Revert "Test pypi upload"

whisper_live/client.py

@@ -233,15 +233,10 @@ class Client:
             print(element)
 
     def on_error(self, ws, error):
-        print(f"[ERROR] WebSocket Error: {error}")
-        self.server_error = True
-        self.error_message = error
+        print(error)
 
     def on_close(self, ws, close_status_code, close_msg):
         print(f"[INFO]: Websocket connection closed: {close_status_code}: {close_msg}")
-        self.recording = False
-        self.server_error = False
-        self.waiting = False
 
     def on_open(self, ws):
         """

whisper_live/server.py

@@ -1,4 +1,5 @@
 import os
+import websockets
 import time
 import threading
 import json
@@ -11,8 +12,10 @@ from websockets.sync.server import serve
 
 import torch
 import numpy as np
+import queue
 
 from whisper_live.vad import VoiceActivityDetection
+from scipy.io.wavfile import write
 import functools
 
 from whisper_live.vad import VoiceActivityDetection
@@ -20,7 +23,7 @@ from whisper_live.transcriber import WhisperModel
 try:
     from whisper_live.transcriber_tensorrt import WhisperTRTLLM
 except Exception as e:
-    pass
+    logging.warn("cannot import WhisperTRTLLM")
 
 
 class TranscriptionServer:

whisper_live/vad.py

@@ -10,7 +10,9 @@ import onnxruntime
 class VoiceActivityDetection():
 
     def __init__(self, force_onnx_cpu=True):
+        print("downloading ONNX model...")
         path = self.download()
+        print("loading session")
 
         opts = onnxruntime.SessionOptions()
         opts.log_severity_level = 3
@@ -18,11 +20,13 @@ class VoiceActivityDetection():
         opts.inter_op_num_threads = 1
         opts.intra_op_num_threads = 1
 
+        print("loading onnx model")
         if force_onnx_cpu and 'CPUExecutionProvider' in onnxruntime.get_available_providers():
             self.session = onnxruntime.InferenceSession(path, providers=['CPUExecutionProvider'], sess_options=opts)
         else:
             self.session = onnxruntime.InferenceSession(path, providers=['CUDAExecutionProvider'], sess_options=opts)
 
+        print("reset states")
         self.reset_states()
         self.sample_rates = [8000, 16000]
 
@@ -106,6 +110,7 @@ class VoiceActivityDetection():
         # Check if the model file already exists
         if not os.path.exists(model_filename):
             # If it doesn't exist, download the model using wget
+            print("Downloading VAD ONNX model...")
             try:
                 subprocess.run(["wget", "-O", model_filename, model_url], check=True)
             except subprocess.CalledProcessError: