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@@ -66,7 +66,13 @@ The server will broadcast real-time transcription updates to all connected clien
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"""
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+extended_logging = True
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+send_recorded_chunk = False
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+log_incoming_chunks = False
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+
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+
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import asyncio
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+import base64
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import sys
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if sys.platform == 'win32':
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@@ -95,7 +101,19 @@ check_and_install_packages([
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}
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])
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-print("Starting server, please wait...")
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+# Define ANSI color codes for terminal output
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+class bcolors:
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+ HEADER = '\033[95m' # Magenta
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+ OKBLUE = '\033[94m' # Blue
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+ OKCYAN = '\033[96m' # Cyan
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+ OKGREEN = '\033[92m' # Green
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+ WARNING = '\033[93m' # Yellow
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+ FAIL = '\033[91m' # Red
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+ ENDC = '\033[0m' # Reset to default
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+ BOLD = '\033[1m'
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+ UNDERLINE = '\033[4m'
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+
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+print(f"{bcolors.BOLD}{bcolors.OKCYAN}Starting server, please wait...{bcolors.ENDC}")
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import threading
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import json
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@@ -175,7 +193,10 @@ def text_detected(text, loop):
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'text': text
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})
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asyncio.run_coroutine_threadsafe(audio_queue.put(message), loop)
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- print(f"\r{text}", flush=True, end='')
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+ if extended_logging:
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+ print(f"Realtime text: {bcolors.OKCYAN}{text}{bcolors.ENDC}\n", flush=True, end="")
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+ else:
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+ print(f"\r{bcolors.OKCYAN}{text}{bcolors.ENDC}", flush=True, end='')
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def on_recording_start(loop):
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# Send a message to the client indicating recording has started
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@@ -197,6 +218,19 @@ def on_vad_detect_start(loop):
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})
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asyncio.run_coroutine_threadsafe(audio_queue.put(message), loop)
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+def on_vad_detect_stop(loop):
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+ message = json.dumps({
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+ 'type': 'vad_detect_stop'
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+ })
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+ asyncio.run_coroutine_threadsafe(audio_queue.put(message), loop)
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+
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+def on_wakeword_detected(loop):
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+ # Send a message to the client when wake word detection starts
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+ message = json.dumps({
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+ 'type': 'wakeword_detected'
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+ })
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+ asyncio.run_coroutine_threadsafe(audio_queue.put(message), loop)
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+
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def on_wakeword_detection_start(loop):
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# Send a message to the client when wake word detection starts
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message = json.dumps({
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@@ -227,83 +261,124 @@ def on_realtime_transcription_update(text, loop):
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})
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asyncio.run_coroutine_threadsafe(audio_queue.put(message), loop)
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-def on_recorded_chunk(chunk):
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- # Process each recorded audio chunk (optional implementation)
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- pass
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+def on_recorded_chunk(chunk, loop):
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+ if send_recorded_chunk:
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+ bytes_b64 = base64.b64encode(chunk.tobytes()).decode('utf-8')
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+ message = json.dumps({
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+ 'type': 'recorded_chunk',
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+ 'bytes': bytes_b64
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+ })
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+ asyncio.run_coroutine_threadsafe(audio_queue.put(message), loop)
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# Define the server's arguments
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def parse_arguments():
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import argparse
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parser = argparse.ArgumentParser(description='Start the Speech-to-Text (STT) server with various configuration options.')
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-
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+
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parser.add_argument('--model', type=str, default='large-v2',
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- help='Path to the STT model or model size. Options: tiny, tiny.en, base, base.en, small, small.en, medium, medium.en, large-v1, large-v2 or any hugginface CTranslate2 stt model like deepdml/faster-whisper-large-v3-turbo-ct2. Default: medium.en')
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-
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+ help='Path to the STT model or model size. Options include: tiny, tiny.en, base, base.en, small, small.en, medium, medium.en, large-v1, large-v2, or any huggingface CTranslate2 STT model such as deepdml/faster-whisper-large-v3-turbo-ct2. Default is large-v2.')
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+
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parser.add_argument('--realtime_model_type', type=str, default='tiny.en',
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- help='Model size for real-time transcription. Same options as --model. Used only if real-time transcription is enabled. Default: tiny.en')
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-
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+ help='Model size for real-time transcription. The options are the same as --model. This is used only if real-time transcription is enabled. Default is tiny.en.')
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+
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parser.add_argument('--language', type=str, default='en',
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- help='Language code for the STT model. Leave empty for auto-detection. Default: en')
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-
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+ help='Language code for the STT model to transcribe in a specific language. Leave this empty for auto-detection based on input audio. Default is en.')
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+
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parser.add_argument('--input_device_index', type=int, default=1,
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- help='Index of the audio input device to use. Default: 1')
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-
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+ help='Index of the audio input device to use. Use this option to specify a particular microphone or audio input device based on your system. Default is 1.')
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+
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parser.add_argument('--silero_sensitivity', type=float, default=0.05,
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- help='Sensitivity for Silero Voice Activity Detection (0 to 1). Lower values are less sensitive. Default: 0.05')
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-
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+ help='Sensitivity level for Silero Voice Activity Detection (VAD), with a range from 0 to 1. Lower values make the model less sensitive, useful for noisy environments. Default is 0.05.')
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+
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+ parser.add_argument('--silero_use_onnx', action='store_true', default=False,
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+ help='Enable ONNX version of Silero model for faster performance with lower resource usage. Default is False.')
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+
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parser.add_argument('--webrtc_sensitivity', type=int, default=3,
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- help='Sensitivity for WebRTC Voice Activity Detection (0 to 3). Higher values are less sensitive. Default: 3')
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-
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+ help='Sensitivity level for WebRTC Voice Activity Detection (VAD), with a range from 0 to 3. Higher values make the model less sensitive, useful for cleaner environments. Default is 3.')
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+
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parser.add_argument('--min_length_of_recording', type=float, default=1.1,
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- help='Minimum duration (in seconds) for a valid recording. Prevents excessively short recordings. Default: 1.1')
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-
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+ help='Minimum duration of valid recordings in seconds. This prevents very short recordings from being processed, which could be caused by noise or accidental sounds. Default is 1.1 seconds.')
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+
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parser.add_argument('--min_gap_between_recordings', type=float, default=0,
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- help='Minimum time (in seconds) between consecutive recordings. Prevents rapid successive recordings. Default: 0')
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-
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+ help='Minimum time (in seconds) between consecutive recordings. Setting this helps avoid overlapping recordings when there’s a brief silence between them. Default is 0 seconds.')
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+
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parser.add_argument('--enable_realtime_transcription', action='store_true', default=True,
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- help='Enable continuous real-time transcription of audio. Default: True')
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-
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+ help='Enable continuous real-time transcription of audio as it is received. When enabled, transcriptions are sent in near real-time. Default is True.')
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+
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parser.add_argument('--realtime_processing_pause', type=float, default=0.02,
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- help='Time interval (in seconds) between processing audio chunks for real-time transcription. Lower values increase responsiveness but may increase CPU load. Default: 0.02')
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-
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+ help='Time interval (in seconds) between processing audio chunks for real-time transcription. Lower values increase responsiveness but may put more load on the CPU. Default is 0.02 seconds.')
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+
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parser.add_argument('--silero_deactivity_detection', action='store_true', default=True,
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- help='Use Silero model for end-of-speech detection. More robust against background noise but uses more GPU resources. Default: True')
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-
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+ help='Use the Silero model for end-of-speech detection. This option can provide more robust silence detection in noisy environments, though it consumes more GPU resources. Default is True.')
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+
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parser.add_argument('--early_transcription_on_silence', type=float, default=0.2,
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- help='Start transcription after specified seconds of silence. Should be lower than post_speech_silence_duration. Set to 0 to disable. Default: 0.2')
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-
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+ help='Start transcription after the specified seconds of silence. This is useful when you want to trigger transcription mid-speech when there is a brief pause. Should be lower than post_speech_silence_duration. Set to 0 to disable. Default is 0.2 seconds.')
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+
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parser.add_argument('--beam_size', type=int, default=5,
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- help='Beam size for the main transcription model. Larger values may improve accuracy but increase processing time. Default: 5')
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-
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+ help='Beam size for the main transcription model. Larger values may improve transcription accuracy but increase the processing time. Default is 5.')
