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

👋 Sign in for the ability to sort posts by relevant, latest, or top.
How GenAI Gets Smarter: The Power of Context with RAG

How GenAI Gets Smarter: The Power of Context with RAG

2
Comments
3 min read
Advanced Prompting Techniques and Embeddings in AI

Advanced Prompting Techniques and Embeddings in AI

Comments
4 min read
Supercharging Retrieval-Augmented Generation with NodeRAG: A Graph-Centric Approach

Supercharging Retrieval-Augmented Generation with NodeRAG: A Graph-Centric Approach

Comments
5 min read
🧠 RAG in Minutes with MultiMind SDK — No LangChain Needed

🧠 RAG in Minutes with MultiMind SDK — No LangChain Needed

4
Comments
2 min read
How AI Agents Empower Small Businesses for Global Success

How AI Agents Empower Small Businesses for Global Success

5
Comments
4 min read
How to Evaluate RAG Applications with Amazon Bedrock Knowledge Base Evaluation

How to Evaluate RAG Applications with Amazon Bedrock Knowledge Base Evaluation

Comments
16 min read
⚡️ BREAKING: Docling Unlocks ASR (automatic speech recognition) Power!

⚡️ BREAKING: Docling Unlocks ASR (automatic speech recognition) Power!

1
Comments
5 min read
Secure Local RAG with Role-Based Access: Spring AI, Ollama & MongoDB

Secure Local RAG with Role-Based Access: Spring AI, Ollama & MongoDB

15
Comments
14 min read
Open-Source AI Stacks for E-Commerce (2025 Guide)

Open-Source AI Stacks for E-Commerce (2025 Guide)

Comments
7 min read
Local Elasticsearch Playground: A Practical Introduction and hands-on test (and moving to a RAG solution)

Local Elasticsearch Playground: A Practical Introduction and hands-on test (and moving to a RAG solution)

Comments
12 min read
Engineering a Production-Grade RAG Pipeline with Gemini & Qdrant (Design Guide + Code)

Engineering a Production-Grade RAG Pipeline with Gemini & Qdrant (Design Guide + Code)

Comments
8 min read
A Complete Guide to Retrieval-Augmented Generation

A Complete Guide to Retrieval-Augmented Generation

6
Comments
8 min read
Semantic Similarity Score for AI RAG

Semantic Similarity Score for AI RAG

Comments
1 min read
RAG Made Simple: Simplicity’s Approach to Modular Retrieval & Generation (Part 1)

RAG Made Simple: Simplicity’s Approach to Modular Retrieval & Generation (Part 1)

Comments
3 min read
AI Fiqh & Retrieval-augmented generation (RAG)

AI Fiqh & Retrieval-augmented generation (RAG)

Comments
8 min read
RAG to Riches

RAG to Riches

Comments 4
3 min read
RAG Made Simple: Demonstration and Analysis of Simplicity (Part 3)

RAG Made Simple: Demonstration and Analysis of Simplicity (Part 3)

Comments 3
2 min read
RAG Made Simple: Technical Design and Architecture of Simplicity (Part 2)

RAG Made Simple: Technical Design and Architecture of Simplicity (Part 2)

Comments 2
3 min read
VLM Pipeline with Docling

VLM Pipeline with Docling

Comments
7 min read
Demystifying RAG 🔍: Retrieval-Augmented Generation Explained

Demystifying RAG 🔍: Retrieval-Augmented Generation Explained

Comments
3 min read
Built an AI Assistant to Summarize and Query My Emails – Seeking Feedback

Built an AI Assistant to Summarize and Query My Emails – Seeking Feedback

Comments
1 min read
Cosine Similarity in Vector Databases: Why It Matters for GenAI & RAG Systems

Cosine Similarity in Vector Databases: Why It Matters for GenAI & RAG Systems

Comments
2 min read
Getting Started with LangChain: Build Smarter AI Apps with LLMs

Getting Started with LangChain: Build Smarter AI Apps with LLMs

6
Comments
3 min read
🤖 Retrieval-Augmented Generation (RAG): The Future of AI Search

🤖 Retrieval-Augmented Generation (RAG): The Future of AI Search

3
Comments
2 min read
RAG na prática: transformando PDFs em respostas inteligentes com LLMs

RAG na prática: transformando PDFs em respostas inteligentes com LLMs

2
Comments 2
6 min read
loading...