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# 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.

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LimeLight-An Autonomous Assistant for Enterprise Community Platforms Using RAG, LangChain, and LLaMA 3
Cover image for LimeLight-An Autonomous Assistant for Enterprise Community Platforms Using RAG, LangChain, and LLaMA 3

LimeLight-An Autonomous Assistant for Enterprise Community Platforms Using RAG, LangChain, and LLaMA 3

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Comments 1
3 min read
Retrieval Technique Series-4.How Search Engines Generate Indexes for Trillions of Websites?

Retrieval Technique Series-4.How Search Engines Generate Indexes for Trillions of Websites?

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5 min read
Beyond Borders: Seamless Document Translation with Docling and Granite

Beyond Borders: Seamless Document Translation with Docling and Granite

1
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5 min read
NVIDIA Agentic AI 전략

NVIDIA Agentic AI 전략

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1 min read
How AI Understands Your Documents: The Secret Sauce of RAG
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How AI Understands Your Documents: The Secret Sauce of RAG

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2 min read
LangGraph + Graphiti + Long Term Memory = Powerful Agentic Memory
Cover image for LangGraph + Graphiti + Long Term Memory = Powerful Agentic Memory

LangGraph + Graphiti + Long Term Memory = Powerful Agentic Memory

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11 min read
Generative Engine Optimization (GEO): The New Frontier Beyond SEO
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Generative Engine Optimization (GEO): The New Frontier Beyond SEO

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Comments 2
3 min read
VectorRAG is naive, lacks domain awareness, and can’t handle full dataset retrieval
Cover image for VectorRAG is naive, lacks domain awareness, and can’t handle full dataset retrieval

VectorRAG is naive, lacks domain awareness, and can’t handle full dataset retrieval

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1 min read
Retrieval Metrics Demystified: From BM25 Baselines to EM@5 & Answer F1
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Retrieval Metrics Demystified: From BM25 Baselines to EM@5 & Answer F1

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4 min read
Tools to Detect & Reduce Hallucinations in a LangChain RAG Pipeline in Production

Tools to Detect & Reduce Hallucinations in a LangChain RAG Pipeline in Production

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6 min read
How to Build Agentic Rag in Rust
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How to Build Agentic Rag in Rust

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6 min read
🌟 Day 8: RAG & Prompt Templates — Wisdom Meets AI the Indian Way
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🌟 Day 8: RAG & Prompt Templates — Wisdom Meets AI the Indian Way

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5 min read
Technical Deep Dive: Building an AI-Powered Real Time Root Cause Analysis System
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Technical Deep Dive: Building an AI-Powered Real Time Root Cause Analysis System

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2 min read
How run LLM in local using Docker.
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How run LLM in local using Docker.

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2 min read
Understanding Reciprocal Rank Fusion (RRF) in Retrieval-Augmented Systems

Understanding Reciprocal Rank Fusion (RRF) in Retrieval-Augmented Systems

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2 min read
What Are LLMs, Really? Why Everyone's Talking About Them (and Why You Should Too)
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What Are LLMs, Really? Why Everyone's Talking About Them (and Why You Should Too)

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4 min read
🛣️ Day 7: From Road Trips to Lost & Found — Mastering Document Splitting & Retrieval with LangChain 🎒🧭
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🛣️ Day 7: From Road Trips to Lost & Found — Mastering Document Splitting & Retrieval with LangChain 🎒🧭

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4 min read
Chat your website to life: The CMS, Reimagined
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Chat your website to life: The CMS, Reimagined

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2 min read
40+ MCP Search Tools
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40+ MCP Search Tools

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1 min read
How to build an AI-Powered Retrieval-Augmented Generation (RAG) Chatbot Assistant with TypeScript, Node.js and LangGraph

How to build an AI-Powered Retrieval-Augmented Generation (RAG) Chatbot Assistant with TypeScript, Node.js and LangGraph

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12 min read
Building a Chatbot With Symfony and MongoDB

Building a Chatbot With Symfony and MongoDB

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15 min read
Building a RAG (Retrieval-Augmented Generation) system in PHP with Neuron AI
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Building a RAG (Retrieval-Augmented Generation) system in PHP with Neuron AI

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7 min read
🧠 Building a Smart Regulatory Chatbot for IRDAI Using LangChain, Angular, FastAPI & OpenAI
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🧠 Building a Smart Regulatory Chatbot for IRDAI Using LangChain, Angular, FastAPI & OpenAI

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3 min read
Mejora tu English Speaking con Amazon Nova Sonic y RAG
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Mejora tu English Speaking con Amazon Nova Sonic y RAG

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6 min read
DualRAG: A Dual-Process Approach to Integrate Reasoning and Retrieval for Multi-Hop Question Answering

DualRAG: A Dual-Process Approach to Integrate Reasoning and Retrieval for Multi-Hop Question Answering

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2 min read
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