Implemented experimental real production ready voice chat, relegated old flow to voice debug mode. New Web UI panel for Voice Chat.
This commit is contained in:
525
stt-realtime/stt_server.py
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525
stt-realtime/stt_server.py
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#!/usr/bin/env python3
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"""
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RealtimeSTT WebSocket Server
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Provides real-time speech-to-text transcription using Faster-Whisper.
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Receives audio chunks via WebSocket and streams back partial/final transcripts.
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Protocol:
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- Client sends: binary audio data (16kHz, 16-bit mono PCM)
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- Client sends: JSON {"command": "reset"} to reset state
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- Server sends: JSON {"type": "partial", "text": "...", "timestamp": float}
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- Server sends: JSON {"type": "final", "text": "...", "timestamp": float}
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"""
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import asyncio
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import json
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import logging
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import time
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import threading
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import queue
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from typing import Optional, Dict, Any
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import numpy as np
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import websockets
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from websockets.server import serve
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from aiohttp import web
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# Configure logging
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logging.basicConfig(
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level=logging.INFO,
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format='%(asctime)s %(levelname)s [%(name)s] %(message)s',
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datefmt='%Y-%m-%d %H:%M:%S'
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)
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logger = logging.getLogger('stt-realtime')
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# Import RealtimeSTT
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from RealtimeSTT import AudioToTextRecorder
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# Global warmup state
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warmup_complete = False
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warmup_lock = threading.Lock()
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warmup_recorder = None
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class STTSession:
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"""
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Manages a single STT session for a WebSocket client.
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Uses RealtimeSTT's AudioToTextRecorder with feed_audio() method.
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"""
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def __init__(self, websocket, session_id: str, config: Dict[str, Any]):
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self.websocket = websocket
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self.session_id = session_id
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self.config = config
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self.recorder: Optional[AudioToTextRecorder] = None
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self.running = False
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self.audio_queue = queue.Queue()
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self.feed_thread: Optional[threading.Thread] = None
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self.last_partial = ""
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self.last_stabilized = "" # Track last stabilized partial
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self.last_text_was_stabilized = False # Track which came last
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self.recording_active = False # Track if currently recording
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logger.info(f"[{session_id}] Session created")
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def _on_realtime_transcription(self, text: str):
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"""Called when partial transcription is available."""
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if text and text != self.last_partial:
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self.last_partial = text
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self.last_text_was_stabilized = False # Partial came after stabilized
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logger.info(f"[{self.session_id}] 📝 Partial: {text}")
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asyncio.run_coroutine_threadsafe(
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self._send_transcript("partial", text),
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self.loop
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)
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def _on_realtime_stabilized(self, text: str):
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"""Called when a stabilized partial is available (high confidence)."""
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if text and text.strip():
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self.last_stabilized = text
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self.last_text_was_stabilized = True # Stabilized came after partial
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logger.info(f"[{self.session_id}] 🔒 Stabilized: {text}")
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asyncio.run_coroutine_threadsafe(
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self._send_transcript("partial", text),
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self.loop
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)
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def _on_recording_stop(self):
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"""Called when recording stops (silence detected)."""
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logger.info(f"[{self.session_id}] ⏹️ Recording stopped")
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self.recording_active = False
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# Use the most recent text: prioritize whichever came last
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if self.last_text_was_stabilized:
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final_text = self.last_stabilized or self.last_partial
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source = "stabilized" if self.last_stabilized else "partial"
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else:
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final_text = self.last_partial or self.last_stabilized
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source = "partial" if self.last_partial else "stabilized"
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if final_text:
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logger.info(f"[{self.session_id}] ✅ Final (from {source}): {final_text}")
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asyncio.run_coroutine_threadsafe(
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self._send_transcript("final", final_text),
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self.loop
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)
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else:
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# No transcript means VAD false positive (detected "speech" in pure noise)
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logger.warning(f"[{self.session_id}] ⚠️ Recording stopped but no transcript available (VAD false positive)")
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logger.info(f"[{self.session_id}] 🔄 Clearing audio buffer to recover")
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# Clear the audio queue to prevent stale data
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try:
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while not self.audio_queue.empty():
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self.audio_queue.get_nowait()
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except Exception:
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pass
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# Reset state
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self.last_stabilized = ""
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self.last_partial = ""
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self.last_text_was_stabilized = False
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def _on_recording_start(self):
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"""Called when recording starts (speech detected)."""
