Why I Used SHA-256 to Solve a Problem Most RAG Tutorials Pretend Doesn't Exist
When I built GridMind — a fully offline RAG assistant designed to run on CPU-only hardware with under...
#RAG
1135 articles tagged with RAG
# Building a Full Evaluation and Guardrail System for a RAG App
Building a Full Evaluation and Guardrail System for a RAG App Publication-ready draft for...
Как я сделал AI-директора для малого бизнеса и почему отказался от RAGМаленькая компания, человек 20. Гендир тонет в зад...
Как я сделал AI-директора для малого бизнеса и почему отказался от RAGМаленькая компания, человек 20. Гендир тонет в задачах. Помнить кто что обещал, отслеживать движение по целям,...
Building Production RAG: From 52% to 89% Accuracy with a 6-Stage Pipeline
Two hard problems in production AI: Accuracy: RAG systems giving wrong answers 48% of the...
Production Reranker Layer for RAG in Python: Cross-Encoder, Cohere Fallback, and Reciprocal Rank Fusion (Runnable Code)
I shipped my fifth RAG pipeline to production in February. Top-10 recall@10 was 0.94. The team ran a...
Taming Unpredictable User Input: Building a RAG Triage Agent in Node.js
The Problem with Raw User Data When building the backend for an urban infrastructure platform, the...
RAG Series (14): Self-RAG — Let the Model Decide Whether to Retrieve
The Hidden Assumption in Traditional RAG Traditional RAG pipelines never question one...
A Bette RAG AlternativeLATCH는 기존 RAG 방식을 대체하는 새로운 문서 메모리 인프라로, 문서를 한 번 컴파일하여 영구적으로 쿼리할 수 있어 최대 210배 빠른 응답 속도와 97% 비용 절감을...
A Bette RAG AlternativeLATCH는 기존 RAG 방식을 대체하는 새로운 문서 메모리 인프라로, 문서를 한 번 컴파일하여 영구적으로 쿼리할 수 있어 최대 210배 빠른 응답 속도와 97% 비용 절감을 실현한다. NVIDIA H100 GPU 기반 vLLM 인프라에서 벤치마크된 이 솔루션은 VRAM 사용량을 ...
FlowFlow, voice notes with on-device RAG in Rust for iOSFlowFlow는 iOS용 100% Rust 기반 음성 메모 앱으로, 사용자의 음성을 녹음하고 Soniox API를...
FlowFlow, voice notes with on-device RAG in Rust for iOSFlowFlow는 iOS용 100% Rust 기반 음성 메모 앱으로, 사용자의 음성을 녹음하고 Soniox API를 통해 실시간 자동 전사하며, RAG(검색-생성) 기능으로 메모 내용을 질의할 수 있다. 로컬 우선 아키텍처...
ZJunCher/xiaoyan-ai-dev-assistant: 基于 RAG 混合检索与多轮记忆的 AI 研发助手，支持团队知识问答，也适合新手学习 RAG 应用开发。
基于 RAG 混合检索与多轮记忆的 AI 研发助手，支持团队知识问答，也适合新手学习 RAG 应用开发。
How I Built a RAG-Powered Conversational Assistant for Odoo ERP
Every enterprise runs on data — sales orders, invoices, inventory counts, customer records — but...
How /search and /ask Work: Local Hybrid RAG with ChromaDB + SQLite FTS5
This is the second article in a five-part series about building Llamail, a private local AI email...
Auto-Merging RAG: Hierarchical Retrieval ⛓️
🚨 The Problem: Context Fragmentation Imagine a 50-page legal contract. If you chunk it...
RAG is Not Dead - It’s Just Becoming Agent Memory
RAG is not dead. It just got promoted. For years, retrieval-augmented generation helped apps pull the...
Agents that monitor themselves: a self-auditing RAG on Tiger's Agentic Postgres
An experiment in giving an LLM agent the SQL primitives to watch its own retrieval quality. We build a tiny RAG on Tiger's Agentic Postgres stack, then expose ragvitals' drift dime...
Fully open-source RAG with pgvector + pgai + Ollama, and ragvitals watching for drift
An end-to-end open-source RAG stack on Postgres: pgvector for storage, pgai for embedding and generation inside SQL, Ollama for serving Gemma 2 and Llama 3.1 locally, and a 5-dimen...
RAG Series (13): Query Optimization — Asking Better Questions
The Same Question, Completely Different Results Vector retrieval has a fragility that's...
Traditional RAG works for simple lookups, but supply chain leaders need AI that can plan, evaluate, and synthesize evide...
Traditional RAG works for simple lookups, but supply chain leaders need AI that can plan, evaluate, and synthesize evidence. https://hackernoon.com/beyond-chat-why-enterprise-suppl...
Why Your RAG Chatbot Looks Great in Week 1 and Hallucinates by Month 2
💡 Week 1 demo → "this is amazing." Month 2 production → "why is it hallucinating?" I've seen this...
Beyond SQL: How to Build a High-Performance On-Device Vector Search Engine for Android
In the traditional world of Android development, we’ve spent decades perfecting the art of the exact...
Building a multi-tenant RAG pipeline with Postgres. Part 0: Overview
Today I want to start with a series of articles describing my experience building a multi-tenant RAG...
Avi Chawla (@_avichawla)프롬프트 엔지니어링, RAG, 컨텍스트 엔지니어링, 파인튜닝, 에이전트, LLM 배포/최적화, 안전성·평가·관측성까지 포함한 풀스택 AI 엔지니어링 로드맵을 소개합니다. 무...
Avi Chawla (@_avichawla)프롬프트 엔지니어링, RAG, 컨텍스트 엔지니어링, 파인튜닝, 에이전트, LLM 배포/최적화, 안전성·평가·관측성까지 포함한 풀스택 AI 엔지니어링 로드맵을 소개합니다. 무료 오픈소스 자료도 함께 제공되어 AI 개발자에게 유용합니다.https://x.com/_avichawla/s...
TechCrunch drops a massive new glossary to define complex terms like RAG, RLHF, and Large Language Models for everyday u...
TechCrunch drops a massive new glossary to define complex terms like RAG, RLHF, and Large Language Models for everyday users. The tech industry is pushing for total AI literacy in ...
Most RAG failures don’t crash. They silently return bad answers. I built a repair layer for that.
Most RAG tooling provides a score but fails to specify what actually went wrong. I had retrieval...