App_Function_Libraries/Gradio_UI/Export_Functionality.py

# Export_Functionality.py
# Functionality for exporting items as markdown files
import os
import json
import math
import logging
import shutil
import tempfile
from typing import List, Dict, Optional, Tuple, Any
import gradio as gr
from App_Function_Libraries.DB.DB_Manager import DatabaseError, fetch_all_notes, fetch_all_conversations, \
    get_keywords_for_note, fetch_notes_by_ids, fetch_conversations_by_ids
from App_Function_Libraries.DB.RAG_QA_Chat_DB import get_keywords_for_conversation
from App_Function_Libraries.Gradio_UI.Gradio_Shared import fetch_item_details, fetch_items_by_keyword, browse_items

logger = logging.getLogger(__name__)

def export_item_as_markdown(media_id: int) -> Tuple[Optional[str], str]:
    try:
        content, prompt, summary = fetch_item_details(media_id)
        title = f"Item {media_id}"  # You might want to fetch the actual title
        markdown_content = f"# {title}\n\n## Prompt\n{prompt}\n\n## Summary\n{summary}\n\n## Content\n{content}"

        filename = f"export_item_{media_id}.md"
        with open(filename, "w", encoding='utf-8') as f:
            f.write(markdown_content)

        logger.info(f"Successfully exported item {media_id} to {filename}")
        return filename, f"Successfully exported item {media_id} to {filename}"
    except Exception as e:
        error_message = f"Error exporting item {media_id}: {str(e)}"
        logger.error(error_message)
        return None, error_message


def export_items_by_keyword(keyword: str) -> str:
    try:
        items = fetch_items_by_keyword(keyword)
        if not items:
            logger.warning(f"No items found for keyword: {keyword}")
            return f"No items found for keyword: {keyword}"

        # Create a temporary directory to store individual markdown files
        with tempfile.TemporaryDirectory() as temp_dir:
            folder_name = f"export_keyword_{keyword}"
            export_folder = os.path.join(temp_dir, folder_name)
            os.makedirs(export_folder)

            for item in items:
                content, prompt, summary = fetch_item_details(item['id'])
                markdown_content = f"# {item['title']}\n\n## Prompt\n{prompt}\n\n## Summary\n{summary}\n\n## Content\n{content}"

                # Create individual markdown file for each item
                file_name = f"{item['id']}_{item['title'][:50]}.md"  # Limit filename length
                file_path = os.path.join(export_folder, file_name)
                with open(file_path, "w", encoding='utf-8') as f:
                    f.write(markdown_content)

            # Create a zip file containing all markdown files
            zip_filename = f"{folder_name}.zip"
            shutil.make_archive(os.path.join(temp_dir, folder_name), 'zip', export_folder)

            # Move the zip file to a location accessible by Gradio
            final_zip_path = os.path.join(os.getcwd(), zip_filename)
            shutil.move(os.path.join(temp_dir, zip_filename), final_zip_path)

        logger.info(f"Successfully exported {len(items)} items for keyword '{keyword}' to {zip_filename}")
        return final_zip_path
    except Exception as e:
        logger.error(f"Error exporting items for keyword '{keyword}': {str(e)}")
        return f"Error exporting items for keyword '{keyword}': {str(e)}"


def export_selected_items(selected_items: List[Dict]) -> Tuple[Optional[str], str]:
    try:
        logger.debug(f"Received selected_items: {selected_items}")
        if not selected_items:
            logger.warning("No items selected for export")
            return None, "No items selected for export"

        markdown_content = "# Selected Items\n\n"
        for item in selected_items:
            logger.debug(f"Processing item: {item}")
            try:
                # Check if 'value' is a string (JSON) or already a dictionary
                if isinstance(item, str):
                    item_data = json.loads(item)
                elif isinstance(item, dict) and 'value' in item:
                    item_data = item['value'] if isinstance(item['value'], dict) else json.loads(item['value'])
                else:
                    item_data = item

                logger.debug(f"Item data after processing: {item_data}")

                if 'id' not in item_data:
                    logger.error(f"'id' not found in item data: {item_data}")
                    continue

