RAG
Best Ways to Connect Local AI to Notion in 2026
4 real ways to connect Notion to a local LLM without sending data to the cloud. MCP servers, RAG pipelines, Open WebUI, and n8n workflows compared with setup steps.
RAG Pipeline for Local AI: A Practical Guide to Retrieval-Augmented Generation
Build a local RAG pipeline with Ollama, ChromaDB, and your own documents. Chunking strategies, embedding models, vector stores, and the failure modes nobody warns you about.
Local AI for Accounting and Tax: Keep Your Financial Data Off the Cloud
Local LLMs can categorize transactions, draft client letters, extract receipt data, and answer questions over tax documents — without sending a single number to OpenAI or Google. What works, what doesn't, and how to set it up.
Local AI for Lawyers: Confidential Document Analysis Without Cloud Risk
A federal judge ordered OpenAI to hand over 20 million chat logs. If you're a lawyer using ChatGPT for client work, that's an ethics problem. Local AI keeps everything on your hardware.
Ghost Knowledge: When Your RAG System Cites Documents That No Longer Exist
Your RAG system confidently quotes a policy that was updated months ago. The old version is still in the vector database. Nobody notices until the wrong answer costs real money. Here's how to find and fix ghost knowledge.
Obsidian + Local LLM: Build a Private AI Second Brain
Connect Obsidian to a local LLM via Ollama for private AI-powered note search, summaries, and chat. Step-by-step setup with Copilot and Smart Connections.
PaddleOCR-VL: A 0.9B OCR Model That Runs on Any Potato
PaddleOCR-VL does document OCR — text, tables, formulas, charts — in 0.9B parameters. 109 languages. Now runs via llama.cpp and Ollama. Private, local, nearly free.
Context Length Exceeded: What To Do When Your Model Runs Out of Space
Model forgetting earlier messages or throwing context errors? How context length works, what happens when it fills, and practical fixes for chat, RAG, and coding.
Why Your AI Keeps Lying: The Hallucination Feedback Loop
How one bad memory poisoned our entire RAG pipeline — and the immune system we built to fix it. Real code from mycoSwarm's self-correcting retrieval system.
The AI Memory Wall: Why Your Chatbot Forgets Everything
Six architectural reasons ChatGPT, Claude, and Gemini forget your conversations — and how local AI setups solve the memory problem with persistent storage and RAG.
Session-as-RAG: Teaching Your Local AI to Actually Remember
Build persistent conversation memory for local LLMs. Chunk sessions, embed in ChromaDB, retrieve relevant past exchanges at query time. Full Python implementation with topic splitting and date citations.
Week 3: Unified Memory Search — The Swarm Remembers
Session-as-RAG, topic splitting, citation tracking, and three releases in two days. The swarm can now search its own conversation history.
Building a Local AI Assistant: Your Private Jarvis
Build a private AI assistant with Ollama, Open WebUI, Whisper, and Kokoro TTS. Voice chat, document Q&A, home automation — all local, no cloud, no subscriptions.
Embedding Models for RAG: Which to Run Locally
nomic-embed-text is still the default for most local RAG setups — 274MB, 8K context, runs on CPU. But Qwen3-Embedding 0.6B just changed the game. Model picks, VRAM needs, speed numbers, and the chunking mistakes that break retrieval.
AnythingLLM Setup Guide: Chat With Your Documents Locally
Upload PDFs, paste URLs, and chat with your files — no coding, no cloud. AnythingLLM connects to Ollama in 5 minutes with point-and-click RAG on 54K+ GitHub stars.
Best Local LLMs for RAG in 2026
The best local models for retrieval-augmented generation by VRAM tier. Qwen 3, Command R 35B, embedding models, and RAG stacks with real failure modes.
Local RAG: Search Your Documents with a Private AI
Search your private PDFs, notes, and code with a local LLM—no cloud, no API calls. 3 setup methods from zero-config Open WebUI to 30 lines of Python with ChromaDB.