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+
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parser.add_argument('--beam_size_realtime', type=int, default=3,
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- help='Beam size for the real-time transcription model. Smaller than main beam_size for faster processing. Default: 3')
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-
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- parser.add_argument('--initial_prompt', type=str,
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- default='End incomplete sentences with ellipses.\nExamples:\nComplete: The sky is blue.\nIncomplete: When the sky...\nComplete: She walked home.\nIncomplete: Because he...',
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- help='Initial prompt for the transcription model to guide its output format and style. Default provides instructions for sentence completion and ellipsis usage.')
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-
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+ help='Beam size for the real-time transcription model. A smaller beam size allows for faster real-time processing but may reduce accuracy. Default is 3.')
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+
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+ parser.add_argument('--initial_prompt', type=str,
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+ default='End incomplete sentences with ellipses. Examples: Complete: The sky is blue. Incomplete: When the sky... Complete: She walked home. Incomplete: Because he...',
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+ help='Initial prompt that guides the transcription model to produce transcriptions in a particular style or format. The default provides instructions for handling sentence completions and ellipsis usage.')
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+
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parser.add_argument('--end_of_sentence_detection_pause', type=float, default=0.45,
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- help='Duration of pause (in seconds) to consider as end of a sentence. Default: 0.45')
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-
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+ help='The duration of silence (in seconds) that the model should interpret as the end of a sentence. This helps the system detect when to finalize the transcription of a sentence. Default is 0.45 seconds.')
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+
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parser.add_argument('--unknown_sentence_detection_pause', type=float, default=0.7,
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- help='Duration of pause (in seconds) to consider as an unknown or incomplete sentence. Default: 0.7')
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-
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+ help='The duration of pause (in seconds) that the model should interpret as an incomplete or unknown sentence. This is useful for identifying when a sentence is trailing off or unfinished. Default is 0.7 seconds.')
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+
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parser.add_argument('--mid_sentence_detection_pause', type=float, default=2.0,
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- help='Duration of pause (in seconds) to consider as a mid-sentence break. Default: 2.0')
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-
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+ help='The duration of pause (in seconds) that the model should interpret as a mid-sentence break. Longer pauses can indicate a pause in speech but not necessarily the end of a sentence. Default is 2.0 seconds.')
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+
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parser.add_argument('--control_port', type=int, default=8011,
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- help='Port for the control WebSocket connection. Default: 8011')
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-
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+ help='The port number used for the control WebSocket connection. Control connections are used to send and receive commands to the server. Default is port 8011.')
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+
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parser.add_argument('--data_port', type=int, default=8012,
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- help='Port for the data WebSocket connection. Default: 8012')
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-
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+ help='The port number used for the data WebSocket connection. Data connections are used to send audio data and receive transcription updates in real time. Default is port 8012.')
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+
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+ parser.add_argument('--wake_words', type=str, default="Jarvis",
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+ help='Specify the wake word(s) that will trigger the server to start listening. For example, setting this to "Jarvis" will make the system start transcribing when it detects the wake word "Jarvis". Default is "Jarvis".')
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+
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+ parser.add_argument('--wake_words_sensitivity', type=float, default=0.5,
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+ help='Sensitivity level for wake word detection, with a range from 0 (most sensitive) to 1 (least sensitive). Adjust this value based on your environment to ensure reliable wake word detection. Default is 0.5.')
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+
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+ parser.add_argument('--wake_word_timeout', type=float, default=5.0,
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+ help='Maximum time in seconds that the system will wait for a wake word before timing out. After this timeout, the system stops listening for wake words until reactivated. Default is 5.0 seconds.')
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+
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+ parser.add_argument('--wake_word_activation_delay', type=float, default=0.5,
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+ help='The delay in seconds before the wake word detection is activated after the system starts listening. This prevents false positives during the start of a session. Default is 0.5 seconds.')
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+
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+ parser.add_argument('--wakeword_backend', type=str, default='pvporcupine',
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+ help='The backend used for wake word detection. You can specify different backends such as "default" or any custom implementations depending on your setup. Default is "pvporcupine".')
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+
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+ parser.add_argument('--openwakeword_model_paths', type=str, nargs='*',
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+ help='A list of file paths to OpenWakeWord models. This is useful if you are using OpenWakeWord for wake word detection and need to specify custom models.')
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+
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+ parser.add_argument('--openwakeword_inference_framework', type=str, default='tensorflow',
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+ help='The inference framework to use for OpenWakeWord models. Supported frameworks could include "tensorflow", "pytorch", etc. Default is "tensorflow".')
