fix for stt-server (got broken by webserver update)

RealtimeSTT/audio_recorder.py

@@ -139,8 +139,13 @@ def run(self):
                 device_index=self.gpu_device_index,
                 download_root=self.download_root,
             )
+            # Create a short dummy audio array, for example 1 second of silence at 16 kHz
             if self.batch_size > 0:
                 model = BatchedInferencePipeline(model=model)
+
+            # Run a warm-up transcription
+            dummy_audio = np.zeros(16000, dtype=np.float32)
+            model.transcribe(dummy_audio, language="en", beam_size=1)
         except Exception as e:
             logging.exception(f"Error initializing main faster_whisper transcription model: {e}")
             raise
@@ -281,6 +286,7 @@ def __init__(self,
                  buffer_size: int = BUFFER_SIZE,
                  sample_rate: int = SAMPLE_RATE,
                  initial_prompt: Optional[Union[str, Iterable[int]]] = None,
+                 initial_prompt_realtime: Optional[Union[str, Iterable[int]]] = None,
                  suppress_tokens: Optional[List[int]] = [-1],
                  print_transcription_time: bool = False,
                  early_transcription_on_silence: int = 0,
@@ -294,12 +300,12 @@ def __init__(self,
 
         Args:
         - model (str, default="tiny"): Specifies the size of the transcription
-          model to use or the path to a converted model directory.
-                Valid options are 'tiny', 'tiny.en', 'base', 'base.en',
-                'small', 'small.en', 'medium', 'medium.en', 'large-v1',
-                'large-v2'.
-                If a specific size is provided, the model is downloaded
-                from the Hugging Face Hub.
+            model to use or the path to a converted model directory.
+            Valid options are 'tiny', 'tiny.en', 'base', 'base.en',
+            'small', 'small.en', 'medium', 'medium.en', 'large-v1',
+            'large-v2'.
+            If a specific size is provided, the model is downloaded
+            from the Hugging Face Hub.
         - download_root (str, default=None): Specifies the root path were the Whisper models 
           are downloaded to. When empty, the default is used. 
         - language (str, default=""): Language code for speech-to-text engine.
@@ -472,7 +478,9 @@ def __init__(self,
             recording. Changing this will very probably functionality (as the
             WebRTC VAD model is very sensitive towards the sample rate).
         - initial_prompt (str or iterable of int, default=None): Initial
-            prompt to be fed to the transcription models.
+            prompt to be fed to the main transcription model.
+        - initial_prompt_realtime (str or iterable of int, default=None):
+            Initial prompt to be fed to the real-time transcription model.
         - suppress_tokens (list of int, default=[-1]): Tokens to be suppressed
             from the transcription output.
         - print_transcription_time (bool, default=False): Logs processing time
@@ -533,6 +541,8 @@ def __init__(self,
         self.enable_realtime_transcription = enable_realtime_transcription
         self.use_main_model_for_realtime = use_main_model_for_realtime
         self.main_model_type = model
+        if not download_root:
+            download_root = None
         self.download_root = download_root
         self.realtime_model_type = realtime_model_type
         self.realtime_processing_pause = realtime_processing_pause
@@ -583,6 +593,7 @@ def __init__(self,
         self.last_transcription_bytes = None
         self.last_transcription_bytes_b64 = None
         self.initial_prompt = initial_prompt
+        self.initial_prompt_realtime = initial_prompt_realtime
         self.suppress_tokens = suppress_tokens
         self.use_wake_words = wake_words or wakeword_backend in {'oww', 'openwakeword', 'openwakewords'}
         self.detected_language = None
@@ -697,7 +708,11 @@ def __init__(self,
         if self.enable_realtime_transcription and not self.use_main_model_for_realtime:
             try:
                 logging.info("Initializing faster_whisper realtime "
-                             f"transcription model {self.realtime_model_type}"
+                             f"transcription model {self.realtime_model_type}, "
+                             f"default device: {self.device}, "
+                             f"compute type: {self.compute_type}, "
+                             f"device index: {self.gpu_device_index}, "
+                             f"download root: {self.download_root}"
                              )
                 self.realtime_model_type = faster_whisper.WhisperModel(
                     model_size_or_path=self.realtime_model_type,
@@ -708,7 +723,8 @@ def __init__(self,
                 )
                 if self.realtime_batch_size > 0:
                     self.realtime_model_type = BatchedInferencePipeline(model=self.realtime_model_type)
-
+                dummy_audio = np.zeros(16000, dtype=np.float32)
+                self.realtime_model_type.transcribe(dummy_audio, language="en", beam_size=1)
             except Exception as e:
                 logging.exception("Error initializing faster_whisper "
                                   f"realtime transcription model: {e}"
@@ -2104,7 +2120,7 @@ def _realtime_worker(self):
                                 audio_array,
                                 language=self.language if self.language else None,
                                 beam_size=self.beam_size_realtime,
-                                initial_prompt=self.initial_prompt,
+                                initial_prompt=self.initial_prompt_realtime,
                                 suppress_tokens=self.suppress_tokens,
                                 batch_size=self.realtime_batch_size
                             )
@@ -2113,7 +2129,7 @@ def _realtime_worker(self):
                                 audio_array,
                                 language=self.language if self.language else None,
                                 beam_size=self.beam_size_realtime,
-                                initial_prompt=self.initial_prompt,
+                                initial_prompt=self.initial_prompt_realtime,
                                 suppress_tokens=self.suppress_tokens
                             )
 

