{ "id": "privacy-first-ai-laptop", "name": "Privacy-First AI Laptop Setup", "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.", "version": "1.0", "author": "ai-lsc", "tags": ["privacy", "offline", "laptop", "document-management", "youtube-trending", "local-first", "foss"], "endpoints": { "ollama_base": "http://localhost:11434", "openwebui": "http://localhost:3000", "paperlessngx": "http://localhost:8000" }, "tools": [ "ollama", "openwebui", "whisper", "docling", "markitdown", "obsidian", "paperlessngx", "fabric" ], "notes": { "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.", "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)", "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.", "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.", "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." } }