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+
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+ parser.add_argument('--wake_word_buffer_duration', type=float, default=1.0,
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+ help='Duration of the buffer in seconds for wake word detection. This sets how long the system will store the audio before and after detecting the wake word. Default is 1.0 seconds.')
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+
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+ parser.add_argument('--use_main_model_for_realtime', action='store_true',
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+ help='Enable this option if you want to use the main model for real-time transcription, instead of the smaller, faster real-time model. Using the main model may provide better accuracy but at the cost of higher processing time.')
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+
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+ parser.add_argument('--use_extended_logging', action='store_true',
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+ help='Writes extensive log messages for the recording worker, that processes the audio chunks.')
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+
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+
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return parser.parse_args()
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def _recorder_thread(loop):
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global recorder, prev_text, stop_recorder
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- print(f"Initializing RealtimeSTT server with parameters {recorder_config}")
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+ print(f"{bcolors.OKGREEN}Initializing RealtimeSTT server with parameters:{bcolors.ENDC}")
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+ for key, value in recorder_config.items():
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+ print(f" {bcolors.OKBLUE}{key}{bcolors.ENDC}: {value}")
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recorder = AudioToTextRecorder(**recorder_config)
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- print("RealtimeSTT initialized")
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+ print(f"{bcolors.OKGREEN}{bcolors.BOLD}RealtimeSTT initialized{bcolors.ENDC}")
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recorder_ready.set()
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def process_text(full_sentence):
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@@ -314,13 +389,16 @@ def _recorder_thread(loop):
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})
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# Use the passed event loop here
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asyncio.run_coroutine_threadsafe(audio_queue.put(message), loop)
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- print(f"\rSentence: {full_sentence}")
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+ if extended_logging:
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+ print(f"Full text: {bcolors.BOLD}Sentence:{bcolors.ENDC} {bcolors.OKGREEN}{full_sentence}{bcolors.ENDC}")
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+ else:
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+ print(f"\r{bcolors.BOLD}Sentence:{bcolors.ENDC} {bcolors.OKGREEN}{full_sentence}{bcolors.ENDC}\n")
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try:
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while not stop_recorder:
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recorder.text(process_text)
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except KeyboardInterrupt:
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- print("Exiting application due to keyboard interrupt")
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+ print(f"{bcolors.WARNING}Exiting application due to keyboard interrupt{bcolors.ENDC}")
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def decode_and_resample(
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audio_data,
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@@ -344,13 +422,13 @@ def decode_and_resample(
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return resampled_audio.astype(np.int16).tobytes()
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async def control_handler(websocket, path):
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- print("Control client connected")
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+ print(f"{bcolors.OKGREEN}Control client connected{bcolors.ENDC}")
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global recorder
