Detail-LoRA", "prithivMLmods/SD3.5-Turbo-Realism-2.0-LoRA", "hugovntr/flux-schnell-realism", "fofr/sdxl-deep-down", "prithivMLmods/Canopus-LoRA-Flux-UltraRealism-2.0", "prithivMLmods/Canopus-Realism-LoRA", "prithivMLmods/Canopus-LoRA-Flux-FaceRealism", "prithivMLmods/SD3.5-Large-Photorealistic-LoRA", "prithivMLmods/Flux.1-Dev-LoRA-HDR-Realism", "prithivMLmods/Ton618-Epic-Realism-Flux-LoRA", "KappaNeuro/john-singer-sargent-style", "KappaNeuro/alphonse-mucha-style", "ntc-ai/SDXL-LoRA-slider.ultra-realistic-illustration", "ntc-ai/SDXL-LoRA-slider.eye-catching", "KappaNeuro/john-constable-style", "dvyio/flux-lora-film-noir", "dvyio/flux-lora-pro-headshot"], label="Custom LoRA",)
                     with gr.Accordion("Advanced options", open=False):