app.py

import gradio as gr
from transformers import pipeline
from gtts import gTTS
import time
import os

# Load models
sentiment_pipeline = pipeline("sentiment-analysis", model="distilbert-base-uncased-finetuned-sst-2-english")
summarization_pipeline = pipeline("summarization", model="facebook/bart-large-cnn")

# Task logic with enhanced feedback
def perform_task(task, text):
    if not text.strip():
        return "⚠️ Please enter some text to analyze.", None, gr.update(visible=False)

    # Simulate processing time for better UX
    time.sleep(0.5)

    if task == "Sentiment Analysis":
        result = sentiment_pipeline(text)[0]
        label = result['label']
        score = round(result['score'], 3)

        # Enhanced sentiment display with emojis
        emoji = "😊" if label == "POSITIVE" else "😟"
        confidence_bar = "█" * int(score * 10) + "░" * (10 - int(score * 10))

        output = f"""
{emoji} **Sentiment Analysis Results**

**Label:** {label}
**Confidence:** {score} ({score*100:.1f}%)
**Visual:** {confidence_bar}

**Interpretation:** This text expresses a {label.lower()} sentiment with {score*100:.1f}% confidence.
        """.strip()

        return output, None, gr.update(visible=False)

    elif task == "Summarization":
        result = summarization_pipeline(text, max_length=100, min_length=30, do_sample=False)
        summary = result[0]['summary_text']

        # Calculate compression ratio
        original_words = len(text.split())
        summary_words = len(summary.split())
        compression_ratio = round((1 - summary_words/original_words) * 100, 1)

        output = f"""
📝 **Text Summarization Results**

**Summary:**
{summary}

**Statistics:**
• Original: {original_words} words
• Summary: {summary_words} words
• Compression: {compression_ratio}% reduction
        """.strip()

        return output, None, gr.update(visible=False)

    elif task == "Text-to-Speech":
        tts = gTTS(text)
        filename = "tts_output.mp3"
        tts.save(filename)

        word_count = len(text.split())
        char_count = len(text)

        output = f"""
🔊 **Text-to-Speech Generated Successfully!**

**Input Statistics:**
• Words: {word_count}
• Characters: {char_count}
• Estimated duration: ~{word_count * 0.5:.1f} seconds

**Audio file ready for playback below** ⬇️
        """.strip()

        return output, filename, gr.update(visible=True, value=filename)

# Enhanced CSS with modern design elements
custom_css = """
<style>
    @import url('https://fonts.googleapis.com/css2?family=Inter:wght@300;400;500;600;700&display=swap');

    :root {
        --primary-bg: #0a0a0a;
        --secondary-bg: #1a1a1a;
        --accent-bg: #2a2a2a;
        --primary-text: #ffffff;
        --secondary-text: #b0b0b0;
        --accent-color: #3b82f6;
        --accent-hover: #2563eb;
        --success-color: #10b981;
        --warning-color: #f59e0b;
        --border-color: #333333;
        --gradient-1: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
        --gradient-2: linear-gradient(135deg, #f093fb 0%, #f5576c 100%);
        --gradient-3: linear-gradient(135deg, #4facfe 0%, #00f2fe 100%);
    }

    * {
        font-family: 'Inter', -apple-system, BlinkMacSystemFont, 'Segoe UI', sans-serif !important;
    }

    body, .gradio-container {
        background: var(--primary-bg) !important;
        color: var(--primary-text) !important;
        background-image:
            radial-gradient(circle at 20% 50%, rgba(59, 130, 246, 0.1) 0%, transparent 50%),
            radial-gradient(circle at 80% 20%, rgba(168, 85, 247, 0.1) 0%, transparent 50%),
            radial_gradient(circle at 40% 80%, rgba(16, 185, 129, 0.1) 0%, transparent 50%);
        min-height: 100vh;
    }

    .gradio-container {
        max-width: 1200px !important;
        margin: 0 auto !important;
        padding: 2rem !important;
    }