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control_connections.add(websocket)
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try:
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async for message in websocket:
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if not recorder_ready.is_set():
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- print("Recorder not ready")
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+ print(f"{bcolors.WARNING}Recorder not ready{bcolors.ENDC}")
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continue
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if isinstance(message, str):
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# Handle text message (command)
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@@ -362,27 +440,47 @@ async def control_handler(websocket, path):
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value = command_data.get("value")
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if parameter in allowed_parameters and hasattr(recorder, parameter):
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setattr(recorder, parameter, value)
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- print(f"Set recorder.{parameter} to {value}")
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+ # Format the value for output
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+ if isinstance(value, float):
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+ value_formatted = f"{value:.2f}"
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+ else:
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+ value_formatted = value
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+ if extended_logging:
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+ print(f"{bcolors.OKGREEN}Set recorder.{parameter} to: {bcolors.OKBLUE}{value_formatted}{bcolors.ENDC}")
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# Optionally send a response back to the client
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await websocket.send(json.dumps({"status": "success", "message": f"Parameter {parameter} set to {value}"}))
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else:
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if not parameter in allowed_parameters:
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- print(f"Parameter {parameter} is not allowed (set_parameter)")
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+ print(f"{bcolors.WARNING}Parameter {parameter} is not allowed (set_parameter){bcolors.ENDC}")
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await websocket.send(json.dumps({"status": "error", "message": f"Parameter {parameter} is not allowed (set_parameter)"}))
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else:
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- print(f"Parameter {parameter} does not exist (set_parameter)")
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+ print(f"{bcolors.WARNING}Parameter {parameter} does not exist (set_parameter){bcolors.ENDC}")
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await websocket.send(json.dumps({"status": "error", "message": f"Parameter {parameter} does not exist (set_parameter)"}))
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+
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elif command == "get_parameter":
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parameter = command_data.get("parameter")
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+ request_id = command_data.get("request_id") # Get the request_id from the command data
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if parameter in allowed_parameters and hasattr(recorder, parameter):
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value = getattr(recorder, parameter)
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- await websocket.send(json.dumps({"status": "success", "parameter": parameter, "value": value}))
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+ if isinstance(value, float):
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+ value_formatted = f"{value:.2f}"
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+ else:
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+ value_formatted = f"{value}"
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+
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+ value_truncated = value_formatted[:39] + "…" if len(value_formatted) > 40 else value_formatted
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+
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+ if extended_logging:
