app.py

import gradio as gr
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
import spaces
import re

# Model configuration
model_name = "HelpingAI/Dhanishtha-2.0-preview"

# Global variables for model and tokenizer
model = None
tokenizer = None

def load_model():
    """Load the model and tokenizer"""
    global model, tokenizer

    print("Loading tokenizer...")
    tokenizer = AutoTokenizer.from_pretrained(model_name)

    # Ensure pad token is set
    if tokenizer.pad_token is None:
        tokenizer.pad_token = tokenizer.eos_token

    print("Loading model...")
    model = AutoModelForCausalLM.from_pretrained(
        model_name,
        torch_dtype="auto",
        device_map="auto",
        trust_remote_code=True
    )

    print("Model loaded successfully!")

def format_thinking_text(text):
    """Format text to properly display <think> and <ser> tags in Gradio with styled borders"""
    if not text:
        return text

    # More sophisticated formatting for thinking and ser blocks
    formatted_text = text

    # Handle thinking blocks with blue styling
    thinking_pattern = r'<think>(.*?)</think>'

    def replace_thinking_block(match):
        thinking_content = match.group(1).strip()
        return f'''

<div style="border-left: 4px solid #4a90e2; background: linear-gradient(135deg, #f0f8ff 0%, #e6f3ff 100%); padding: 16px 20px; margin: 16px 0; border-radius: 12px; font-family: 'Segoe UI', sans-serif; box-shadow: 0 2px 8px rgba(74, 144, 226, 0.15); border: 1px solid rgba(74, 144, 226, 0.2);">
<div style="color: #4a90e2; font-weight: 600; margin-bottom: 10px; display: flex; align-items: center; font-size: 14px;">
<span style="margin-right: 8px;">🧠</span> Think
</div>
<div style="color: #2c3e50; line-height: 1.6; font-size: 14px;">
{thinking_content}
</div>
</div>

'''

    # Handle ser blocks with green styling
    ser_pattern = r'<ser>(.*?)</ser>'

    def replace_ser_block(match):
        ser_content = match.group(1).strip()
        return f'''

<div style="border-left: 4px solid #28a745; background: linear-gradient(135deg, #f0fff4 0%, #e6ffed 100%); padding: 16px 20px; margin: 16px 0; border-radius: 12px; font-family: 'Segoe UI', sans-serif; box-shadow: 0 2px 8px rgba(40, 167, 69, 0.15); border: 1px solid rgba(40, 167, 69, 0.2);">
<div style="color: #28a745; font-weight: 600; margin-bottom: 10px; display: flex; align-items: center; font-size: 14px;">
<span style="margin-right: 8px;">💚</span> Ser
</div>
<div style="color: #155724; line-height: 1.6; font-size: 14px;">
{ser_content}
</div>
</div>

'''

    # Apply both patterns
    formatted_text = re.sub(thinking_pattern, replace_thinking_block, formatted_text, flags=re.DOTALL)
    formatted_text = re.sub(ser_pattern, replace_ser_block, formatted_text, flags=re.DOTALL)

    # Clean up any remaining raw tags
    formatted_text = re.sub(r'</?(?:think|ser)>', '', formatted_text)

    return formatted_text.strip()

@spaces.GPU()
def generate_response(message, history, max_tokens, temperature, top_p):
    """Generate streaming response without threading"""
    global model, tokenizer

    if model is None or tokenizer is None:
        yield "Model is still loading. Please wait..."
        return

    # Prepare conversation history
    messages = []

    # Handle both old tuple format and new message format
    for item in history:
        if isinstance(item, dict):
            # New message format
            messages.append(item)
        elif isinstance(item, (list, tuple)) and len(item) == 2:
            # Old tuple format
            user_msg, assistant_msg = item
            messages.append({"role": "user", "content": user_msg})
            if assistant_msg:
                messages.append({"role": "assistant", "content": assistant_msg})

    # Add current message
    messages.append({"role": "user", "content": message})

    # Apply chat template
    text = tokenizer.apply_chat_template(
        messages,
        tokenize=False,
        add_generation_prompt=True
    )

    # Tokenize input
    model_inputs = tokenizer([text], return_tensors="pt").to(model.device)

    try:
        with torch.no_grad():
            # Use transformers streaming with custom approach
            generated_text = ""
            current_input_ids = model_inputs["input_ids"]
            current_attention_mask = model_inputs["attention_mask"]

            for _ in range(max_tokens):
                # Generate next token
                outputs = model(
                    input_ids=current_input_ids,
                    attention_mask=current_attention_mask,
                    use_cache=True
                )

                # Get logits for the last token
                logits = outputs.logits[0, -1, :]

                # Apply temperature
                if temperature != 1.0:
                    logits = logits / temperature

                # Apply top-p sampling
                if top_p < 1.0:
                    sorted_logits, sorted_indices = torch.sort(logits, descending=True)
                    cumulative_probs = torch.cumsum(torch.softmax(sorted_logits, dim=-1), dim=-1)
                    sorted_indices_to_remove = cumulative_probs > top_p
                    sorted_indices_to_remove[1:] = sorted_indices_to_remove[:-1].clone()
                    sorted_indices_to_remove[0] = 0
                    indices_to_remove = sorted_indices[sorted_indices_to_remove]
                    logits[indices_to_remove] = float('-inf')

                # Sample next token
                probs = torch.softmax(logits, dim=-1)
                next_token = torch.multinomial(probs, num_samples=1)

                # Check for EOS token
                if next_token.item() == tokenizer.eos_token_id:
                    break

                # Decode the new token (preserve special tokens like <think>)
                new_token_text = tokenizer.decode(next_token, skip_special_tokens=False)
                generated_text += new_token_text

                # Format and yield the current text
                formatted_text = format_thinking_text(generated_text)
                yield formatted_text

                # Update inputs for next iteration
                current_input_ids = torch.cat([current_input_ids, next_token.unsqueeze(0)], dim=-1)
                current_attention_mask = torch.cat([current_attention_mask, torch.ones((1, 1), device=model.device)], dim=-1)

    except Exception as e:
        yield f"Error generating response: {str(e)}"
        return

    # Final yield with complete formatted text
    final_text = format_thinking_text(generated_text) if generated_text else "No response generated."
    yield final_text

def chat_interface(message, history, max_tokens, temperature, top_p):
    """Main chat interface with improved streaming"""
    if not message.strip():
        return history, ""

    # Add user message to history in the new message format
    history.append({"role": "user", "content": message})

    # Add placeholder for assistant response
    history.append({"role": "assistant", "content": ""})

    # Generate response with streaming
    for partial_response in generate_response(message, history[:-2], max_tokens, temperature, top_p):
        history[-1]["content"] = partial_response
        yield history, ""

    return history, ""

# Load model on startup
print("Initializing model...")
load_model()

# Advanced CSS for professional UI design
custom_css = """
/* Import Google Fonts */
@import url('https://fonts.googleapis.com/css2?family=Inter:wght@300;400;500;600;700&family=JetBrains+Mono:wght@400;500&display=swap');

/* Global styling */
* {
    font-family: 'Inter', -apple-system, BlinkMacSystemFont, 'Segoe UI', sans-serif;
}

/* Main container */
.gradio-container {
    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
    min-height: 100vh;
}

/* Header styling */
.header-container {
    background: rgba(255, 255, 255, 0.95);
    backdrop-filter: blur(20px);
    border-radius: 20px;
    padding: 24px;
    margin-bottom: 24px;
    box-shadow: 0 8px 32px rgba(0, 0, 0, 0.1);
    border: 1px solid rgba(255, 255, 255, 0.2);
}

/* Main chat container */
.chat-container {
    background: rgba(255, 255, 255, 0.95);
    backdrop-filter: blur(20px);
    border-radius: 20px;
    padding: 24px;
    box-shadow: 0 8px 32px rgba(0, 0, 0, 0.1);
    border: 1px solid rgba(255, 255, 255, 0.2);
}

/* Chatbot styling */
.chatbot {
    font-size: 15px;
    font-family: 'Inter', sans-serif;
    background: transparent;
    border: none;
    border-radius: 16px;
    overflow: hidden;
}

.chatbot .message {
    margin: 12px 0;
    padding: 0;
    background: transparent;
}

