app.py

#!/usr/bin/env python3
"""
Smart Auto-Complete - Main Application
A context-aware text completion tool built with Gradio
"""

from typing import List, Tuple

import gradio as gr

from config.settings import AppSettings
from src.autocomplete import SmartAutoComplete
from src.utils import setup_logging

# Initialize logging
logger = setup_logging()

# Initialize settings and autocomplete engine
settings = AppSettings()
autocomplete = SmartAutoComplete(settings)


class AutoCompleteApp:
    def __init__(self):
        self.last_request_time = 0
        self.current_suggestions = []

    def get_suggestions(
        self, text: str, context: str, output_tokens: int = 150, user_context: str = ""
    ) -> Tuple[List[str], str]:
        """
        Get auto-complete suggestions for the given text and context
        Returns: (suggestions_list, status_message)
        """
        try:
            # Input validation
            if not text or len(text.strip()) < 2:
                return [], "✏️ Please enter some text to get suggestions..."

            if len(text) > settings.MAX_INPUT_LENGTH:
                return (
                    [],
                    f"⚠️ Text too long (max {settings.MAX_INPUT_LENGTH} characters)",
                )

            # Get suggestions from autocomplete engine
            suggestions = autocomplete.get_suggestions(
                text=text,
                context=context,
                max_tokens=output_tokens,
                user_context=user_context,
            )

            self.current_suggestions = suggestions

            if suggestions:
                status = f"✅ Found {len(suggestions)} suggestions"
            else:
                status = "🤔 No suggestions available for this text"

            return suggestions, status

        except Exception as e:
            logger.error(f"Error getting suggestions: {str(e)}")
            return [], f"❌ Error: {str(e)}"

    def get_suggestions_with_custom_prompts(
        self,
        text: str,
        context: str,
        output_tokens: int = 150,
        user_context: str = "",
        custom_prompts: dict = None,
    ) -> Tuple[List[str], str]:
        """
        Get auto-complete suggestions with custom prompts
        Returns: (suggestions_list, status_message)
        """
        try:
            # Input validation
            if not text or len(text.strip()) < 2:
                return [], "✏️ Please enter some text to get suggestions..."

            if len(text) > settings.MAX_INPUT_LENGTH:
                return (
                    [],
                    f"⚠️ Text too long (max {settings.MAX_INPUT_LENGTH} characters)",
                )

            # Create a temporary autocomplete instance with custom prompts
            temp_autocomplete = SmartAutoComplete(settings)
            if custom_prompts:
                temp_autocomplete.CONTEXT_PROMPTS = custom_prompts

            # Get suggestions from autocomplete engine
            suggestions = temp_autocomplete.get_suggestions(
                text=text,
                context=context,
                max_tokens=output_tokens,
                user_context=user_context,
            )

            self.current_suggestions = suggestions

            if suggestions:
                status = f"✅ Found {len(suggestions)} suggestions"
            else:
                status = "🤔 No suggestions available for this text"

            return suggestions, status

        except Exception as e:
            logger.error(f"Error getting suggestions with custom prompts: {str(e)}")
            return [], f"❌ Error: {str(e)}"

    def insert_suggestion(
        self, current_text: str, suggestion: str, cursor_position: int = None
    ) -> str:
        """Insert the selected suggestion into the current text"""
        try:
            # Simple append for now - in a real implementation, this would be more sophisticated
            if not current_text:
                return suggestion

            # If text ends with incomplete sentence, replace the last part
            words = current_text.split()
            if words and not current_text.endswith((".", "!", "?", "\n")):
                # Replace the last partial word/sentence with the suggestion
                return current_text + " " + suggestion.strip()
            else:
                return current_text + " " + suggestion.strip()

        except Exception as e:
            logger.error(f"Error inserting suggestion: {str(e)}")
            return current_text


def create_interface():
    """Create and configure the Gradio interface"""

    app_instance = AutoCompleteApp()

    # Custom CSS for better styling
    custom_css = """
    .suggestion-box {
        background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
        border-radius: 10px;
        padding: 15px;
        margin: 10px 0;
        color: white;
        cursor: pointer;
        transition: transform 0.2s;
    }
    .suggestion-box:hover {
        transform: translateY(-2px);
        box-shadow: 0 4px 12px rgba(0,0,0,0.15);
    }
    .context-selector {
        margin-bottom: 20px;
    }
    .main-input {
        border-radius: 10px;
        border: 2px solid #e1e5e9;
        font-size: 16px;
    }
    """

    with gr.Blocks(
        title="🚀 Smart Auto-Complete", theme=gr.themes.Soft(), css=custom_css
    ) as interface:
        # Header
        gr.Markdown("""
        # 🚀 Smart Auto-Complete

