6115f3bc09
- Chatterbox TTS Server (Multilingual, 23 Sprachen, Voice Cloning) - Whisper STT Server (faster-whisper-small, CPU) - RTX 4060 GPU auf Tdarr VM (node2, 10.2.1.104) - Voice Profile: chantal.wav - Chantal Telegram Voice Integration
50 lines
1.5 KiB
YAML
50 lines
1.5 KiB
YAML
services:
|
|
chatterbox-tts-server:
|
|
build:
|
|
args:
|
|
# Can be nvidia or cpu; Default is Nvidia
|
|
- RUNTIME=nvidia
|
|
context: .
|
|
dockerfile: Dockerfile
|
|
ports:
|
|
- "${PORT:-8004}:8004"
|
|
volumes:
|
|
# Mount local config file for persistence
|
|
- ./config.yaml:/app/config.yaml
|
|
# Mount local directories for persistent app data
|
|
- ./voices:/app/voices
|
|
- ./reference_audio:/app/reference_audio
|
|
- ./outputs:/app/outputs
|
|
- ./logs:/app/logs
|
|
# Named volume for Hugging Face model cache to persist across container rebuilds
|
|
- hf_cache:/app/hf_cache
|
|
|
|
# --- GPU Support (NVIDIA) ---
|
|
# The 'deploy' key is the modern way to request GPU resources.
|
|
# If you get a 'CDI device injection failed' error, comment out the 'deploy' section
|
|
# and uncomment the 'runtime: nvidia' line below.
|
|
|
|
# Method 1: Modern Docker Compose (Recommended)
|
|
deploy:
|
|
resources:
|
|
reservations:
|
|
devices:
|
|
- driver: nvidia
|
|
count: 1
|
|
capabilities: [gpu]
|
|
|
|
# Method 2: Legacy Docker Compose (for older setups)
|
|
# runtime: nvidia
|
|
|
|
restart: unless-stopped
|
|
environment:
|
|
- HF_TOKEN=YOUR_TOKEN_HERE
|
|
# Enable faster Hugging Face downloads inside the container
|
|
- HF_HUB_ENABLE_HF_TRANSFER=1
|
|
# Make NVIDIA GPUs visible and specify capabilities for PyTorch
|
|
- NVIDIA_VISIBLE_DEVICES=all
|
|
- NVIDIA_DRIVER_CAPABILITIES=compute,utility
|
|
|
|
# Define the named volume for the Hugging Face cache
|
|
volumes:
|
|
hf_cache:
|