app.py

import gradio as gr
import matplotlib.pyplot as plt
import numpy as np
from PIL import Image

# Custom CSS
custom_css = """
.container {
    max-width: 900px;
    margin: auto;
    padding: 20px;
}
.gr-header {
    text-align: center;
    margin-bottom: 40px;
}
.gr-header h1 {
    color: #2a2a2a;
    font-size: 2.5em;
    margin-bottom: 10px;
}
.gr-header p {
    color: #666;
    font-size: 1.2em;
}
.gr-tab-text {
    font-size: 1.1em;
    line-height: 1.6;
}
.gr-button {
    background-color: #2e7af5 !important;
    color: white !important;
    border: none !important;
    border-radius: 8px !important;
    padding: 10px 20px !important;
    transition: all 0.3s ease !important;
}
.gr-button:hover {
    background-color: #1c5ed9 !important;
    transform: translateY(-2px);
}
.gr-input {
    border-radius: 8px !important;
    border: 2px solid #e0e0e0 !important;
    padding: 12px !important;
}
.gr-input:focus {
    border-color: #2e7af5 !important;
    box-shadow: 0 0 0 2px rgba(46,122,245,0.2) !important;
}
.gr-box {
    border-radius: 12px !important;
    box-shadow: 0 4px 6px rgba(0,0,0,0.1) !important;
    padding: 20px !important;
    background: white !important;
}
"""

# Application 1: Image Classification
def image_classification(image):
    if image is None:
        return "Please upload an image.", None
    
    # Get basic image information
    info = f"""
    Image Analysis Results:
    - Size: {image.shape}
    - Color Space: RGB
    - Resolution: {image.shape[0]}x{image.shape[1]} pixels
    """
    
    # Generate thumbnail
    thumbnail = Image.fromarray(image).copy()
    thumbnail.thumbnail((200, 200))
    
    return info, thumbnail

# Application 2: Text Summary
def text_summary(text):
    if not text:
        return "Please enter text to summarize."
    
    # Analyze basic text information
    char_count = len(text)
    word_count = len(text.split())
    line_count = len(text.splitlines())
    
    summary = f"""
    Text Analysis Results:
    - Character Count: {char_count}
    - Word Count: {word_count}
    - Line Count: {line_count}
    
    Summary:
    {text[:200] + '...' if len(text) > 200 else text}
    """
    
    return summary

# Application 3: Data Visualization
def visualize_data(x_input, y_input):
    try:
        x = [float(i.strip()) for i in x_input.split(',')]
        y = [float(i.strip()) for i in y_input.split(',')]
        
        if len(x) != len(y):
            return None, "Error: Number of X and Y coordinates must match."
        
        fig = plt.figure(figsize=(10, 6))
        plt.style.use('seaborn')
        plt.plot(x, y, 'o-', linewidth=2, markersize=8, color='#2e7af5')
        plt.title('Data Visualization', fontsize=16, pad=20)
        plt.xlabel('X Axis', fontsize=12)
        plt.ylabel('Y Axis', fontsize=12)
        plt.grid(True, linestyle='--', alpha=0.7)
        
        # Improve graph appearance
        plt.tick_params(axis='both', which='major', labelsize=10)
        plt.gca().spines['top'].set_visible(False)
        plt.gca().spines['right'].set_visible(False)
        
        return fig, "Graph generated successfully."
    except ValueError:
        return None, "Error: Invalid input. Please enter numbers separated by commas."

# Build Gradio interface
with gr.Blocks(css=custom_css, theme=gr.themes.Soft()) as portfolio:
    # Header
    with gr.Column(elem_classes="container"):
        gr.Markdown(
            """
            # Portfolio Site
            
            Welcome to my portfolio site where you can experience various applications I've developed.
            Try out different applications in each tab.
            """,
            elem_classes="gr-header"
        )
        