    /* Header styling */
    #title {
        background: var(--gradient-1);
        background-clip: text;
        -webkit-background-clip: text;
        -webkit-text-fill-color: transparent;
        font-size: 3rem !important;
        font-weight: 700 !important;
        text-align: center !important;
        margin-bottom: 2rem !important;
        animation: glow 2s ease-in-out infinite alternate;
    }

    @keyframes glow {
        from { filter: drop-shadow(0 0 20px rgba(59, 130, 246, 0.3)); }
        to { filter: drop_shadow(0 0 30px rgba(168, 85, 247, 0.5)); }
    }

    /* Card-like containers */
    .gr-box, .gr-form {
        background: var(--secondary-bg) !important;
        border: 1px solid var(--border-color) !important;
        border-radius: 16px !important;
        padding: 1.5rem !important;
        backdrop-filter: blur(10px) !important;
        box-shadow: 0 8px 32px rgba(0, 0, 0, 0.3) !important;
        transition: all 0.3s ease !important;
    }

    .gr-box:hover, .gr-form:hover {
        border-color: var(--accent-color) !important;
        box-shadow: 0 12px 40px rgba(59, 130, 246, 0.2) !important;
        transform: translateY(-2px) !important;
    }

    /* Input fields */
    .gr-input, .gr-textbox, .gr-dropdown {
        background: var(--accent-bg) !important;
        color: var(--primary-text) !important;
        border: 2px solid var(--border-color) !important;
        border-radius: 12px !important;
        padding: 1rem !important;
        font-size: 1rem !important;
        transition: all 0.3s ease !important;
    }

    .gr-input:focus, .gr-textbox:focus, .gr-dropdown:focus {
        border-color: var(--accent-color) !important;
        box-shadow: 0 0 0 3px rgba(59, 130, 246, 0.1) !important;
        outline: none !important;
    }

    /* Buttons */
    .gr-button {
        background: var(--gradient-1) !important;
        color: white !important;
        border: none !important;
        border-radius: 12px !important;
        padding: 1rem 2rem !important;
        font-size: 1.1rem !important;
        font-weight: 600 !important;
        cursor: pointer !important;
        transition: all 0.3s ease !important;
        box-shadow: 0 4px 20px rgba(59, 130, 246, 0.3) !important;
    }

    .gr-button:hover {
        transform: translateY(-2px) !important;
        box-shadow: 0 8px 30px rgba(59, 130, 246, 0.4) !important;
    }

    .gr-button:active {
        transform: translateY(0) !important;
    }

    /* Labels */
    label {
        color: var(--primary-text) !important;
        font-weight: 500 !important;
        font-size: 1.1rem !important;
        margin-bottom: 0.5rem !important;
    }

    /* Placeholders */
    input::placeholder, textarea::placeholder {
        color: var(--secondary-text) !important;
        opacity: 0.7 !important;
    }

    /* Output areas */
    .gr-textbox[data-testid="textbox"] {
        background: var(--accent-bg) !important;
        border: 1px solid var(--border-color) !important;
        border-radius: 12px !important;
        padding: 1.5rem !important;
        font-family: 'Inter', monospace !important;
        line-height: 1.6 !important;
    }

    /* Audio component */
    .gr-audio {
        background: var(--secondary-bg) !important;
        border: 1px solid var(--border-color) !important;
        border-radius: 12px !important;
        padding: 1rem !important;
    }

    /* Markdown content */
    .markdown-content {
        line-height: 1.8 !important;
    }

    .markdown-content strong {
        color: var(--accent-color) !important;
    }

    /* Task selector special styling */
    .gr-dropdown {
        background: var(--gradient-2) !important;
        color: white !important;
        font-weight: 500 !important;
    }

    /* Responsive design */
    @media (max-width: 768px) {
        #title {
            font-size: 2rem !important;
        }

