Daniil Klimov
780f6f0084
- Add training/ pipeline (step_1..step_5) and own-samples flow
- record_wav.py with single-shot and long-record modes, RMS-based silence filter
- remove_silent.py to drop silent samples and renumber
- modes.py: openwakeword inference with reset() and quiet predictions; commented Lusya block for later
- stt.py: drop local faster-whisper fallback, Groq-only
- config.py: remove unused STT_PROVIDER/WHISPER_*
- llm.py: replace __import__("os") hack with proper import
- tts.py: remove debug traceback in play_error_sound
- requirements.txt: add openwakeword/sounddevice/scipy, drop faster-whisper
- deploy/setup.sh: validate ELEVENLABS_API_KEY and WAKE_WORD_COSMO presence
- README.md, CLAUDE.md, project_roadmap memory updated to reflect new architecture
98 lines
3.9 KiB
Python
98 lines
3.9 KiB
Python
import sounddevice as sd
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import scipy.io.wavfile as wav
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import numpy as np
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import os
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import sys
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MIN_RMS = 300 # ниже = почти тишина, не сохраняем
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SAMPLE_RATE = 16000
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CHUNK_DURATION = 2 # сек на один wav
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INPUT_DEVICE = os.getenv("INPUT_DEVICE") # имя или индекс устройства, иначе системный default
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if INPUT_DEVICE and INPUT_DEVICE.isdigit():
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INPUT_DEVICE = int(INPUT_DEVICE)
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if len(sys.argv) < 3:
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print("Использование: python record_wav.py <имя_модели> <positive/negative> [long [секунд]]")
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print("Примеры:")
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print(" python record_wav.py cosmo positive # по 2с с Enter")
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print(" python record_wav.py cosmo negative long # 5 минут подряд → нарезать")
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print(" python record_wav.py cosmo negative long 600 # 10 минут подряд")
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sys.exit(1)
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MODEL_NAME = sys.argv[1]
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MODE = sys.argv[2]
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LONG_MODE = len(sys.argv) > 3 and sys.argv[3] == "long"
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LONG_DURATION = int(sys.argv[4]) if LONG_MODE and len(sys.argv) > 4 else 300
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BASE_DIR = os.path.join("training", "own_samples", MODEL_NAME, MODE)
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os.makedirs(BASE_DIR, exist_ok=True)
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def next_index() -> int:
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files = [f for f in os.listdir(BASE_DIR) if f.endswith('.wav')]
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return len(files) + 1
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def record_sample():
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idx = next_index()
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filename = f"{idx:03d}.wav"
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filepath = os.path.join(BASE_DIR, filename)
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print(f"\n[!] Файл {filename} готов к записи.")
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input(f"Нажмите Enter, чтобы начать запись ({CHUNK_DURATION} секунды)...")
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print("Запись...")
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recording = sd.rec(device=INPUT_DEVICE, frames=int(CHUNK_DURATION * SAMPLE_RATE), samplerate=SAMPLE_RATE, channels=1, dtype='int16')
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sd.wait()
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rms = float(np.sqrt(np.mean(recording.astype(np.float64) ** 2)))
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if rms < MIN_RMS:
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print(f"⚠️ Тишина (RMS={rms:.0f} < {MIN_RMS}) — не сохраняю, повтори")
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return
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wav.write(filepath, SAMPLE_RATE, recording)
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print(f"Сохранено: {filepath} (RMS={rms:.0f})")
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def record_long(total_seconds: int):
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"""Запись N секунд непрерывно, потом нарезка на CHUNK_DURATION-секундные wav."""
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print(f"\n[!] Запись {total_seconds}с одним куском, потом нарежу по {CHUNK_DURATION}с.")
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input("Нажмите Enter, чтобы начать (Ctrl+C прервёт сохранение)...")
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print(f"🎙️ Запись... ({total_seconds}с)")
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recording = sd.rec(device=INPUT_DEVICE, frames=int(total_seconds * SAMPLE_RATE), samplerate=SAMPLE_RATE, channels=1, dtype='int16')
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try:
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sd.wait()
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except KeyboardInterrupt:
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sd.stop()
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print("\n⏹️ Прервано — сохраняю записанное")
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audio = recording.flatten()
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chunk_samples = CHUNK_DURATION * SAMPLE_RATE
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n_chunks = len(audio) // chunk_samples
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saved = skipped = 0
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start_idx = next_index()
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for i in range(n_chunks):
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chunk = audio[i * chunk_samples:(i + 1) * chunk_samples]
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rms = float(np.sqrt(np.mean(chunk.astype(np.float64) ** 2)))
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if rms < MIN_RMS:
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skipped += 1
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continue
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filename = f"{start_idx + saved:03d}.wav"
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wav.write(os.path.join(BASE_DIR, filename), SAMPLE_RATE, chunk)
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saved += 1
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print(f"\n✅ Нарезано {n_chunks} кусков → сохранено {saved}, пропущено тихих {skipped}")
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print(f"--- Режим записи: {MODEL_NAME} / {MODE}{' / LONG' if LONG_MODE else ''} ---")
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if LONG_MODE:
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record_long(LONG_DURATION)
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else:
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print("Для выхода нажмите Ctrl+C")
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try:
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while True:
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record_sample()
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except KeyboardInterrupt:
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print("\nЗапись завершена.")
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