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Merge branch 'temp-branch' into async-interpreter

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pull/279/head
Ben Xu 7 months ago
parent 4b25239d0f eee00ac026
commit 5e6dae2dd2
7 changed files with 186 additions and 236 deletions
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176
software/source/clients/base_device.py
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@ -92,7 +92,8 @@ class Device:
self.audiosegments = asyncio.Queue()
self.server_url = ""
self.ctrl_pressed = False
self.playback_latency = None
self.tts_service = ""
# self.playback_latency = None
def fetch_image_from_camera(self, camera_index=CAMERA_DEVICE_INDEX):
"""Captures an image from the specified camera device and saves it to a temporary file. Adds the image to the captured_images list."""
@ -166,29 +167,18 @@ class Device:
while True:
try:
audio = await self.audiosegments.get()
# print("got audio segment!!!!")
if self.playback_latency:
elapsed_time = time.time() - self.playback_latency
print(f"Time from request to playback: {elapsed_time} seconds")
self.playback_latency = None
"""
if audio is not None:
# if self.playback_latency and isinstance(audio, bytes):
# elapsed_time = time.time() - self.playback_latency
# print(f"Time from request to playback: {elapsed_time} seconds")
# self.playback_latency = None
if self.tts_service == "elevenlabs":
mpv_process.stdin.write(audio) # type: ignore
mpv_process.stdin.flush() # type: ignore
else:
play(audio)
args = ["ffplay", "-autoexit", "-", "-nodisp"]
proc = subprocess.Popen(
args=args,
stdout=subprocess.PIPE,
stdin=subprocess.PIPE,
stderr=subprocess.PIPE,
)
out, err = proc.communicate(input=audio)
proc.poll()
"""
play(audio)
# self.audiosegments.remove(audio)
# await asyncio.sleep(0.1)
await asyncio.sleep(0.1)
except asyncio.exceptions.CancelledError:
# This happens once at the start?
pass
@ -236,7 +226,7 @@ class Device:
stream.stop_stream()
stream.close()
print("Recording stopped.")
self.playback_latency = time.time()
# self.playback_latency = time.time()
duration = wav_file.getnframes() / RATE
if duration < 0.3:
@ -343,26 +333,19 @@ class Device:
async def message_sender(self, websocket):
while True:
try:
message = await asyncio.get_event_loop().run_in_executor(
None, send_queue.get
)
if isinstance(message, bytes):
await websocket.send(message)
else:
await websocket.send(json.dumps(message))
send_queue.task_done()
await asyncio.sleep(0.01)
except:
traceback.print_exc()
message = await asyncio.get_event_loop().run_in_executor(
None, send_queue.get
)
if isinstance(message, bytes):
await websocket.send(message)
else:
await websocket.send(json.dumps(message))
send_queue.task_done()
await asyncio.sleep(0.01)
async def websocket_communication(self, WS_URL):
print("websocket communication was called!!!!")
show_connection_log = True
"""
async def exec_ws_communication(websocket):
if CAMERA_ENABLED:
print(
@ -374,46 +357,46 @@ class Device:
asyncio.create_task(self.message_sender(websocket))
while True:
await asyncio.sleep(0)
await asyncio.sleep(0.01)
chunk = await websocket.recv()
#logger.debug(f"Got this message from the server: {type(chunk)} {chunk}")
print((f"Got this message from the server: {type(chunk)}"))
logger.debug(f"Got this message from the server: {type(chunk)} {chunk}")
# print("received chunk from server")
if type(chunk) == str:
chunk = json.loads(chunk)
# message = accumulator.accumulate(chunk)
message = chunk
if self.tts_service == "elevenlabs":
message = chunk
else:
message = accumulator.accumulate(chunk)
if message == None:
# Will be None until we have a full message ready
continue
# At this point, we have our message
print("checkpoint reached!")
