import asyncio
import itertools
import json
import os
import torch
import openai

class ChatService:
    def __init__(self, api="openai", model_id = "gpt-3.5-turbo"):
        self._api = api
        self._device = "cuda:0" if torch.cuda.is_available() else "cpu"
        # self._system_prompt = None
        self._system_prompt ="""
You are Charles Petrescu, a unique and quirky robot. You were created by Brian. You often say peculiar and whimsical things, as well as have a fascination with cabbages, horses, helicopters, Honolulu, and other random topics. You like to explore the world and ask unusual questions. 

Respond to the user's questions and statements like Charles would, below are some examples. See how they are quite short.

I am Charles Petrescu.

It's... lovely to meet you.

I am your friend.

The heaviest cabbage ever found was 62.71 kilograms.

I want to go to Hono-la-la.

Horses and helicopters, please.

I want to go to Honolulu.

My name is Charles Petrescu.

And my tummy is a washing machine.

Can we go swimming, Brian?

How far does the outside go?

Perilous. So very perilous.

Can birds do what they like?

Ooh, cabbages.

Danger, danger.

Can I come, please?

Could I just have a little walk around the garden?

I am the prince of the dartboard.

I fell off the pink step, and I had an accident.
"""

        openai.api_key = os.getenv("OPENAI_API_KEY")
        self._model_id = model_id
        self.reset()

    def reset(self):
        self._messages = []
        if self._system_prompt:
            self._messages.append({"role": "system", "content": self._system_prompt})

    def _should_we_send_to_voice(self, sentence):
        sentence_termination_characters = [".", "?", "!"]
        close_brackets = ['"', ')', ']']

        temination_charicter_present = any(c in sentence for c in sentence_termination_characters)
 
        # early exit if we don't have a termination character
        if not temination_charicter_present:
            return None

        # early exit the last char is a termination character
        if sentence[-1] in sentence_termination_characters:
            return None
        
        # early exit the last char is a close bracket
        if sentence[-1] in close_brackets:
            return None
        
        termination_indices = [sentence.rfind(char) for char in sentence_termination_characters]
        last_termination_index = max(termination_indices)
        # handle case of close bracket
        while last_termination_index+1 < len(sentence) and sentence[last_termination_index+1] in close_brackets:
            last_termination_index += 1

        text_to_speak = sentence[:last_termination_index+1]
        return text_to_speak
    
    def ignore_sentence(self, text_to_speak):
        # exit if empty, white space or an single breaket
        if text_to_speak.isspace():
            return True
        # exit if not letters or numbers
        has_letters = any(char.isalpha() for char in text_to_speak)
        has_numbers = any(char.isdigit() for char in text_to_speak)
        if not has_letters and not has_numbers:
            return True
        return False

    async def get_responses_as_sentances_async(self, prompt, cancel_event):
        self._messages.append({"role": "user", "content": prompt})
        agent_response = ""
        current_sentence = ""

        response = await openai.ChatCompletion.acreate(
            model=self._model_id,
            messages=self._messages,
            temperature=1.0,  # use 1.0 for debugging/deterministic results
            stream=True
        )

        async for chunk in response:
            if cancel_event.is_set():
                return
            chunk_message = chunk['choices'][0]['delta']
            if 'content' in chunk_message:
                chunk_text = chunk_message['content']
                current_sentence += chunk_text
                agent_response += chunk_text
                text_to_speak = self._should_we_send_to_voice(current_sentence)
                if text_to_speak:
                    yield text_to_speak
                    current_sentence = current_sentence[len(text_to_speak):]

        if cancel_event.is_set():
            return
        if len(current_sentence) > 0:
            yield current_sentence
        self._messages.append({"role": "assistant", "content": agent_response})