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import os | |
import wave | |
import numpy as np | |
import scipy | |
import ffmpeg | |
import pyaudio | |
import threading | |
import textwrap | |
import json | |
import websocket | |
import uuid | |
import time | |
def resample(file: str, sr: int = 16000): | |
""" | |
# https://github.com/openai/whisper/blob/7858aa9c08d98f75575035ecd6481f462d66ca27/whisper/audio.py#L22 | |
Open an audio file and read as mono waveform, resampling as necessary, | |
save the resampled audio | |
Args: | |
file (str): The audio file to open | |
sr (int): The sample rate to resample the audio if necessary | |
Returns: | |
resampled_file (str): The resampled audio file | |
""" | |
try: | |
# This launches a subprocess to decode audio while down-mixing and resampling as necessary. | |
# Requires the ffmpeg CLI and `ffmpeg-python` package to be installed. | |
out, _ = ( | |
ffmpeg.input(file, threads=0) | |
.output("-", format="s16le", acodec="pcm_s16le", ac=1, ar=sr) | |
.run(cmd=["ffmpeg", "-nostdin"], capture_stdout=True, capture_stderr=True) | |
) | |
except ffmpeg.Error as e: | |
raise RuntimeError(f"Failed to load audio: {e.stderr.decode()}") from e | |
np_buffer = np.frombuffer(out, dtype=np.int16) | |
resampled_file = f"{file.split('.')[0]}_resampled.wav" | |
scipy.io.wavfile.write(resampled_file, sr, np_buffer.astype(np.int16)) | |
return resampled_file | |
class Client: | |
""" | |
Handles audio recording, streaming, and communication with a server using WebSocket. | |
""" | |
INSTANCES = {} | |
def __init__( | |
self, host=None, port=None, is_multilingual=False, lang=None, translate=False, model_size="small" | |
): | |
""" | |
Initializes a Client instance for audio recording and streaming to a server. | |
If host and port are not provided, the WebSocket connection will not be established. | |
When translate is True, the task will be set to "translate" instead of "transcribe". | |
he audio recording starts immediately upon initialization. | |
Args: | |
host (str): The hostname or IP address of the server. | |
port (int): The port number for the WebSocket server. | |
is_multilingual (bool, optional): Specifies if multilingual transcription is enabled. Default is False. | |
lang (str, optional): The selected language for transcription when multilingual is disabled. Default is None. | |
translate (bool, optional): Specifies if the task is translation. Default is False. | |
""" | |
self.chunk = 1024 * 3 | |
self.format = pyaudio.paInt16 | |
self.channels = 1 | |
self.rate = 16000 | |
self.record_seconds = 60000 | |
self.recording = False | |
self.multilingual = False | |
self.language = None | |
self.task = "transcribe" | |
self.uid = str(uuid.uuid4()) | |
self.waiting = False | |
self.last_response_recieved = None | |
self.disconnect_if_no_response_for = 15 | |
self.multilingual = is_multilingual | |
self.language = lang | |
self.model_size = model_size | |
self.server_error = False | |
if translate: | |
self.task = "translate" | |
self.timestamp_offset = 0.0 | |
self.audio_bytes = None | |
self.p = pyaudio.PyAudio() | |
self.stream = self.p.open( | |
format=self.format, | |
channels=self.channels, | |
rate=self.rate, | |
input=True, | |
frames_per_buffer=self.chunk, | |
) | |
if host is not None and port is not None: | |
socket_url = f"ws://{host}:{port}" | |
self.client_socket = websocket.WebSocketApp( | |
socket_url, | |
on_open=lambda ws: self.on_open(ws), | |
on_message=lambda ws, message: self.on_message(ws, message), | |
on_error=lambda ws, error: self.on_error(ws, error), | |
on_close=lambda ws, close_status_code, close_msg: self.on_close( | |
ws, close_status_code, close_msg | |
), | |
) | |
else: | |
print("[ERROR]: No host or port specified.") | |
return | |
Client.INSTANCES[self.uid] = self | |
# start websocket client in a thread | |
self.ws_thread = threading.Thread(target=self.client_socket.run_forever) | |
self.ws_thread.setDaemon(True) | |
self.ws_thread.start() | |
self.frames = b"" | |
print("[INFO]: * recording") | |
def on_message(self, ws, message): | |
""" | |
Callback function called when a message is received from the server. | |
It updates various attributes of the client based on the received message, including | |
recording status, language detection, and server messages. If a disconnect message | |
is received, it sets the recording status to False. | |