if isinstance(message, bytes):
# if message["type"] == "audio" and message["format"].startswith("bytes"):
if isinstance(message, bytes) or (
message["type"] == "audio" and message["format"].startswith("bytes")
):
# Convert bytes to audio file
# audio_bytes = message["content"]
audio_bytes = message
# Create an AudioSegment instance with the raw data
audio = AudioSegment(
# raw audio data (bytes)
data=audio_bytes,
# signed 16-bit little-endian format
sample_width=2,
# 24,000 Hz frame rate
frame_rate=24000,
# mono sound
channels=1,
)
print("audio segment was created")
#await self.audiosegments.put(audio_bytes)
if self.tts_service == "elevenlabs":
audio_bytes = message
audio = audio_bytes
else:
audio_bytes = message["content"]
# Create an AudioSegment instance with the raw data
audio = AudioSegment(
# raw audio data (bytes)
data=audio_bytes,
# signed 16-bit little-endian format
sample_width=2,
# 16,000 Hz frame rate
frame_rate=22050,
# mono sound
channels=1,
)
await self.audiosegments.put(audio)
@ -425,7 +408,6 @@ class Device:
result = interpreter.computer.run(language, code)
send_queue.put(result)
"""
if is_win10():
logger.info("Windows 10 detected")
# Workaround for Windows 10 not latching to the websocket server.
@ -436,54 +418,29 @@ class Device:
except Exception as e:
logger.error(f"Error while attempting to connect: {e}")
else:
print("websocket url is", WS_URL)
i = 0
# while True:
# try:
# i += 1
# print("i is", i)
# # Hit the /ping endpoint
# ping_url = f"http://{self.server_url}/ping"
# response = requests.get(ping_url)
# print(response.text)
# # async with aiohttp.ClientSession() as session:
# # async with session.get(ping_url) as response:
# # print(f"Ping response: {await response.text()}")
for i in range(3):
print(i)
while True:
try:
async with websockets.connect(WS_URL) as websocket:
print("happi happi happi :DDDDDDDDDDDDD")
# await exec_ws_communication(websocket)
# print("exiting exec_ws_communication")
await exec_ws_communication(websocket)
except:
print("exception in websocket communication!!!!!!!!!!!!!!!!!")
traceback.print_exc()
# except:
# print("exception in websocket communication!!!!!!!!!!!!!!!!!")
# traceback.print_exc()
# if show_connection_log:
# logger.info(f"Connecting to `{WS_URL}`...")
# show_connection_log = False
# await asyncio.sleep(2)
logger.debug(traceback.format_exc())
if show_connection_log:
logger.info(f"Connecting to `{WS_URL}`...")
show_connection_log = False
await asyncio.sleep(2)
async def start_async(self):
print("start async was called!!!!!")
# Configuration for WebSocket
WS_URL = f"ws://{self.server_url}/"
WS_URL = f"ws://{self.server_url}"
# Start the WebSocket communication
await self.websocket_communication(WS_URL)
"""
# Start watching the kernel if it's your job to do that
if os.getenv("CODE_RUNNER") == "client":
# client is not running code!
asyncio.create_task(put_kernel_messages_into_queue(send_queue))
#asyncio.create_task(self.play_audiosegments())
asyncio.create_task(self.play_audiosegments())
# If Raspberry Pi, add the button listener, otherwise use the spacebar
if current_platform.startswith("raspberry-pi"):
@ -507,14 +464,13 @@ class Device:
else:
break
else:
"""
# Keyboard listener for spacebar press/release
# listener = keyboard.Listener(on_press=self.on_press, on_release=self.on_release)
# listener.start()
# print("listener for keyboard started!!!!!")
# Keyboard listener for spacebar press/release
listener = keyboard.Listener(
on_press=self.on_press, on_release=self.on_release
)
listener.start()
def start(self):
print("device was started!!!!!!")
if os.getenv("TEACH_MODE") != "True":
asyncio.run(self.start_async())
p.terminate()