                content, prompt, summary = fetch_item_details(item_data['id'])
                markdown_content += f"## {item_data.get('title', 'Item {}'.format(item_data['id']))}\n\n### Prompt\n{prompt}\n\n### Summary\n{summary}\n\n### Content\n{content}\n\n---\n\n"
            except Exception as e:
                logger.error(f"Error processing item {item}: {str(e)}")
                markdown_content += f"## Error\n\nUnable to process this item.\n\n---\n\n"

        filename = "export_selected_items.md"
        with open(filename, "w", encoding='utf-8') as f:
            f.write(markdown_content)

        logger.info(f"Successfully exported {len(selected_items)} selected items to {filename}")
        return filename, f"Successfully exported {len(selected_items)} items to {filename}"
    except Exception as e:
        error_message = f"Error exporting selected items: {str(e)}"
        logger.error(error_message)
        return None, error_message


def display_search_results_export_tab(search_query: str, search_type: str, page: int = 1, items_per_page: int = 10):
    logger.info(f"Searching with query: '{search_query}', type: '{search_type}', page: {page}")
    try:
        results = browse_items(search_query, search_type)
        logger.info(f"browse_items returned {len(results)} results")

        if not results:
            return [], f"No results found for query: '{search_query}'", 1, 1

        total_pages = math.ceil(len(results) / items_per_page)
        start_index = (page - 1) * items_per_page
        end_index = start_index + items_per_page
        paginated_results = results[start_index:end_index]

        checkbox_data = [
            {
                "name": f"Name: {item[1]}\nURL: {item[2]}",
                "value": {"id": item[0], "title": item[1], "url": item[2]}
            }
            for item in paginated_results
        ]

        logger.info(f"Returning {len(checkbox_data)} items for checkbox (page {page} of {total_pages})")
        return checkbox_data, f"Found {len(results)} results (showing page {page} of {total_pages})", page, total_pages

    except DatabaseError as e:
        error_message = f"Error in display_search_results_export_tab: {str(e)}"
        logger.error(error_message)
        return [], error_message, 1, 1
    except Exception as e:
        error_message = f"Unexpected error in display_search_results_export_tab: {str(e)}"
        logger.error(error_message)
        return [], error_message, 1, 1

#
# End of Media DB Export functionality
################################################################


################################################################
#
# Functions for RAG Chat DB Export functionality


def export_rag_conversations_as_json(

    selected_conversations: Optional[List[Dict[str, Any]]] = None

) -> Tuple[Optional[str], str]:
    """

    Export conversations to a JSON file.



    Args:

        selected_conversations: Optional list of conversation dictionaries



    Returns:

        Tuple of (filename or None, status message)

    """
    try:
        if selected_conversations:
            # Extract conversation IDs from selected items
            conversation_ids = []
            for item in selected_conversations:
                if isinstance(item, str):
                    item_data = json.loads(item)
                elif isinstance(item, dict) and 'value' in item:
                    item_data = item['value'] if isinstance(item['value'], dict) else json.loads(item['value'])
                else:
                    item_data = item
                conversation_ids.append(item_data['conversation_id'])

            conversations = fetch_conversations_by_ids(conversation_ids)
        else:
            conversations = fetch_all_conversations()

        export_data = []
        for conversation_id, title, messages in conversations:
            # Get keywords for the conversation
            keywords = get_keywords_for_conversation(conversation_id)

            conversation_data = {
                "conversation_id": conversation_id,
                "title": title,
                "keywords": keywords,
                "messages": [
                    {"role": role, "content": content}
                    for role, content in messages
                ]
            }
            export_data.append(conversation_data)

        filename = "rag_conversations_export.json"
        with open(filename, "w", encoding='utf-8') as f:
            json.dump(export_data, f, indent=2, ensure_ascii=False)

        logger.info(f"Successfully exported {len(export_data)} conversations to {filename}")
        return filename, f"Successfully exported {len(export_data)} conversations to {filename}"
    except Exception as e:
        error_message = f"Error exporting conversations: {str(e)}"
        logger.error(error_message)
        return None, error_message


def export_rag_notes_as_json(

    selected_notes: Optional[List[Dict[str, Any]]] = None

) -> Tuple[Optional[str], str]:
    """

    Export notes to a JSON file.