        # Tab container
        with gr.Tabs():
            # Image Classification Tab
            with gr.TabItem("📷 Image Classification", elem_classes="gr-tab"):
                with gr.Column(elem_classes="gr-box"):
                    gr.Markdown(
                        """
                        ### Image Classification App
                        Upload an image to analyze its features. Higher quality images will yield
                        more accurate analysis results.
                        """,
                        elem_classes="gr-tab-text"
                    )
                    with gr.Row():
                        with gr.Column():
                            image_input = gr.Image(
                                label="Upload Image",
                                type="numpy",
                                elem_classes="gr-input"
                            )
                            image_button = gr.Button(
                                "Analyze",
                                elem_classes="gr-button"
                            )
                        with gr.Column():
                            image_output = gr.Textbox(
                                label="Analysis Results",
                                elem_classes="gr-input"
                            )
                            image_thumbnail = gr.Image(
                                label="Thumbnail",
                                elem_classes="gr-input"
                            )
                    
                    image_button.click(
                        image_classification,
                        inputs=image_input,
                        outputs=[image_output, image_thumbnail]
                    )
            
            # Text Summary Tab
            with gr.TabItem("📝 Text Summary", elem_classes="gr-tab"):
                with gr.Column(elem_classes="gr-box"):
                    gr.Markdown(
                        """
                        ### Text Summary App
                        Enter text to generate a summary and basic statistics.
                        Works with both English and other languages.
                        """,
                        elem_classes="gr-tab-text"
                    )
                    text_input = gr.Textbox(
                        label="Enter Text",
                        placeholder="Enter the text you want to summarize...",
                        lines=5,
                        elem_classes="gr-input"
                    )
                    text_button = gr.Button(
                        "Summarize",
                        elem_classes="gr-button"
                    )
                    text_output = gr.Textbox(
                        label="Summary Results",
                        elem_classes="gr-input"
                    )
                    
                    text_button.click(
                        text_summary,
                        inputs=text_input,
                        outputs=text_output
                    )
            
            # Data Visualization Tab
            with gr.TabItem("📊 Data Visualization", elem_classes="gr-tab"):
                with gr.Column(elem_classes="gr-box"):
                    gr.Markdown(
                        """
                        ### Data Visualization Tool
                        Enter X and Y coordinates to generate a beautiful graph.
                        Separate numbers with commas.
                        
                        Example:
                        - X coordinates: 1, 2, 3, 4, 5
                        - Y coordinates: 10, 20, 15, 25, 30
                        """,
                        elem_classes="gr-tab-text"
                    )
                    with gr.Row():
                        x_input = gr.Textbox(
                            label="X Coordinates",
                            placeholder="Example: 1, 2, 3, 4, 5",
                            value="1, 2, 3, 4, 5",
                            elem_classes="gr-input"
                        )
                        y_input = gr.Textbox(
                            label="Y Coordinates",
                            placeholder="Example: 10, 20, 30, 40, 50",
                            value="10, 20, 30, 40, 50",
                            elem_classes="gr-input"
                        )
                    
                    plot_button = gr.Button(
                        "Generate Graph",
                        elem_classes="gr-button"
                    )
                    with gr.Row():
                        plot_output = gr.Plot(label="Graph")
                        plot_message = gr.Textbox(
                            label="Message",
                            elem_classes="gr-input"
                        )
                    
                    plot_button.click(
                        visualize_data,
                        inputs=[x_input, y_input],
                        outputs=[plot_output, plot_message]
                    )
            
            # Project Information Tab
            with gr.TabItem("ℹ️ Project Information", elem_classes="gr-tab"):
                with gr.Column(elem_classes="gr-box"):
                    gr.Markdown(
                        """
                        ### About the Project
                        
                        This portfolio site integrates multiple applications built using Python's powerful
                        Gradio library.
                        
                        #### Features
                        1. **Image Classification App** 🖼️
                           - Upload and analyze images
                           - Display basic image information
                           - Thumbnail generation
                        
                        2. **Text Summary App** 📚
                           - Basic text statistics
                           - Text summarization
                           - Multi-language support
                        
                        3. **Data Visualization Tool** 📈
                           - Interactive graph generation
                           - Beautiful data visualization
                           - Customizable plots
                        
                        #### Tech Stack
                        - Python 3.8+
                        - Gradio 4.0+
                        - Matplotlib 3.7+
                        - NumPy 1.24+
                        - Pillow 10.0+
                        
                        #### Source Code
                        The source code for this project is available on [GitHub](https://github.com/yourusername/portfolio)
                        
                        #### Contact
                        For questions or feedback, please reach out:
                        - Email: your.email@example.com
                        - Twitter: @yourusername
                        - LinkedIn: [Your Name](https://linkedin.com/in/yourprofile)
                        """,
                        elem_classes="gr-tab-text"
                    )

# Launch application
if __name__ == "__main__":
    portfolio.launch(share=True)