Args: | |
ws (websocket.WebSocketApp): The WebSocket client instance. | |
message (str): The received message from the server. | |
""" | |
self.last_response_recieved = time.time() | |
message = json.loads(message) | |
if self.uid != message.get("uid"): | |
print("[ERROR]: invalid client uid") | |
return | |
if "status" in message.keys(): | |
if message["status"] == "WAIT": | |
self.waiting = True | |
print( | |
f"[INFO]:Server is full. Estimated wait time {round(message['message'])} minutes." | |
) | |
elif message["status"] == "ERROR": | |
print(f"Message from Server: {message['message']}") | |
self.server_error = True | |
return | |
if "message" in message.keys() and message["message"] == "DISCONNECT": | |
print("[INFO]: Server overtime disconnected.") | |
self.recording = False | |
if "message" in message.keys() and message["message"] == "SERVER_READY": | |
self.recording = True | |
return | |
if "language" in message.keys(): | |
self.language = message.get("language") | |
lang_prob = message.get("language_prob") | |
print( | |
f"[INFO]: Server detected language {self.language} with probability {lang_prob}" | |
) | |
return | |
if "llm_output" in message.keys(): | |
print("LLM output: ") | |
for item in message["llm_output"]: | |
print(item) | |
if "segments" not in message.keys(): | |
return | |
message = message["segments"] | |
text = [] | |
print(message) | |
if len(message): | |
for seg in message: | |
if text and text[-1] == seg["text"]: | |
# already got it | |
continue | |
text.append(seg["text"]) | |
# keep only last 3 | |
if len(text) > 3: | |
text = text[-3:] | |
wrapper = textwrap.TextWrapper(width=60) | |
word_list = wrapper.wrap(text="".join(text)) | |
# Print each line. | |
if os.name == "nt": | |
os.system("cls") | |
else: | |
os.system("clear") | |
for element in word_list: | |
print(element) | |
def on_error(self, ws, error): | |
print(error) | |
def on_close(self, ws, close_status_code, close_msg): | |
print(f"[INFO]: Websocket connection closed: {close_status_code}: {close_msg}") | |
def on_open(self, ws): | |
""" | |
Callback function called when the WebSocket connection is successfully opened. | |
Sends an initial configuration message to the server, including client UID, multilingual mode, | |
language selection, and task type. | |
Args: | |
ws (websocket.WebSocketApp): The WebSocket client instance. | |
""" | |
print(self.multilingual, self.language, self.task) | |
print("[INFO]: Opened connection") | |
ws.send( | |
json.dumps( | |
{ | |
"uid": self.uid, | |
"multilingual": self.multilingual, | |
"language": self.language, | |
"task": self.task, | |
"model_size": self.model_size, | |
} | |
) | |
) | |
def bytes_to_float_array(audio_bytes): | |
""" | |
Convert audio data from bytes to a NumPy float array. | |
It assumes that the audio data is in 16-bit PCM format. The audio data is normalized to | |
have values between -1 and 1. | |
Args: | |
audio_bytes (bytes): Audio data in bytes. | |
Returns: | |
np.ndarray: A NumPy array containing the audio data as float values normalized between -1 and 1. | |
""" | |
raw_data = np.frombuffer(buffer=audio_bytes, dtype=np.int16) | |
return raw_data.astype(np.float32) / 32768.0 | |
def send_packet_to_server(self, message): | |
""" | |
Send an audio packet to the server using WebSocket. | |
Args: | |
message (bytes): The audio data packet in bytes to be sent to the server. | |
""" | |
try: | |
self.client_socket.send(message, websocket.ABNF.OPCODE_BINARY) | |
except Exception as e: | |
print(e) | |
def play_file(self, filename): | |
""" | |
Play an audio file and send it to the server for processing. | |
Reads an audio file, plays it through the audio output, and simultaneously sends | |
the audio data to the server for processing. It uses PyAudio to create an audio | |
stream for playback. The audio data is read from the file in chunks, converted to | |
floating-point format, and sent to the server using WebSocket communication. | |
This method is typically used when you want to process pre-recorded audio and send it | |
to the server in real-time. | |
Args: | |
filename (str): The path to the audio file to be played and sent to the server. | |
""" | |
# read audio and create pyaudio stream | |
with wave.open(filename, "rb") as wavfile: | |
self.stream = self.p.open( | |
format=self.p.get_format_from_width(wavfile.getsampwidth()), | |
