"""
GenAI for Easy Read: Open-Source Multimodal Solution
A Gradio-based prototype for converting documents into accessible Easy Read formats.
"""
import gradio as gr
import os
from typing import List, Tuple, Optional
import re

# ============================================================================
# DUMMY/MOCK FUNCTIONS FOR BACKEND PROCESSING
# TODO: Replace these with actual API calls to OpenAI, GlobalSymbols, etc.
# ============================================================================

def split_into_sentences(text: str) -> List[str]:
    """
    Splits text into individual sentences.
    TODO: Enhance with better sentence boundary detection (e.g., using spaCy)
    """
    if not text or not text.strip():
        return []
    # Simple sentence splitting (can be improved with NLP libraries like spaCy)
    sentences = re.split(r'(?<=[.!?])\s+', text.strip())
    return [s.strip() for s in sentences if s.strip()]

def convert_to_easy_read(
    pdf_file: Optional[str],
    text_input: Optional[str],
    context: str,
    unalterable_terms: str
) -> Tuple[str, List[str], List[str]]:
    """
    Simulates the conversion of complex text to simplified Easy Read format.
    TODO: Replace with actual LLM API call (e.g., OpenAI GPT-4, Anthropic Claude)
    - Process PDF if provided, or use text_input
    - Apply simplification rules
    - Respect context/custom instructions
    - Preserve unalterable terms
    """
    # Use text_input if provided, otherwise dummy text
    input_text = text_input if text_input else (
        "This is sentence one. "
        "This is sentence two. "
        "This is sentence three. "
        "Each sentence can be edited separately."
    )
    
    # Split into sentences
    sentences = split_into_sentences(input_text)
    
    # Dummy simplified text (sentence-by-sentence)
    dummy_simplified = "\n".join(sentences)
    
    # Dummy keyword list for symbol matching
    dummy_keywords = ["person", "help", "document", "read"]
    
    return dummy_simplified, dummy_keywords, sentences

def update_sentence(sentence_index: int, new_text: str, all_sentences: List[str]) -> str:
    """
    Updates a specific sentence and returns the combined text.
    """
    if 0 <= sentence_index < len(all_sentences):
        all_sentences[sentence_index] = new_text
    return "\n".join(all_sentences)

def fetch_symbols_from_libraries(
    keywords: List[str], selected_libraries: List[str]
) -> List[str]:
    """
    Fetches symbols from selected symbol libraries based on keywords.
    TODO: Replace with actual API calls to:
    - GlobalSymbols API
    - ARASAAC API
    - AAC Image Library API
    - PiCom API
    """
    # Dummy: Return placeholder image paths
    # In production, these would be URLs or file paths to actual symbols
    dummy_symbols = [
        "https://via.placeholder.com/200x200/4A90E2/FFFFFF?text=Symbol1",
        "https://via.placeholder.com/200x200/50C878/FFFFFF?text=Symbol2",
        "https://via.placeholder.com/200x200/E94B3C/FFFFFF?text=Symbol3",
        "https://via.placeholder.com/200x200/F5A623/FFFFFF?text=Symbol4",
    ]
    return dummy_symbols

def generate_ai_image(prompt: str) -> Optional[str]:
    """
    Generates an image using AI based on the provided prompt.
    TODO: Replace with actual AI image generation API call:
    - OpenAI DALL-E
    - Stability AI Stable Diffusion
    - Midjourney API
    - Other image generation services
    """
    # Dummy: Return placeholder image
    return "https://via.placeholder.com/400x400/9B59B6/FFFFFF?text=AI+Generated"

def export_to_pdf(text: str, images: List[str]) -> str:
    """
    Exports the Easy Read document to PDF format.
    TODO: Implement PDF generation using libraries like:
    - reportlab
    - fpdf
    - weasyprint
    """
    return "PDF export functionality - TODO: Implement"

def export_to_word(text: str, images: List[str]) -> str:
    """
    Exports the Easy Read document to Word format.
    TODO: Implement Word document generation using:
    - python-docx
    """
    return "Word export functionality - TODO: Implement"

def generate_audio(text: str) -> str:
    """
    Generates audio narration of the Easy Read text.
    TODO: Implement text-to-speech using:
    - OpenAI TTS API
    - Google Cloud Text-to-Speech
    - Amazon Polly
    - Azure Cognitive Services
    """
    return "Audio generation functionality - TODO: Implement"

# ============================================================================
# GRADIO INTERFACE COMPONENTS
# ============================================================================

def create_convert_handler(
    pdf_file, text_input, context, unalterable_terms, selected_libraries
):
    """
    Main handler for the "Convert to Easy Read" button.
    Processes input and returns simplified text and symbol suggestions.
    """
    # Step 1: Convert text to Easy Read format
    simplified_text, keywords, sentences = convert_to_easy_read(
        pdf_file, text_input, context, unalterable_terms
    )
    
    # Step 2: Fetch symbols from selected libraries
    symbols = fetch_symbols_from_libraries(keywords, selected_libraries)
    
    # Step 3: Create sentence components for display
    sentence_components = []
    for i, sentence in enumerate(sentences):
        sentence_components.append((sentence, i))
    
    return simplified_text, symbols, sentences

def create_ai_image_handler(prompt: str):
    """Handler for AI image generation tab."""
    if not prompt.strip():
        return None
    return generate_ai_image(prompt)

# ============================================================================
# MAIN GRADIO INTERFACE
# ============================================================================

def create_interface():
    """Creates and configures the main Gradio interface."""
    
    with gr.Blocks(theme=gr.themes.Soft()) as app:
        # Store sentences in state
        sentences_state = gr.State([])
        
        # ====================================================================
        # HEADER SECTION
        # ====================================================================
        gr.Markdown(
            """
            # GenAI for Easy Read: Open-Source Multimodal Solution
            Convert documents into accessible Easy Read formats with simplified text and supported symbols.
            """,
            elem_classes=["header"]
        )
        
        # ====================================================================
        # STEP 1: INPUT SECTION
        # ====================================================================
        gr.Markdown("## Step 1: Input Document or Text")
        
        with gr.Row():
            # Left Column: File Upload
            with gr.Column():
                pdf_upload = gr.File(
                    label="Upload Document",
                    file_types=[".pdf"],
                    type="filepath"
                )
            
            # Right Column: Text Input
            with gr.Column():
                text_input = gr.Textbox(
                    label="Or Paste Text Here",
                    lines=10,
                    placeholder="Enter your text here..."
                )
        
        # Advanced Settings Accordion
        with gr.Accordion("Advanced Settings", open=False):
            context_input = gr.Textbox(
                label="Context/Custom Instructions",
                placeholder="e.g., 'never use term X', 'target audience: children'",
                lines=3
            )
            unalterable_terms_input = gr.Textbox(
                label="Unalterable Terms",
                placeholder="Enter terms that must not be changed (comma-separated)",
                lines=2
            )
        
        # ====================================================================
        # STEP 2: SYMBOL CONFIGURATION
        # ====================================================================
        gr.Markdown("## Step 2: Select Symbol Libraries")
        
        symbol_libraries = gr.CheckboxGroup(
            choices=[
                "AAC Image Library",
                "GlobalSymbols",
                "ARASAAC",
                "PiCom",
                "AI Realistic Symbols"
            ],
            label="Available Symbol Libraries",
            value=["ARASAAC", "GlobalSymbols"]  # Default selections
        )
        
        # ====================================================================
        # STEP 3: EASY READ EDITOR
        # ====================================================================
        gr.Markdown("## Step 3: Easy Read Editor")
        
        # Convert Button
        convert_btn = gr.Button(
            "Convert to Easy Read",
            variant="primary",
            size="lg"
        )
        
        # Main Editor Layout: Text Editing + Image Selection
        with gr.Row():
            # Left Side: Full Text Editor
            with gr.Column(scale=1):
                simplified_text = gr.Textbox(
                    label="Full Simplified Text (Editable)",
                    lines=15,
                    placeholder="Simplified text will appear here after conversion..."
                )
            
            # Right Side: Multi-Tab Image Interface
            with gr.Column(scale=1):
                with gr.Tabs() as image_tabs:
                    # Tab 1: Symbol Library / Alternatives
                    with gr.Tab("Symbol Library / Alternatives"):
                        symbol_gallery = gr.Gallery(
                            label="Available Symbols",
                            show_label=True,
                            elem_id="symbol_gallery",
                            columns=3,
                            rows=2,
                            height="auto"
                        )
                    
                    # Tab 2: Generate with AI
                    with gr.Tab("Generate with AI"):
                        ai_prompt = gr.Textbox(
                            label="Image Prompt",
                            placeholder="Describe the image you want to generate...",
                            lines=3
                        )
                        generate_ai_btn = gr.Button("Generate", variant="secondary")
                        ai_generated_image = gr.Image(
                            label="Generated Image",
                            type="filepath"
                        )
                    
                    # Tab 3: Upload / Personal
                    with gr.Tab("Upload / Personal"):
                        personal_image_upload = gr.Image(
                            label="Upload Your Image",
                            sources=["upload"],
                            type="filepath"
                        )
                    
