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.
Easiest Way to Build a RAG AI Agent Application

Easiest Way to Build a RAG AI Agent Application

19
Comments 1
6 min read
Ollama Unveiled: Run LLMs Locally

Ollama Unveiled: Run LLMs Locally

2
Comments
2 min read
Understanding the Knowledge Graph: A Deep Dive into Its Benefits and Applications

Understanding the Knowledge Graph: A Deep Dive into Its Benefits and Applications

3
Comments
3 min read
How I Built ‘University Course Finder’ Using RAG

How I Built ‘University Course Finder’ Using RAG

2
Comments
2 min read
RAGEval: Scenario-specific RAG evaluation dataset generation framework

RAGEval: Scenario-specific RAG evaluation dataset generation framework

1
Comments
8 min read
Rag Architecture Easy Explained

Rag Architecture Easy Explained

13
Comments 2
3 min read
From Notebook to Serverless: Creating a Multimodal Search Engine with Amazon Bedrock and PostgreSQL

From Notebook to Serverless: Creating a Multimodal Search Engine with Amazon Bedrock and PostgreSQL

5
Comments
3 min read
Context Caching: Is It the End of Retrieval-Augmented Generation (RAG)? 🤔

Context Caching: Is It the End of Retrieval-Augmented Generation (RAG)? 🤔

7
Comments
3 min read
Desplegando una Aplicación de Embeddings Serverless con AWS CDK, Lambda y Amazon Aurora PostgreSQL

Desplegando una Aplicación de Embeddings Serverless con AWS CDK, Lambda y Amazon Aurora PostgreSQL

5
Comments
6 min read
How OpenAI o1 works in a simple way and why it matters for RAG and Agentic 🤯

How OpenAI o1 works in a simple way and why it matters for RAG and Agentic 🤯

Comments
6 min read
Dockerize Local RAG with Models

Dockerize Local RAG with Models

12
Comments
3 min read
AI-Powered Bot using Vectorized knowledge Architecture

AI-Powered Bot using Vectorized knowledge Architecture

1
Comments
4 min read
Construyendo un Motor de Búsqueda Multimodal con Amazon Titan Embeddings, Aurora Serveless PostgreSQL y LangChain

Construyendo un Motor de Búsqueda Multimodal con Amazon Titan Embeddings, Aurora Serveless PostgreSQL y LangChain

2
Comments
4 min read
De Notebook a Serverless: Creando un Motor de Búsqueda Multimodal con Amazon Bedrock y PostgreSQL

De Notebook a Serverless: Creando un Motor de Búsqueda Multimodal con Amazon Bedrock y PostgreSQL

1
Comments
4 min read
Deploying Serverless Embedding App with AWS CDK, Lambda and Amazon Aurora PostgreSQL

Deploying Serverless Embedding App with AWS CDK, Lambda and Amazon Aurora PostgreSQL

2
Comments
6 min read
👋 Sign in for the ability to sort posts by relevant, latest, or top.