    Args:

        selected_notes: Optional list of note dictionaries



    Returns:

        Tuple of (filename or None, status message)

    """
    try:
        if selected_notes:
            # Extract note IDs from selected items
            note_ids = []
            for item in selected_notes:
                if isinstance(item, str):
                    item_data = json.loads(item)
                elif isinstance(item, dict) and 'value' in item:
                    item_data = item['value'] if isinstance(item['value'], dict) else json.loads(item['value'])
                else:
                    item_data = item
                note_ids.append(item_data['id'])

            notes = fetch_notes_by_ids(note_ids)
        else:
            notes = fetch_all_notes()

        export_data = []
        for note_id, title, content in notes:
            # Get keywords for the note
            keywords = get_keywords_for_note(note_id)

            note_data = {
                "note_id": note_id,
                "title": title,
                "content": content,
                "keywords": keywords
            }
            export_data.append(note_data)

        filename = "rag_notes_export.json"
        with open(filename, "w", encoding='utf-8') as f:
            json.dump(export_data, f, indent=2, ensure_ascii=False)

        logger.info(f"Successfully exported {len(export_data)} notes to {filename}")
        return filename, f"Successfully exported {len(export_data)} notes to {filename}"
    except Exception as e:
        error_message = f"Error exporting notes: {str(e)}"
        logger.error(error_message)
        return None, error_message


def display_rag_conversations(search_query: str = "", page: int = 1, items_per_page: int = 10):
    """Display conversations for selection in the export tab."""
    try:
        conversations = fetch_all_conversations()

        if search_query:
            # Simple search implementation - can be enhanced based on needs
            conversations = [
                conv for conv in conversations
                if search_query.lower() in conv[1].lower()  # Search in title
            ]

        # Implement pagination
        start_idx = (page - 1) * items_per_page
        end_idx = start_idx + items_per_page
        paginated_conversations = conversations[start_idx:end_idx]
        total_pages = (len(conversations) + items_per_page - 1) // items_per_page

        # Format for checkbox group
        checkbox_data = [
            {
                "name": f"Title: {title}\nMessages: {len(messages)}",
                "value": {"conversation_id": conv_id, "title": title}
            }
            for conv_id, title, messages in paginated_conversations
        ]

        return (
            checkbox_data,
            f"Found {len(conversations)} conversations (showing page {page} of {total_pages})",
            page,
            total_pages
        )
    except Exception as e:
        error_message = f"Error displaying conversations: {str(e)}"
        logger.error(error_message)
        return [], error_message, 1, 1


def display_rag_notes(search_query: str = "", page: int = 1, items_per_page: int = 10):
    """Display notes for selection in the export tab."""
    try:
        notes = fetch_all_notes()

        if search_query:
            # Simple search implementation - can be enhanced based on needs
            notes = [
                note for note in notes
                if search_query.lower() in note[1].lower()  # Search in title
                   or search_query.lower() in note[2].lower()  # Search in content
            ]

        # Implement pagination
        start_idx = (page - 1) * items_per_page
        end_idx = start_idx + items_per_page
        paginated_notes = notes[start_idx:end_idx]
        total_pages = (len(notes) + items_per_page - 1) // items_per_page

        # Format for checkbox group
        checkbox_data = [
            {
                "name": f"Title: {title}\nContent preview: {content[:100]}...",
                "value": {"id": note_id, "title": title}
            }
            for note_id, title, content in paginated_notes
        ]

        return (
            checkbox_data,
            f"Found {len(notes)} notes (showing page {page} of {total_pages})",
            page,
            total_pages
        )
    except Exception as e:
        error_message = f"Error displaying notes: {str(e)}"
        logger.error(error_message)
        return [], error_message, 1, 1


def create_rag_export_tab():
    """Create the RAG QA Chat export tab interface."""
    with gr.Tab("RAG QA Chat Export"):
        with gr.Tabs():
            # Conversations Export Tab
            with gr.Tab("Export Conversations"):
                with gr.Row():
                    with gr.Column():
                        gr.Markdown("## Export RAG QA Chat Conversations")
                        conversation_search = gr.Textbox(label="Search Conversations")
                        conversation_search_button = gr.Button("Search")

                    with gr.Column():
                        conversation_prev_button = gr.Button("Previous Page")
                        conversation_next_button = gr.Button("Next Page")

                conversation_current_page = gr.State(1)
                conversation_total_pages = gr.State(1)

                conversation_results = gr.CheckboxGroup(label="Select Conversations to Export")
                export_selected_conversations_button = gr.Button("Export Selected Conversations")
                export_all_conversations_button = gr.Button("Export All Conversations")

                conversation_export_output = gr.File(label="Download Exported Conversations")
                conversation_status = gr.Textbox(label="Status", interactive=False)

