app.py

import gradio as gr
import time
import requests
import io
from PIL import Image
from huggingface_hub import InferenceClient, HfApi
from deep_translator import GoogleTranslator
from indic_transliteration import sanscript
from indic_transliteration.detect import detect as detect_script
from indic_transliteration.sanscript import transliterate
import langdetect
import re
import os

# Get secrets from Hugging Face Space
HF_TOKEN = os.environ.get('HF_TOKEN')
if not HF_TOKEN:
    raise ValueError("Please set the HF_TOKEN secret in your HuggingFace Space")

# Initialize clients
text_client = InferenceClient(
    "HuggingFaceH4/zephyr-7b-beta",
    token=HF_TOKEN
)

# Image generation setup
API_URL = "https://api-inference.huggingface.co/models/SG161222/RealVisXL_V4.0"
headers = {"Authorization": f"Bearer {HF_TOKEN}"}

def detect_language_script(text: str) -> tuple[str, str]:
    """Detect language and script of the input text.
    Returns (language_code, script_type)"""
    try:
        # Use confidence threshold to avoid false detections
        lang_detect = langdetect.detect_langs(text)
        if lang_detect[0].prob > 0.8:
            # Only accept high confidence detections
            lang = lang_detect[0].lang
        else:
            lang = 'en'  # Default to English if unsure
        
        script = None
        try:
            script = detect_script(text)
        except:
            pass
        return lang, script
    except:
        return 'en', None

def is_romanized_indic(text: str) -> bool:
    """Check if text appears to be romanized Indic language.
    More strict pattern matching."""
    # Common Bengali romanized patterns with word boundaries
    bengali_patterns = [
        r'\b(ami|tumi|apni)\b',  # Common pronouns
        r'\b(ache|achen|thako|thaken)\b',  # Common verbs
        r'\b(kemon|bhalo|kharap)\b',  # Common adjectives
        r'\b(ki|kothay|keno)\b'  # Common question words
    ]
    
    # Require multiple matches to confirm it's actually Bengali
    text_lower = text.lower()
    matches = sum(1 for pattern in bengali_patterns if re.search(pattern, text_lower))
    return matches >= 2  # Require at least 2 matches to consider it Bengali

def translate_text(text: str, target_lang='en') -> tuple[str, str, bool]:
    """Translate text to target language, with more conservative translation logic."""
    # Skip translation for very short inputs or basic greetings
    if len(text.split()) <= 2 or text.lower() in ['hello', 'hi', 'hey']:
        return text, 'en', False
    
    original_lang, script = detect_language_script(text)
    is_transliterated = False
    
    # Only process if confident it's non-English
    if original_lang != 'en' and len(text.split()) > 2:
        try:
            translator = GoogleTranslator(source='auto', target=target_lang)
            translated = translator.translate(text)
            return translated, original_lang, is_transliterated
        except Exception as e:
            print(f"Translation error: {e}")
            return text, 'en', False
    
    # Check for romanized Indic text only if it's a longer input
    if original_lang == 'en' and len(text.split()) > 2 and is_romanized_indic(text):
        text = romanized_to_bengali(text)
        return translate_text(text, target_lang)  # Recursive call with Bengali script
    
    return text, 'en', False

def check_custom_responses(message: str) -> str:
    """Check for specific patterns and return custom responses."""
    message_lower = message.lower()
    custom_responses = {
        "what is ur name?": "xylaria",
        "what is your name?": "xylaria",
        "what's your name?": "xylaria",
        "whats your name": "xylaria",
        "how many 'r' is in strawberry?": "3",
        "who is your developer?": "sk md saad amin",
        "how many r is in strawberry": "3",
        "who is ur dev": "sk md saad amin",
        "who is ur developer": "sk md saad amin",
    }
    for pattern, response in custom_responses.items():
        if pattern in message_lower:
            return response
    return None

def is_image_request(message: str) -> bool:
    """Detect if the message is requesting image generation."""
    image_triggers = [
        "generate an image",
        "create an image",
        "draw",
        "make a picture",
        "generate a picture",
        "create a picture",
        "generate art",
        "create art",
        "make art",
        "visualize",
        "show me",
    ]
    message_lower = message.lower()
    return any(trigger in message_lower for trigger in image_triggers)

def generate_image(prompt):
    """Generate image using HuggingFace inference API"""
    try:
        response = requests.post(API_URL, headers=headers, json={"inputs": prompt})
        image = Image.open(io.BytesIO(response.content))
        return image
    except Exception as e:
        print(f"Image generation error: {e}")
        return None
        
