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.
Weather App With State Management for Long Running Conversations Using AI Agents

Weather App With State Management for Long Running Conversations Using AI Agents

Comments
2 min read
Build RAG Chatbot with LangChain, Milvus, Anthropic Claude 3 Haiku, and voyage-3-large

Build RAG Chatbot with LangChain, Milvus, Anthropic Claude 3 Haiku, and voyage-3-large

Comments
8 min read
Running locally DeepSeek-R1 for RAG

Running locally DeepSeek-R1 for RAG

Comments
4 min read
Building a Multi-modal Production RAG

Building a Multi-modal Production RAG

Comments
2 min read
Virtual Research Analyst - Harnessing Agentic and Multi-modal RAG

Virtual Research Analyst - Harnessing Agentic and Multi-modal RAG

Comments
1 min read
Best Practices for Production-Scale RAG Systems — An Implementation Guide

Best Practices for Production-Scale RAG Systems — An Implementation Guide

Comments
12 min read
Let’s Build Enterprise Cybersecurity Risk Assessment Using AI Agents

Let’s Build Enterprise Cybersecurity Risk Assessment Using AI Agents

Comments
2 min read
Building an IBM AIX Expert Chatbot using RAG and FAISS

Building an IBM AIX Expert Chatbot using RAG and FAISS

Comments
3 min read
Building Local AI Agents: A Practical Guide to Frameworks and Deployment

Building Local AI Agents: A Practical Guide to Frameworks and Deployment

Comments
6 min read
NoLiMA: GPT-4o achieve 99.3% accuracy in short contexts (<1K tokens), performance degrades to 69.7% at 32K tokens.

NoLiMA: GPT-4o achieve 99.3% accuracy in short contexts (<1K tokens), performance degrades to 69.7% at 32K tokens.

5
Comments 1
1 min read
Build RAG Chatbot with LangChain, Milvus, GPT-4o mini, and text-embedding-3-large

Build RAG Chatbot with LangChain, Milvus, GPT-4o mini, and text-embedding-3-large

5
Comments
4 min read
GraphRAG: Augmenting Retrieval-Augmented Generation with Knowledge Graphs

GraphRAG: Augmenting Retrieval-Augmented Generation with Knowledge Graphs

Comments
4 min read
Understanding and Implementing ReAct

Understanding and Implementing ReAct

Comments
4 min read
RAG: What, Why and How

RAG: What, Why and How

Comments
6 min read
How Vector Search is Changing the Game for AI-Powered Discovery

How Vector Search is Changing the Game for AI-Powered Discovery

Comments
5 min read
Best AI Setups for Multi-Agent Workflows in KaibanJS

Best AI Setups for Multi-Agent Workflows in KaibanJS

Comments
3 min read
Thriving as a Personal Tech Consultant: Navigating the AI Revolution

Thriving as a Personal Tech Consultant: Navigating the AI Revolution

2
Comments
6 min read
Extracting code snippets from a call graph for LLM context

Extracting code snippets from a call graph for LLM context

Comments
3 min read
Let’s Build HealthIQ AI — A Vertical AI Agent System

Let’s Build HealthIQ AI — A Vertical AI Agent System

Comments
2 min read
Announcing Kreuzberg v2.0: A Lightweight, Modern Python Text Extraction library

Announcing Kreuzberg v2.0: A Lightweight, Modern Python Text Extraction library

Comments
2 min read
Corrective Retrieval-Augmented Generation: Enhancing Robustness in AI Language Models

Corrective Retrieval-Augmented Generation: Enhancing Robustness in AI Language Models

Comments
2 min read
Evaluate your LLM! Ok, but what's next? 🤔

Evaluate your LLM! Ok, but what's next? 🤔

5
Comments
1 min read
Building CSV RAG with Rig and Rust 🔥🔥🔥

Building CSV RAG with Rig and Rust 🔥🔥🔥

2
Comments
5 min read
How Generative AI is Revolutionizing Financial Institutions in 2025: Top 10 Use Cases

How Generative AI is Revolutionizing Financial Institutions in 2025: Top 10 Use Cases

Comments
7 min read
DO NOT use these LLM Metrics â›” And what to do instead!

DO NOT use these LLM Metrics â›” And what to do instead!

6
Comments
1 min read
loading...