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+ print(f"{bcolors.OKGREEN}Get recorder.{parameter}: {bcolors.OKBLUE}{value_truncated}{bcolors.ENDC}")
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+ response = {"status": "success", "parameter": parameter, "value": value}
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+ if request_id is not None:
|
|
|
+ response["request_id"] = request_id
|
|
|
+ await websocket.send(json.dumps(response))
|
|
|
else:
|
|
|
if not parameter in allowed_parameters:
|
|
|
- print(f"Parameter {parameter} is not allowed (get_parameter)")
|
|
|
+ print(f"{bcolors.WARNING}Parameter {parameter} is not allowed (get_parameter){bcolors.ENDC}")
|
|
|
await websocket.send(json.dumps({"status": "error", "message": f"Parameter {parameter} is not allowed (get_parameter)"}))
|
|
|
else:
|
|
|
- print(f"Parameter {parameter} does not exist (get_parameter)")
|
|
|
+ print(f"{bcolors.WARNING}Parameter {parameter} does not exist (get_parameter){bcolors.ENDC}")
|
|
|
await websocket.send(json.dumps({"status": "error", "message": f"Parameter {parameter} does not exist (get_parameter)"}))
|
|
|
elif command == "call_method":
|
|
|
method_name = command_data.get("method")
|
|
@@ -392,34 +490,36 @@ async def control_handler(websocket, path):
|
|
|
args = command_data.get("args", [])
|
|
|
kwargs = command_data.get("kwargs", {})
|
|
|
method(*args, **kwargs)
|
|
|
- print(f"Called method recorder.{method_name}")
|
|
|
+ print(f"{bcolors.OKGREEN}Called method recorder.{bcolors.OKBLUE}{method_name}{bcolors.ENDC}")
|
|
|
await websocket.send(json.dumps({"status": "success", "message": f"Method {method_name} called"}))
|
|
|
else:
|
|
|
- print(f"Recorder does not have method {method_name}")
|
|
|
+ print(f"{bcolors.WARNING}Recorder does not have method {method_name}{bcolors.ENDC}")
|
|
|
await websocket.send(json.dumps({"status": "error", "message": f"Recorder does not have method {method_name}"}))
|
|
|
else:
|
|
|
- print(f"Method {method_name} is not allowed")
|
|
|
+ print(f"{bcolors.WARNING}Method {method_name} is not allowed{bcolors.ENDC}")
|
|
|
await websocket.send(json.dumps({"status": "error", "message": f"Method {method_name} is not allowed"}))
|
|
|
else:
|
|
|
- print(f"Unknown command: {command}")
|
|
|
+ print(f"{bcolors.WARNING}Unknown command: {command}{bcolors.ENDC}")
|
|
|
await websocket.send(json.dumps({"status": "error", "message": f"Unknown command {command}"}))
|
|
|
except json.JSONDecodeError:
|
|
|
- print("Received invalid JSON command")
|
|
|
+ print(f"{bcolors.WARNING}Received invalid JSON command{bcolors.ENDC}")
|
|
|
await websocket.send(json.dumps({"status": "error", "message": "Invalid JSON command"}))
|
|
|
else:
|
|
|
- print("Received unknown message type on control connection")
|
|
|
+ print(f"{bcolors.WARNING}Received unknown message type on control connection{bcolors.ENDC}")
|
|
|
except websockets.exceptions.ConnectionClosed as e:
|
|
|
- print(f"Control client disconnected: {e}")
|
|
|
+ print(f"{bcolors.WARNING}Control client disconnected: {e}{bcolors.ENDC}")
|
|
|
finally:
|
|
|
control_connections.remove(websocket)
|
|
|
|
|
|
async def data_handler(websocket, path):
|
|
|
- print("Data client connected")
|
|
|
+ print(f"{bcolors.OKGREEN}Data client connected{bcolors.ENDC}")
|
|
|
data_connections.add(websocket)
|
|
|
try:
|
|
|
while True:
|
|
|
message = await websocket.recv()
|
|
|
if isinstance(message, bytes):
|
|
|
+ if log_incoming_chunks:
|
|
|
+ print(".", end='', flush=True)
|
|
|
# Handle binary message (audio data)
|
|
|
metadata_length = int.from_bytes(message[:4], byteorder='little')
|
|
|
metadata_json = message[4:4+metadata_length].decode('utf-8')
|
|
@@ -429,9 +529,9 @@ async def data_handler(websocket, path):
|
|
|
resampled_chunk = decode_and_resample(chunk, sample_rate, 16000)
|
|
|
recorder.feed_audio(resampled_chunk)
|
|
|
else:
|
|
|
- print("Received non-binary message on data connection")
|
|
|
+ print(f"{bcolors.WARNING}Received non-binary message on data connection{bcolors.ENDC}")
|
|
|
except websockets.exceptions.ConnectionClosed as e:
|
|
|
- print(f"Data client disconnected: {e}")
|
|
|
+ print(f"{bcolors.WARNING}Data client disconnected: {e}{bcolors.ENDC}")
|
|
|
finally:
|
|
|
data_connections.remove(websocket)
|
|
|
recorder.clear_audio_queue() # Ensure audio queue is cleared if client disconnects
|
|
@@ -441,7 +541,8 @@ async def broadcast_audio_messages():
|
|
|
message = await audio_queue.get()
|
|
|
for conn in list(data_connections):
|
|
|
try:
|
|
|
- # print(f"Sending message: {message}")
|
|
|
+ if extended_logging:
|
|
|
+ print(f" {bcolors.OKBLUE}Sending message: {message}{bcolors.ENDC}\n", flush=True, end="")
|
|
|
await conn.send(message)
|
|
|
except websockets.exceptions.ConnectionClosed:
|
|
|
data_connections.remove(conn)
|
|
@@ -466,6 +567,7 @@ async def main_async():
|
|
|
'language': args.language,
|
|
|
'input_device_index': args.input_device_index,
|
|
|
'silero_sensitivity': args.silero_sensitivity,
|
|
|
+ 'silero_use_onnx': args.silero_use_onnx,
|
|
|
'webrtc_sensitivity': args.webrtc_sensitivity,
|
|
|
'post_speech_silence_duration': args.unknown_sentence_detection_pause,
|
|
|
'min_length_of_recording': args.min_length_of_recording,
|
|
@@ -477,24 +579,35 @@ async def main_async():
|
|
|
'beam_size': args.beam_size,
|
|
|
'beam_size_realtime': args.beam_size_realtime,
|
|
|
'initial_prompt': args.initial_prompt,
|
|
|
-
|
|
|
+ 'wake_words': args.wake_words,
|
|
|
+ 'wake_words_sensitivity': args.wake_words_sensitivity,
|
|
|
+ 'wake_word_timeout': args.wake_word_timeout,
|
|
|
+ 'wake_word_activation_delay': args.wake_word_activation_delay,
|
|
|
+ 'wakeword_backend': args.wakeword_backend,
|
|
|
+ 'openwakeword_model_paths': args.openwakeword_model_paths,
|
|
|
+ 'openwakeword_inference_framework': args.openwakeword_inference_framework,
|
|
|
+ 'wake_word_buffer_duration': args.wake_word_buffer_duration,
|
|
|
+ 'use_main_model_for_realtime': args.use_main_model_for_realtime,
|
|
|
'spinner': False,
|
|
|
'use_microphone': False,
|
|
|
-
|
|
|
'on_realtime_transcription_update': make_callback(loop, text_detected),
|
|
|
'on_recording_start': make_callback(loop, on_recording_start),
|
|
|
'on_recording_stop': make_callback(loop, on_recording_stop),
|
|
|
'on_vad_detect_start': make_callback(loop, on_vad_detect_start),
|
|
|
+ 'on_vad_detect_stop': make_callback(loop, on_vad_detect_stop),
|
|
|
+ 'on_wakeword_detected': make_callback(loop, on_wakeword_detected),
|
|
|
'on_wakeword_detection_start': make_callback(loop, on_wakeword_detection_start),
|
|
|
'on_wakeword_detection_end': make_callback(loop, on_wakeword_detection_end),
|
|
|
'on_transcription_start': make_callback(loop, on_transcription_start),
|
|
|
- 'no_log_file': True,
|
|
|
+ 'on_recorded_chunk': make_callback(loop, on_recorded_chunk),
|
|
|
+ 'no_log_file': True, # Disable logging to file
|
|
|
+ 'use_extended_logging': args.use_extended_logging,
|
|
|
}
|
|
|
|
|
|
control_server = await websockets.serve(control_handler, "localhost", args.control_port)
|
|
|
data_server = await websockets.serve(data_handler, "localhost", args.data_port)
|
|
|
- print(f"Control server started on ws://localhost:{args.control_port}")
|
|
|
- print(f"Data server started on ws://localhost:{args.data_port}")
|
|
|
+ print(f"{bcolors.OKGREEN}Control server started on {bcolors.OKBLUE}ws://localhost:{args.control_port}{bcolors.ENDC}")
|
|
|
+ print(f"{bcolors.OKGREEN}Data server started on {bcolors.OKBLUE}ws://localhost:{args.data_port}{bcolors.ENDC}")
|
|
|
|
|
|
# Task to broadcast audio messages
|
|
|
broadcast_task = asyncio.create_task(broadcast_audio_messages())
|
|
@@ -503,12 +616,12 @@ async def main_async():
|
|
|
recorder_thread.start()
|
|
|
recorder_ready.wait()
|
|
|
|
|
|
- print("Server started. Press Ctrl+C to stop the server.")
|
|
|
+ print(f"{bcolors.OKGREEN}Server started. Press Ctrl+C to stop the server.{bcolors.ENDC}")
|
|
|
|
|
|
try:
|
|
|
await asyncio.gather(control_server.wait_closed(), data_server.wait_closed(), broadcast_task)
|
|
|
except KeyboardInterrupt:
|
|
|
- print("Shutting down gracefully...")
|
|
|
+ print(f"{bcolors.WARNING}{bcolors.BOLD}Shutting down gracefully...{bcolors.ENDC}")
|
|
|
finally:
|
|
|
# Shut down the recorder
|
|
|
if recorder:
|
|
@@ -516,10 +629,10 @@ async def main_async():
|
|
|
recorder.abort()
|
|
|
recorder.stop()
|
|
|
recorder.shutdown()
|
|
|
- print("Recorder shut down")
|
|
|
+ print(f"{bcolors.OKGREEN}Recorder shut down{bcolors.ENDC}")
|
|
|
|
|
|
recorder_thread.join()
|
|
|
- print("Recorder thread finished")
|
|
|
+ print(f"{bcolors.OKGREEN}Recorder thread finished{bcolors.ENDC}")
|
|
|
|
|
|
# Cancel all active tasks in the event loop
|
|
|
tasks = [t for t in asyncio.all_tasks() if t is not asyncio.current_task()]
|
|
@@ -529,14 +642,14 @@ async def main_async():
|
|
|
# Run pending tasks and handle cancellation
|
|
|
await asyncio.gather(*tasks, return_exceptions=True)
|
|
|
|
|
|
- print("All tasks cancelled, closing event loop now.")
|
|
|
+ print(f"{bcolors.OKGREEN}All tasks cancelled, closing event loop now.{bcolors.ENDC}")
|
|
|
|
|
|
def main():
|
|
|
try:
|
|
|
asyncio.run(main_async())
|
|
|
except KeyboardInterrupt:
|
|
|
# Capture any final KeyboardInterrupt to prevent it from showing up in logs
|
|
|
- print("Server interrupted by user.")
|
|
|
+ print(f"{bcolors.WARNING}Server interrupted by user.{bcolors.ENDC}")
|
|
|
exit(0)
|
|
|
|
|
|
if __name__ == '__main__':
|