def romanized_to_bengali(text: str) -> str:
    """Convert romanized Bengali text to Bengali script."""
    bengali_mappings = {
        'ami': 'আমি',
        'tumi': 'তুমি',
        'apni': 'আপনি',
        'kemon': 'কেমন',
        'achen': 'আছেন',
        'acchen': 'আছেন',
        'bhalo': 'ভালো',
        'achi': 'আছি',
        'ki': 'কি',
        'kothay': 'কোথায়',
        'keno': 'কেন',
    }
    
    text_lower = text.lower()
    for roman, bengali in bengali_mappings.items():
        text_lower = re.sub(r'\b' + roman + r'\b', bengali, text_lower)
    
    if text_lower == text.lower():
        try:
            return transliterate(text, sanscript.ITRANS, sanscript.BENGALI)
        except:
            return text
            
    return text_lower



def create_chat_interface():
    # Custom CSS for better styling with Inter font and animations
    custom_css = """
    @import url('https://fonts.googleapis.com/css2?family=Inter:wght@400;500;600;700&display=swap');
    
    * {
        font-family: 'Inter', sans-serif !important;
    }
    
    .container {
        max-width: 850px !important;
        margin: auto;
    }
    
    .chat-window {
        height: 600px !important;
        overflow-y: auto;
        border-radius: 15px !important;
        box-shadow: 0 8px 16px rgba(0, 0, 0, 0.1) !important;
        transition: all 0.3s ease !important;
    }
    
    .chat-window:hover {
        box-shadow: 0 12px 20px rgba(0, 0, 0, 0.15) !important;
    }
    
    .chat-message {
        padding: 1rem !important;
        margin: 0.5rem !important;
        border-radius: 12px !important;
        transition: all 0.2s ease !important;
        opacity: 0;
        animation: messageSlide 0.3s ease forwards;
    }
    
    @keyframes messageSlide {
        from {
            opacity: 0;
            transform: translateY(10px);
        }
        to {
            opacity: 1;
            transform: translateY(0);
        }
    }
    
    .user-message {
        background: linear-gradient(135deg, #6366f1 0%, #8b5cf6 100%) !important;
        color: white !important;
        margin-left: 2rem !important;
    }
    
    .bot-message {
        background: linear-gradient(135deg, #f3f4f6 0%, #e5e7eb 100%) !important;
        margin-right: 2rem !important;
    }
    
    /* Button Styles */
    button.primary {
        background: linear-gradient(135deg, #6366f1 0%, #8b5cf6 100%) !important;
        border: none !important;
        color: white !important;
        padding: 0.75rem 1.5rem !important;
        border-radius: 12px !important;
        font-weight: 600 !important;
        transition: all 0.3s ease !important;
        transform: translateY(0);
        box-shadow: 0 4px 6px rgba(99, 102, 241, 0.2) !important;
    }
    
    button.primary:hover {
        transform: translateY(-2px);
        box-shadow: 0 8px 12px rgba(99, 102, 241, 0.3) !important;
    }
    
    button.primary:active {
        transform: translateY(0);
    }
    
    button.secondary {
        background: #f3f4f6 !important;
        border: 2px solid #e5e7eb !important;
        color: #4b5563 !important;
        padding: 0.75rem 1.5rem !important;
        border-radius: 12px !important;
        font-weight: 600 !important;
        transition: all 0.3s ease !important;
    }
    
    button.secondary:hover {
        background: #e5e7eb !important;
        border-color: #d1d5db !important;
    }
    
    /* Input Styles */
    .input-container {
        position: relative;
        margin-bottom: 1rem;
    }
    
    textarea {
        border: 2px solid #e5e7eb !important;
        border-radius: 12px !important;
        padding: 1rem !important;
        transition: all 0.3s ease !important;
        font-size: 1rem !important;
        line-height: 1.5 !important;
        box-shadow: 0 2px 4px rgba(0, 0, 0, 0.05) !important;
    }
    
    textarea:focus {
        border-color: #6366f1 !important;
        box-shadow: 0 4px 6px rgba(99, 102, 241, 0.1) !important;
    }
    
    /* Settings Panel */
    .settings-block {
        background: white !important;
        border-radius: 15px !important;
        padding: 1.5rem !important;
        margin-top: 1rem !important;
        box-shadow: 0 4px 6px rgba(0, 0, 0, 0.05) !important;
        transition: all 0.3s ease !important;
    }
    
