"""
This plugin provides commands to interact with different AI models.
"""

import logging
import requests
import json
import simplematrixbotlib as botlib
import re
import markdown2

async def handle_command(room, message, bot, prefix, config):
    """
    Function to handle AI commands.

    Args:
        room (Room): The Matrix room where the command was invoked.
        message (RoomMessage): The message object containing the command.
        bot (Bot): The bot object.
        prefix (str): The command prefix.
        config (dict): Configuration parameters.

    Returns:
        None
    """
    match = botlib.MessageMatch(room, message, bot, prefix)
    if match.is_not_from_this_bot() and match.prefix():
        logging.info(f"Received command: {match.command()}")

        command = match.command()
        conf = load_config()
        if command in conf:
            await handle_ai_command(room, bot, command, match.args(), conf)

async def handle_ai_command(room, bot, command, args, config):
    """
    Function to handle AI commands.

    Args:
        room (Room): The Matrix room where the command was invoked.
        bot (Bot): The bot object.
        command (str): The name of the AI model command.
        args (list): List of arguments provided with the command.
        config (dict): Configuration parameters.

    Returns:
        None
    """
    if len(args) < 1:
        await bot.api.send_text_message(room.room_id, f"Usage: !{command} [prompt]")
        logging.info("Sent usage message to the room")
        return

    prompt = ' '.join(args)

    # Prepare data for the API request
    url = "http://127.0.0.1:5000/v1/completions"
    headers = {
        "Content-Type": "application/json"
    }

    data = {
        "prompt": f"<s>[INST]{config[command]['prompt']}{prompt}[/INST]",
        "max_tokens": 1024,
        "temperature": config[command]["temperature"],
        "top_p": config[command]["top_p"],
        "top_k": config[command]["top_k"],
        "repetition_penalty": config[command]["repetition_penalty"],
        "seed": -1,
        "stream": False
    }

    # Make HTTP request to the API endpoint
    try:
        response = requests.post(url, headers=headers, json=data, verify=False)
        response.raise_for_status()  # Raise HTTPError for bad responses
        payload = response.json()
        new_text = payload['choices'][0]['text']
        new_text = markdown_to_html(new_text)

        if new_text.count('<p>') > 1 or new_text.count('<li>') > 1:  # Check if new_text has more than one paragraph
            new_text = f"<details><summary><strong>{config[command]['summary']}</strong></summary>{new_text}</details>"
            await bot.api.send_markdown_message(room.room_id, new_text)
        else:
            await bot.api.send_markdown_message(room.room_id, new_text)
        logging.info("Sent generated text to the room")
    except requests.exceptions.RequestException as e:
        logging.error(f"HTTP request failed for '{prompt}': {e}")
        await bot.api.send_text_message(room.room_id, f"Error generating text: {e}")

def markdown_to_html(markdown_text):
    """
    Convert Markdown text to HTML.

    Args:
        markdown_text (str): Markdown formatted text.

    Returns:
        str: HTML formatted text.
    """
    html_content = markdown2.markdown(markdown_text)
    return html_content

def load_config():
    """
    Load configuration from ai.json file.

    Returns:
        dict: Configuration parameters.
    """
    with open("plugins/ai.json", "r") as f:
        config = json.load(f)
    return config

CONFIG = load_config()