            # Notes Export Tab
            with gr.Tab("Export Notes"):
                with gr.Row():
                    with gr.Column():
                        gr.Markdown("## Export RAG QA Chat Notes")
                        notes_search = gr.Textbox(label="Search Notes")
                        notes_search_button = gr.Button("Search")

                    with gr.Column():
                        notes_prev_button = gr.Button("Previous Page")
                        notes_next_button = gr.Button("Next Page")

                notes_current_page = gr.State(1)
                notes_total_pages = gr.State(1)

                notes_results = gr.CheckboxGroup(label="Select Notes to Export")
                export_selected_notes_button = gr.Button("Export Selected Notes")
                export_all_notes_button = gr.Button("Export All Notes")

                notes_export_output = gr.File(label="Download Exported Notes")
                notes_status = gr.Textbox(label="Status", interactive=False)

        # Event handlers for conversations
        def search_conversations(query, page):
            return display_rag_conversations(query, page)

        conversation_search_button.click(
            fn=search_conversations,
            inputs=[conversation_search, conversation_current_page],
            outputs=[conversation_results, conversation_status, conversation_current_page, conversation_total_pages]
        )

        def update_conversation_page(current, total, direction):
            new_page = max(1, min(total, current + direction))
            return new_page

        conversation_prev_button.click(
            fn=update_conversation_page,
            inputs=[conversation_current_page, conversation_total_pages, gr.State(-1)],
            outputs=[conversation_current_page]
        ).then(
            fn=search_conversations,
            inputs=[conversation_search, conversation_current_page],
            outputs=[conversation_results, conversation_status, conversation_current_page, conversation_total_pages]
        )

        conversation_next_button.click(
            fn=update_conversation_page,
            inputs=[conversation_current_page, conversation_total_pages, gr.State(1)],
            outputs=[conversation_current_page]
        ).then(
            fn=search_conversations,
            inputs=[conversation_search, conversation_current_page],
            outputs=[conversation_results, conversation_status, conversation_current_page, conversation_total_pages]
        )

        export_selected_conversations_button.click(
            fn=export_rag_conversations_as_json,
            inputs=[conversation_results],
            outputs=[conversation_export_output, conversation_status]
        )

        export_all_conversations_button.click(
            fn=lambda: export_rag_conversations_as_json(),
            outputs=[conversation_export_output, conversation_status]
        )

        # Event handlers for notes
        def search_notes(query, page):
            return display_rag_notes(query, page)

        notes_search_button.click(
            fn=search_notes,
            inputs=[notes_search, notes_current_page],
            outputs=[notes_results, notes_status, notes_current_page, notes_total_pages]
        )

        def update_notes_page(current, total, direction):
            new_page = max(1, min(total, current + direction))
            return new_page

        notes_prev_button.click(
            fn=update_notes_page,
            inputs=[notes_current_page, notes_total_pages, gr.State(-1)],
            outputs=[notes_current_page]
        ).then(
            fn=search_notes,
            inputs=[notes_search, notes_current_page],
            outputs=[notes_results, notes_status, notes_current_page, notes_total_pages]
        )

        notes_next_button.click(
            fn=update_notes_page,
            inputs=[notes_current_page, notes_total_pages, gr.State(1)],
            outputs=[notes_current_page]
        ).then(
            fn=search_notes,
            inputs=[notes_search, notes_current_page],
            outputs=[notes_results, notes_status, notes_current_page, notes_total_pages]
        )

        export_selected_notes_button.click(
            fn=export_rag_notes_as_json,
            inputs=[notes_results],
            outputs=[notes_export_output, notes_status]
        )

        export_all_notes_button.click(
            fn=lambda: export_rag_notes_as_json(),
            outputs=[notes_export_output, notes_status]
        )