.chatbot .message.user {
    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
    color: white;
    border-radius: 18px 18px 4px 18px;
    padding: 16px 20px;
    margin-left: 20%;
    box-shadow: 0 4px 16px rgba(102, 126, 234, 0.3);
}

.chatbot .message.bot {
    background: linear-gradient(135deg, #f8f9fa 0%, #ffffff 100%);
    color: #2c3e50;
    border-radius: 18px 18px 18px 4px;
    padding: 16px 20px;
    margin-right: 20%;
    box-shadow: 0 4px 16px rgba(0, 0, 0, 0.05);
    border: 1px solid rgba(0, 0, 0, 0.05);
}

/* Input styling */
.input-container {
    background: rgba(255, 255, 255, 0.9);
    border-radius: 25px;
    padding: 8px;
    box-shadow: 0 4px 20px rgba(0, 0, 0, 0.1);
    border: 2px solid transparent;
    transition: all 0.3s ease;
}

.input-container:focus-within {
    border-color: #667eea;
    box-shadow: 0 4px 20px rgba(102, 126, 234, 0.2);
}

.gradio-textbox {
    border: none !important;
    background: transparent !important;
    font-size: 15px;
    padding: 12px 20px;
    border-radius: 20px;
    font-family: 'Inter', sans-serif;
}

.gradio-textbox:focus {
    outline: none !important;
    box-shadow: none !important;
}

/* Button styling */
.gradio-button {
    border-radius: 20px !important;
    font-weight: 600 !important;
    font-family: 'Inter', sans-serif !important;
    transition: all 0.3s ease !important;
    border: none !important;
    font-size: 14px !important;
    padding: 12px 24px !important;
}

.gradio-button.primary {
    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%) !important;
    color: white !important;
    box-shadow: 0 4px 16px rgba(102, 126, 234, 0.3) !important;
}

.gradio-button.primary:hover {
    transform: translateY(-2px) !important;
    box-shadow: 0 6px 20px rgba(102, 126, 234, 0.4) !important;
}

.gradio-button.secondary {
    background: linear-gradient(135deg, #f8f9fa 0%, #e9ecef 100%) !important;
    color: #495057 !important;
    box-shadow: 0 2px 8px rgba(0, 0, 0, 0.1) !important;
}

.gradio-button.secondary:hover {
    transform: translateY(-1px) !important;
    box-shadow: 0 4px 12px rgba(0, 0, 0, 0.15) !important;
}

/* Parameter panel styling */
.parameter-panel {
    background: rgba(255, 255, 255, 0.9);
    backdrop-filter: blur(20px);
    border-radius: 20px;
    padding: 24px;
    box-shadow: 0 8px 32px rgba(0, 0, 0, 0.1);
    border: 1px solid rgba(255, 255, 255, 0.2);
}

/* Slider styling */
.gradio-slider {
    margin: 16px 0 !important;
}

.gradio-slider .wrap {
    background: linear-gradient(135deg, #f8f9fa 0%, #ffffff 100%);
    border-radius: 12px;
    padding: 16px;
    border: 1px solid rgba(0, 0, 0, 0.05);
}

/* Examples styling */
.gradio-examples {
    margin-top: 20px;
}

.gradio-examples .gradio-button {
    background: rgba(255, 255, 255, 0.8) !important;
    border: 1px solid rgba(102, 126, 234, 0.2) !important;
    color: #667eea !important;
    font-size: 13px !important;
    padding: 10px 16px !important;
    margin: 4px !important;
    border-radius: 15px !important;
    transition: all 0.2s ease !important;
}

.gradio-examples .gradio-button:hover {
    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%) !important;
    color: white !important;
    transform: translateY(-1px) !important;
    box-shadow: 0 4px 12px rgba(102, 126, 234, 0.3) !important;
}

/* Footer styling */
.footer-container {
    background: rgba(255, 255, 255, 0.9);
    backdrop-filter: blur(20px);
    border-radius: 20px;
    padding: 20px;
    margin-top: 24px;
    box-shadow: 0 8px 32px rgba(0, 0, 0, 0.1);
    border: 1px solid rgba(255, 255, 255, 0.2);
    text-align: center;
}