RealtimeSTT/audio_recorder_client.py

@@ -28,6 +28,7 @@
 INIT_MODEL_TRANSCRIPTION = "tiny"
 INIT_MODEL_TRANSCRIPTION_REALTIME = "tiny"
 INIT_REALTIME_PROCESSING_PAUSE = 0.2
+INIT_REALTIME_INITIAL_PAUSE = 0.2
 INIT_SILERO_SENSITIVITY = 0.4
 INIT_WEBRTC_SENSITIVITY = 3
 INIT_POST_SPEECH_SILENCE_DURATION = 0.6
@@ -68,6 +69,7 @@ class AudioToTextRecorderClient:
 
     def __init__(self,
                  model: str = INIT_MODEL_TRANSCRIPTION,
+                 download_root: str = None, 
                  language: str = "",
                  compute_type: str = "default",
                  input_device_index: int = None,
@@ -81,14 +83,17 @@ def __init__(self,
                  use_microphone=True,
                  spinner=True,
                  level=logging.WARNING,
+                 batch_size: int = 16,
 
                  # Realtime transcription parameters
                  enable_realtime_transcription=False,
                  use_main_model_for_realtime=False,
                  realtime_model_type=INIT_MODEL_TRANSCRIPTION_REALTIME,
                  realtime_processing_pause=INIT_REALTIME_PROCESSING_PAUSE,
+                 init_realtime_after_seconds=INIT_REALTIME_INITIAL_PAUSE,
                  on_realtime_transcription_update=None,
                  on_realtime_transcription_stabilized=None,
+                 realtime_batch_size: int = 16,
 
                  # Voice activation parameters
                  silero_sensitivity: float = INIT_SILERO_SENSITIVITY,
@@ -133,6 +138,7 @@ def __init__(self,
                  buffer_size: int = BUFFER_SIZE,
                  sample_rate: int = SAMPLE_RATE,
                  initial_prompt: Optional[Union[str, Iterable[int]]] = None,
+                 initial_prompt_realtime: Optional[Union[str, Iterable[int]]] = None,
                  suppress_tokens: Optional[List[int]] = [-1],
                  print_transcription_time: bool = False,
                  early_transcription_on_silence: int = 0,
@@ -162,10 +168,14 @@ def __init__(self,
         self.use_microphone = use_microphone
         self.spinner = spinner
         self.level = level
+        self.batch_size = batch_size
+        self.init_realtime_after_seconds = init_realtime_after_seconds
+        self.realtime_batch_size = realtime_batch_size
 
         # Real-time transcription parameters
         self.enable_realtime_transcription = enable_realtime_transcription
         self.use_main_model_for_realtime = use_main_model_for_realtime
+        self.download_root = download_root
         self.realtime_model_type = realtime_model_type
         self.realtime_processing_pause = realtime_processing_pause
         self.on_realtime_transcription_update = on_realtime_transcription_update
@@ -204,6 +214,7 @@ def __init__(self,
         self.buffer_size = buffer_size
         self.sample_rate = sample_rate
         self.initial_prompt = initial_prompt
+        self.initial_prompt_realtime = initial_prompt_realtime
         self.suppress_tokens = suppress_tokens
         self.print_transcription_time = print_transcription_time
         self.early_transcription_on_silence = early_transcription_on_silence
@@ -376,6 +387,43 @@ def start_server(self):
             args += ['--model', self.model]
         if self.realtime_model_type:
             args += ['--realtime_model_type', self.realtime_model_type]
+        if self.download_root:
+            args += ['--root', self.download_root]
+        if self.batch_size is not None:
+            args += ['--batch', str(self.batch_size)]
+        if self.realtime_batch_size is not None:
+            args += ['--realtime_batch_size', str(self.realtime_batch_size)]
+        if self.init_realtime_after_seconds is not None:
+            args += ['--init_realtime_after_seconds', str(self.init_realtime_after_seconds)]
+        if self.initial_prompt_realtime:
+            sanitized_prompt = self.initial_prompt_realtime.replace("\n", "\\n")
+            args += ['--initial_prompt_realtime', sanitized_prompt]
+
+        # if self.compute_type:
+        #     args += ['--compute_type', self.compute_type]
+        # if self.input_device_index is not None:
+        #     args += ['--input_device_index', str(self.input_device_index)]
+        # if self.gpu_device_index is not None:
+        #     args += ['--gpu_device_index', str(self.gpu_device_index)]
+        # if self.device:
+        #     args += ['--device', self.device]
+        # if self.spinner:
+        #     args.append('--spinner')  # flag, no need for True/False
+        # if self.enable_realtime_transcription:
+        #     args.append('--enable_realtime_transcription')  # flag, no need for True/False
+        # if self.handle_buffer_overflow:
+        #     args.append('--handle_buffer_overflow')  # flag, no need for True/False
+        # if self.suppress_tokens:
+        #     args += ['--suppress_tokens', str(self.suppress_tokens)]
+        # if self.print_transcription_time:
+        #     args.append('--print_transcription_time')  # flag, no need for True/False
+        # if self.allowed_latency_limit is not None:
+        #     args += ['--allowed_latency_limit', str(self.allowed_latency_limit)]
+        # if self.no_log_file:
+        #     args.append('--no_log_file')  # flag, no need for True
+        # if self.debug_mode:
+        #     args.append('--debug')  # flag, no need for True/False
+
         if self.language:
             args += ['--language', self.language]
         if self.silero_sensitivity is not None: