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Rag

A Developer’s Roadmap to Getting Started with AI in 2025

A Developer’s Roadmap to Getting Started with AI in 2025

In my last article, I wrote about a learning path of AI for beginners, in an attempt to demystify its tools and applications for day-to-day tasks. This time, we’re taking a sharp left, so to

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Building Graph RAG for structured and unstructured data.

Building Graph RAG for structured and unstructured data.

RAG architecture is, by far, the most adapted and sophisticated solution for missing contextualisation of LLM’s. With no overhead of fine tuning, to a huge extent problems concerning the usage o

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Building and Serving a RAG Agent with Custom Tools: A Complete Guide

Building and Serving a RAG Agent with Custom Tools: A Complete Guide

Goal The goal of this article is to demonstrate how to create a Large Language Model (LLM) agent using LangGraph and LangChain, which will perform Retrieval-Augmented Generation (RAG) on a

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Building RAG research Multi-Agent with LangGraph

Building RAG research Multi-Agent with LangGraph

❓Introduction — Naive vs Agentic RAG 🧠 Project overview 📊 Results 🔚 ConclusionIn this article, we present a practical project featuring a RAG Research Multi-Agent tool deve

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AI Agents Simplified: How AI Agents Answer Questions Using Domain Knowledge

AI Agents Simplified: How AI Agents Answer Questions Using Domain Knowledge

Demystify how enterprise AI agents are tailored to answer client questions using domain knowledge and strictly confine answers to domain knowledge. Background Have you ever wondered w

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Build your own personalized Fitness RAG Agent using Python!

Build your own personalized Fitness RAG Agent using Python!

AI Agent | RAG Agent | Python | DSPy | Fitness Agent | Beginner-Friendly A complete and beginner-friendly guide to building your fully personalized Fitness RAG Agent with Python.

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Building RAG for Product Recommendation using Google Gemini 2.0 API’s

Building RAG for Product Recommendation using Google Gemini 2.0 API’s

A Comparison of LangChain and Vertex AI RAG Engine on Amazon Product Data using Vertex AI Search Google has always seemed behind in the AI race, but with the release of Gemini 2.0

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Top 21 Famous RAG Frameworks in 2025

Top 21 Famous RAG Frameworks in 2025

Revolutionizing AI with Advanced Retrieval-Augmented Generation Disclosure: I use GPT search. The entire article is still drafted by me.My writing style tends to be assertive and anal

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OpenAI’s o3 + Swarm + RAG Python Project: Easy AI/Chat for your Docs | by Gao Dalie (高達烈) | Dec, 2024 | Towards AI

OpenAI’s o3 + Swarm + RAG Python Project: Easy AI/Chat for your Docs | by Gao Dalie (高達烈) | Dec, 2024 | Towards AI

In this story, I have a super quick tutorial showing you how to create a multi-agent chatbot with Swarm, Rag and OpenAI’s o3 to make a powerful Agent Chatbot for your business or personal use.

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Agentic RAG Series: Exploring LangGraph for Advanced Workflows

Agentic RAG Series: Exploring LangGraph for Advanced Workflows

Stuck behind a paywall? Read for Free! Introduction In the previous article, we introduced the concept of Agentic RAG, highlighting how it extends the traditional Retrieval-Augme

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The Core of Modern AI: Knowledge Graphs and Vector Databases

The Core of Modern AI: Knowledge Graphs and Vector Databases

In the rapidly evolving AI landscape, Retrieval-Augmented Generation (RAG) systems are gaining popularity for their ability to enhance traditional AI models by retrieving relevant informati

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The Rise and Evolution of RAG in 2024: A Year in Review

The Rise and Evolution of RAG in 2024: A Year in Review

As 2024 comes to a close, the development of Retrieval-Augmented Generation (RAG) has been nothing short of turbulent. Let’s take a comprehensive look back at the year’s progress from various per

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Build Production Ready AI Assistant Backend Service (in Python) — Part 2

Build Production Ready AI Assistant Backend Service (in Python) — Part 2

— Build a multi agent RAG system using LangGraph + Secure your Application with Authorization Key Headers *Disclosure — *the contents in this article are my own, and represent no one but myself

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Gemini 2.0 Flash + Local Multimodal RAG + Context-aware Python Project: Easy AI/Chat for your Docs

Gemini 2.0 Flash + Local Multimodal RAG + Context-aware Python Project: Easy AI/Chat for your Docs

In this video, I have a super quick tutorial showing you how to create a local Multimodal RAG, Gemini 2.0 Flash and Context-aware response to make a powerful agent chatbot for your business or

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Hands-on demo with building Agentic RAG (Retrieval-Augmented Generation) pipeline

Hands-on demo with building Agentic RAG (Retrieval-Augmented Generation) pipeline

Illustration to see how autonomous agents can be involved in the RAG system to retrieve the most relevant piece of information What is Agentic RAG? So, we all know what Retrieval Augmented G

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How to build Agentic RAG using CrewAI and Langchain

How to build Agentic RAG using CrewAI and Langchain

In the rapidly evolving landscape of AI, the ability to provide accurate, context-aware responses to user queries is a game-changer. Retrieval-Augmented Generation (RAG) has emerged as a powerf

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Unlocking PDFs for RAG with Markdown and Gemini

Unlocking PDFs for RAG with Markdown and Gemini

It’s safe to say that Retrieval Augmented Generation (RAG) has changed the world for many businesses and organizations. By supplementing the built-in capabilities that an LLM like [Gemini](http

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Agentic Workflow and Retrieval-Augmented Generation: A Real-Time Health Monitoring Guide

Agentic Workflow and Retrieval-Augmented Generation: A Real-Time Health Monitoring Guide