/* Animations */
@keyframes fadeInUp {
    from {
        opacity: 0;
        transform: translateY(30px);
    }
    to {
        opacity: 1;
        transform: translateY(0);
    }
}

@keyframes pulse {
    0%, 100% {
        opacity: 1;
    }
    50% {
        opacity: 0.5;
    }
}

@keyframes slideIn {
    from {
        opacity: 0;
        transform: translateX(-20px);
    }
    to {
        opacity: 1;
        transform: translateX(0);
    }
}

.animate-fade-in {
    animation: fadeInUp 0.6s ease-out;
}

.animate-slide-in {
    animation: slideIn 0.4s ease-out;
}

/* Loading states */
.loading {
    position: relative;
    overflow: hidden;
}

.loading::after {
    content: '';
    position: absolute;
    top: 0;
    left: -100%;
    width: 100%;
    height: 100%;
    background: linear-gradient(90deg, transparent, rgba(255,255,255,0.4), transparent);
    animation: shimmer 1.5s infinite;
}

@keyframes shimmer {
    0% { left: -100%; }
    100% { left: 100%; }
}

/* Responsive design */
@media (max-width: 768px) {
    .chat-container, .parameter-panel, .header-container {
        margin: 12px;
        padding: 16px;
        border-radius: 16px;
    }

    .chatbot .message.user {
        margin-left: 10%;
    }

    .chatbot .message.bot {
        margin-right: 10%;
    }
}

/* Dark mode support */
@media (prefers-color-scheme: dark) {
    .gradio-container {
        background: linear-gradient(135deg, #2d3748 0%, #4a5568 100%);
    }

    .chat-container, .parameter-panel, .header-container, .footer-container {
        background: rgba(45, 55, 72, 0.95);
        color: #e2e8f0;
    }

    .chatbot .message.bot {
        background: linear-gradient(135deg, #4a5568 0%, #2d3748 100%);
        color: #e2e8f0;
    }
}
"""

# Create advanced Gradio interface with professional design
with gr.Blocks(
    title="� Dhanishtha-2.0-preview | Advanced Reasoning AI",
    theme=gr.themes.Soft(),
    css=custom_css,
    head="""
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <meta name="description" content="Chat with Dhanishtha-2.0-preview - The world's first LLM with multi-step reasoning capabilities">
    """
) as demo:
    # Header Section
    with gr.Row():
        with gr.Column():
            gr.HTML("""
                <div style="text-align: center; padding: 20px 0;">
                    <h1 style="font-size: 3em; font-weight: 700; background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); -webkit-background-clip: text; -webkit-text-fill-color: transparent; margin: 0; font-family: 'Inter', sans-serif;">
                        🧠 Dhanishtha-2.0-preview
                    </h1>
                    <p style="font-size: 1.2em; color: #6c757d; margin: 10px 0 0 0; font-weight: 400;">
                        Advanced Reasoning AI with Multi-Step Thinking
                    </p>
                </div>
            """)

            # Feature highlights
            with gr.Row():
                with gr.Column(scale=1):
                    gr.HTML("""
                        <div style="text-align: center; padding: 15px; background: linear-gradient(135deg, #f0f8ff 0%, #e6f3ff 100%); border-radius: 15px; border-left: 4px solid #4a90e2;">
                            <div style="font-size: 2em; margin-bottom: 8px;">🧠</div>
                            <div style="font-weight: 600; color: #4a90e2;">Think Blocks</div>
                            <div style="font-size: 0.9em; color: #6c757d;">Internal reasoning process</div>
                        </div>
                    """)
                with gr.Column(scale=1):
                    gr.HTML("""
                        <div style="text-align: center; padding: 15px; background: linear-gradient(135deg, #f0fff4 0%, #e6ffed 100%); border-radius: 15px; border-left: 4px solid #28a745;">
                            <div style="font-size: 2em; margin-bottom: 8px;">💚</div>
                            <div style="font-weight: 600; color: #28a745;">Ser Blocks</div>
                            <div style="font-size: 0.9em; color: #6c757d;">Emotional understanding</div>
                        </div>
                    """)
                with gr.Column(scale=1):
                    gr.HTML("""
                        <div style="text-align: center; padding: 15px; background: linear-gradient(135deg, #fff5f5 0%, #fed7d7 100%); border-radius: 15px; border-left: 4px solid #e53e3e;">
                            <div style="font-size: 2em; margin-bottom: 8px;">⚡</div>
                            <div style="font-weight: 600; color: #e53e3e;">Real-time</div>
                            <div style="font-size: 0.9em; color: #6c757d;">Streaming responses</div>
                        </div>
                    """)
                with gr.Column(scale=1):
                    gr.HTML("""
                        <div style="text-align: center; padding: 15px; background: linear-gradient(135deg, #fefcbf 0%, #fef08a 100%); border-radius: 15px; border-left: 4px solid #f59e0b;">
                            <div style="font-size: 2em; margin-bottom: 8px;">🎯</div>
                            <div style="font-weight: 600; color: #f59e0b;">Precise</div>
                            <div style="font-size: 0.9em; color: #6c757d;">Step-by-step solutions</div>
                        </div>
                    """)

