app.py

import spaces
import gradio as gr
import torch
from transformers import pipeline

# Set up the model
model_id = "meta-llama/Llama-3.2-3B"
pipe = pipeline(
    "text-generation", 
    model=model_id, 
    torch_dtype=torch.bfloat16, 
    device_map="cuda"
)

@spaces.GPU
def generate_text(prompt):
    response = pipe(prompt, max_length=100, num_return_sequences=1)
    return response[0]['generated_text']

# Custom CSS for the app
css = """
body {background-color: #f0f8ff; font-family: 'Arial', sans-serif;}
.gradio-container {max-width: 900px; margin: 0 auto; border-radius: 15px; padding: 30px; background-color: white; box-shadow: 0 4px 8px rgba(0,0,0,0.1);}
textarea {border-radius: 10px; padding: 15px; font-size: 16px; border: 2px solid #ddd; width: 100%;}
button {background-color: #4caf50; color: white; border-radius: 10px; padding: 10px 15px; font-size: 16px; border: none; cursor: pointer; margin-top: 10px; margin-right: 5px;}
button:hover {background-color: #45a049;}
h1 {color: #333; font-size: 36px; text-align: center; margin-bottom: 20px;}
h2 {color: #555; font-size: 24px; margin-bottom: 10px;}
footer {text-align: center; padding: 20px; font-size: 14px;}
"""

# Define example entries
example_entries = [
    "Today, I finished a major project that I’ve been working on for weeks. It felt great to finally get it done, and I’m proud of the effort I put in.",
    "I faced a tough challenge today when I had to give a presentation with very little preparation. Despite feeling nervous, I managed to pull through by staying calm and focused.",
    "Tomorrow, my goal is to focus on improving my communication skills during team meetings. I want to make sure I’m clear and concise in expressing my ideas.",
    "I’m grateful for the support I received from my coworkers today. Their encouragement really helped me push through a stressful moment.",
    "I learned a new approach to managing my time more effectively today. I’m going to apply this to my daily routine to see if it helps me stay more productive."
]

# Function to return the selected prompt
def fill_prompt(selected_prompt):
    return selected_prompt

# Create the Gradio interface
with gr.Blocks(css=css) as journal_app:
    
    # Header and introduction
    gr.Markdown("# 📝 Productivity Journal")
    gr.Markdown("Welcome to your personalized productivity journal. Click an example below or write your thoughts!")

    # Example journal entries section
    gr.Markdown("### **Select an example to start writing:**")

    # Input text box for writing thoughts
    prompt_textbox = gr.Textbox(label="Write your thoughts here:", placeholder="Start writing or select an example...", elem_id="prompt_box", lines=5)
    
    # Align buttons using rows and columns for better layout
    with gr.Row():
        for i, entry in enumerate(example_entries):
            gr.Button(f"Example {i+1}").click(fn=lambda e=entry: fill_prompt(e), outputs=prompt_textbox)

    with gr.Row():
        # Output for generated text
        output = gr.Textbox(label="Your AI Journal Entry ✨", lines=6)
    
    # Generate button
    generate_button = gr.Button("Generate Entry ✍️")

    # Define the click event for text generation
    generate_button.click(fn=generate_text, inputs=prompt_textbox, outputs=output)

    # Footer
    gr.Markdown("🌞 Keep your spirits high and stay productive! 😊")
    gr.Markdown("Made with ❤️ using Gradio and Llama-3.2")

# Launch the app
journal_app.launch()