#
# End of RAG Chat DB Export functionality
#####################################################

def create_export_tabs():
    """Create the unified export interface with all export tabs."""
    with gr.Tabs():
        # Media DB Export Tab
        with gr.Tab("Media DB Export"):
            with gr.Row():
                with gr.Column():
                    gr.Markdown("# Search and Export Items")
                    gr.Markdown("Search for items and export them as markdown files")
                    gr.Markdown("You can also export items by keyword")
                    search_query = gr.Textbox(label="Search Query")
                    search_type = gr.Radio(["Title", "URL", "Keyword", "Content"], label="Search By")
                    search_button = gr.Button("Search")

                with gr.Column():
                    prev_button = gr.Button("Previous Page")
                    next_button = gr.Button("Next Page")

            current_page = gr.State(1)
            total_pages = gr.State(1)

            search_results = gr.CheckboxGroup(label="Search Results", choices=[])
            export_selected_button = gr.Button("Export Selected Items")

            keyword_input = gr.Textbox(label="Enter keyword for export")
            export_by_keyword_button = gr.Button("Export items by keyword")

            export_output = gr.File(label="Download Exported File")
            error_output = gr.Textbox(label="Status/Error Messages", interactive=False)

        # Conversations Export Tab
        with gr.Tab("RAG Conversations Export"):
            with gr.Row():
                with gr.Column():
                    gr.Markdown("## Export RAG QA Chat Conversations")
                    conversation_search = gr.Textbox(label="Search Conversations")
                    conversation_search_button = gr.Button("Search")

                with gr.Column():
                    conversation_prev_button = gr.Button("Previous Page")
                    conversation_next_button = gr.Button("Next Page")

            conversation_current_page = gr.State(1)
            conversation_total_pages = gr.State(1)

            conversation_results = gr.CheckboxGroup(label="Select Conversations to Export")
            export_selected_conversations_button = gr.Button("Export Selected Conversations")
            export_all_conversations_button = gr.Button("Export All Conversations")

            conversation_export_output = gr.File(label="Download Exported Conversations")
            conversation_status = gr.Textbox(label="Status", interactive=False)

        # Notes Export Tab
        with gr.Tab("RAG Notes Export"):
            with gr.Row():
                with gr.Column():
                    gr.Markdown("## Export RAG QA Chat Notes")
                    notes_search = gr.Textbox(label="Search Notes")
                    notes_search_button = gr.Button("Search")

                with gr.Column():
                    notes_prev_button = gr.Button("Previous Page")
                    notes_next_button = gr.Button("Next Page")

            notes_current_page = gr.State(1)
            notes_total_pages = gr.State(1)

            notes_results = gr.CheckboxGroup(label="Select Notes to Export")
            export_selected_notes_button = gr.Button("Export Selected Notes")
            export_all_notes_button = gr.Button("Export All Notes")

            notes_export_output = gr.File(label="Download Exported Notes")
            notes_status = gr.Textbox(label="Status", interactive=False)

        # Event handlers for media DB
        def search_and_update(query, search_type, page):
            results, message, current, total = display_search_results_export_tab(query, search_type, page)
            logger.debug(f"search_and_update results: {results}")
            return results, message, current, total, gr.update(choices=results)

        def update_page(current, total, direction):
            new_page = max(1, min(total, current + direction))
            return new_page

        def handle_export_selected(selected_items):
            logger.debug(f"Exporting selected items: {selected_items}")
            return export_selected_items(selected_items)

        def handle_item_selection(selected_items):
            logger.debug(f"Selected items: {selected_items}")
            if not selected_items:
                return None, "No item selected"

            try:
                selected_item = selected_items[0]
                logger.debug(f"First selected item: {selected_item}")

                if isinstance(selected_item['value'], str):
                    item_data = json.loads(selected_item['value'])
                else:
                    item_data = selected_item['value']

                logger.debug(f"Item data: {item_data}")
                item_id = item_data['id']
                return export_item_as_markdown(item_id)
            except Exception as e:
                error_message = f"Error processing selected item: {str(e)}"
                logger.error(error_message)
                return None, error_message

        search_button.click(
            fn=search_and_update,
            inputs=[search_query, search_type, current_page],
            outputs=[search_results, error_output, current_page, total_pages, search_results],
            show_progress="full"
        )