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logger.info(f"[{self.session_id}] 🎙️ Recording started")
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self.recording_active = True
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self.last_stabilized = ""
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self.last_partial = ""
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def _on_transcription(self, text: str):
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"""Not used - we use stabilized partials as finals."""
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pass
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async def _send_transcript(self, transcript_type: str, text: str):
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"""Send transcript to client via WebSocket."""
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try:
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message = {
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"type": transcript_type,
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"text": text,
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"timestamp": time.time()
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}
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await self.websocket.send(json.dumps(message))
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except Exception as e:
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logger.error(f"[{self.session_id}] Failed to send transcript: {e}")
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def _feed_audio_thread(self):
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"""Thread that feeds audio to the recorder."""
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logger.info(f"[{self.session_id}] Audio feed thread started")
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while self.running:
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try:
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# Get audio chunk with timeout
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audio_chunk = self.audio_queue.get(timeout=0.1)
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if audio_chunk is not None and self.recorder:
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self.recorder.feed_audio(audio_chunk)
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except queue.Empty:
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continue
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except Exception as e:
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logger.error(f"[{self.session_id}] Error feeding audio: {e}")
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logger.info(f"[{self.session_id}] Audio feed thread stopped")
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async def start(self, loop: asyncio.AbstractEventLoop):
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"""Start the STT session."""
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self.loop = loop
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self.running = True
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logger.info(f"[{self.session_id}] Starting RealtimeSTT recorder...")
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logger.info(f"[{self.session_id}] Model: {self.config['model']}")
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logger.info(f"[{self.session_id}] Device: {self.config['device']}")
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try:
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# Create recorder in a thread to avoid blocking
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def init_recorder():
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self.recorder = AudioToTextRecorder(
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# Model settings - using same model for both partial and final
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model=self.config['model'],
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language=self.config['language'],
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compute_type=self.config['compute_type'],
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device=self.config['device'],
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# Disable microphone - we feed audio manually
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use_microphone=False,
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# Real-time transcription - use same model for everything
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enable_realtime_transcription=True,
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realtime_model_type=self.config['model'], # Use same model
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realtime_processing_pause=0.05, # 50ms between updates
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on_realtime_transcription_update=self._on_realtime_transcription,
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on_realtime_transcription_stabilized=self._on_realtime_stabilized,
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# VAD settings - very permissive, rely on Discord's VAD for speech detection
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# Our VAD is only for silence detection, not filtering audio content
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silero_sensitivity=0.05, # Very low = barely filters anything
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silero_use_onnx=True, # Faster
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webrtc_sensitivity=3,
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post_speech_silence_duration=self.config['silence_duration'],
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min_length_of_recording=self.config['min_recording_length'],
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min_gap_between_recordings=self.config['min_gap'],
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pre_recording_buffer_duration=1.0, # Capture more audio before/after speech
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# Callbacks
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on_recording_start=self._on_recording_start,
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on_recording_stop=self._on_recording_stop,
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on_vad_detect_start=lambda: logger.debug(f"[{self.session_id}] VAD listening"),
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on_vad_detect_stop=lambda: logger.debug(f"[{self.session_id}] VAD stopped"),
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# Other settings
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spinner=False, # No spinner in container
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level=logging.WARNING, # Reduce internal logging
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# Beam search settings
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beam_size=5, # Higher beam = better accuracy (used for final processing)
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beam_size_realtime=5, # Increased from 3 for better real-time accuracy
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# Batch sizes
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batch_size=16,
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realtime_batch_size=8,
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initial_prompt="", # Can add context here if needed
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)
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logger.info(f"[{self.session_id}] ✅ Recorder initialized")
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# Run initialization in thread pool
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await asyncio.get_event_loop().run_in_executor(None, init_recorder)
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# Start audio feed thread
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self.feed_thread = threading.Thread(target=self._feed_audio_thread, daemon=True)
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self.feed_thread.start()
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# Start the recorder's text processing loop in a thread
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def run_text_loop():
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while self.running:
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try:
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# This blocks until speech is detected and transcribed
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text = self.recorder.text(self._on_transcription)
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except Exception as e:
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if self.running:
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logger.error(f"[{self.session_id}] Text loop error: {e}")
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break
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self.text_thread = threading.Thread(target=run_text_loop, daemon=True)
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self.text_thread.start()
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logger.info(f"[{self.session_id}] ✅ Session started successfully")
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except Exception as e:
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logger.error(f"[{self.session_id}] Failed to start session: {e}", exc_info=True)
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raise
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def feed_audio(self, audio_data: bytes):
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"""Feed audio data to the recorder."""
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if self.running:
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# Convert bytes to numpy array (16-bit PCM)
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audio_np = np.frombuffer(audio_data, dtype=np.int16)
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self.audio_queue.put(audio_np)
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def reset(self):
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"""Reset the session state."""
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logger.info(f"[{self.session_id}] Resetting session")
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self.last_partial = ""
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# Clear audio queue
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while not self.audio_queue.empty():
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try:
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self.audio_queue.get_nowait()
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except queue.Empty:
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break
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async def stop(self):
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"""Stop the session and cleanup."""
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logger.info(f"[{self.session_id}] Stopping session...")
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self.running = False
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# Wait for threads to finish
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if self.feed_thread and self.feed_thread.is_alive():
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self.feed_thread.join(timeout=2)
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# Shutdown recorder
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if self.recorder:
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try:
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self.recorder.shutdown()
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except Exception as e:
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logger.error(f"[{self.session_id}] Error shutting down recorder: {e}")
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logger.info(f"[{self.session_id}] Session stopped")
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class STTServer:
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"""
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WebSocket server for RealtimeSTT.
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Handles multiple concurrent clients (one per Discord user).
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"""
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def __init__(self, host: str = "0.0.0.0", port: int = 8766):
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self.host = host
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self.port = port
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self.sessions: Dict[str, STTSession] = {}
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self.session_counter = 0
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# Default configuration
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self.config = {
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# Model - using small.en (English-only, more accurate than multilingual small)
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'model': 'small.en',
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'language': 'en',
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'compute_type': 'float16', # FP16 for GPU efficiency
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'device': 'cuda',
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# VAD settings
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'silero_sensitivity': 0.6,
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'webrtc_sensitivity': 3,
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'silence_duration': 0.8, # Shorter to improve responsiveness
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'min_recording_length': 0.5,
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'min_gap': 0.3,
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}
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logger.info("=" * 60)
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logger.info("RealtimeSTT Server Configuration:")
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logger.info(f" Host: {host}:{port}")
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logger.info(f" Model: {self.config['model']} (English-only, optimized)")
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logger.info(f" Beam size: 5 (higher accuracy)")
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logger.info(f" Strategy: Use last partial as final (instant response)")
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logger.info(f" Language: {self.config['language']}")
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logger.info(f" Device: {self.config['device']}")
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logger.info(f" Compute Type: {self.config['compute_type']}")
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logger.info(f" Silence Duration: {self.config['silence_duration']}s")
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logger.info("=" * 60)
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async def handle_client(self, websocket):
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"""Handle a WebSocket client connection."""
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self.session_counter += 1
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session_id = f"session_{self.session_counter}"
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session = None
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try:
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logger.info(f"[{session_id}] Client connected from {websocket.remote_address}")
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# Create session
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session = STTSession(websocket, session_id, self.config)
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self.sessions[session_id] = session
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# Start session
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await session.start(asyncio.get_event_loop())
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# Process messages
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async for message in websocket:
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try:
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if isinstance(message, bytes):
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# Binary audio data
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session.feed_audio(message)
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else:
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# JSON command
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data = json.loads(message)
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command = data.get('command', '')
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if command == 'reset':
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session.reset()
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elif command == 'ping':
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await websocket.send(json.dumps({
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'type': 'pong',
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'timestamp': time.time()
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}))
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else:
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logger.warning(f"[{session_id}] Unknown command: {command}")
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except json.JSONDecodeError:
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logger.warning(f"[{session_id}] Invalid JSON message")
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except Exception as e:
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logger.error(f"[{session_id}] Error processing message: {e}")
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except websockets.exceptions.ConnectionClosed:
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logger.info(f"[{session_id}] Client disconnected")
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except Exception as e:
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logger.error(f"[{session_id}] Error: {e}", exc_info=True)
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finally:
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# Cleanup
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if session:
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await session.stop()
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del self.sessions[session_id]
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async def run(self):
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"""Run the WebSocket server."""