        **Intelligent text completion powered by AI**

        Choose your context, enter your text, and click submit to get AI-powered completions! ✨
        """)

        with gr.Row():
            with gr.Column(scale=2):
                # Context selection
                context_selector = gr.Radio(
                    choices=[
                        ("📧 Email Writing", "email"),
                        ("✍️ Creative Writing", "creative"),
                        ("💼 LinkedIn Content", "linkedin"),
                    ],
                    value="linkedin",
                    label="Select Context",
                    elem_classes=["context-selector"],
                )

                # User context input
                context_input = gr.Textbox(
                    label="📝 Reference Information (Optional)",
                    placeholder="Add any background information, previous context, or references that should inform the writing...",
                    lines=4,
                    elem_classes=["context-input"],
                )

                # Main text input
                text_input = gr.Textbox(
                    label="✏️ Enter your text here...",
                    placeholder="Enter your text and click Submit to get suggestions!",
                    lines=8,
                    elem_classes=["main-input"],
                )

                # Submit button
                submit_btn = gr.Button(
                    "🚀 Get Suggestions", variant="primary", size="lg"
                )

                # Settings
                with gr.Accordion("⚙️ Settings", open=False):
                    output_length = gr.Slider(
                        minimum=50,
                        maximum=500,
                        value=150,
                        step=10,
                        label="Output Length (tokens)",
                    )

                    gr.Checkbox(label="Show debug information", value=False)

                # Context Prompt Editor
                with gr.Accordion("🔧 Edit Context Prompts", open=False):
                    gr.Markdown(
                        "**Customize your writing style for each context type. Changes apply immediately.**"
                    )

                    with gr.Tab("📧 Email Context"):
                        email_system_prompt = gr.Textbox(
                            label="System Prompt",
                            value="""You are an expert email writing assistant. Generate professional,
            contextually appropriate email completions. Focus on:
            - Professional tone and structure
            - Clear, concise communication
            - Appropriate greetings and closings
            - Business communication best practices

            IMPORTANT: Generate a completion that is approximately {max_tokens} tokens long.
            Adjust your response length accordingly - shorter for fewer tokens, longer for more tokens.""",
                            lines=8,
                            placeholder="Enter the system prompt for email context...",
                        )
                        email_user_template = gr.Textbox(
                            label="User Message Template",
                            value="Complete this email text naturally and professionally with approximately {max_tokens} tokens: {text}",
                            lines=3,
                            placeholder="Enter the user message template...",
                        )

                    with gr.Tab("🎨 Creative Context"):
                        creative_system_prompt = gr.Textbox(
                            label="System Prompt",
                            value="""You are a creative writing assistant. Generate engaging,
            imaginative story continuations. Focus on:
            - Narrative consistency and flow
            - Character development
            - Descriptive and engaging language
            - Plot advancement

            IMPORTANT: Generate a completion that is approximately {max_tokens} tokens long.
            Adjust your response length accordingly - shorter for fewer tokens, longer for more tokens.""",
                            lines=8,
                            placeholder="Enter the system prompt for creative context...",
                        )
                        creative_user_template = gr.Textbox(
                            label="User Message Template",
                            value="Continue this creative writing piece naturally with approximately {max_tokens} tokens: {text}",
                            lines=3,
                            placeholder="Enter the user message template...",
                        )

                    with gr.Tab("💼 LinkedIn Context"):
                        linkedin_system_prompt = gr.Textbox(
                            label="System Prompt",
                            value="""You are a LinkedIn writing assistant specialized in professional networking content. Generate engaging,
            professional LinkedIn-appropriate text completions. Focus on:
            - Professional networking tone
            - Industry-relevant language
            - Engaging and authentic voice
            - LinkedIn best practices (hashtags, mentions, professional insights)
            - Career development and business communication

            IMPORTANT: Generate a completion that is approximately {max_tokens} tokens long.
            Adjust your response length accordingly - shorter for fewer tokens, longer for more tokens.""",
                            lines=8,
                            placeholder="Enter the system prompt for LinkedIn context...",
                        )
                        linkedin_user_template = gr.Textbox(
                            label="User Message Template",
                            value="Complete this LinkedIn post/content naturally and professionally with approximately {max_tokens} tokens: {text}",
                            lines=3,
                            placeholder="Enter the user message template...",
                        )

            with gr.Column(scale=1):
                # Status display
                status_display = gr.Textbox(
                    label="📊 Status",
                    value="Ready to help! Start typing...",
                    interactive=False,
                    lines=2,
                )

                # Copyable textbox for suggestions (only output)
                copy_textbox = gr.Textbox(
                    label="📋 Generated Text (Select All and Copy with Ctrl+C/Cmd+C)",
                    placeholder="Generated suggestions will appear here for easy copying...",
                    lines=8,
                    max_lines=15,
                    interactive=True,
                    visible=False,
                )

