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import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
import gradio as gr
import re
# Set page title and description
title = "π Pickup Line Generator"
description = """
<div style="text-align: center; max-width: 650px; margin: 0 auto;">
<div>
<p style="color: #333333; font-size: 1.1rem; font-weight: 500;">Generate fun, clever, or cringey pickup lines using SmolLM-135M! Select a vibe and click generate to get started! π</p>
</div>
</div>
"""
# Load model and tokenizer
print("Loading SmolLM-135M model...")
MODEL_NAME = "HuggingFaceTB/SmolLM-135M"
# Check for CUDA availability
device = "cuda" if torch.cuda.is_available() else "cpu"
print(f"Using device: {device}")
# Load the model and tokenizer
tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
# Set pad_token to eos_token to handle padding
tokenizer.pad_token = tokenizer.eos_token
model = AutoModelForCausalLM.from_pretrained(MODEL_NAME).to(device)
print(f"Model loaded successfully! Memory footprint: {model.get_memory_footprint() / 1e6:.2f} MB")
def get_vibe_guidance(vibe):
"""Get specific guidance for each vibe with examples"""
vibe_patterns = {
"romantic": """Generate a romantic and sweet pickup line that's genuine and heartfelt.
Example:
Input: Generate a romantic pickup line
Output: Are you a magician? Because whenever I look at you, everyone else disappears. β€οΈ
Now generate a romantic pickup line: """,
"cheesy": """Generate a super cheesy and over-the-top pickup line.
Example:
Input: Generate a cheesy pickup line
Output: Are you a parking ticket? Because you've got FINE written all over you! π
Now generate a cheesy pickup line: """,
"nerdy": """Generate a nerdy, science-themed pickup line.
Example:
Input: Generate a nerdy pickup line
Output: Are you made of copper and tellurium? Because you're Cu-Te! π¬
Now generate a nerdy pickup line: """,
"cringe": """Generate the most cringey and over-the-top pickup line imaginable.
Example:
Input: Generate a cringe pickup line
Output: Are you a dictionary? Because you're adding meaning to my life! π
Now generate a cringe pickup line: """,
"flirty": """Generate a bold and flirty pickup line.
Example:
Input: Generate a flirty pickup line
Output: Is your name Google? Because you've got everything I've been searching for! π
Now generate a flirty pickup line: """
}
return vibe_patterns.get(vibe, "Generate a pickup line with a ")
def generate_pickup_line(vibe):
"""Generate a pickup line based on the selected vibe"""
# Get the vibe guidance
vibe_guide = get_vibe_guidance(vibe)
# Create the prompt
prompt = f"""Instructions: Generate a pickup line with a {vibe} vibe.
{vibe_guide}"""
# Prepare inputs with explicit attention mask
encoded_input = tokenizer.encode_plus(
prompt,
return_tensors="pt",
padding=True,
return_attention_mask=True
)
input_ids = encoded_input["input_ids"].to(device)
attention_mask = encoded_input["attention_mask"].to(device)
# Generate multiple responses and pick the best one
num_tries = 3
best_response = None
for _ in range(num_tries):
with torch.no_grad():
outputs = model.generate(
input_ids,
attention_mask=attention_mask,
max_new_tokens=100,
do_sample=True,
temperature=0.8,
top_p=0.92,
top_k=50,
pad_token_id=tokenizer.eos_token_id,
eos_token_id=tokenizer.eos_token_id,
)
# Get the full generated text
full_response = tokenizer.decode(outputs[0], skip_special_tokens=True)
# Extract just the pickup line
if full_response.startswith(prompt):
response = full_response[len(prompt):].strip()
else:
response = full_response.replace(prompt, "").strip()
# Clean up the response
for marker in ["Instructions:", "Generate a pickup line:", "\n"]:
if marker in response:
response = response.split(marker, 1)[0].strip()