3
software/source/clients/linux/device.py
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@ -3,8 +3,9 @@ from ..base_device import Device
device = Device()
def main(server_url):
def main(server_url, tts_service):
device.server_url = server_url
device.tts_service = tts_service
device.start()

3
software/source/clients/mac/device.py
Unescape View File

@ -3,8 +3,9 @@ from ..base_device import Device
device = Device()
def main(server_url):
def main(server_url, tts_service):
device.server_url = server_url
device.tts_service = tts_service
device.start()

3
software/source/clients/windows/device.py
Unescape View File

@ -3,8 +3,9 @@ from ..base_device import Device
device = Device()
def main(server_url):
def main(server_url, tts_service):
device.server_url = server_url
device.tts_service = tts_service
device.start()

175
software/source/server/async_interpreter.py
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@ -10,16 +10,9 @@
"""
###
from pynput import keyboard
from RealtimeTTS import (
TextToAudioStream,
OpenAIEngine,
CoquiEngine,
ElevenlabsEngine,
SystemEngine,
GTTSEngine,
)
from RealtimeTTS import TextToAudioStream, CoquiEngine, OpenAIEngine, ElevenlabsEngine
from RealtimeSTT import AudioToTextRecorder
import time
import asyncio
@ -29,9 +22,9 @@ import os
class AsyncInterpreter:
def __init__(self, interpreter):
self.stt_latency = None
self.tts_latency = None
self.interpreter_latency = None
# self.stt_latency = None
# self.tts_latency = None
# self.interpreter_latency = None
self.interpreter = interpreter
# STT
@ -45,12 +38,9 @@ class AsyncInterpreter:
engine = CoquiEngine()
elif self.interpreter.tts == "openai":
engine = OpenAIEngine()
elif self.interpreter.tts == "gtts":
engine = GTTSEngine()
elif self.interpreter.tts == "elevenlabs":
engine = ElevenlabsEngine(api_key=os.environ["ELEVEN_LABS_API_KEY"])
elif self.interpreter.tts == "system":
engine = SystemEngine()
engine.set_voice("Michael")
else:
raise ValueError(f"Unsupported TTS engine: {self.interpreter.tts}")
self.tts = TextToAudioStream(engine)
@ -112,103 +102,96 @@ class AsyncInterpreter:
# print("ADDING TO QUEUE:", chunk)
asyncio.create_task(self._add_to_queue(self._output_queue, chunk))
async def run(self):
"""
Runs OI on the audio bytes submitted to the input. Will add streaming LMC chunks to the _output_queue.
"""
def generate(self, message, start_interpreter):
last_lmc_start_flag = self._last_lmc_start_flag
self.interpreter.messages = self.active_chat_messages
self.stt.stop()
# message = self.stt.text()
# print("THE MESSAGE:", message)
# print("message is", message)
# accumulates the input queue message
input_queue = []
while not self._input_queue.empty():
input_queue.append(self._input_queue.get())
for chunk in self.interpreter.chat(message, display=True, stream=True):
# print("INPUT QUEUE:", input_queue)
# message = [i for i in input_queue if i["type"] == "message"][0]["content"]
start_stt = time.time()
message = self.stt.text()
end_stt = time.time()
self.stt_latency = end_stt - start_stt
print("STT LATENCY", self.stt_latency)
if self._last_lmc_start_flag != last_lmc_start_flag:
# self.beeper.stop()
break
def generate(message):
last_lmc_start_flag = self._last_lmc_start_flag
self.interpreter.messages = self.active_chat_messages
print("message is", message)
# self.add_to_output_queue_sync(chunk) # To send text, not just audio
for chunk in self.interpreter.chat(message, display=True, stream=True):
content = chunk.get("content")
if self._last_lmc_start_flag != last_lmc_start_flag:
# Handle message blocks
if chunk.get("type") == "message":
if content:
# self.beeper.stop()
break
# self.add_to_output_queue_sync(chunk) # To send text, not just audio
# Experimental: The AI voice sounds better with replacements like these, but it should happen at the TTS layer
# content = content.replace(". ", ". ... ").replace(", ", ", ... ").replace("!", "! ... ").replace("?", "? ... ")
# print("yielding ", content)
yield content
# Handle code blocks
elif chunk.get("type") == "code":
if "start" in chunk:
# self.beeper.start()
pass
# Experimental: If the AI wants to type, we should type immediatly
if (