                    # Tab 4: Favorites
                    with gr.Tab("Favorites"):
                        favorites_gallery = gr.Gallery(
                            label="Saved Favorites",
                            show_label=True,
                            elem_id="favorites_gallery",
                            columns=3,
                            rows=2,
                            height="auto"
                        )
        
        # ====================================================================
        # INDIVIDUAL SENTENCE EDITOR
        # ====================================================================
        gr.Markdown("## Individual Sentence Editor")
        gr.Markdown("*Edit each sentence separately below*")
        
        # Container for individual sentences
        sentence_editor_container = gr.Column()
        
        with sentence_editor_container:
            # Dynamic sentence textboxes will be created here
            sentence_textboxes = []
            for i in range(10):  # Pre-create 10 textboxes (will show/hide as needed)
                with gr.Row(visible=False) as sentence_row:
                    sentence_num = gr.Markdown(f"**Sentence {i+1}:**")
                    sentence_box = gr.Textbox(
                        label="",
                        lines=2,
                        show_label=False,
                        scale=4
                    )
                sentence_textboxes.append((sentence_row, sentence_box, sentence_num))
        
        # ====================================================================
        # FOOTER / EXPORT SECTION
        # ====================================================================
        gr.Markdown("## Export Options")
        
        with gr.Row():
            export_pdf_btn = gr.Button("Export to PDF", variant="secondary")
            export_word_btn = gr.Button("Export to Word", variant="secondary")
            generate_audio_btn = gr.Button("Generate Audio", variant="secondary")
        
        # ====================================================================
        # EVENT HANDLERS
        # ====================================================================
        
        def update_sentence_display(sentences):
            """Updates the visibility and content of sentence textboxes"""
            updates = []
            for i, (row, box, num) in enumerate(sentence_textboxes):
                if i < len(sentences):
                    # Show this sentence
                    updates.extend([
                        gr.update(visible=True),  # row
                        gr.update(value=sentences[i]),  # textbox
                        gr.update(value=f"**Sentence {i+1}:**")  # label
                    ])
                else:
                    # Hide this sentence
                    updates.extend([
                        gr.update(visible=False),  # row
                        gr.update(value=""),  # textbox
                        gr.update(value="")  # label
                    ])
            return updates
        
        def merge_sentences_to_full_text(*sentence_values):
            """Merges individual sentence values back into full text"""
            # Filter out empty sentences
            sentences = [s for s in sentence_values if s and s.strip()]
            return "\n".join(sentences)
        
        # Convert button handler
        def convert_handler(*args):
            simplified_text, symbols, sentences = create_convert_handler(*args)
            
            # Update sentence display
            sentence_updates = update_sentence_display(sentences)
            
            return [simplified_text, symbols, sentences] + sentence_updates
        
        # Collect all outputs for convert button
        convert_outputs = [simplified_text, symbol_gallery, sentences_state]
        for row, box, num in sentence_textboxes:
            convert_outputs.extend([row, box, num])
        
        convert_btn.click(
            fn=convert_handler,
            inputs=[
                pdf_upload,
                text_input,
                context_input,
                unalterable_terms_input,
                symbol_libraries
            ],
            outputs=convert_outputs
        )
        
        # Update full text when any sentence is edited
        for row, box, num in sentence_textboxes:
            box.change(
                fn=merge_sentences_to_full_text,
                inputs=[b for r, b, n in sentence_textboxes],
                outputs=[simplified_text]
            )
        
        # AI image generation handler
        generate_ai_btn.click(
            fn=create_ai_image_handler,
            inputs=[ai_prompt],
            outputs=[ai_generated_image]
        )
        
        # Export handlers (placeholder)
        export_pdf_btn.click(
            fn=lambda t, imgs: gr.Info("PDF export - TODO: Implement backend"),
            inputs=[simplified_text, symbol_gallery],
            outputs=[]
        )
        
        export_word_btn.click(
            fn=lambda t, imgs: gr.Info("Word export - TODO: Implement backend"),
            inputs=[simplified_text, symbol_gallery],
            outputs=[]
        )
        
        generate_audio_btn.click(
            fn=lambda t: gr.Info("Audio generation - TODO: Implement backend"),
            inputs=[simplified_text],
            outputs=[]
        )
    
    return app

def main():
    """Main entry point for the application."""
    app = create_interface()
    app.launch(
        server_name="0.0.0.0",
        server_port=7860,
        share=False
    )

if __name__ == "__main__":
    main()