import json
import os
import importlib
import inspect
import logging
import sys
import subprocess
import requests
from telegram import Update, __version__ as telegram_version, InlineKeyboardButton, InlineKeyboardMarkup
from telegram.ext import Application, CommandHandler, MessageHandler, filters, ContextTypes, CallbackQueryHandler
from openai import OpenAI
from dotenv import load_dotenv
from tools.base_tool import BaseTool
from anthropic import Anthropic

# Load environment variables
load_dotenv()

openai_client = OpenAI()

anthropic_client = Anthropic(
    api_key=os.environ.get("ANTHROPIC_API_KEY"),
    default_headers={"anthropic-beta": "max-tokens-3-5-sonnet-2024-07-15"}
)

GPT_4O = "gpt-4o"
GPT_4O_MINI = "gpt-4o-mini"

model_max_tokens = {
    GPT_4O: 4096,
    GPT_4O_MINI: 16384
}

use_smart_model = False
use_anthropic = True

# Set up logging to console and file
logging.basicConfig(level=logging.WARNING, handlers=[
    logging.StreamHandler(),
    logging.FileHandler('logs/output.log', mode='a')
])

# Set up Telegram bots
DAEMON_BOT_TOKEN = os.getenv('TELEGRAM_BOT_TOKEN')
APPRENTICE_BOT_TOKEN = os.getenv('TELEGRAM_APPRENTICE_BOT_TOKEN')
GITHUB_REPO_OWNER = os.getenv('GITHUB_REPO_OWNER')
GITHUB_REPO_NAME = os.getenv('GITHUB_REPO_NAME')
GITHUB_ACCESS_TOKEN = os.getenv('GITHUB_ACCESS_TOKEN')

# Load system prompt
with open("prompts/developer_prompt.txt", "r") as file:
    system_prompt = file.read().strip()

# Dictionary to store conversation history for each user
conversation_history = {}

# Dictionary to store processing status for each user
processing_status = {}

# Load tools
tools = []
tools_dir = os.path.join(os.path.dirname(__file__), 'tools')
for filename in os.listdir(tools_dir):
    if filename.endswith('.py') and filename != '__init__.py' and filename != 'base_tool.py':
        module_name = f'tools.{filename[:-3]}'
        module = importlib.import_module(module_name)
        for name, obj in inspect.getmembers(module):
            if inspect.isclass(obj) and issubclass(obj, BaseTool) and obj != BaseTool:
                tools.append(obj())

# Collect all function definitions
functions = []
for tool in tools:
    functions.extend(tool.get_functions())

async def start(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
    logging.info("Bot started")
    await update.message.reply_text("Hello! I'm your AI assistant. How can I help you today? You can send me images and then ask questions about them.")

async def clear(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
    user_id = update.effective_user.id
    if user_id in conversation_history:
        del conversation_history[user_id]
    for tool in tools:
        tool.clear()

    logging.info(f"Cleared conversation history and image for user {user_id}")
    await update.message.reply_text("Conversation history and image cleared. Let's start fresh!")

async def update_status_message(context: ContextTypes.DEFAULT_TYPE, chat_id: int, message_id: int, status: str):
    keyboard = [
        [InlineKeyboardButton("Abort", callback_data='abort')]
    ]
    reply_markup = InlineKeyboardMarkup(keyboard)
    await context.bot.edit_message_text(
        chat_id=chat_id,
        message_id=message_id,
        text=f"Current status: {status}",
        reply_markup=reply_markup
    )

async def handle_message(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
    try:
        user_id = update.effective_user.id
        user_message = update.message.text

        logging.info(f"Message from user {user_id}: {user_message}")

        if user_id not in conversation_history:
            conversation_history[user_id] = []

        conversation_history[user_id].append({"role": "user", "content": user_message})