self.interpreter.messages[-1]
.get("content", "")
.startswith("computer.keyboard.write(")
):
keyboard.controller.type(content)
self._in_keyboard_write_block = True
if "end" in chunk and self._in_keyboard_write_block:
self._in_keyboard_write_block = False
# (This will make it so it doesn't type twice when the block executes)
if self.interpreter.messages[-1]["content"].startswith(
"computer.keyboard.write("
):
self.interpreter.messages[-1]["content"] = (
"dummy_variable = ("
+ self.interpreter.messages[-1]["content"][
len("computer.keyboard.write(") :
]
)
# Send a completion signal
# end_interpreter = time.time()
# self.interpreter_latency = end_interpreter - start_interpreter
# print("INTERPRETER LATENCY", self.interpreter_latency)
# self.add_to_output_queue_sync({"role": "server","type": "completion", "content": "DONE"})
content = chunk.get("content")
async def run(self):
"""
Runs OI on the audio bytes submitted to the input. Will add streaming LMC chunks to the _output_queue.
"""
self.interpreter.messages = self.active_chat_messages
# Handle message blocks
if chunk.get("type") == "message":
if content:
# self.beeper.stop()
self.stt.stop()
# Experimental: The AI voice sounds better with replacements like these, but it should happen at the TTS layer
# content = content.replace(". ", ". ... ").replace(", ", ", ... ").replace("!", "! ... ").replace("?", "? ... ")
# print("yielding this", content)
yield content
input_queue = []
while not self._input_queue.empty():
input_queue.append(self._input_queue.get())
# Handle code blocks
elif chunk.get("type") == "code":
if "start" in chunk:
# self.beeper.start()
pass
# start_stt = time.time()
message = self.stt.text()
# end_stt = time.time()
# self.stt_latency = end_stt - start_stt
# print("STT LATENCY", self.stt_latency)
# Experimental: If the AI wants to type, we should type immediatly
if (
self.interpreter.messages[-1]
.get("content", "")
.startswith("computer.keyboard.write(")
):
keyboard.controller.type(content)
self._in_keyboard_write_block = True
if "end" in chunk and self._in_keyboard_write_block:
self._in_keyboard_write_block = False
# (This will make it so it doesn't type twice when the block executes)
if self.interpreter.messages[-1]["content"].startswith(
"computer.keyboard.write("
):
self.interpreter.messages[-1]["content"] = (
"dummy_variable = ("
+ self.interpreter.messages[-1]["content"][
len("computer.keyboard.write(") :
]
)
# Send a completion signal
end_interpreter = time.time()
self.interpreter_latency = end_interpreter - start_interpreter
print("INTERPRETER LATENCY", self.interpreter_latency)
# self.add_to_output_queue_sync({"role": "server","type": "completion", "content": "DONE"})
# print(message)
# Feed generate to RealtimeTTS
self.add_to_output_queue_sync(
{"role": "assistant", "type": "audio", "format": "bytes.wav", "start": True}
)
start_interpreter = time.time()
text_iterator = generate(message)
text_iterator = self.generate(message, start_interpreter)
self.tts.feed(text_iterator)
self.tts.play_async(on_audio_chunk=self.on_tts_chunk, muted=False)
while True:
if self.tts.is_playing():
start_tts = time.time()
self.tts.play_async(on_audio_chunk=self.on_tts_chunk, muted=True)
break
await asyncio.sleep(0.1)
while True:
await asyncio.sleep(0.1)
# print("is_playing", self.tts.is_playing())
@ -221,14 +204,14 @@ class AsyncInterpreter:
"end": True,
}
)
end_tts = time.time()
self.tts_latency = end_tts - start_tts
print("TTS LATENCY", self.tts_latency)
# end_tts = time.time()
# self.tts_latency = end_tts - self.tts.stream_start_time
# print("TTS LATENCY", self.tts_latency)
self.tts.stop()
break
async def _on_tts_chunk_async(self, chunk):
print(f"Adding chunk to output queue")
# print("adding chunk to queue")
await self._add_to_queue(self._output_queue, chunk)
def on_tts_chunk(self, chunk):
@ -236,7 +219,5 @@ class AsyncInterpreter:
asyncio.run(self._on_tts_chunk_async(chunk))
async def output(self):
print("entering output method")
value = await self._output_queue.get()
print("output method returning")
return value
# print("outputting chunks")
return await self._output_queue.get()

