import streamlit as st
import nltk
import os
from enhanced_text_humanizer import EnhancedTextHumanizer
import time
# Set NLTK data path
nltk.data.path.append('./nltk_data')

# Download required NLTK resources at startup
@st.cache_resource
def download_nltk_resources():
    try:
        # Create NLTK data directory if it doesn't exist
        os.makedirs('nltk_data', exist_ok=True)
        
        # Download required resources
        nltk.download('punkt', download_dir='./nltk_data')
        nltk.download('punkt_tab', download_dir='./nltk_data')
        nltk.download('averaged_perceptron_tagger', download_dir='./nltk_data')
        nltk.download('wordnet', download_dir='./nltk_data')
        nltk.download('omw-1.4', download_dir='./nltk_data')
        
        return True
    except Exception as e:
        st.error(f"Error downloading NLTK resources: {e}")
        return False

def initialize_humanizer():
    # First ensure NLTK resources are downloaded
    resources_downloaded = download_nltk_resources()
    
    with st.spinner('Loading language models... This may take a moment.'):
        humanizer = EnhancedTextHumanizer()
    return humanizer




def main():
    st.set_page_config(
        page_title="Text Humanizer App",
        page_icon="🤖",
        layout="wide"
    )

    st.title("🤖 Enhanced Text Humanizer")
    st.markdown("""
    Transform formal text into more natural, human-like language with various personality styles and regional dialects.
    """)

    # Initialize the humanizer
    if 'humanizer' not in st.session_state:
        st.session_state.humanizer = initialize_humanizer()

    # Create two columns for input and output
    col1, col2 = st.columns(2)

    with col1:
        st.subheader("Input Text")
        input_text = st.text_area(
            "Enter your text here:",
            height=200,
            placeholder="Type or paste your text here..."
        )

        st.subheader("Customization Options")
        
        # Personality selection
        personality = st.selectbox(
            "Select Personality Style:",
            ['casual', 'formal', 'academic', 'enthusiastic'],
            help="Choose the personality style for the output text"
        )

        # Regional dialect selection
        dialect = st.selectbox(
            "Select Regional Dialect:",
            [None, 'us_south', 'british'],
            help="Choose a regional dialect (optional)"
        )

        # Emotional tone selection
        emotional_tone = st.selectbox(
            "Select Emotional Tone:",
            [None, 'positive', 'negative', 'neutral'],
            help="Choose the emotional tone (optional)"
        )

        # Transformation intensity
        intensity = st.slider(
            "Transformation Intensity:",
            min_value=0.0,
            max_value=1.0,
            value=0.7,
            step=0.1,
            help="Control how much the text is transformed"
        )

        # Error inclusion
        add_errors = st.checkbox(
            "Include Natural Speech Errors",
            value=True,
            help="Add realistic speech/typing errors"
        )

    with col2:
        st.subheader("Output Text")
        if st.button("Transform Text", type="primary"):
            if input_text.strip():
                try:
                    with st.spinner('Transforming text...'):
                        humanized_text = st.session_state.humanizer.humanize_text(
                            input_text,
                            intensity=intensity,
                            personality=personality,
                            add_errors=add_errors,
                            regional_dialect=dialect,
                            emotional_tone=emotional_tone
                        )
                        st.text_area(
                            "Transformed Text:",
                            value=humanized_text,
                            height=400,
                            disabled=True
                        )
                        
                        # Show transformation details
                        st.success("Text transformation complete!")
                        st.markdown("### Transformation Details")
                        st.markdown(f"""
                        - **Personality**: {personality}
                        - **Dialect**: {dialect if dialect else 'None'}
                        - **Emotional Tone**: {emotional_tone if emotional_tone else 'Auto-detected'}
                        - **Intensity**: {intensity}
                        - **Speech Errors**: {'Enabled' if add_errors else 'Disabled'}
                        """)
                except Exception as e:
                    st.error(f"An error occurred: {str(e)}")
            else:
                st.warning("Please enter some text to transform.")

    # Add footer with information
    st.markdown("---")
    st.markdown("""
    ### About This Tool
    This text humanizer uses advanced NLP techniques to transform formal text into more natural, human-like language. 
    It can apply different personality styles, regional dialects, and emotional tones to the text.
    
    **Features:**
    - Multiple personality styles
    - Regional dialect support
    - Emotional tone adjustment
    - Controllable transformation intensity
    - Natural speech error simulation
    """)

if __name__ == "__main__":
    main()