        prev_button.click(
            fn=update_page,
            inputs=[current_page, total_pages, gr.State(-1)],
            outputs=[current_page]
        ).then(
            fn=search_and_update,
            inputs=[search_query, search_type, current_page],
            outputs=[search_results, error_output, current_page, total_pages],
            show_progress=True
        )

        next_button.click(
            fn=update_page,
            inputs=[current_page, total_pages, gr.State(1)],
            outputs=[current_page]
        ).then(
            fn=search_and_update,
            inputs=[search_query, search_type, current_page],
            outputs=[search_results, error_output, current_page, total_pages],
            show_progress=True
        )

        export_selected_button.click(
            fn=handle_export_selected,
            inputs=[search_results],
            outputs=[export_output, error_output],
            show_progress="full"
        )

        export_by_keyword_button.click(
            fn=export_items_by_keyword,
            inputs=[keyword_input],
            outputs=[export_output, error_output],
            show_progress="full"
        )

        search_results.select(
            fn=handle_item_selection,
            inputs=[search_results],
            outputs=[export_output, error_output],
            show_progress="full"
        )

        # Event handlers for conversations
        def search_conversations(query, page):
            return display_rag_conversations(query, page)

        def update_conversation_page(current, total, direction):
            new_page = max(1, min(total, current + direction))
            return new_page

        conversation_search_button.click(
            fn=search_conversations,
            inputs=[conversation_search, conversation_current_page],
            outputs=[conversation_results, conversation_status, conversation_current_page, conversation_total_pages]
        )

        conversation_prev_button.click(
            fn=update_conversation_page,
            inputs=[conversation_current_page, conversation_total_pages, gr.State(-1)],
            outputs=[conversation_current_page]
        ).then(
            fn=search_conversations,
            inputs=[conversation_search, conversation_current_page],
            outputs=[conversation_results, conversation_status, conversation_current_page, conversation_total_pages]
        )

        conversation_next_button.click(
            fn=update_conversation_page,
            inputs=[conversation_current_page, conversation_total_pages, gr.State(1)],
            outputs=[conversation_current_page]
        ).then(
            fn=search_conversations,
            inputs=[conversation_search, conversation_current_page],
            outputs=[conversation_results, conversation_status, conversation_current_page, conversation_total_pages]
        )

        export_selected_conversations_button.click(
            fn=export_rag_conversations_as_json,
            inputs=[conversation_results],
            outputs=[conversation_export_output, conversation_status]
        )

        export_all_conversations_button.click(
            fn=lambda: export_rag_conversations_as_json(),
            outputs=[conversation_export_output, conversation_status]
        )

        # Event handlers for notes
        def search_notes(query, page):
            return display_rag_notes(query, page)

        def update_notes_page(current, total, direction):
            new_page = max(1, min(total, current + direction))
            return new_page

        notes_search_button.click(
            fn=search_notes,
            inputs=[notes_search, notes_current_page],
            outputs=[notes_results, notes_status, notes_current_page, notes_total_pages]
        )

        notes_prev_button.click(
            fn=update_notes_page,
            inputs=[notes_current_page, notes_total_pages, gr.State(-1)],
            outputs=[notes_current_page]
        ).then(
            fn=search_notes,
            inputs=[notes_search, notes_current_page],
            outputs=[notes_results, notes_status, notes_current_page, notes_total_pages]
        )

        notes_next_button.click(
            fn=update_notes_page,
            inputs=[notes_current_page, notes_total_pages, gr.State(1)],
            outputs=[notes_current_page]
        ).then(
            fn=search_notes,
            inputs=[notes_search, notes_current_page],
            outputs=[notes_results, notes_status, notes_current_page, notes_total_pages]
        )

        export_selected_notes_button.click(
            fn=export_rag_notes_as_json,
            inputs=[notes_results],
            outputs=[notes_export_output, notes_status]
        )

        export_all_notes_button.click(
            fn=lambda: export_rag_notes_as_json(),
            outputs=[notes_export_output, notes_status]
        )

        with gr.TabItem("Export Prompts", visible=True):
            gr.Markdown("# Export Prompts Database Content")

            with gr.Row():
                with gr.Column():
                    export_type = gr.Radio(
                        choices=["All Prompts", "Prompts by Keyword"],
                        label="Export Type",
                        value="All Prompts"
                    )

