DEV Community

# rag

Retrieval augmented generation, or RAG, is an architectural approach that can improve the efficacy of large language model (LLM) applications by leveraging custom data.

Posts

đź‘‹ Sign in for the ability to sort posts by relevant, latest, or top.
What Is GraphRAG Really Doing? — A Deep Dive into Microsoft's Blog Post

What Is GraphRAG Really Doing? — A Deep Dive into Microsoft's Blog Post

1
Comments
6 min read
RAG Architecture — Prototype to Production in Three Stages

RAG Architecture — Prototype to Production in Three Stages

1
Comments
8 min read
EidolonDB – Self-managing memory for AI agents

EidolonDB – Self-managing memory for AI agents

Comments
1 min read
Teaching Machines to Understand Documents with Docling

Teaching Machines to Understand Documents with Docling

Comments
10 min read
The 5 Levels of RAG Maturity: How to Know When Your RAG Is Actually Production-Ready

The 5 Levels of RAG Maturity: How to Know When Your RAG Is Actually Production-Ready

4
Comments
8 min read
Simplifying the AI Testing through Evaliphy

Simplifying the AI Testing through Evaliphy

1
Comments
5 min read
Speaking the Corpus's Language: How Multilingual RAG Stays Coherent Across Turns

Speaking the Corpus's Language: How Multilingual RAG Stays Coherent Across Turns

Comments 1
8 min read
What are Pre-Trained Models, Fine-Tuning, RAG, and Prompt Engineering? A Simple Kitchen Guide

What are Pre-Trained Models, Fine-Tuning, RAG, and Prompt Engineering? A Simple Kitchen Guide

1
Comments
11 min read
Why Search Breaks in Production

Why Search Breaks in Production

Comments
6 min read
Building a Multi-Agent Research System with LangGraph: How I Taught Three AI Agents to Collaborate

Building a Multi-Agent Research System with LangGraph: How I Taught Three AI Agents to Collaborate

Comments
6 min read
AI Agents: Cost-Optimized Orchestration & Robust Text-to-SQL with Python

AI Agents: Cost-Optimized Orchestration & Robust Text-to-SQL with Python

Comments
4 min read
I built a production RAG pipeline. Here's what most tutorials skip.

I built a production RAG pipeline. Here's what most tutorials skip.

3
Comments 2
7 min read
Embeddings Just Went Multimodal: What Sentence Transformers 5.4 Means for RAG

Embeddings Just Went Multimodal: What Sentence Transformers 5.4 Means for RAG

Comments
2 min read
Marker, hosted: a scientific PDF parser API with LaTeX equations preserved

Marker, hosted: a scientific PDF parser API with LaTeX equations preserved

Comments
4 min read
Anthropic Launches Managed Agents, Optimize LLM Context, Python Memory Needed

Anthropic Launches Managed Agents, Optimize LLM Context, Python Memory Needed

Comments
3 min read
đź‘‹ Sign in for the ability to sort posts by relevant, latest, or top.