How I fixed silent Ollama failures in my local AI Assistant
How I fixed silent Ollama failures in my local AI assistant Neo-AI is an offline assistant with episodic memory, running entirely on-device using Olla…
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Локальные LLM на Arch Linux и как увеличить скорость генерации в 20 раз
Приветствую всех читателей Хабра, в этой статье я хочу поделиться своим опытом в запуске локальных LLM, протестировать работоспособность инт…
NeoBrain: A Local Alternative to Character.AI
🧠 NeoBrain: локальный аналог Character.AI Запусти ИИ-персонажей на своём ПК — без интернета, VPN и слежки. 🤔 Проблема Character.AI хорош, но: ❌ Заблок…
Local-first: a Model on Your Own Machine, Zero Cloud
This is the concrete, runnable walkthrough for Post 1 of the Portway series . The goal: stand up a single model behind an OpenAI-compatible endpoint o…
CrawlForge v4.2.2: New CLI + 3 Tools for Local AI Scraping
Today we are shipping CrawlForge v4.2.2 , our biggest release since launch. It brings three new tools, a standalone command-line interface, and a quie…
Using Ollama with the Laravel AI SDK: Run Local LLMs for Free
Originally published at hafiz.dev API costs add up fast during AI development. You prompt an agent 50 times debugging a tool, that's 50 API calls. You…
I shipped local LLM features two months ago. Production never ran them once.
This is a submission for the Gemma 4 Challenge: Build with Gemma 4 Two months ago I shipped local-LLM features in TextStack — an open-source reader fo…
No More Hallucinated Citations: A Domain-Specific RAG System with Ollama, ChromaDB and AI Agents
TL;DR: I built a full-stack knowledge pipeline around a corpus of 2,514 academic PDFs focused on urban art. The system combines ChromaDB vector search…
[Day 3] I Had a Local LLM Analyze a Year of My Credit Card Statements
[Day 3] I Had a Local LLM Analyze a Year of My Credit Card Statements Intro Day 3: I'm going to hand a year of credit card statements over to a local …
Build a RAG agent with LangChain and Ollama
I started where a lot of us do: a LangChain RAG walkthrough. You chunk some text, embed it, retrieve top‑k chunks, and wire an LLM to answer questions…