#RAG

Mastodon discussion May 24

LMIM OS v2.1 "Tezcat · Sharpened" drops tomorrow.This isn't a patch. It's a different animal:• RAG Lite — drop a PDF, as...

LMIM OS v2.1 "Tezcat · Sharpened" drops tomorrow.This isn't a patch. It's a different animal:• RAG Lite — drop a PDF, ask anything about it• Workspace sandbox — point LMIM at a fol...

RAG

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Dev.to tutorial May 24

How We Built a Production RAG Chatbot for a Client in 72 Hours (Full Stack Breakdown)

A client messaged us on a Tuesday night. By Friday afternoon, their customer support chatbot was live...

RAG

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Mastodon discussion May 23

Show HN: I built a RAG and knowledge graph agent that runs locallyhttps://news.ycombinator.com/item?id=48248801#HackerNe...

Show HN: I built a RAG and knowledge graph agent that runs locallyhttps://news.ycombinator.com/item?id=48248801#HackerNews #Tech #AI

RAG

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Dev.to tutorial May 23

Building a Private RAG System: Lessons from a Local-First AI Journal

Most AI apps quietly send your data to the cloud. DiaryGPT does the opposite — and this is the full...

RAG

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GitHub Trending repo May 23

study8677/awesome-architecture: 🗺️ Think like a software architect, not just a coder — 21 architecture maps (incl. AI gateway, RAG, agents, inference serving, vector DB) + a language-agnostic system-design tutorial. Every template links to real open-source prototypes. 中英文双语。

🗺️ Think like a software architect, not just a coder — 21 architecture maps (incl. AI gateway, RAG, agents, inference serving, vector DB) + a language-agnostic system-design tutori...

RAG Open Source

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Dev.to tutorial May 23

From Manual RAG to Real Retrieval — Embedding-Based RAG with NVIDIA NIM

Replace hardcoded context with real retrieval using NVIDIA's nv-embedqa-e5-v5 embedding model. Cosine similarity, the query vs passage input distinction most beginners get wrong, n...

NVIDIA RAG

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Dev.to tutorial May 22

What Enterprise RAG Is Ready For Today and What Production Deployment Actually Requires

Enterprise RAG — A practitioner's build log | Post 6 of 6 This series has documented a system built...

RAG

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Mastodon discussion May 22

RAG en PostgreSQL con pgEdge: búsqueda híbrida 2026¿Necesitás una base de datos vectorial o alcanza pgvector? Armá tu pi...

RAG en PostgreSQL con pgEdge: búsqueda híbrida 2026¿Necesitás una base de datos vectorial o alcanza pgvector? Armá tu pipeline RAG en PostgreSQL con búsqueda híbrida y cero infraes...

RAG

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Mastodon discussion May 22

In RAG, the bottleneck isn’t your app server—it’s vector search, rerankers, and LLM latency.Go is fast glue around slow ...

In RAG, the bottleneck isn’t your app server—it’s vector search, rerankers, and LLM latency.Go is fast glue around slow calls. TypeScript on Bun matches that speed *and* brings bet...

LLM RAG

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Dev.to tutorial May 22

I Stacked 4 More Context Layers on Top of RAG. Sonnet Got 12% Better. Haiku Got 14% Worse.

I read about Full Context Engineering and added structured output, hierarchical layout, role definition, and few-shot examples to my RAG pipeline. Sonnet got 12% better. Haiku got ...

RAG

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Dev.to tutorial May 22

I tested 7 vector databases for my RAG stack in 2026, here's the one nobody is talking about (yet)

TL;DR: I spent 1 week benchmarking Pinecone, Weaviate, Qdrant, Milvus, pgvector, SurrealDB, and...

RAG

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Dev.to tutorial May 22

LLM-Wiki: Multi-Agent Memory Without RAG

How three AI agents can collaborate on a complex task by sharing a folder of markdown files — and...

LLM RAG

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Dev.to tutorial May 22

Building a P2P 'Wikipedia for Machines': Verifiable RAG with the Holepunch Stack

Current LLMs hallucinate when they lack context. While Retrieval-Augmented Generation (RAG) helps,...

RAG

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Mastodon discussion May 22

I'm very pleased to release our first work on "RAG and GraphRAG Experiments on MCPs: Perspectives for Historical Researc...

I'm very pleased to release our first work on "RAG and GraphRAG Experiments on MCPs: Perspectives for Historical Research." This work was conducted with historian Caroline Muller (...

RAG

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Dev.to tutorial May 22

GLIA — A holographic memory for AI agents that isn't a graph and isn't RAG

Every AI coding agent I've used (Cline, Claude, Cursor, etc) has the same problem: it forgets...

Anthropic RAG

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Dev.to tutorial May 22

How to build a production RAG pipeline in Python (without a vector database)

Everyone reaching for a vector database when building RAG is solving the wrong problem first. For...

RAG

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Dev.to tutorial May 22

How a Single PDF Can Poison 100 RAG Systems: The Vulnerability We Aren't Talking About

How a PDF hijacked a $50K/month RAG pipeline Recently, a security report surfaced about an...

RAG

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Dev.to tutorial May 22

Como treinei uma IA de suporte com histórico real de atendimento: da conversa bruta ao RAG em produção

Esse artigo é a documentação completa do pipeline que construí para extrair conhecimento do histórico...

RAG

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Dev.to tutorial May 21

Four Metrics That Actually Tell You Whether Your Enterprise RAG Is Working

Enterprise RAG — A practitioner's build log | Post 4 of 6 RAG evaluation in most implementations...

RAG

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Dev.to tutorial May 21

I was embarrassed by my RAG demo. Turns out the bug was never in my code.

I showed my RAG app to a friend. He asked: "which region grew the most last quarter?" It said...

RAG

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Dev.to tutorial May 21

Three Design Decisions That Shaped the Enterprise RAG Retrieval Pipeline

Enterprise RAG — A practitioner's build log | Post 3 of 6 A retrieval pipeline has more design...

RAG

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Dev.to tutorial May 21

Built a 100k-Document RAG System by Hand. Hermes Read the Architecture in 47 Seconds.

This is a submission for the Hermes Agent Challenge For the past six months, I have been building...

RAG

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Dev.to tutorial May 21

RAG Series (24): Code RAG — Teaching AI to Understand Your Codebase

The Difference Between Code and Documents Split a Python file into 1000-character chunks...

RAG

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GitHub Trending repo May 21

Neal006/memorylens: The open-source benchmark for LLM memory decay. Measure how Naive, RAG, Chunked RAG, Cascading, and SummaryMemory degrade over 100 conversation turns. Ebbinghaus forgetting curves, 5-provider LLM eval, multi-seed CI. No API key needed.

The open-source benchmark for LLM memory decay. Measure how Naive, RAG, Chunked RAG, Cascading, and SummaryMemory degrade over 100 conversation turns. Ebbinghaus forgetting curves,...

LLM RAG Open Source

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