channels=wavfile.getnchannels(), | |
rate=wavfile.getframerate(), | |
input=True, | |
output=True, | |
frames_per_buffer=self.chunk, | |
) | |
try: | |
while self.recording: | |
data = wavfile.readframes(self.chunk) | |
if data == b"": | |
break | |
audio_array = self.bytes_to_float_array(data) | |
self.send_packet_to_server(audio_array.tobytes()) | |
self.stream.write(data) | |
wavfile.close() | |
assert self.last_response_recieved | |
while time.time() - self.last_response_recieved < self.disconnect_if_no_response_for: | |
continue | |
self.stream.close() | |
self.close_websocket() | |
except KeyboardInterrupt: | |
wavfile.close() | |
self.stream.stop_stream() | |
self.stream.close() | |
self.p.terminate() | |
self.close_websocket() | |
print("[INFO]: Keyboard interrupt.") | |
def close_websocket(self): | |
""" | |
Close the WebSocket connection and join the WebSocket thread. | |
First attempts to close the WebSocket connection using `self.client_socket.close()`. After | |
closing the connection, it joins the WebSocket thread to ensure proper termination. | |
""" | |
try: | |
self.client_socket.close() | |
except Exception as e: | |
print("[ERROR]: Error closing WebSocket:", e) | |
try: | |
self.ws_thread.join() | |
except Exception as e: | |
print("[ERROR:] Error joining WebSocket thread:", e) | |
def get_client_socket(self): | |
""" | |
Get the WebSocket client socket instance. | |
Returns: | |
WebSocketApp: The WebSocket client socket instance currently in use by the client. | |
""" | |
return self.client_socket | |
def write_audio_frames_to_file(self, frames, file_name): | |
""" | |
Write audio frames to a WAV file. | |
The WAV file is created or overwritten with the specified name. The audio frames should be | |
in the correct format and match the specified channel, sample width, and sample rate. | |
Args: | |
frames (bytes): The audio frames to be written to the file. | |
file_name (str): The name of the WAV file to which the frames will be written. | |
""" | |
with wave.open(file_name, "wb") as wavfile: | |
wavfile: wave.Wave_write | |
wavfile.setnchannels(self.channels) | |
wavfile.setsampwidth(2) | |
wavfile.setframerate(self.rate) | |
wavfile.writeframes(frames) | |
def process_hls_stream(self, hls_url): | |
""" | |
Connect to an HLS source, process the audio stream, and send it for transcription. | |
Args: | |
hls_url (str): The URL of the HLS stream source. | |
""" | |
print("[INFO]: Connecting to HLS stream...") | |
process = None # Initialize process to None | |
try: | |
# Connecting to the HLS stream using ffmpeg-python | |
process = ( | |
ffmpeg | |
.input(hls_url, threads=0) | |
.output('-', format='s16le', acodec='pcm_s16le', ac=1, ar=self.rate) | |
.run_async(pipe_stdout=True, pipe_stderr=True) | |
) | |
# Process the stream | |
while True: | |
in_bytes = process.stdout.read(self.chunk * 2) # 2 bytes per sample | |
if not in_bytes: | |
break | |
audio_array = self.bytes_to_float_array(in_bytes) | |
self.send_packet_to_server(audio_array.tobytes()) | |
except Exception as e: | |
print(f"[ERROR]: Failed to connect to HLS stream: {e}") | |
finally: | |
if process: | |
process.kill() | |
print("[INFO]: HLS stream processing finished.") | |
def record(self, out_file="output_recording.wav"): | |
""" | |
Record audio data from the input stream and save it to a WAV file. | |
Continuously records audio data from the input stream, sends it to the server via a WebSocket | |
connection, and simultaneously saves it to multiple WAV files in chunks. It stops recording when | |
the `RECORD_SECONDS` duration is reached or when the `RECORDING` flag is set to `False`. | |
Audio data is saved in chunks to the "chunks" directory. Each chunk is saved as a separate WAV file. | |
The recording will continue until the specified duration is reached or until the `RECORDING` flag is set to `False`. | |
The recording process can be interrupted by sending a KeyboardInterrupt (e.g., pressing Ctrl+C). After recording, | |
the method combines all the saved audio chunks into the specified `out_file`. | |
Args: | |
out_file (str, optional): The name of the output WAV file to save the entire recording. Default is "output_recording.wav". | |
""" | |
n_audio_file = 0 | |
if not os.path.exists("chunks"): | |
os.makedirs("chunks", exist_ok=True) | |
try: | |
for _ in range(0, int(self.rate / self.chunk * self.record_seconds)): | |
