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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
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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