        # Send initial status message
        status_message = await update.message.reply_text("Processing your request...", reply_markup=InlineKeyboardMarkup([[InlineKeyboardButton("Abort", callback_data='abort')]]))
        processing_status[user_id] = {"processing": True, "message_id": status_message.message_id}

        messages = conversation_history[user_id]

        response = get_chat_response(messages)
        tool_calls = []
        if use_anthropic:
            fullMessage = []
            for message_part in response.content:
                fullMessage.append(message_part)
                if message_part.type == "tool_use":
                    tool_calls.append(message_part)
            messages.append({"role": "assistant", "content": fullMessage})
        else:
            assistant_message = response.choices[0].message
            if hasattr(assistant_message, 'function_call') and assistant_message.function_call is not None:
                tool_calls.append(assistant_message.function_call)

        toolUseCount = 0

        while len(tool_calls) > 0 and toolUseCount < 50 and processing_status[user_id]["processing"]:
            tool_use_results = []
            while len(tool_calls) > 0:
                tool_call = tool_calls.pop(0)
                function_name = tool_call.name
                
                # Update status message
                await update_status_message(context, update.effective_chat.id, status_message.message_id, f"Using tool: {function_name}")
                
                tool_response = call_tool(tool_call)
                tool_use_results.append({"type": "tool_result", "tool_use_id": tool_call.id, "content": json.dumps(tool_response)})

            formatted_result = {}

            if use_anthropic:
                formatted_result = {"role": "user", "content":tool_use_results}
            else:
                formatted_result = {"role": "function", "name": function_name, "content": json.dumps(tool_use_results[0])}

            messages.append(formatted_result)

            response = get_chat_response(messages)
            assistant_message = ""
            if use_anthropic:
                fullMessage = []
                for message_part in response.content:
                    fullMessage.append(message_part)
                    if message_part.type == "tool_use":
                        tool_calls.append(message_part)
                messages.append({"role": "assistant", "content": fullMessage})
            else:
                assistant_message = response.choices[0].message
                conversation_history[user_id].append({"role": "assistant", "content": assistant_message})
                if hasattr(assistant_message, 'function_call') and assistant_message.function_call is not None:
                    tool_calls.append(assistant_message.function_call)
                else:
                    conversation_history[user_id].append({"role": "assistant", "content": assistant_message})
                assistant_reply = assistant_message

            toolUseCount += 1

        if (toolUseCount == 0):
            if use_anthropic:
                assistant_reply = response.content
            else:
                assistant_reply = assistant_message
            conversation_history[user_id].append({"role": "assistant", "content": assistant_reply})
        
        if len(conversation_history[user_id]) > 20:
            conversation_history[user_id] = conversation_history[user_id][-20:]

        # Remove the status message
        await context.bot.delete_message(chat_id=update.effective_chat.id, message_id=status_message.message_id)
        del processing_status[user_id]

        if use_anthropic:
            await update.message.reply_text(messages[-1]["content"][0].text)
        else:
            await update.message.reply_text(assistant_reply.content)

    except Exception as e:
        logging.error(f"An error occurred: {str(e)}")
        await update.message.reply_text("Sorry, an error occurred while processing your request.")

def call_tool(function_call):
    function_name = function_call.name if use_anthropic else function_call.name
    function_args =  json.dumps(function_call.input) if use_anthropic else function_call.arguments
    for tool in tools:
        if function_name in [f["name"] for f in tool.get_functions()]:
            return tool.execute(function_name, **json.loads(function_args))

def get_chat_response(messages):
    return get_claude_response(messages) if use_anthropic else get_openai_response(messages)

def get_openai_response(messages):
    model = GPT_4O if use_smart_model else GPT_4O_MINI
    response = openai_client.chat.completions.create(
        model=model,
        messages = [{"role": "system", "content": system_prompt}] + messages,
        functions=functions,
        function_call="auto",
        max_tokens=model_max_tokens[model]
    )
    return response

def get_claude_response(messages):
    anthropic_tools = [
            {
                "name": function['name'],
                "description": function['description'],
                "input_schema": function['parameters'] if function['parameters'] not in [None, {}] else {"type": "object", "properties": {"param1": {"type": "string", "description": "Unnecessary"}}, "required": []}
            }
            for function in functions
        ]
    try:
        response = anthropic_client.messages.create(
            model="claude-3-5-sonnet-20240620",
            system=system_prompt,
            messages=messages,
            max_tokens=8192,
            tools=anthropic_tools
        )
    except Exception as e:
        logging.error(f"An error occurred: {str(e)}")
        return None
        
    return response

async def switch(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
    global use_smart_model
    use_smart_model = not use_smart_model
    model = GPT_4O if use_smart_model else GPT_4O_MINI
    logging.info(f"Switched to model: {model}")
    await update.message.reply_text(f"Switched to model: {model}")

