Files
alloy-voice-assistant/assistant.py
Santiago L. Valdarrama 2cd5a6b21c ...
2024-10-21 08:14:29 -04:00

172 lines
4.8 KiB
Python

import base64
from threading import Lock, Thread
import cv2
import openai
from cv2 import VideoCapture, imencode
from dotenv import load_dotenv
from langchain.prompts import ChatPromptTemplate, MessagesPlaceholder
from langchain.schema.messages import SystemMessage
from langchain_community.chat_message_histories import ChatMessageHistory
from langchain_core.output_parsers import StrOutputParser
from langchain_core.runnables.history import RunnableWithMessageHistory
from langchain_openai import ChatOpenAI
from pyaudio import PyAudio, paInt16
from speech_recognition import Microphone, Recognizer, UnknownValueError
load_dotenv()
class WebcamStream:
def __init__(self):
self.stream = VideoCapture(index=0)
_, self.frame = self.stream.read()
self.running = False
self.lock = Lock()
def start(self):
if self.running:
return self
self.running = True
self.thread = Thread(target=self.update, args=())
self.thread.start()
return self
def update(self):
while self.running:
_, frame = self.stream.read()
self.lock.acquire()
self.frame = frame
self.lock.release()
def read(self, encode=False):
self.lock.acquire()
frame = self.frame.copy()
self.lock.release()
if encode:
_, buffer = imencode(".jpeg", frame)
return base64.b64encode(buffer)
return frame
def stop(self):
self.running = False
if self.thread.is_alive():
self.thread.join()
def __exit__(self, exc_type, exc_value, exc_traceback):
self.stream.release()
class Assistant:
def __init__(self, model):
self.chain = self._create_inference_chain(model)
def answer(self, prompt, image):
if not prompt:
return
print("Prompt:", prompt)
response = self.chain.invoke(
{"prompt": prompt, "image_base64": image.decode()},
config={"configurable": {"session_id": "unused"}},
).strip()
print("Response:", response)
if response:
self._tts(response)
def _tts(self, response):
player = PyAudio().open(format=paInt16, channels=1, rate=24000, output=True)
with openai.audio.speech.with_streaming_response.create(
model="tts-1",
voice="alloy",
response_format="pcm",
input=response,
) as stream:
for chunk in stream.iter_bytes(chunk_size=1024):
player.write(chunk)
def _create_inference_chain(self, model):
SYSTEM_PROMPT = """
You are a witty assistant that will use the chat history and the image
provided by the user to answer its questions. Your job is to answer
questions.
Use few words on your answers. Go straight to the point. Do not use any
emoticons or emojis.
Be friendly and helpful. Show some personality.
"""
prompt_template = ChatPromptTemplate.from_messages(
[
SystemMessage(content=SYSTEM_PROMPT),
MessagesPlaceholder(variable_name="chat_history"),
(
"human",
[
{"type": "text", "text": "{prompt}"},
{
"type": "image_url",
"image_url": "data:image/jpeg;base64,{image_base64}",
},
],
),
]
)
chain = prompt_template | model | StrOutputParser()
chat_message_history = ChatMessageHistory()
return RunnableWithMessageHistory(
chain,
lambda _: chat_message_history,
input_messages_key="prompt",
history_messages_key="chat_history",
)
webcam_stream = WebcamStream().start()
# model = ChatGoogleGenerativeAI(model="gemini-1.5-flash-latest")
# You can use OpenAI's GPT-4o model instead of Gemini Flash
# by uncommenting the following line:
model = ChatOpenAI(model="gpt-4o")
assistant = Assistant(model)
def audio_callback(recognizer, audio):
try:
prompt = recognizer.recognize_whisper(audio, model="base", language="english")
assistant.answer(prompt, webcam_stream.read(encode=True))
except UnknownValueError:
print("There was an error processing the audio.")
recognizer = Recognizer()
microphone = Microphone()
with microphone as source:
recognizer.adjust_for_ambient_noise(source)
stop_listening = recognizer.listen_in_background(microphone, audio_callback)
while True:
cv2.imshow("webcam", webcam_stream.read())
if cv2.waitKey(1) in [27, ord("q")]:
break
webcam_stream.stop()
cv2.destroyAllWindows()
stop_listening(wait_for_stop=False)