if not self.recording: | |
break | |
data = self.stream.read(self.chunk) | |
self.frames += data | |
audio_array = Client.bytes_to_float_array(data) | |
self.send_packet_to_server(audio_array.tobytes()) | |
# save frames if more than a minute | |
if len(self.frames) > 60 * self.rate: | |
t = threading.Thread( | |
target=self.write_audio_frames_to_file, | |
args=( | |
self.frames[:], | |
f"chunks/{n_audio_file}.wav", | |
), | |
) | |
t.start() | |
n_audio_file += 1 | |
self.frames = b"" | |
except KeyboardInterrupt: | |
if len(self.frames): | |
self.write_audio_frames_to_file( | |
self.frames[:], f"chunks/{n_audio_file}.wav" | |
) | |
n_audio_file += 1 | |
self.stream.stop_stream() | |
self.stream.close() | |
self.p.terminate() | |
self.close_websocket() | |
self.write_output_recording(n_audio_file, out_file) | |
def write_output_recording(self, n_audio_file, out_file): | |
""" | |
Combine and save recorded audio chunks into a single WAV file. | |
The individual audio chunk files are expected to be located in the "chunks" directory. Reads each chunk | |
file, appends its audio data to the final recording, and then deletes the chunk file. After combining | |
and saving, the final recording is stored in the specified `out_file`. | |
Args: | |
n_audio_file (int): The number of audio chunk files to combine. | |
out_file (str): The name of the output WAV file to save the final recording. | |
""" | |
input_files = [ | |
f"chunks/{i}.wav" | |
for i in range(n_audio_file) | |
if os.path.exists(f"chunks/{i}.wav") | |
] | |
with wave.open(out_file, "wb") as wavfile: | |
wavfile: wave.Wave_write | |
wavfile.setnchannels(self.channels) | |
wavfile.setsampwidth(2) | |
wavfile.setframerate(self.rate) | |
for in_file in input_files: | |
with wave.open(in_file, "rb") as wav_in: | |
while True: | |
data = wav_in.readframes(self.chunk) | |
if data == b"": | |
break | |
wavfile.writeframes(data) | |
# remove this file | |
os.remove(in_file) | |
wavfile.close() | |
class TranscriptionClient: | |
""" | |
Client for handling audio transcription tasks via a WebSocket connection. | |
Acts as a high-level client for audio transcription tasks using a WebSocket connection. It can be used | |
to send audio data for transcription to a server and receive transcribed text segments. | |
Args: | |
host (str): The hostname or IP address of the server. | |
port (int): The port number to connect to on the server. | |
is_multilingual (bool, optional): Indicates whether the transcription should support multiple languages (default is False). | |
lang (str, optional): The primary language for transcription (used if `is_multilingual` is False). Default is None, which defaults to English ('en'). | |
translate (bool, optional): Indicates whether translation tasks are required (default is False). | |
Attributes: | |
client (Client): An instance of the underlying Client class responsible for handling the WebSocket connection. | |
Example: | |
To create a TranscriptionClient and start transcription on microphone audio: | |
```python | |
transcription_client = TranscriptionClient(host="localhost", port=9090, is_multilingual=True) | |
transcription_client() | |
``` | |
""" | |
def __init__(self, host, port, is_multilingual=False, lang=None, translate=False, model_size="small"): | |
self.client = Client(host, port, is_multilingual, lang, translate, model_size) | |
def __call__(self, audio=None, hls_url=None): | |
""" | |
Start the transcription process. | |
Initiates the transcription process by connecting to the server via a WebSocket. It waits for the server | |
to be ready to receive audio data and then sends audio for transcription. If an audio file is provided, it | |
will be played and streamed to the server; otherwise, it will perform live recording. | |
Args: | |
audio (str, optional): Path to an audio file for transcription. Default is None, which triggers live recording. | |
""" | |
print("[INFO]: Waiting for server ready ...") | |
while not self.client.recording: | |
if self.client.waiting or self.client.server_error: | |
self.client.close_websocket() | |
return | |
print("[INFO]: Server Ready!") | |
if hls_url is not None: | |
self.client.process_hls_stream(hls_url) | |
elif audio is not None: | |
resampled_file = resample(audio) | |
self.client.play_file(resampled_file) | |
else: | |
self.client.record() |