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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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Taming the Data Tsunami: Handling Big Data in Real-Time

Taming the Data Tsunami: Handling Big Data in Real-Time

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2 min read
Cloud Cost Optimization: The Ultimate Guide to Saving You from Bill Shock

Cloud Cost Optimization: The Ultimate Guide to Saving You from Bill Shock

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2 min read
Unlocking the Power of AI: What is Prompt Engineering?

Unlocking the Power of AI: What is Prompt Engineering?

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3 min read
From Query Understanding to Retrieval: Evaluating Rewriting, Filters, and Routing With Online Evals

From Query Understanding to Retrieval: Evaluating Rewriting, Filters, and Routing With Online Evals

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12 min read
Ten Failure Modes of RAG Nobody Talks About (And How to Detect Them Systematically)

Ten Failure Modes of RAG Nobody Talks About (And How to Detect Them Systematically)

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10 min read
🧠 Comunicando o Entity Framework .NET com LLM

🧠 Comunicando o Entity Framework .NET com LLM

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4 min read
What is Context Engineering?

What is Context Engineering?

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12 min read
Spring AI: How to use Generative AI and apply RAG?

Spring AI: How to use Generative AI and apply RAG?

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10 min read
Blockchain Analytics: Exploring Ethereum Data with BigQuery, RAG, and AI

Blockchain Analytics: Exploring Ethereum Data with BigQuery, RAG, and AI

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1 min read
🧑‍⚖️ Building a Saudi Labor Law AI Assistant — Bilingual, Semantic, and Context-Aware

🧑‍⚖️ Building a Saudi Labor Law AI Assistant — Bilingual, Semantic, and Context-Aware

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3 min read
Behind the Scenes: How I Built ResumeMatcher’s RAG Pipeline

Behind the Scenes: How I Built ResumeMatcher’s RAG Pipeline

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3 min read
No More Forgetful Robots: My Test Drive with Cognee AI's "AI Memory"

No More Forgetful Robots: My Test Drive with Cognee AI's "AI Memory"

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3 min read
LLPY-04: Vectorización y Embeddings - Preparando Datos para RAG

LLPY-04: Vectorización y Embeddings - Preparando Datos para RAG

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13 min read
Building a RAG from Scratch: A Beginner's Guide (Part 3: Dockerization and Flexible Configuration)

Building a RAG from Scratch: A Beginner's Guide (Part 3: Dockerization and Flexible Configuration)

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3 min read
Building a RAG from Scratch: A Beginner's Guide (Part 2: Building a Web API)

Building a RAG from Scratch: A Beginner's Guide (Part 2: Building a Web API)

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2 min read
Building a 'Chat with Your Logs' System on AWS Using OpenSearch Serverless and Bedrock

Building a 'Chat with Your Logs' System on AWS Using OpenSearch Serverless and Bedrock

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7 min read
RAG Firewall: The missing retrieval-time security layer for LLMs (v0.4.1)

RAG Firewall: The missing retrieval-time security layer for LLMs (v0.4.1)

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2 min read
Building a RAG from Scratch: A Beginner's Guide (Part 1: The Basic Pipeline)

Building a RAG from Scratch: A Beginner's Guide (Part 1: The Basic Pipeline)

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3 min read
Why Agents, Not Just LLMs?

Why Agents, Not Just LLMs?

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2 min read
Building a Local Documentation Chatbot with Python, FAISS, and OpenAI

Building a Local Documentation Chatbot with Python, FAISS, and OpenAI

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7 min read
Beyond the Diff: How Deep Context Analysis Caught a Critical Bug in a 20K-Star Open Source Project

Beyond the Diff: How Deep Context Analysis Caught a Critical Bug in a 20K-Star Open Source Project

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7 min read
🎥 Model Context Protocol (MCP) Clearly Explained in Hindi

🎥 Model Context Protocol (MCP) Clearly Explained in Hindi

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1 min read
From Knowledge Graph Generation to RAG for Stablecoin Regulatory Intelligence

From Knowledge Graph Generation to RAG for Stablecoin Regulatory Intelligence

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11 min read
Quick Framework and some Performance Improvements

Quick Framework and some Performance Improvements

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6 min read
Building an Intelligent RAG Agent with Azure AI Foundry: A Deep Dive into Sreeni-RAG

Building an Intelligent RAG Agent with Azure AI Foundry: A Deep Dive into Sreeni-RAG

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8 min read
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