voice-to-text-config

# Voice-to-Text Configuration Set up local Whisper-based transcription for Telegram voice messages. ## Steps Run each step sequentially. Report status clearly after each one. ### 1. Check faster-whisper installation ```bash python -c "import faster_whisper; print(f'faster-whisper {faster_whisper.__version__} installed')" 2>&1 ``` - **If installed**: print the version, move to step 2. - **If ImportError**: tell the user and install it: ```bash pip install faster-whisper ``` Verify the install succeeded before continuing. ### 2. Check / download Whisper model The default model is controlled by the `WHISPER_MODEL` env var (default: `base`). Available sizes: `tiny` (~40MB, fastest), `base` (~75MB, good balance), `small` (~250MB), `medium` (~750MB, most accurate for CPU). Ask the user which model size they want if they haven't specified one. Then check if it's cached: ```bash python -c " import os, sys from huggingface_hub import try_to_load_from_cache model = os.environ.get('WHISPER_MODEL', 'base') cached = try_to_load_from_cache(f'Systran/faster-whisper-{model}', 'model.bin') if cached: print(f'Model \"{model}\" is cached at: {cached}') else: print(f'Model \"{model}\" is NOT cached yet — needs download') sys.exit(1) " 2>&1 ``` If not cached, download it: ```bash python -c " import os, sys model = os.environ.get('WHISPER_MODEL', 'base') print(f'Downloading whisper model \"{model}\"... (this may take a minute)') from faster_whisper import WhisperMod...