# Add appropriate emoji based on vibe
if vibe == "romantic":
response += " β€οΈ"
elif vibe == "cheesy":
response += " π"
elif vibe == "nerdy":
response += " π¬"
elif vibe == "cringe":
response += " π"
elif vibe == "flirty":
response += " π"
best_response = response
break
return best_response
# Create custom CSS
custom_css = """
#component-0 {
background-color: #fef6f9 !important;
max-width: 800px !important;
margin: 0 auto !important;
padding: 2rem !important;
border-radius: 15px !important;
box-shadow: 0 4px 6px rgba(255, 105, 180, 0.1) !important;
}
h1 {
font-family: 'Lobster', cursive !important;
color: #ff1493 !important;
text-align: center !important;
font-size: 2.5rem !important;
margin-bottom: 1rem !important;
text-shadow: 1px 1px 2px rgba(0,0,0,0.1) !important;
}
.generate-btn {
background: linear-gradient(45deg, #ff69b4, #ff1493) !important;
color: white !important;
border: none !important;
padding: 0.75rem 1.5rem !important;
border-radius: 8px !important;
font-weight: bold !important;
transition: all 0.3s ease !important;
width: 100% !important;
margin-top: 1rem !important;
font-size: 1.1rem !important;
}
.generate-btn:hover {
transform: translateY(-2px) !important;
box-shadow: 0 4px 8px rgba(255, 105, 180, 0.3) !important;
}
.copy-btn {
background: white !important;
color: #ff1493 !important;
border: 2px solid #ff1493 !important;
padding: 0.75rem 1.5rem !important;
border-radius: 8px !important;
font-weight: bold !important;
transition: all 0.3s ease !important;
width: 100% !important;
font-size: 1.1rem !important;
}
.copy-btn:hover {
background: #ff1493 !important;
color: white !important;
}
.gr-dropdown {
border: 2px solid #ff69b4 !important;
border-radius: 8px !important;
background: white !important;
}
.gr-dropdown > select {
color: #333333 !important;
font-size: 1.1rem !important;
}
.gr-textbox {
border: 2px solid #ff69b4 !important;
border-radius: 8px !important;
background: white !important;
color: #333333 !important;
font-size: 1.1rem !important;
}
.gr-form {
background: white !important;
padding: 1rem !important;
border-radius: 8px !important;
box-shadow: 0 2px 4px rgba(0,0,0,0.1) !important;
}
/* Label styling */
label {
color: #333333 !important;
font-weight: 600 !important;
font-size: 1.1rem !important;
}
/* Examples styling */
.gr-samples {
background: white !important;
border-radius: 8px !important;
padding: 1rem !important;
margin-top: 1rem !important;
}
.gr-samples button {
color: #333333 !important;
font-weight: 500 !important;
}
/* Footer styling */
.footer-text {
color: #666666 !important;
font-size: 1rem !important;
margin-top: 2rem !important;
}
"""
# Create the Gradio interface
with gr.Blocks(theme=gr.themes.Soft(), css=custom_css) as demo:
gr.Markdown(f"# {title}")
gr.Markdown(description)
with gr.Row():
with gr.Column():
vibe_dropdown = gr.Dropdown(
choices=[
"romantic",
"cheesy",
"nerdy",
"cringe",
"flirty"
],
label="Pick a vibe",
value="romantic"
)
generate_btn = gr.Button("Generate Line β¨", elem_classes=["generate-btn"])
with gr.Column():
output = gr.Textbox(
label="Your pickup line",
lines=3,
interactive=False
)
copy_btn = gr.Button("π Copy to Clipboard", elem_classes=["copy-btn"])
generate_btn.click(
fn=generate_pickup_line,
inputs=[vibe_dropdown],
outputs=output
)
# Updated copy functionality
copy_btn.click(
fn=lambda x: x,
inputs=[output],
outputs=[],
js="(text) => { navigator.clipboard.writeText(text); }"
)
# Footer with custom class
gr.Markdown("""
<div class="footer-text" style="text-align: center;">
Built by Nath with SmolLM π₯
</div>
""")
# Launch the app
if __name__ == "__main__":
demo.launch(share=True) # Set share=False if you don't want to create a public link
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