streaming_chat_service.py

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

from audio_stream_processor import AudioStreamProcessor
from speech_service import SpeechService


class StreamingChatService:
    def __init__(self, audio_processor:AudioStreamProcessor()=None, api="openai", model_id = "gpt-3.5-turbo", voice_id="Bella"):
        self._audio_processor = audio_processor
        self._speech_service = SpeechService(voice_id=voice_id)
        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
    
    def _safe_enqueue_text_to_speak(self, text_to_speak):
        if self.ignore_sentence(text_to_speak):
            return
        stream = self._speech_service.stream(text_to_speak)
        self._audio_processor.add_audio_stream(stream)        

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

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

        for chunk in response:
            chunk_message = chunk['choices'][0]['delta']
            if 'content' in chunk_message:
                chunk_text = chunk_message['content']
                # print(chunk_text)
                current_sentence += chunk_text
                agent_response += chunk_text
                text_to_speak = self._should_we_send_to_voice(current_sentence)
                if text_to_speak:
                    self._safe_enqueue_text_to_speak(text_to_speak)
                    print(text_to_speak)
                    current_sentence = current_sentence[len(text_to_speak):]

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

    async def get_responses_as_sentances_async(self, prompt):
        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:
            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 len(current_sentence) > 0:
            yield current_sentence
        self._messages.append({"role": "assistant", "content": agent_response})
     
    async def get_speech_chunks_async(self, text_to_speak):
        stream = self._speech_service.stream(text_to_speak)
        stream, stream_backup = itertools.tee(stream)
        while True:
            # Check if there's a next item in the stream
            next_item = next(stream_backup, None)
            if next_item is None:
                # Stream is exhausted, exit the loop
                break

            # Run next(stream) in a separate thread to avoid blocking the event loop
            chunk = await asyncio.to_thread(next, stream)
            yield chunk

    def enqueue_speech_bytes_to_play(self, speech_bytes):
        self._audio_processor.add_audio_stream(speech_bytes)