        # Demo section
        with gr.Accordion("🎯 Try These Examples", open=False):
            gr.Examples(
                examples=[
                    [
                        "Meeting scheduled for next Tuesday to discuss the quarterly budget review",
                        "Dear Mr. Johnson,\n\nI hope this email finds you well. I wanted to follow up on",
                        "email",
                    ],
                    [
                        "Fantasy adventure story with magical creatures and brave heroes",
                        "Once upon a time, in a kingdom far away, there lived a",
                        "creative",
                    ],
                    [
                        "Professional networking and career development",
                        "Excited to share my thoughts on the future of AI in our industry",
                        "linkedin",
                    ],
                ],
                inputs=[context_input, text_input, context_selector],
                label="Click any example to try it out!",
            )

        # Event handlers
        def update_suggestions(
            text,
            context,
            output_tokens,
            user_context,
            email_sys,
            email_user,
            creative_sys,
            creative_user,
            linkedin_sys,
            linkedin_user,
        ):
            """Update suggestions based on input with custom prompts"""
            logger.info(
                f"Getting suggestions with context: '{user_context[:50] if user_context else 'None'}...'"
            )
            logger.info(f"Requested output tokens: {output_tokens}")

            # Create custom prompts dictionary
            custom_prompts = {
                "email": {
                    "system_prompt": email_sys,
                    "user_template": email_user,
                    "temperature": 0.6,
                },
                "creative": {
                    "system_prompt": creative_sys,
                    "user_template": creative_user,
                    "temperature": 0.8,
                },
                "linkedin": {
                    "system_prompt": linkedin_sys,
                    "user_template": linkedin_user,
                    "temperature": 0.7,
                },
            }

            suggestions, status = app_instance.get_suggestions_with_custom_prompts(
                text, context, output_tokens, user_context, custom_prompts
            )

            # Update the copy textbox with the suggestion
            if suggestions:
                copy_text = suggestions[0] if suggestions else ""
                copy_visible = True
            else:
                copy_text = ""
                copy_visible = False

            # Return the copy textbox update
            copy_update = gr.update(visible=copy_visible, value=copy_text)
            return status, copy_update

        # Submit button handler
        submit_btn.click(
            fn=update_suggestions,
            inputs=[
                text_input,
                context_selector,
                output_length,
                context_input,
                email_system_prompt,
                email_user_template,
                creative_system_prompt,
                creative_user_template,
                linkedin_system_prompt,
                linkedin_user_template,
            ],
            outputs=[status_display, copy_textbox],
        )

        # Footer
        gr.Markdown("""
        ---
        
        ### 🎮 How to Use:
        1. **Select your context** (Email, Creative, or LinkedIn)
        2. **Add context information** (optional) - background info, references, or previous context
        3. **Enter your text** in the main text area
        4. **Adjust output length** (50-500 tokens) in settings
        5. **Customize prompts** (optional) - edit AI prompts in "Edit Context Prompts" section
        6. **Click "Get Suggestions"** to generate completions
        7. **Copy from the generated text box** (Select All + Ctrl+C/Cmd+C)

        ### 🌟 Pro Tips:
        - **Context Window**: Add background info, previous conversations, or references to improve suggestions
        - **Email**: Try starting with "Dear..." or "I hope..." + add meeting context
        - **Creative**: Start with "Once upon a time..." + add story background
        - **LinkedIn**: Perfect for professional posts, career updates, industry insights + add professional context
        - **Output Length**: Adjust the token slider for longer or shorter completions
        - **Custom Prompts**: Edit the AI prompts to customize behavior for your specific needs
        
        ### 🔧 Built With:
        - **Gradio** for the beautiful interface
        - **OpenAI GPT** for intelligent completions
        - **Python** for robust backend processing
        
        ---
        <div style='text-align: center; color: #666;'>
            Made with ❤️ for writers, developers, and creators everywhere
        </div>
        """)

    return interface


def main():
    """Main function to run the application"""
    try:
        # Check API configuration
        if not settings.validate_api_keys():
            logger.error("No valid API keys found. Please configure your API keys.")
            print("❌ Error: No valid API keys configured!")
            print("Please set OPENAI_API_KEY or ANTHROPIC_API_KEY in your .env file")
            return

        logger.info("Starting Smart Auto-Complete application...")

        # Create and launch interface
        interface = create_interface()

        interface.launch(
            server_name="0.0.0.0",
            server_port=7860,
            share=False,  # Set to True for public sharing
            show_error=True,
        )

    except Exception as e:
        logger.error(f"Failed to start application: {str(e)}")
        print(f"❌ Error starting application: {str(e)}")


if __name__ == "__main__":
    main()