import gradio as gr
import random
from transformers import pipeline
# Predefined words to check
SPECIAL_WORDS = ['weather', 'sun', 'middle', 'summer', 'heat']
def generate_circular_text_design(word):
"""Generate a consistent but randomized text design for a word using CSS animations"""
# Controlled randomization parameters
font_sizes = [18, 20, 22, 24, 26]
letter_spacings = [-3, -2, -4]
skew_angles = [-25, -20, -15, -10, 0, 10, 15, 20, 25]
# Random single color
base_color = f'#{random.randint(0, 0xFFFFFF):06x}'
# Fonts with a controlled set
fonts = [
"'Dosis', sans-serif",
"'Josefin Sans', sans-serif",
"'Orbitron', sans-serif",
"'Roboto Condensed', sans-serif"
]
# Generate a unique animation name for CSS
animation_name = f"animation_{random.randint(0, 10000)}"
# Create HTML for each letter with dynamic styling
letters = list(word)
styled_letters = []
# Prepare CSS keyframes for animation
keyframes = f"""
@keyframes {animation_name} {{
0% {{
transform: scale(1) rotate(0deg);
color: {base_color};
}}
50% {{
transform: scale(1.2) rotate({random.randint(-20, 20)}deg);
color: #{random.randint(0, 0xFFFFFF):06x};
}}
100% {{
transform: scale(1) rotate(0deg);
color: {base_color};
}}
}}
"""
for i, letter in enumerate(letters):
style = {
'font-family': random.choice(fonts),
'line-height': '138%',
'font-size': f'{random.choice(font_sizes)}px',
'letter-spacing': f'{random.choice(letter_spacings)}px',
'text-shadow': '1px 2px 1px',
'transform': f'skew({random.choice(skew_angles)}deg)',
'margin-top': f'{random.uniform(-0.1, 0.1):.2f}cm',
'position': 'relative',
'top': f'{random.randint(3, 11)}px',
'color': base_color,
'animation': f'{animation_name} 2s ease-in-out infinite',
}
# Convert style to inline CSS
style_str = '; '.join([f'{k}: {v}' for k, v in style.items()])
styled_letter = f'
{letter}
'
styled_letters.append(styled_letter)
# Wrap styled letters in a flex container and include keyframes in a style tag
return f'''
{" ".join(styled_letters)}
'''
def process_text(input_text):
"""Process text and apply special styling to matching words"""
# Use inference model
generator = pipeline('text-generation', model='gpt2')
generated_text = generator(input_text, max_length=50, num_return_sequences=1)[0]['generated_text']
# Split text into words
words = generated_text.split()
# Check for special words
for i, word in enumerate(words):
clean_word = ''.join(e for e in word if e.isalnum()).lower()
if clean_word in SPECIAL_WORDS:
# Apply circular text design
words[i] = generate_circular_text_design(word)
# Combine words with HTML
output_html = f"""
{" ".join(words)}
"""
return output_html
# Create Gradio interface
iface = gr.Interface(
fn=process_text,
inputs="text",
outputs=gr.HTML(label="Generated Text"),
title="Circular Text Styler",
description="Enter a prompt to generate text with special word styling. If the generated text contains specific words, they'll be styled with dynamic animations."
)
# Launch the interface
iface.launch()