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logger.info(f"Starting RealtimeSTT server on ws://{self.host}:{self.port}")
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async with serve(
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self.handle_client,
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self.host,
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self.port,
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ping_interval=30,
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ping_timeout=10,
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max_size=10 * 1024 * 1024, # 10MB max message size
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):
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logger.info("✅ Server ready and listening for connections")
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await asyncio.Future() # Run forever
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async def warmup_model(config: Dict[str, Any]):
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"""
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Warm up the STT model by loading it and processing test audio.
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This ensures the model is cached in memory before handling real requests.
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"""
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global warmup_complete, warmup_recorder
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with warmup_lock:
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if warmup_complete:
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logger.info("Model already warmed up")
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return
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logger.info("🔥 Starting model warmup...")
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try:
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# Generate silent test audio (1 second of silence, 16kHz)
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test_audio = np.zeros(16000, dtype=np.int16)
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# Initialize a temporary recorder to load the model
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logger.info("Loading Faster-Whisper model...")
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def dummy_callback(text):
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pass
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# This will trigger model loading and compilation
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warmup_recorder = AudioToTextRecorder(
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model=config['model'],
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language=config['language'],
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compute_type=config['compute_type'],
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device=config['device'],
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silero_sensitivity=config['silero_sensitivity'],
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webrtc_sensitivity=config['webrtc_sensitivity'],
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post_speech_silence_duration=config['silence_duration'],
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min_length_of_recording=config['min_recording_length'],
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min_gap_between_recordings=config['min_gap'],
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enable_realtime_transcription=True,
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realtime_processing_pause=0.1,
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on_realtime_transcription_update=dummy_callback,
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on_realtime_transcription_stabilized=dummy_callback,
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spinner=False,
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level=logging.WARNING,
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beam_size=5,
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beam_size_realtime=5,
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batch_size=16,
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realtime_batch_size=8,
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initial_prompt="",
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)
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logger.info("✅ Model loaded and warmed up successfully")
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warmup_complete = True
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except Exception as e:
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logger.error(f"❌ Warmup failed: {e}", exc_info=True)
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warmup_complete = False
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async def health_handler(request):
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"""HTTP health check endpoint"""
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if warmup_complete:
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return web.json_response({
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"status": "ready",
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"warmed_up": True,
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"model": "small.en",
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"device": "cuda"
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})
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else:
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return web.json_response({
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"status": "warming_up",
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"warmed_up": False,
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"model": "small.en",
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"device": "cuda"
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}, status=503)
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async def start_http_server(host: str, http_port: int):
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"""Start HTTP server for health checks"""
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app = web.Application()
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app.router.add_get('/health', health_handler)
|
||||
|
||||
runner = web.AppRunner(app)
|
||||
await runner.setup()
|
||||
site = web.TCPSite(runner, host, http_port)
|
||||
await site.start()
|
||||
|
||||
logger.info(f"✅ HTTP health server listening on http://{host}:{http_port}")
|
||||
|
||||
|
||||
def main():
|
||||
"""Main entry point."""
|
||||
import os
|
||||
|
||||
# Get configuration from environment
|
||||
host = os.environ.get('STT_HOST', '0.0.0.0')
|
||||
port = int(os.environ.get('STT_PORT', '8766'))
|
||||
http_port = int(os.environ.get('STT_HTTP_PORT', '8767')) # HTTP health check port
|
||||
|
||||
# Configuration
|
||||
config = {
|
||||
'model': 'small.en',
|
||||
'language': 'en',
|
||||
'compute_type': 'float16',
|
||||
'device': 'cuda',
|
||||
'silero_sensitivity': 0.6,
|
||||
'webrtc_sensitivity': 3,
|
||||
'silence_duration': 0.8,
|
||||
'min_recording_length': 0.5,
|
||||
'min_gap': 0.3,
|
||||
}
|
||||
|
||||
# Create and run server
|
||||
server = STTServer(host=host, port=port)
|
||||
|
||||
async def run_all():
|
||||
# Start warmup in background
|
||||
asyncio.create_task(warmup_model(config))
|
||||
|
||||
# Start HTTP health server
|
||||
asyncio.create_task(start_http_server(host, http_port))
|
||||
|
||||
# Start WebSocket server
|
||||
await server.run()
|
||||
|
||||
try:
|
||||
asyncio.run(run_all())
|
||||
except KeyboardInterrupt:
|
||||
logger.info("Server shutdown requested")
|
||||
except Exception as e:
|
||||
logger.error(f"Server error: {e}", exc_info=True)
|
||||
raise
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
Reference in New Issue
Block a user