    # Main Chat Interface
    with gr.Row():
        with gr.Column(scale=4):
            # Status indicator
            gr.HTML("""
                <div style="display: flex; align-items: center; justify-content: space-between; margin-bottom: 16px; padding: 12px 20px; background: linear-gradient(135deg, #e8f5e8 0%, #f0fff4 100%); border-radius: 12px; border-left: 4px solid #28a745;">
                    <div style="display: flex; align-items: center;">
                        <div style="width: 8px; height: 8px; background: #28a745; border-radius: 50%; margin-right: 8px; animation: pulse 2s infinite;"></div>
                        <span style="font-weight: 600; color: #28a745;">Model Ready</span>
                    </div>
                    <div style="font-size: 0.9em; color: #6c757d;">
                        HelpingAI/Dhanishtha-2.0-preview
                    </div>
                </div>
            """)

            chatbot = gr.Chatbot(
                [],
                elem_id="chatbot",
                type='messages',
                height=650,
                show_copy_button=True,
                show_share_button=True,
                avatar_images=("👤", "🤖"),
                render_markdown=True,
                sanitize_html=False,  # Allow HTML for thinking and ser blocks
                latex_delimiters=[
                    {"left": "$$", "right": "$$", "display": True},
                    {"left": "$", "right": "$", "display": False}
                ],
                container=True,
                scale=1
            )

            # Enhanced input section
            with gr.Row():
                with gr.Column(scale=1):
                    msg = gr.Textbox(
                        container=False,
                        placeholder="💭 Ask me anything! I'll show you my thinking and reasoning process...",
                        label="",
                        autofocus=True,
                        lines=1,
                        max_lines=4
                    )
                with gr.Column(scale=0, min_width=120):
                    with gr.Row():
                        send_btn = gr.Button(
                            "🚀 Send",
                            variant="primary",
                            size="lg"
                        )
                        clear_btn = gr.Button(
                            "🗑️",
                            variant="secondary",
                            size="lg"
                        )

        with gr.Column(scale=1, min_width=320):
            # Parameter header
            gr.HTML("""
                <div style="text-align: center; margin-bottom: 20px;">
                    <h3 style="margin: 0; color: #4a5568; font-weight: 600;">⚙️ Generation Settings</h3>
                    <p style="margin: 5px 0 0 0; color: #6c757d; font-size: 0.9em;">Fine-tune the AI's responses</p>
                </div>
            """)

            # Enhanced sliders with better styling
            max_tokens = gr.Slider(
                minimum=50,
                maximum=8192,
                value=2048,
                step=50,
                label="🎯 Max Tokens",
                info="Maximum number of tokens to generate"
            )

            temperature = gr.Slider(
                minimum=0.1,
                maximum=2.0,
                value=0.7,
                step=0.1,
                label="🌡️ Temperature",
                info="Higher = more creative, Lower = more focused"
            )

            top_p = gr.Slider(
                minimum=0.1,
                maximum=1.0,
                value=0.9,
                step=0.05,
                label="🎲 Top-p",
                info="Nucleus sampling threshold"
            )

            # Action buttons
            with gr.Row():
                stop_btn = gr.Button(
                    "⏹️ Stop",
                    variant="stop",
                    scale=1
                )

