"""
Simple AI Text Humanizer using Gradio

A clean text-to-text interface for humanizing AI-generated content.
"""

import gradio as gr
import time
from typing import Optional

from transformer.app import AdvancedAcademicTextHumanizer, download_nltk_resources

# Global humanizer instance
humanizer_instance = None

def initialize_humanizer():
    """Initialize the humanizer model."""
    global humanizer_instance
    if humanizer_instance is None:
        try:
            print("🔄 Downloading NLTK resources...")
            # Download NLTK resources
            download_nltk_resources()
            
            print("🔄 Initializing lightweight models...")
            # Initialize humanizer with lightweight, fast settings
            humanizer_instance = AdvancedAcademicTextHumanizer(
                sentence_model="fast",           # Uses all-MiniLM-L6-v2 (lightweight)
                paraphrase_model="fast",         # Uses t5-small (fast)
                enable_advanced_models=True,
                ai_avoidance_mode=True
            )
            print("✅ All models loaded successfully and ready!")
            return "✅ Models loaded successfully"
        except Exception as e:
            error_msg = f"❌ Error loading models: {str(e)}"
            print(error_msg)
            return error_msg
    return "✅ Models already loaded"

def humanize_text(input_text: str, use_passive: bool, use_synonyms: bool, use_paraphrasing: bool) -> str:
    """Transform AI text to human-like text."""
    if not input_text.strip():
        return "Please enter some text to transform."
    
    global humanizer_instance
    if humanizer_instance is None:
        init_result = initialize_humanizer()
        if "Error" in init_result:
            return init_result
    
    try:
        # Transform the text
        transformed = humanizer_instance.humanize_text(
            input_text,
            use_passive=use_passive,
            use_synonyms=use_synonyms,
            use_paraphrasing=use_paraphrasing
        )
        return transformed
    except Exception as e:
        return f"❌ Error during transformation: {str(e)}"

def create_interface():
    """Create the Gradio interface."""
    
    with gr.Blocks(title="AI Text Humanizer", theme=gr.themes.Soft()) as interface:
        gr.Markdown("# 🤖➡️🧔🏻‍♂️ AI Text Humanizer")
        gr.Markdown("Transform AI-generated text into human-like content using advanced ML models.")
        
        with gr.Row():
            with gr.Column():
                input_text = gr.Textbox(
                    label="Input Text",
                    placeholder="Paste your AI-generated text here...",
                    lines=10,
                    max_lines=20
                )
                
                with gr.Row():
                    use_passive = gr.Checkbox(
                        label="Passive Voice Transformation",
                        value=False,
                        info="Convert active voice to passive"
                    )
                    use_synonyms = gr.Checkbox(
                        label="Synonym Replacement",
                        value=True,
                        info="AI-powered contextual synonyms"
                    )
                    use_paraphrasing = gr.Checkbox(
                        label="Neural Paraphrasing",
                        value=True,
                        info="T5 sentence-level rewriting"
                    )
                
                transform_btn = gr.Button("🚀 Transform Text", variant="primary")
            
            with gr.Column():
                output_text = gr.Textbox(
                    label="Transformed Text",
                    lines=10,
                    max_lines=20,
                    interactive=False
                )
        
        # Initialize models on startup
        gr.Markdown("### Model Status")
        status_text = gr.Textbox(
            label="Initialization Status",
            value="Click 'Transform Text' to load models...",
            interactive=False
        )
        
        # Connect the transformation function
        transform_btn.click(
            fn=humanize_text,
            inputs=[input_text, use_passive, use_synonyms, use_paraphrasing],
            outputs=output_text
        )
        
        # Initialize models when interface loads
        interface.load(
            fn=initialize_humanizer,
            outputs=status_text
        )
        
        gr.Markdown("---")
        gr.Markdown("**Note:** First-time model loading may take a few moments.")
    
    return interface

def main():
    """Launch the Gradio interface."""
    interface = create_interface()
    
    # Launch with Mac-optimized settings
    interface.launch(
        show_api=False,
        share=False,
        debug=False,
        show_error=True
    )

if __name__ == "__main__":
    main()