                    # Keyword selection for filtered export
                    with gr.Column(visible=False) as keyword_col:
                        keyword_input = gr.Textbox(
                            label="Enter Keywords (comma-separated)",
                            placeholder="Enter keywords to filter prompts..."
                        )

                    # Export format selection
                    export_format = gr.Radio(
                        choices=["CSV", "Markdown (ZIP)"],
                        label="Export Format",
                        value="CSV"
                    )

                    # Export options
                    include_options = gr.CheckboxGroup(
                        choices=[
                            "Include System Prompts",
                            "Include User Prompts",
                            "Include Details",
                            "Include Author",
                            "Include Keywords"
                        ],
                        label="Export Options",
                        value=["Include Keywords", "Include Author"]
                    )

                    # Markdown-specific options (only visible when Markdown is selected)
                    with gr.Column(visible=False) as markdown_options_col:
                        markdown_template = gr.Radio(
                            choices=[
                                "Basic Template",
                                "Detailed Template",
                                "Custom Template"
                            ],
                            label="Markdown Template",
                            value="Basic Template"
                        )
                        custom_template = gr.Textbox(
                            label="Custom Template",
                            placeholder="Use {title}, {author}, {details}, {system}, {user}, {keywords} as placeholders",
                            visible=False
                        )

                    export_button = gr.Button("Export Prompts")

                with gr.Column():
                    export_status = gr.Textbox(label="Export Status", interactive=False)
                    export_file = gr.File(label="Download Export")

            def update_ui_visibility(export_type, format_choice, template_choice):
                """Update UI elements visibility based on selections"""
                show_keywords = export_type == "Prompts by Keyword"
                show_markdown_options = format_choice == "Markdown (ZIP)"
                show_custom_template = template_choice == "Custom Template" and show_markdown_options

                return [
                    gr.update(visible=show_keywords),  # keyword_col
                    gr.update(visible=show_markdown_options),  # markdown_options_col
                    gr.update(visible=show_custom_template)  # custom_template
                ]

            def handle_export(export_type, keywords, export_format, options, markdown_template, custom_template):
                """Handle the export process based on selected options"""
                try:
                    # Parse options
                    include_system = "Include System Prompts" in options
                    include_user = "Include User Prompts" in options
                    include_details = "Include Details" in options
                    include_author = "Include Author" in options
                    include_keywords = "Include Keywords" in options

                    # Handle keyword filtering
                    keyword_list = None
                    if export_type == "Prompts by Keyword" and keywords:
                        keyword_list = [k.strip() for k in keywords.split(",") if k.strip()]

                    # Get the appropriate template
                    template = None
                    if export_format == "Markdown (ZIP)":
                        if markdown_template == "Custom Template":
                            template = custom_template
                        else:
                            template = markdown_template

                    # Perform export
                    from App_Function_Libraries.DB.Prompts_DB import export_prompts
                    status, file_path = export_prompts(
                        export_format=export_format.split()[0].lower(),  # 'csv' or 'markdown'
                        filter_keywords=keyword_list,
                        include_system=include_system,
                        include_user=include_user,
                        include_details=include_details,
                        include_author=include_author,
                        include_keywords=include_keywords,
                        markdown_template=template
                    )

                    return status, file_path

                except Exception as e:
                    error_msg = f"Export failed: {str(e)}"
                    logging.error(error_msg)
                    return error_msg, None

            # Event handlers
            export_type.change(
                fn=lambda t, f, m: update_ui_visibility(t, f, m),
                inputs=[export_type, export_format, markdown_template],
                outputs=[keyword_col, markdown_options_col, custom_template]
            )

            export_format.change(
                fn=lambda t, f, m: update_ui_visibility(t, f, m),
                inputs=[export_type, export_format, markdown_template],
                outputs=[keyword_col, markdown_options_col, custom_template]
            )

            markdown_template.change(
                fn=lambda t, f, m: update_ui_visibility(t, f, m),
                inputs=[export_type, export_format, markdown_template],
                outputs=[keyword_col, markdown_options_col, custom_template]
            )

            export_button.click(
                fn=handle_export,
                inputs=[
                    export_type,
                    keyword_input,
                    export_format,
                    include_options,
                    markdown_template,
                    custom_template
                ],
                outputs=[export_status, export_file]
            )

#
# End of Export_Functionality.py
######################################################################################################################