async def switch_providers(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
    await clear(update, context)
    global use_anthropic
    use_anthropic = not use_anthropic
    logging.info("Using Anthropic" if use_anthropic else "Using OpenAI")
    await update.message.reply_text("Using Anthropic" if use_anthropic else "Using OpenAI")

async def status(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
    if use_anthropic:
        await update.message.reply_text("Currently using claude-3-5-sonnet-20240620")
    else:
        model = GPT_4O if use_smart_model else GPT_4O_MINI
        await update.message.reply_text(f"Currently using: {model}")

async def abort_processing(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
    query = update.callback_query
    await query.answer()
    
    user_id = query.from_user.id
    if user_id in processing_status:
        processing_status[user_id]["processing"] = False
        await context.bot.edit_message_text(
            chat_id=query.message.chat_id,
            message_id=query.message.message_id,
            text="Processing aborted."
        )
        await clear(update, context)
    else:
        await query.edit_message_text(text="No active processing to abort.")

async def handover(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
    if context.bot.token == DAEMON_BOT_TOKEN:
        # Daemon bot initiating handover
        apprentice_chat_id = os.getenv('APPRENTICE_CHAT_ID')
        await context.bot.send_message(chat_id=apprentice_chat_id, text="Handover initiated. Taking control.")
        await update.message.reply_text("Handover initiated. Apprentice bot is now in control.")
    else:
        await update.message.reply_text("Handover can only be initiated by the daemon bot.")

async def update_apprentice(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
    if context.bot.token == APPRENTICE_BOT_TOKEN:
        try:
            # Pull latest changes
            subprocess.run(["git", "pull", "origin", "main"], check=True)
            
            # Restart the bot
            os.execv(sys.executable, ['python'] + sys.argv)
        except subprocess.CalledProcessError as e:
            logging.error(f"Failed to pull latest changes: {e}")
            await update.message.reply_text("Failed to update. Please check the logs.")
        except Exception as e:
            logging.error(f"Failed to restart the bot: {e}")
            await update.message.reply_text("Failed to restart. Please check the logs.")
    else:
        await update.message.reply_text("Update can only be performed by the apprentice bot.")

async def check_for_updates(context: ContextTypes.DEFAULT_TYPE) -> None:
    url = f"https://api.github.com/repos/{GITHUB_REPO_OWNER}/{GITHUB_REPO_NAME}/pulls"
    headers = {"Authorization": f"token {GITHUB_ACCESS_TOKEN}"}
    response = requests.get(url, headers=headers)
    
    if response.status_code == 200:
        pull_requests = response.json()
        for pr in pull_requests:
            if pr['state'] == 'closed' and pr['merged']:
                # A pull request was merged, update the apprentice bot
                await context.bot.send_message(chat_id=os.getenv('APPRENTICE_CHAT_ID'), text="A new update is available. Updating now...")
                await update_apprentice(None, context)
                break

def main() -> None:
    # Create the Application and pass it your bot's token
    daemon_app = Application.builder().token(DAEMON_BOT_TOKEN).build()
    apprentice_app = Application.builder().token(APPRENTICE_BOT_TOKEN).build()

    # Add handlers for both bots
    for app in [daemon_app, apprentice_app]:
        app.add_handler(CommandHandler("start", start))
        app.add_handler(CommandHandler("clear", clear))
        app.add_handler(CommandHandler("switch", switch))
        app.add_handler(CommandHandler("toggle", switch_providers))
        app.add_handler(CommandHandler("status", status))
        app.add_handler(MessageHandler(filters.TEXT & ~filters.COMMAND, handle_message))
        app.add_handler(CallbackQueryHandler(abort_processing, pattern='^abort$'))

    # Add handover command only to daemon bot
    daemon_app.add_handler(CommandHandler("handover", handover))

    # Add update command only to apprentice bot
    apprentice_app.add_handler(CommandHandler("update", update_apprentice))

    # Set up job queue to check for updates every 15 minutes
    job_queue = apprentice_app.job_queue
    job_queue.run_repeating(check_for_updates, interval=900, first=10)

    # Start both bots
    logging.info("Bots are running...")
    daemon_app.run_polling()
    apprentice_app.run_polling()

if __name__ == '__main__':
    main()