koko210Serve
9e5511da21
- miku-stt: switch PyTorch CUDA -> CPU-only (~2.5 GB savings) - Silero VAD already runs on CPU via ONNX (onnx=True), CUDA PyTorch was waste - faster-whisper/CTranslate2 uses CUDA directly, no PyTorch GPU needed - torch+torchaudio layer: 3.3 GB -> 796 MB; total image 9+ GB -> 6.83 GB - Tested: Silero VAD loads (ONNX), Whisper loads on cuda, server ready - llama-swap-rocm: add root .dockerignore to fix 31 GB build context - Dockerfile clones all sources from git, never COPYs from context - 19 GB of GGUF model files were being transferred on every build - Now excludes everything (*), near-zero context transfer - anime-face-detector: add .dockerignore to exclude accumulated outputs - api/outputs/ (56 accumulated detection files) no longer baked into image - api/__pycache__/ and images/ also excluded - .gitignore: remove .dockerignore exclusion so these files are tracked
80 lines
881 B
Plaintext
80 lines
881 B
Plaintext
# ============================================
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# Python
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__pycache__/
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*.py[cod]
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*$py.class
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*.so
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.Python
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*.egg-info/
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dist/
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build/
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# Virtual environments
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venv/
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env/
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ENV/
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# IDE
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.vscode/
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.idea/
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*.swp
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*.swo
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# Models (too large for git)
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models/*.gguf
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models/*.bin
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# Keep the directory structure
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!models/.gitkeep
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# Environment variables & Secrets
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.env
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.env.local
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.env.*.local
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*.secret
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# Logs
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*.log
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logs/
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# OS
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.DS_Store
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Thumbs.db
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# Bot memory (contains user data)
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bot/memory/*.json
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bot/memory/autonomous_context.json
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!bot/memory/.gitkeep
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# Sensitive files
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*credentials*.json
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*secrets*.json
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*keys*.json
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*cookies*.json
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# Test outputs
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*.tmp
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*.temp
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test_output.*
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output/
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temp_*
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# Audio files (except static assets)
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*.mp3
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*.wav
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*.ogg
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!static/audio/*.mp3
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!static/audio/*.wav
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# Images (except static assets)
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*.png
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*.jpg
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*.jpeg
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*.gif
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!static/images/*
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# Backups
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backups/
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*.bak
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*.backup
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