    .settings-block:hover {
        box-shadow: 0 6px 8px rgba(0, 0, 0, 0.08) !important;
    }
    
    /* Slider Styles */
    .gr-slider {
        height: 4px !important;
        background: #e5e7eb !important;
        border-radius: 2px !important;
    }
    
    .gr-slider .handle {
        width: 16px !important;
        height: 16px !important;
        border: 2px solid #6366f1 !important;
        background: white !important;
        border-radius: 50% !important;
        box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1) !important;
        transition: all 0.2s ease !important;
    }
    
    .gr-slider .handle:hover {
        transform: scale(1.1);
    }
    
    /* Loading Animation */
    @keyframes pulse {
        0% { opacity: 1; }
        50% { opacity: 0.5; }
        100% { opacity: 1; }
    }
    
    .loading {
        animation: pulse 1.5s ease-in-out infinite;
    }
    """

    # Create the interface with custom theme
    with gr.Blocks(css=custom_css, theme=gr.themes.Soft()) as demo:
        # Header
        with gr.Row():
            gr.HTML("""
                <div style="text-align: center; margin-bottom: 2rem; padding: 2rem;">
                    <h1 style="font-size: 3rem; font-weight: 700; color: #4f46e5; margin-bottom: 0.5rem;">
                        ✨ Xylaria Chat
                    </h1>
                    <p style="color: #6b7280; font-size: 1.2rem; font-weight: 500;">
                        Your Intelligent Multilingual Assistant
                    </p>
                </div>
            """)

        # Main chat interface
        with gr.Row():
            with gr.Column(scale=4):
                chatbot = gr.Chatbot(
                    height=500,
                    show_label=False,
                    container=True,
                    elem_classes=["chat-window"],
                    type='messages'
                )
                
                image_output = gr.Image(
                    type="pil",
                    label="Generated Image",
                    visible=False,
                    elem_classes=["generated-image"]
                )
                
                with gr.Row():
                    with gr.Column(scale=8):
                        txt = gr.Textbox(
                            show_label=False,
                            placeholder="Type your message here...",
                            container=False,
                            elem_classes=["input-textbox"]
                        )
                    with gr.Column(scale=1):
                        send_btn = gr.Button(
                            "Send",
                            variant="primary",
                            elem_classes=["primary"]
                        )
                    with gr.Column(scale=1):
                        clear_btn = gr.Button(
                            "Clear",
                            variant="secondary",
                            elem_classes=["secondary"]
                        )

        # Settings panel
        with gr.Accordion(
            "⚙️ Advanced Settings",
            open=False,
            elem_classes=["settings-accordion"]
        ):
            with gr.Row():
                with gr.Column():
                    system_msg = gr.Textbox(
                        value="You are a friendly Chatbot who always responds in English unless the user specifically uses another language.",
                        label="System Message",
                        lines=2
                    )
                    max_tokens = gr.Slider(
                        minimum=1,
                        maximum=2048,
                        value=512,
                        step=1,
                        label="Max Tokens"
                    )
                with gr.Column():
                    temperature = gr.Slider(
                        minimum=0.1,
                        maximum=4.0,
                        value=0.7,
                        step=0.1,
                        label="Temperature"
                    )
                    top_p = gr.Slider(
                        minimum=0.1,
                        maximum=1.0,
                        value=0.95,
                        step=0.05,
                        label="Top-p (nucleus sampling)"
                    )

        # Rest of your existing functions (user_message, bot_response, etc.)
        # ... (keep the same function implementations)

        # Update the event handlers to use the new classes
        send_event = txt.submit(
            user_message,
            [txt, chatbot],
            [txt, chatbot],
            queue=False
        ).then(
            bot_response,
            [chatbot, system_msg, max_tokens, temperature, top_p],
            [chatbot, image_output]
        )

        send_btn.click(
            user_message,
            [txt, chatbot],
            [txt, chatbot],
            queue=False
        ).then(
            bot_response,
            [chatbot, system_msg, max_tokens, temperature, top_p],
            [chatbot, image_output]
        )

        clear_btn.click(
            lambda: (None, None),
            None,
            [chatbot, image_output],
            queue=False
        )

        # Update image visibility
        send_event.then(
            lambda img: gr.update(visible=img is not None),
            image_output,
            image_output
        )

    return demo

# Create and launch the interface
demo = create_chat_interface()

if __name__ == "__main__":
    demo.launch(share=True)