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import gradio as gr | |
import requests | |
import io | |
import random | |
import os | |
import time | |
from PIL import Image | |
from deep_translator import GoogleTranslator | |
import json | |
from gradio_client import Client | |
# Project by Nymbo | |
API_URL = "https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-3.5-large" | |
API_TOKEN = os.getenv("HF_READ_TOKEN") | |
headers = {"Authorization": f"Bearer {API_TOKEN}"} | |
timeout = 100 | |
# Initialize the prompt enhancer client | |
prompt_enhancer = Client("K00B404/mistral-nemo-prompt-enhancer") | |
def enhance_prompt(prompt, enable_enhancement=True): | |
"""Enhance the given prompt using the Mistral Nemo prompt enhancer.""" | |
if not enable_enhancement: | |
print(f'\033[1mPrompt enhancement disabled, using original prompt:\033[0m {prompt}') | |
return prompt | |
try: | |
system_message = "You are an expert at writing detailed, high-quality image generation prompts. Enhance the given prompt by adding relevant artistic details, style elements, and quality descriptors. Keep the original intent but make it more elaborate and specific." | |
enhanced = prompt_enhancer.predict( | |
message=prompt, | |
system_message=system_message, | |
max_tokens=512, | |
temperature=0.7, | |
top_p=0.95, | |
api_name="/chat" | |
) | |
print(f'\033[1mOriginal prompt:\033[0m {prompt}') | |
print(f'\033[1mEnhanced prompt:\033[0m {enhanced}') | |
return enhanced | |
except Exception as e: | |
print(f"Error enhancing prompt: {e}") | |
return prompt # Fall back to original prompt if enhancement fails | |
# Function to query the API and return the generated image | |
def query(prompt, is_negative=False, steps=35, cfg_scale=7, sampler="DPM++ 2M Karras", seed=-1, strength=0.7, width=1024, height=1024, enable_enhancement=True): | |
if prompt == "" or prompt is None: | |
return None, None | |
key = random.randint(0, 999) | |
API_TOKEN = random.choice([os.getenv("HF_READ_TOKEN")]) | |
headers = {"Authorization": f"Bearer {API_TOKEN}"} | |
# Translate the prompt from Russian to English if necessary | |
prompt = GoogleTranslator(source='ru', target='en').translate(prompt) | |
print(f'\033[1mGeneration {key} translation:\033[0m {prompt}') | |
# Enhance the prompt using the Mistral Nemo model if enabled | |
enhanced_prompt = enhance_prompt(prompt, enable_enhancement) | |
# Add some extra flair to the prompt | |
final_prompt = f"{enhanced_prompt} | ultra detail, ultra elaboration, ultra quality, perfect." | |
print(f'\033[1mGeneration {key} final prompt:\033[0m {final_prompt}') | |
# Prepare the payload for the API call, including width and height | |
payload = { | |
"inputs": final_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, | |
"height": height | |
} | |
} | |
# Send the request to the API and handle the response | |
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: | |
# Convert the response content into an image | |
image_bytes = response.content | |
image = Image.open(io.BytesIO(image_bytes)) | |
print(f'\033[1mGeneration {key} completed!\033[0m ({final_prompt})') | |
return image, enhanced_prompt | |
except Exception as e: | |
print(f"Error when trying to open the image: {e}") | |
return None, None | |
# CSS to style the app | |
css = """ | |
#app-container { | |
max-width: 800px; | |
margin-left: auto; | |
margin-right: auto; | |
} | |
""" | |
# Build the Gradio UI with Blocks | |
with gr.Blocks(theme='Nymbo/Nymbo_Theme', css=css) as app: | |
# Add a title to the app | |
gr.HTML("<center><h1>Stable Diffusion 3.5 Large with Prompt Enhancement</h1></center>") | |
# Container for all the UI elements | |
with gr.Column(elem_id="app-container"): | |
# Add a text input for the main prompt | |
with gr.Row(): | |
with gr.Column(elem_id="prompt-container"): | |
with gr.Row(): | |
text_prompt = gr.Textbox( | |
label="Prompt", | |
placeholder="Enter a prompt here - it will be automatically enhanced for better results", | |
lines=2, | |
elem_id="prompt-text-input" | |
) | |
# Accordion for advanced settings | |
with gr.Row(): | |
with gr.Accordion("Advanced Settings", open=False): | |
enable_enhancement = gr.Checkbox( | |
label="Enable Prompt Enhancement", | |
value=True | |
) | |
negative_prompt = gr.Textbox( | |
label="Negative Prompt", | |
placeholder="What should not be in the image", | |
value="(deformed, distorted, disfigured), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, (mutated hands and fingers), disconnected limbs, mutation, mutated, ugly, disgusting, blurry, amputation, misspellings, typos", | |
lines=3, | |
elem_id="negative-prompt-text-input" | |
) | |
with gr.Row(): | |
width = gr.Slider(label="Width", value=1024, minimum=64, maximum=1216, step=32) | |
height = gr.Slider(label="Height", value=1024, minimum=64, maximum=1216, step=32) | |
steps = gr.Slider(label="Sampling steps", value=35, minimum=1, maximum=100, step=1) | |
cfg = gr.Slider(label="CFG Scale", value=7, minimum=1, maximum=20, step=1) | |
strength = gr.Slider(label="Strength", value=0.7, minimum=0, maximum=1, step=0.001) | |
seed = gr.Slider(label="Seed", value=-1, minimum=-1, maximum=1000000000, step=1) | |
method = gr.Radio( | |
label="Sampling method", | |
value="DPM++ 2M Karras", | |
choices=["DPM++ 2M Karras", "DPM++ SDE Karras", "Euler", "Euler a", "Heun", "DDIM"] | |
) | |
# Add a button to trigger the image generation | |
with gr.Row(): | |
text_button = gr.Button("Generate Enhanced Image", variant='primary', elem_id="gen-button") | |
# Image output area to display the generated image | |
with gr.Row(): | |
image_output = gr.Image(type="pil", label="Image Output", elem_id="gallery") | |
# Text output area to display the enhanced prompt | |
with gr.Row(): | |
prompt_output = gr.Textbox(label="Enhanced Prompt", elem_id="prompt-output") | |
# Bind the button to the query function with all inputs | |
text_button.click( | |
query, | |
inputs=[text_prompt, negative_prompt, steps, cfg, method, seed, strength, width, height, enable_enhancement], | |
outputs=[image_output, prompt_output] | |
) | |
# Launch the Gradio app | |
app.launch(show_api=True, share=False) |