31 lines
2.1 KiB
JSON
Executable File
31 lines
2.1 KiB
JSON
Executable File
{
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"id": "privacy-first-ai-laptop",
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"name": "Privacy-First AI Laptop Setup",
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"description": "The complete privacy-respecting AI stack for your laptop. All processing on-device, no telemetry, no cloud APIs. Ollama + Whisper + Obsidian + Paperless-NGX + local search. Popular with privacy-focused YouTubers and FOSS advocates.",
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"version": "1.0",
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"author": "ai-lsc",
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"tags": ["privacy", "offline", "laptop", "document-management", "youtube-trending", "local-first", "foss"],
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"endpoints": {
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"ollama_base": "http://localhost:11434",
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"openwebui": "http://localhost:3000",
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"paperlessngx": "http://localhost:8000"
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},
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"tools": [
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"ollama",
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"openwebui",
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"whisper",
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"docling",
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"markitdown",
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"obsidian",
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"paperlessngx",
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"fabric"
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],
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"notes": {
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"youtube_context": "Privacy-focused AI content has exploded. Channels like @TheLinuxExperiment, @crosstalksolutions, and @braveouterweb showcase fully local AI setups. The message: 'Your AI should stay on your machine.' This template builds that exact vision.",
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"recommended_models": "llama3.1:8b (daily driver, 4GB VRAM), phi-4:14b (quality on 8GB), mistral-nemo:12b (sweet spot), gemma2:9b (fast), nomic-embed-text (document embeddings)",
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"setup": "Ollama runs as a systemd service. Open WebUI provides the chat frontend. Paperless-NGX ingests scanned documents. Docling/MarkItDown converts them for RAG. Whisper handles voice memos. Obsidian links everything with local markdown notes.",
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"workflow": "Paper documents → scan → Paperless-NGX (OCR + tagging) → Docling (extract text) → Open WebUI RAG (chat with your documents). Voice notes → Whisper → text → Fabric → summarized notes → Obsidian vault. All data stays on your NVMe.",
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"tips": "For laptops with <8GB VRAM, use 4-bit quantized models. Set OLLAMA_NUM_PARALLEL=1 to prevent VRAM thrashing. Paperless-NGX works great with 2GB RAM allocated. Use Obsidian's local graph view to visualize connections between your AI-generated notes and source documents."
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}
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}
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