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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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Getting Started with Google Gemini Embeddings in Python: A Hands-On Guide
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Getting Started with Google Gemini Embeddings in Python: A Hands-On Guide

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3 min read
Document Chat: Open Source AI-Powered Document Management
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Document Chat: Open Source AI-Powered Document Management

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3 min read
Research paper - Bridging Analytics and Semantics with SurrealDB
Cover image for Research paper - Bridging Analytics and Semantics with SurrealDB

Research paper - Bridging Analytics and Semantics with SurrealDB

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1 min read
Unlocking the Power of Vector Databases and AI Search: A Comprehensive Guide 🚀

Unlocking the Power of Vector Databases and AI Search: A Comprehensive Guide 🚀

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7 min read
Apache Spark vs Apache Flink: Choosing the Right Tool for Your Data Journey

Apache Spark vs Apache Flink: Choosing the Right Tool for Your Data Journey

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6 min read
Accessing Low Level Vector APIs

Accessing Low Level Vector APIs

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7 min read
ETL vs ELT: The Great Data Pipeline Debate

ETL vs ELT: The Great Data Pipeline Debate

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2 min read
AI Agents – The Next Big Thing: Revolutionizing Industries with Intelligent Automation

AI Agents – The Next Big Thing: Revolutionizing Industries with Intelligent Automation

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2 min read
AI: RAG Python Problem

AI: RAG Python Problem

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7 min read
Beyond Basic Chunks: Supercharge Your RAG with Docling and OpenSearch

Beyond Basic Chunks: Supercharge Your RAG with Docling and OpenSearch

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9 min read
🧠OrKa docs grew up: a YAML-first reference for Agents, Nodes, and Tools
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🧠OrKa docs grew up: a YAML-first reference for Agents, Nodes, and Tools

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4 min read
Cloud Migration Strategies: A Step-by-Step Guide to a Seamless Transition

Cloud Migration Strategies: A Step-by-Step Guide to a Seamless Transition

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2 min read
Why Your RAG System is Failing: The Graph Database Secret That Boosted Our Retrieval Accuracy by 60%
Cover image for Why Your RAG System is Failing: The Graph Database Secret That Boosted Our Retrieval Accuracy by 60%

Why Your RAG System is Failing: The Graph Database Secret That Boosted Our Retrieval Accuracy by 60%

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7 min read
Revolutionizing Data Pipelines: The Role of AI in Data Engineering

Revolutionizing Data Pipelines: The Role of AI in Data Engineering

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2 min read
Traditional RAG vs Agentic RAG: How AI is Learning to Think for Itself
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Traditional RAG vs Agentic RAG: How AI is Learning to Think for Itself

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4 min read
PPT : Generative AI in Fintech
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PPT : Generative AI in Fintech

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2 min read
Snowflake vs BigQuery vs Redshift: The Ultimate Cloud Data Warehouse Showdown

Snowflake vs BigQuery vs Redshift: The Ultimate Cloud Data Warehouse Showdown

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2 min read
Why LLMs Generate Non-Working Nodes and How to Fix Them
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Why LLMs Generate Non-Working Nodes and How to Fix Them

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5 min read
The Cloud Revolution: Why Cloud Data Engineering is Growing

The Cloud Revolution: Why Cloud Data Engineering is Growing

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2 min read
LLM's Functions, Use-cases & Architecture: Introduction
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LLM's Functions, Use-cases & Architecture: Introduction

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2 min read
Model Context Protocol (MCP)
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Model Context Protocol (MCP)

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1 min read
The Great Debate: Open-Source LLMs vs Proprietary Models

The Great Debate: Open-Source LLMs vs Proprietary Models

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2 min read
BuildingRetrieval-AugmentedGenerationRAGSystemonAmazonBedrock

BuildingRetrieval-AugmentedGenerationRAGSystemonAmazonBedrock

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7 min read
Unraveling the Mysteries of Data: A Beginner's Guide to Data Versioning & Lineage Explained

Unraveling the Mysteries of Data: A Beginner's Guide to Data Versioning & Lineage Explained

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2 min read
Retrieval Augmented Generation (RAG) for Dummies
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Retrieval Augmented Generation (RAG) for Dummies

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2 min read
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