            # Model information card
            gr.HTML("""
                <div style="margin-top: 24px; padding: 20px; background: linear-gradient(135deg, #f8f9fa 0%, #ffffff 100%); border-radius: 16px; border: 1px solid rgba(0,0,0,0.05);">
                    <h4 style="margin: 0 0 12px 0; color: #4a5568; font-weight: 600; display: flex; align-items: center;">
                        <span style="margin-right: 8px;">🧠</span> Model Information
                    </h4>
                    <div style="space-y: 8px;">
                        <div style="display: flex; justify-content: space-between; margin-bottom: 8px;">
                            <span style="color: #6c757d; font-size: 0.9em;">Model:</span>
                            <span style="color: #4a5568; font-weight: 500; font-size: 0.9em;">Dhanishtha-2.0-preview</span>
                        </div>
                        <div style="display: flex; justify-content: space-between; margin-bottom: 8px;">
                            <span style="color: #6c757d; font-size: 0.9em;">Type:</span>
                            <span style="color: #4a5568; font-weight: 500; font-size: 0.9em;">Reasoning LLM</span>
                        </div>
                        <div style="display: flex; justify-content: space-between; margin-bottom: 8px;">
                            <span style="color: #6c757d; font-size: 0.9em;">Features:</span>
                            <span style="color: #4a5568; font-weight: 500; font-size: 0.9em;">Think + Ser blocks</span>
                        </div>
                        <div style="margin-top: 12px; padding: 8px; background: rgba(74, 144, 226, 0.1); border-radius: 8px; border-left: 3px solid #4a90e2;">
                            <div style="font-size: 0.85em; color: #4a90e2; font-weight: 500;">💡 Tip</div>
                            <div style="font-size: 0.8em; color: #6c757d; margin-top: 4px;">Ask complex questions to see multi-step reasoning in action!</div>
                        </div>
                    </div>
                </div>
            """)
    
    # Enhanced Examples Section
    with gr.Row():
        with gr.Column():
            gr.HTML("""
                <div style="text-align: center; margin: 24px 0 16px 0;">
                    <h3 style="margin: 0; color: #4a5568; font-weight: 600;">💡 Try These Examples</h3>
                    <p style="margin: 5px 0 0 0; color: #6c757d; font-size: 0.9em;">Click any example to see the AI's thinking process</p>
                </div>
            """)

            gr.Examples(
                examples=[
                    ["🧮 Solve this step by step: What is 15% of 240?"],
                    ["🔤 How many letter 'r' are in the words 'strawberry' and 'raspberry'?"],
                    ["🤖 Hello! Can you introduce yourself and show me how you think?"],
                    ["⚛️ Explain quantum entanglement in simple terms with examples"],
                    ["🐍 Write a Python function to find the factorial of a number"],
                    ["🌱 What are the pros and cons of renewable energy sources?"],
                    ["🧠 What's the difference between AI and machine learning?"],
                    ["🎨 Create a haiku about artificial intelligence and consciousness"],
                    ["🌌 Why is the sky blue? Explain using physics principles"],
                    ["📊 Compare bubble sort and quick sort algorithms"],
                    ["🎯 Plan a 7-day trip to Japan with budget considerations"],
                    ["🔬 How does CRISPR gene editing work in simple terms?"]
                ],
                inputs=msg,
                examples_per_page=6
            )

    # Event handlers
    def clear_chat():
        """Clear the chat history"""
        return [], ""

    # Message submission events
    msg.submit(
        chat_interface,
        inputs=[msg, chatbot, max_tokens, temperature, top_p],
        outputs=[chatbot, msg],
        concurrency_limit=1,
        show_progress="minimal"
    )

    send_btn.click(
        chat_interface,
        inputs=[msg, chatbot, max_tokens, temperature, top_p],
        outputs=[chatbot, msg],
        concurrency_limit=1,
        show_progress="minimal"
    )

    # Clear chat event
    clear_btn.click(
        clear_chat,
        outputs=[chatbot, msg],
        show_progress=False
    )

