"""Gradio web application for Francis Botcon."""

import gradio as gr
from typing import List, Tuple
import sys
from pathlib import Path

# Add project root to path
sys.path.insert(0, str(Path(__file__).parent.parent))

from src.model import FrancisModel
from src.rag_system import RAGSystem
from src.logger import LoggerSetup
from src.config_loader import config

logger = LoggerSetup.setup("INFO", "./logs/app.log")


class FrancisBotconApp:
    """Gradio application for Francis Botcon chatbot."""

    def __init__(self):
        """Initialize the application."""
        logger.info("Initializing Francis Botcon Application...")

        try:
            # Check if LoRA adapter exists
            adapter_path = None
            if Path("./models/francis_botcon_lora").exists():
                adapter_path = "./models/francis_botcon_lora"
                logger.info("✓ LoRA adapter found, will use fine-tuned model")

            # Initialize model
            logger.info("Loading language model...")
            self.model = FrancisModel(adapter_path=adapter_path)
            logger.info("✓ Model loaded")

            # Initialize RAG system
            logger.info("Initializing RAG system...")
            self.rag_system = RAGSystem()
            logger.info("✓ RAG system initialized")

            self.conversation_history: List[Tuple[str, str]] = []

        except Exception as e:
            logger.error(f"Failed to initialize application: {str(e)}")
            raise

    def respond(self, message: str, history: List) -> Tuple[str, List]:
        """Generate a response to a user message.

        Args:
            message: User's input message
            history: Conversation history

        Returns:
            Tuple of (response, updated_history)
        """
        if not message.strip():
            return "", history

        logger.info(f"User: {message[:100]}...")

        try:
            # Retrieve context using RAG
            context_docs = self.rag_system.retrieve_context(message, top_k=5)

            # Build prompt with context
            prompt = self.rag_system.build_prompt(message, context_docs)

            # Generate response
            response = self.model.generate(
                prompt,
                max_length=512,
                temperature=0.7,
                top_p=0.9
            )

            logger.info(f"Generated response ({len(response)} chars)")

            # Format response with citations
            formatted_response = self._format_response(response, context_docs)

            return formatted_response

        except Exception as e:
            logger.error(f"Error generating response: {str(e)}")
            return f"I apologize, but I encountered an error: {str(e)}", history

    def _format_response(self, response: str, context_docs: List) -> str:
        """Format response with citations.

        Args:
            response: Generated response text
            context_docs: Retrieved context documents

        Returns:
            Formatted response with citations
        """
        formatted = f"{response}\n\n"

        if context_docs:
            formatted += "---\n**Sources from My Works:**\n"
            for i, doc in enumerate(context_docs[:3], 1):  # Show top 3 sources
                metadata = doc["metadata"]
                title = metadata.get("title", "Unknown Work")
                source = metadata.get("source", "")
                similarity = doc["similarity"]

                formatted += f"\n{i}. *{title}*"
                if source:
                    formatted += f" ({source})"
                formatted += f" - Relevance: {similarity:.1%}"

        return formatted

    def create_interface(self) -> gr.Interface:
        """Create Gradio interface.

        Returns:
            Gradio Interface
        """
        with gr.Blocks(title="Francis Botcon", theme=gr.themes.Soft()) as interface:
            gr.Markdown("# Francis Botcon")
            gr.Markdown(
                "A conversational AI that emulates the philosophical style of Francis Bacon (1561-1626). "
                "Ask questions and receive responses in his distinctive voice, with citations from his works."
            )

            chatbot = gr.Chatbot(
                label="Conversation with Francis Bacon",
                height=500
            )

            with gr.Row():
                message_input = gr.Textbox(
                    label="Your Question",
                    placeholder="Ask Francis Bacon anything...",
                    lines=2
                )
                submit_button = gr.Button("Send", variant="primary")

            with gr.Accordion("Settings", open=False):
                with gr.Row():
                    temperature = gr.Slider(
                        label="Temperature",
                        minimum=0.1,
                        maximum=1.0,
                        value=0.7,
                        step=0.1
                    )
                    top_p = gr.Slider(
                        label="Top P",
                        minimum=0.0,
                        maximum=1.0,
                        value=0.9,
                        step=0.1
                    )

            def chat(message, chat_history):
                """Chat function."""
                response = self.respond(message, chat_history)
                chat_history.append((message, response))
                return "", chat_history

            # Connect events
            submit_button.click(
                chat,
                inputs=[message_input, chatbot],
                outputs=[message_input, chatbot]
            )

            message_input.submit(
                chat,
                inputs=[message_input, chatbot],
                outputs=[message_input, chatbot]
            )

            gr.Markdown("""
            ---
            **About Francis Botcon:**
            - Based on Llama 3.2:3b fine-tuned on Francis Bacon's works
            - Uses Retrieval-Augmented Generation (RAG) for contextual responses
            - Citations refer to passages from Bacon's authentic works

            **Note:** This is an AI model trained to emulate Bacon's style.
            For academic purposes, always verify citations with original sources.
            """)

        return interface

    def launch(self, share: bool = False, server_name: str = "0.0.0.0", server_port: int = 7860):
        """Launch the Gradio app.

        Args:
            share: Whether to create a shareable link
            server_name: Server address
            server_port: Server port
        """
        logger.info(f"Launching Francis Botcon on {server_name}:{server_port}")

        interface = self.create_interface()

        interface.launch(
            share=share,
            server_name=server_name,
            server_port=server_port,
        )


def main():
    """Main entry point."""
    try:
        app = FrancisBotconApp()
        app.launch(
            share=config.get("app.share", False),
            server_port=config.get("app.port", 7860)
        )
    except Exception as e:
        logger.error(f"Application failed: {str(e)}", exc_info=True)
        sys.exit(1)


if __name__ == "__main__":
    main()