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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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**Processing Mode**

**Processing Mode**

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3 min read
Vector Databases Guide: RAG Applications 2025
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Vector Databases Guide: RAG Applications 2025

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10 min read
The Secret to Efficient RAG: A Step-by-Step Guide to Chunking and Counting Your Vectors

The Secret to Efficient RAG: A Step-by-Step Guide to Chunking and Counting Your Vectors

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11 min read
LLPY-03: Extracción y Procesamiento Inteligente de Datos Legales
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LLPY-03: Extracción y Procesamiento Inteligente de Datos Legales

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21 min read
Embedded Intelligence: How SQLite-vec Delivers Fast, Local Vector Search for AI.

Embedded Intelligence: How SQLite-vec Delivers Fast, Local Vector Search for AI.

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7 min read
RAG: experiments with prompting using 3 LLM's
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RAG: experiments with prompting using 3 LLM's

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8 min read
Exposing the Magic of Large Language Models Like ChatGPT Explained Simply for CEOs and Lawyers

Exposing the Magic of Large Language Models Like ChatGPT Explained Simply for CEOs and Lawyers

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4 min read
How I Built an AI Workspace To Help Students & Researchers
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How I Built an AI Workspace To Help Students & Researchers

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2 min read
Build Agentic Video RAG with Strands Agents and Containerized Infrastructure
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Build Agentic Video RAG with Strands Agents and Containerized Infrastructure

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6 min read
How We Used RAG to Power an AI-First Internal Tool Builder
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How We Used RAG to Power an AI-First Internal Tool Builder

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2 min read
LLPY-02: Configurando un Entorno de Desarrollo Moderno con UV
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LLPY-02: Configurando un Entorno de Desarrollo Moderno con UV

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5 min read
🚀 Sample RAG app with Strands, Reflex and S3
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🚀 Sample RAG app with Strands, Reflex and S3

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2 min read
But what is “contextual search” — case study of KENDO-RAG and how it beats Google for private data
Cover image for But what is “contextual search” — case study of KENDO-RAG and how it beats Google for private data

But what is “contextual search” — case study of KENDO-RAG and how it beats Google for private data

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7 min read
From Documents to Dialogue: A step-by-step RAG Journey

From Documents to Dialogue: A step-by-step RAG Journey

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5 min read
From Zero to 1 B Vectors: the 2025 No-BS Picking Guide

From Zero to 1 B Vectors: the 2025 No-BS Picking Guide

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2 min read
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