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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)
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