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| """Gradio web interface for synthetic data generation.""" | |
| import logging | |
| import gradio as gr | |
| from src.pipeline import DatasetPipeline | |
| from src.constants import PROJECT_NAME, VERSION | |
| # Set up logger | |
| logger = logging.getLogger(__name__) | |
| logging.basicConfig( | |
| level=logging.INFO, format="%(asctime)s - %(name)s - %(levelname)s - %(message)s" | |
| ) | |
| pipeline = DatasetPipeline() | |
| PROJECT_NAME_CAP = PROJECT_NAME.capitalize() | |
| REPO_URL = f"https://github.com/lisekarimi/{PROJECT_NAME}" | |
| def update_output_format(dataset_type): | |
| """Update output format choices based on selected dataset type.""" | |
| if dataset_type in ["Tabular", "Time-series"]: | |
| return gr.update(choices=["JSON", "csv", "Parquet"], value="JSON") | |
| elif dataset_type == "Text": | |
| return gr.update(choices=["JSON", "Markdown"], value="JSON") | |
| def build_ui(css_path="assets/styles.css"): | |
| """Build and return the complete Gradio user interface with error handling.""" | |
| # Try to load CSS file with error handling | |
| try: | |
| with open(css_path, encoding="utf-8") as f: | |
| css = f.read() | |
| except Exception as e: | |
| css = "" | |
| logger.warning("⚠️ Failed to load CSS: %s", e) | |
| # Building the UI with error handling | |
| try: | |
| with gr.Blocks(css=css, title=f"{PROJECT_NAME_CAP}") as ui: | |
| with gr.Column(elem_id="app-container"): | |
| gr.Markdown(f"<h1 id='app-title'>🏷️ {PROJECT_NAME_CAP} </h1>") | |
| gr.Markdown( | |
| "<h2 id='app-subtitle'>AI-Powered Synthetic Dataset Generator</h2>" | |
| ) | |
| # Fix the f-string in HTML | |
| intro_html = f""" | |
| <div id="intro-text"> | |
| <p>With {PROJECT_NAME_CAP}, easily generate | |
| <strong>diverse datasets</strong> | |
| for testing, development, and AI training.</p> | |
| <h4>🎯 How It Works:</h4> | |
| <p>1️⃣ Define your business problem.</p> | |
| <p>2️⃣ Select dataset type, format, model, and samples.</p> | |
| <p>3️⃣ Download your synthetic dataset!</p> | |
| </div> | |
| """ | |
| gr.HTML(intro_html) | |
| learn_more_html = """ | |
| <div id="learn-more-button"> | |
| <a href="https://datagen.lisekarimi.com/docs" | |
| class="button-link">Documentation</a> | |
| </div> | |
| """ | |
| gr.HTML(learn_more_html) | |
| examples_md = """ | |
| <p><strong>🧠 Need inspiration?</strong> Try these examples:</p> | |
| <ul> | |
| <li>Movie summaries for genre classification.</li> | |
| <li>Customer chats with dialogue and sentiment labels.</li> | |
| <li>Stock prices with date, ticker, open, close, volume.</li> | |
| </ul> | |
| """ | |
| gr.Markdown(examples_md) | |
| gr.Markdown("<p><strong>Start generating now!</strong> 🗂️✨</p>") | |
| with gr.Group(elem_id="input-container"): | |
| business_problem = gr.Textbox( | |
| placeholder=( | |
| "Describe the dataset you want " | |
| "(e.g., Job postings, Customer reviews)" | |
| ), | |
| lines=2, | |
| label="📌 Business Problem", | |
| elem_classes=["label-box"], | |
| elem_id="business-problem-box", | |
| ) | |
| with gr.Row(elem_classes="column-gap"): | |
| with gr.Column(scale=1): | |
| dataset_type = gr.Dropdown( | |
| ["Tabular", "Time-series", "Text"], | |
| value="Tabular", | |
| label="📊 Dataset Type", | |
| elem_classes=["label-box"], | |
| elem_id="custom-dropdown", | |
| ) | |
| with gr.Column(scale=1): | |
| output_format = gr.Dropdown( | |
| choices=["JSON", "csv", "Parquet"], | |
| value="JSON", | |
| label="📁 Output Format", | |
| elem_classes=["label-box"], | |
| elem_id="custom-dropdown", | |
| ) | |
| # Bind the update function to the dataset type dropdown | |
| dataset_type.change( | |
| update_output_format, | |
| inputs=[dataset_type], | |
| outputs=[output_format], | |
| ) | |
| with gr.Row(elem_classes="row-spacer column-gap"): | |
| with gr.Column(scale=1): | |
| num_samples = gr.Slider( | |
| minimum=10, | |
| maximum=1000, | |
| value=10, | |
| step=1, | |
| interactive=True, | |
| label="🔢 Number of Samples", | |
| elem_classes=["label-box"], | |
| ) | |
| # Hidden file component for dataset download | |
| file_download = gr.File( | |
| visible=False, elem_id="download-box", label=None | |
| ) | |
| # Component to display status messages | |
| status_message = gr.Markdown("", label="Status") | |
| # Button to trigger dataset generation | |
| run_btn = gr.Button("Create a dataset", elem_id="run-btn") | |
| run_btn.click( | |
| pipeline.generate, | |
| inputs=[ | |
| business_problem, | |
| dataset_type, | |
| output_format, | |
| num_samples, | |
| ], | |
| outputs=[file_download, run_btn, status_message], | |
| ) | |
| # Explore More Projects section | |
| explore_projects_html = """ | |
| <div id="explore-projects"> | |
| <h3>🚀 Explore More Projects</h3> | |
| <p>Discover a comprehensive portfolio of AI/ML solutions.</p> | |
| <div id="explore-projects-button"> | |
| <a href="https://lisekarimi.com" | |
| class="portfolio-link" | |
| target="_blank"> | |
| View Full Portfolio | |
| </a> | |
| </div> | |
| </div> | |
| """ | |
| gr.HTML(explore_projects_html) | |
| # Bottom: version info | |
| gr.Markdown( | |
| f""" | |
| <p class="version-banner"> | |
| 🔖 <strong> | |
| <a href="{REPO_URL}/blob/main/CHANGELOG.md" | |
| target="_blank">Version {VERSION}</a> | |
| </strong> | |
| </p> | |
| """ | |
| ) | |
| return ui | |
| except Exception as e: | |
| logger.error("❌ Error building UI: %s", e) | |
| # Return a minimal error UI | |
| with gr.Blocks() as error_ui: | |
| gr.Markdown("# Error Loading Application") | |
| gr.Markdown(f"An error occurred: {str(e)}") | |
| return error_ui | |