71 lines
2.3 KiB
Plaintext
71 lines
2.3 KiB
Plaintext
# Copy this file to .env and fill in secrets
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# Meilisearch keys
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MEILI_MASTER_KEY=change_me_to_strong_random
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MEILI_KEY=${MEILI_MASTER_KEY}
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# OpenWebUI integration
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OPENWEBUI_URL=http://openwebui:3000
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OPENWEBUI_API_KEY=put_your_openwebui_api_key_here
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OPENWEBUI_KB_NAME=Homelab Library
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OPENWEBUI_KB_ID=your_kb_uuid_here
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OPENWEBUI_AUTO_FIX_METADATA=1
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# Optional: JSON string to enforce as metadata template when auto-fix runs
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# OPENWEBUI_METADATA_TEMPLATE_JSON={}
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# Media normalisation
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MEDIA_NORMALIZE=1
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MEDIA_NORMALIZE_KEEP_ORIGINAL=0
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VIDEO_NORMALIZE_CODEC=hevc
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VIDEO_NORMALIZE_EXTENSION=.mp4
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VIDEO_NORMALIZE_CRF=28
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VIDEO_NORMALIZE_PRESET=medium
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VIDEO_NORMALIZE_AUDIO_CODEC=aac
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VIDEO_NORMALIZE_AUDIO_BITRATE=160k
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AUDIO_NORMALIZE_CODEC=libmp3lame
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AUDIO_NORMALIZE_EXTENSION=.mp3
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AUDIO_NORMALIZE_BITRATE=192k
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AUDIO_NORMALIZE_CHANNELS=2
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# Transcription backend (local Whisper by default)
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TRANSCRIBE_BACKEND=local
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OPENAI_API_KEY=
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# Uncomment to customize OpenAI settings when offloading transcription
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# OPENAI_BASE_URL=https://api.openai.com/v1
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# OPENAI_TRANSCRIBE_MODEL=whisper-1
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# OPENAI_TRANSCRIBE_TIMEOUT=600
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# Local Whisper settings
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# Choose CPU explicitly unless you have a working GPU runtime in Docker
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WHISPER_DEVICE=cpu
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# Model and precision (large-v3 int8 is accurate but heavy; consider medium/small for speed)
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WHISPER_MODEL=large-v3
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WHISPER_PRECISION=int8
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# Threads for CPU inference
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WHISPER_CPU_THREADS=4
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# --- GPU (CUDA) optional setup ---
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# To enable NVIDIA GPU acceleration:
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# 1) Install NVIDIA driver on the host and the NVIDIA Container Toolkit
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# 2) Set the Docker runtime to NVIDIA for the worker containers
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# DOCKER_GPU_RUNTIME=nvidia
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# 3) Ensure GPU visibility (default is all)
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# NVIDIA_VISIBLE_DEVICES=all
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# 4) Use GPU-friendly precision and device
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# WHISPER_DEVICE=cuda
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# WHISPER_PRECISION=float16
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# 5) (Build-time) use an NVIDIA CUDA runtime base image for the app containers.
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# Set an image tag that exists for your architecture (most CUDA images are amd64):
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# GPU_BASE_IMAGE=nvidia/cuda:11.8.0-cudnn8-runtime-ubuntu22.04
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#
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# If you are on ARM64 without discrete NVIDIA GPU, leave GPU_BASE_IMAGE unset and run CPU-only.
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# Docker volumes paths
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LIBRARY_HOST_DIR=/mnt/nfs/library
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TRANSCRIPTS_HOST_DIR=/mnt/nfs/transcripts
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# leave others as-is or customize:
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# TMP_HOST_DIR=./tmp
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# MODELS_HOST_DIR=./models
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# MEILI_DATA_HOST_DIR=./data/meili
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# REDIS_DATA_HOST_DIR=./data/redis
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