        .gradio-container {
            padding: 1rem !important;
        }

        .gr-box, .gr-form {
            padding: 1rem !important;
        }
    }

    /* Loading animation */
    @keyframes pulse {
        0%, 100% { opacity: 1; }
        50% { opacity: 0.5; }
    }

    .loading {
        animation: pulse 1.5s infinite;
    }

    /* Success/Error states */
    .success {
        border-color: var(--success-color) !important;
        box-shadow: 0 0 20px rgba(16, 185, 129, 0.2) !important;
    }

    .warning {
        border-color: var(--warning-color) !important;
        box-shadow: 0 0 20px rgba(245, 158, 11, 0.2) !important;
    }
</style>
"""

# UI with enhanced design
with gr.Blocks(theme=gr.themes.Soft(), css=custom_css) as demo:
    gr.HTML(custom_css)

    # Header with enhanced styling
    gr.Markdown("# 🤖 Multi-Task AI Assistant", elem_id="title")
    gr.Markdown("""
    <div style="text-align: center; margin-bottom: 2rem; color: #b0b0b0; font-size: 1.2rem;">
        Harness the power of AI for <strong>sentiment analysis</strong>, <strong>text summarization</strong>, and <strong>text-to-speech</strong> conversion
    </div>
    """)

    # Main interface
    with gr.Row():
        with gr.Column(scale=1, min_width=250):
            task_selector = gr.Dropdown(
                choices=["Sentiment Analysis", "Summarization", "Text-to-Speech"],
                label="🔧 Select AI Task",
                value="Sentiment Analysis",
                info="Choose the AI capability you want to use"
            )

            # Task descriptions
            gr.Markdown("""
            **📊 Sentiment Analysis**: Analyze emotional tone and polarity of text

            **✂️ Summarization**: Generate concise summaries of long text

            **🔊 Text-to-Speech**: Convert text into natural-sounding audio
            """, elem_classes=["task-info"])

        with gr.Column(scale=2):
            textbox = gr.Textbox(
                lines=8,
                label="📝 Input Text",
                placeholder="Enter your text here... \n\nTip: For best results:\n• Sentiment: Use complete sentences\n• Summary: Provide longer text (100+ words)\n• TTS: Use natural, conversational text",
                info="Type or paste the text you want to process"
            )

    # Action button
    with gr.Row():
        run_button = gr.Button("🚀 Process with AI", size="lg", variant="primary")

    # Results section
    gr.Markdown("## 📋 Results", elem_classes=["results-header"])

    with gr.Row():
        with gr.Column(scale=2):
            output_text = gr.Textbox(
                label="📊 Analysis Results",
                lines=8,
                info="Detailed results and insights will appear here",
                interactive=False
            )

        with gr.Column(scale=1):
            output_audio = gr.Audio(
                label="🔊 Generated Audio",
                type="filepath",
                visible=False,
            )

    # Enhanced event handler
    def handle_task_processing(task, text):
        if not text.strip():
            return "⚠️ Please enter some text to get started!", None, gr.update(visible=False)

        # Show processing message
        processing_msg = f"🔄 Processing your {task.lower()} request..."

        # Process the task
        result_text, audio_file, audio_update = perform_task(task, text)

        return result_text, audio_file, audio_update

    # Event binding
    run_button.click(
        fn=handle_task_processing,
        inputs=[task_selector, textbox],
        outputs=[output_text, output_audio, output_audio]
    )

    # Footer
    gr.Markdown("""
    <div style="text-align: center; margin-top: 3rem; padding: 2rem; color: #666; border-top: 1px solid #333;">
        <p>✨ <strong>Multi-Task AI Assistant</strong> - Powered by Transformers & Gradio</p>
        <p>Built with ❤️ for seamless AI interaction</p>
    </div>
    """)

# Launch with enhanced settings
if __name__ == "__main__":
    demo.launch(
        # Removing server_name and server_port to let Gradio handle networking
        share=True, # share=True is often necessary in Colab environments
        debug=True,
        show_error=True,
        favicon_path=None,
        app_kwargs={"docs_url": "/docs"}
    )