    # Enhanced Footer
    with gr.Row():
        with gr.Column():
            gr.HTML("""
                <div style="text-align: center; padding: 20px 0;">
                    <div style="display: flex; justify-content: center; align-items: center; margin-bottom: 16px;">
                        <div style="height: 1px; background: linear-gradient(90deg, transparent, #667eea, transparent); flex: 1;"></div>
                        <span style="margin: 0 20px; color: #6c757d; font-weight: 500;">Technical Specifications</span>
                        <div style="height: 1px; background: linear-gradient(90deg, transparent, #667eea, transparent); flex: 1;"></div>
                    </div>

                    <div style="display: grid; grid-template-columns: repeat(auto-fit, minmax(200px, 1fr)); gap: 20px; margin-bottom: 20px;">
                        <div style="text-align: center;">
                            <div style="font-size: 1.5em; margin-bottom: 8px;">🧠</div>
                            <div style="font-weight: 600; color: #4a5568;">Model Architecture</div>
                            <div style="font-size: 0.9em; color: #6c757d;">Transformer-based reasoning</div>
                        </div>
                        <div style="text-align: center;">
                            <div style="font-size: 1.5em; margin-bottom: 8px;">⚡</div>
                            <div style="font-weight: 600; color: #4a5568;">Real-time Streaming</div>
                            <div style="font-size: 0.9em; color: #6c757d;">Token-by-token generation</div>
                        </div>
                        <div style="text-align: center;">
                            <div style="font-size: 1.5em; margin-bottom: 8px;">🎯</div>
                            <div style="font-weight: 600; color: #4a5568;">Advanced Reasoning</div>
                            <div style="font-size: 0.9em; color: #6c757d;">Multi-step thinking process</div>
                        </div>
                        <div style="text-align: center;">
                            <div style="font-size: 1.5em; margin-bottom: 8px;">🔧</div>
                            <div style="font-weight: 600; color: #4a5568;">Custom Sampling</div>
                            <div style="font-size: 0.9em; color: #6c757d;">Temperature & Top-p control</div>
                        </div>
                    </div>

                    <div style="background: linear-gradient(135deg, #f8f9fa 0%, #ffffff 100%); border-radius: 12px; padding: 16px; margin: 16px 0; border: 1px solid rgba(0,0,0,0.05);">
                        <div style="font-weight: 600; color: #4a5568; margin-bottom: 8px;">🌟 Key Features</div>
                        <div style="display: flex; flex-wrap: wrap; gap: 8px; justify-content: center;">
                            <span style="background: #e3f2fd; color: #1976d2; padding: 4px 12px; border-radius: 20px; font-size: 0.85em;">Think Blocks</span>
                            <span style="background: #e8f5e8; color: #2e7d32; padding: 4px 12px; border-radius: 20px; font-size: 0.85em;">Ser Blocks</span>
                            <span style="background: #fff3e0; color: #f57c00; padding: 4px 12px; border-radius: 20px; font-size: 0.85em;">Real-time Streaming</span>
                            <span style="background: #fce4ec; color: #c2185b; padding: 4px 12px; border-radius: 20px; font-size: 0.85em;">LaTeX Support</span>
                            <span style="background: #f3e5f5; color: #7b1fa2; padding: 4px 12px; border-radius: 20px; font-size: 0.85em;">Code Highlighting</span>
                        </div>
                    </div>

                    <div style="margin-top: 20px; padding-top: 16px; border-top: 1px solid rgba(0,0,0,0.1);">
                        <div style="color: #6c757d; font-size: 0.9em;">
                            Built with ❤️ using <strong>Gradio</strong> and <strong>Transformers</strong> |
                            Model: <strong>HelpingAI/Dhanishtha-2.0-preview</strong>
                        </div>
                        <div style="color: #6c757d; font-size: 0.8em; margin-top: 4px;">
                            Experience the future of AI reasoning with transparent thinking processes
                        </div>
                    </div>
                </div>
            """)

if __name__ == "__main__":
    # Launch with enhanced configuration
    demo.queue(
        max_size=20,
        default_concurrency_limit=1
    ).launch(
        server_name="0.0.0.0",
        server_port=7860,
        share=False,
        show_error=True,
        quiet=False,
        favicon_path=None,
        ssl_verify=False,
        show_tips=True,
        enable_queue=True
    )