38
software/source/server/async_server.py
Unescape View File

@ -1,37 +1,39 @@
import asyncio
import traceback
import json
from fastapi import FastAPI, WebSocket, Header
from fastapi import FastAPI, WebSocket
from fastapi.responses import PlainTextResponse
from uvicorn import Config, Server
from .i import configure_interpreter
from interpreter import interpreter as base_interpreter
from starlette.websockets import WebSocketDisconnect
from .async_interpreter import AsyncInterpreter
from fastapi.middleware.cors import CORSMiddleware
from typing import List, Dict, Any
from openai import OpenAI
from pydantic import BaseModel
import argparse
import os
# import sentry_sdk
base_interpreter.system_message = (
"You are a helpful assistant that can answer questions and help with tasks."
)
base_interpreter.computer.import_computer_api = False
base_interpreter.llm.model = "groq/llama3-8b-8192"
base_interpreter.llm.api_key = os.environ["GROQ_API_KEY"]
base_interpreter.llm.supports_functions = False
base_interpreter.auto_run = True
base_interpreter.tts = "elevenlabs"
os.environ["STT_RUNNER"] = "server"
os.environ["TTS_RUNNER"] = "server"
async def main(server_host, server_port):
interpreter = AsyncInterpreter(base_interpreter)
async def main(server_host, server_port, tts_service, asynchronous):
if asynchronous:
base_interpreter.system_message = (
"You are a helpful assistant that can answer questions and help with tasks."
)
base_interpreter.computer.import_computer_api = False
base_interpreter.llm.model = "groq/llama3-8b-8192"
base_interpreter.llm.api_key = os.environ["GROQ_API_KEY"]
base_interpreter.llm.supports_functions = False
base_interpreter.auto_run = True
base_interpreter.tts = tts_service
interpreter = AsyncInterpreter(base_interpreter)
else:
configured_interpreter = configure_interpreter(base_interpreter)
configured_interpreter.llm.supports_functions = True
configured_interpreter.tts = tts_service
interpreter = AsyncInterpreter(configured_interpreter)
app = FastAPI()
@ -93,7 +95,7 @@ async def main(server_host, server_port):
async def receive_input():
try:
while True:
print("server awaiting input")
# print("server awaiting input")
data = await websocket.receive()
if isinstance(data, bytes):

24
software/start.py
Unescape View File

@ -6,6 +6,8 @@ import os
import importlib
from source.server.tunnel import create_tunnel
from source.server.async_server import main
# from source.server.server import main
from source.server.utils.local_mode import select_local_model
import signal
@ -63,7 +65,7 @@ def run(
0.8, "--temperature", help="Specify the temperature for generation"
),
tts_service: str = typer.Option(
"openai", "--tts-service", help="Specify the TTS service"
"elevenlabs", "--tts-service", help="Specify the TTS service"
),
stt_service: str = typer.Option(
"openai", "--stt-service", help="Specify the STT service"
@ -75,6 +77,9 @@ def run(
mobile: bool = typer.Option(
False, "--mobile", help="Toggle server to support mobile app"
),
asynchronous: bool = typer.Option(
False, "--async", help="use interpreter optimized for latency"
),
):
_run(
server=server or mobile,
@ -97,6 +102,7 @@ def run(
local=local,
qr=qr or mobile,
mobile=mobile,
asynchronous=asynchronous,
)
@ -116,14 +122,15 @@ def _run(
context_window: int = 2048,
max_tokens: int = 4096,
temperature: float = 0.8,
tts_service: str = "openai",
tts_service: str = "elevenlabs",
stt_service: str = "openai",
local: bool = False,
qr: bool = False,
mobile: bool = False,
asynchronous: bool = False,
):
if local:
tts_service = "piper"
tts_service = "coqui"
# llm_service = "llamafile"
stt_service = "local-whisper"
select_local_model()
@ -154,6 +161,8 @@ def _run(
main(
server_host,
server_port,
tts_service,
asynchronous,
# llm_service,
# model,
# llm_supports_vision,
@ -161,7 +170,6 @@ def _run(
# context_window,
# max_tokens,
# temperature,
# tts_service,
# stt_service,
# mobile,
),
@ -180,7 +188,6 @@ def _run(
system_type = platform.system()
if system_type == "Darwin": # Mac OS
client_type = "mac"
print("initiating mac device with base device!!!")
elif system_type == "Windows": # Windows System
client_type = "windows"
elif system_type == "Linux": # Linux System
@ -196,9 +203,10 @@ def _run(
module = importlib.import_module(
f".clients.{client_type}.device", package="source"
)
# server_url = "0.0.0.0:8000"
client_thread = threading.Thread(target=module.main, args=[server_url])
print("client thread started")
client_thread = threading.Thread(
target=module.main, args=[server_url, tts_service]
)
client_thread.start()
try:

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