*Discover how this modular architecture revolutionizes real-time medical data analysis, enhancing the supervision of at-risk seniors. By integrating an Multi-agent-Systems (MAS) with Retriev

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LangChain vs. LlamaIndex: A Comprehensive Comparison for Retrieval-Augmented Generation (RAG)

LangChain vs. LlamaIndex: A Comprehensive Comparison for Retrieval-Augmented Generation (RAG)

Introduction Retrieval-Augmented Generation (RAG) combines information retrieval with generative models, making it a powerful technique for applications like question answering, summarizat

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What are AI Agents: From Virtual Assistants to Intelligent Decision-Makers

What are AI Agents: From Virtual Assistants to Intelligent Decision-Makers

A Ground-Up Guide to Understanding AI Agents The recent shift from LLM-powered chatbots to what the field now defines as agentic systems or agentic AI can be summarized with a good old s

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Building Enterprise AI Apps with Multi-Agent RAG!

Building Enterprise AI Apps with Multi-Agent RAG!

Authors: Pavan Belagatti & Madhukar Kumar In the rapidly evolving landscape of AI, [multi-agent Retrieval-Augmen

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Mastering the 25 Types of RAG Architectures: When and How to Use Each One

Introduction Retrieval-Augmented Generation (RAG) architectures have revolutionized the way we approach information retrieval. These architectures bridge the gap between generating responses

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LazyGraphRAG: A New Era of Efficient and Effective RAG | by Ankush k Singal | Nov, 2024 | Medium

LazyGraphRAG: A New Era of Efficient and Effective RAG | by Ankush k Singal | Nov, 2024 | Medium

Introduction In the realm of artificial intelligence, Retrieval Augmented Generation (RAG) has emerged as a powerful technique to enhance the capabilities of large language models (LLMs). RAG e

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How to Build AI Agents with LangGraph: A Step-by-Step Guide

How to Build AI Agents with LangGraph: A Step-by-Step Guide

Introduction In the world of AI, retrieval-augmented generation (RAG) systems have become common tools for handling simple queries and generating contextually relevant responses. However, as

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Introducing LightRAG: A New Era in Retrieval Augmented Generation

Introducing LightRAG: A New Era in Retrieval Augmented Generation

In the rapidly evolving field of natural language processing, Retrieval-Augmented Generation (RAG) systems have become essential for providing accurate, contextually rich responses. However, trad

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Mastering LangGraph: The Ultimate Guide to AI Systems, RAG, Agents, and Tools

Are you looking to dive deep into LangGraph, the latest buzzword in AI technology? Whether you’re a developer, student, or tech enthusiast, understanding LangGraph and its associated concepts like

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Claude 3.5 Sonnet on Amazon Bedrock: A New Era for AI-Powered Knowledge Bases

Claude 3.5 Sonnet on Amazon Bedrock: A New Era for AI-Powered Knowledge Bases

In the ever-evolving landscape of artificial intelligence, staying ahead of the curve means embracing the latest innovations with both enthusiasm and strategic insight. One such innovation that

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Program a RAG LLM Chat App with LangChain + Streamlit + *o1, GTP-4o and Claude 3.5

Program a RAG LLM Chat App with LangChain + Streamlit + *o1, GTP-4o and Claude 3.5

Learn how to build a RAG web application using Python, Streamlit and LangChain, so you can chat with Documents, Websites and other custom data. GitHub Code: <https://github.com/enricd/rag_l

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Leveraging Large Language Models (LLMs) in B2C Industries: Transforming Customer Experience with…

Leveraging Large Language Models (LLMs) in B2C Industries: Transforming Customer Experience with…

In the rapidly evolving landscape of B2C industries such as financial services, retail, and eCommerce, customer expectations for personalized and instant responses are at an all-time high. With

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AI Research Agents: Set to Transform Knowledge Research in 2025 (Plus Top 3 Free Tools)

AI Research Agents: Set to Transform Knowledge Research in 2025 (Plus Top 3 Free Tools)

Here’s the deal: Something massive is about to shake up the world of knowledge research. After spending months diving deep into AI research agents and seeing them in action across various industr

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Build a RAG-based scientific ChatBot with LangChain, Streamlit & PubMed — Part 4(Put it all…

Build a RAG-based scientific ChatBot with LangChain, Streamlit & PubMed — Part 4(Put it all…

Hello and welcome to the last part of the series to build a scientific ChatBot with Langchain, Streamlit, and PubMed! In the previous part, we built the data persistence and RAG pipeline with v

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Why embedding matters when building a non-English RAG system — Multilingual embeddings

Why embedding matters when building a non-English RAG system — Multilingual embeddings

Why Embeddings are Key Embeddings are a cornerstone of modern generative AI, silently driving the functionality of many systems we interact with daily. At their simplest, embeddings are **num

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Using Llama 3 for Building AI Agents

Using Llama 3 for Building AI Agents

Comprehensive guide to building AI Agents with Llama 3 function calling capabilities. Introduction Imagine you want to buy something. You visit an e-commerce website and use the sea

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Multimodal RAG with Gemini Pro and LangChain

Multimodal RAG with Gemini Pro and LangChain

Introduction In this tutorial, we will explore the integration of Gemini Pro and Gemini Pro Vision with the [LangChain](https://www.

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LongRAG: Giving AI a Bigger Net to Catch More Fish in the Sea of Information

LongRAG: Giving AI a Bigger Net to Catch More Fish in the Sea of Information

In my previous article, I introduced whether RAG would become obsolete due to long-context LLMs. Today, let’

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Visualize your RAG Data — Evaluate your Retrieval-Augmented Generation System with Ragas

Visualize your RAG Data — Evaluate your Retrieval-Augmented Generation System with Ragas

How to use UMAP dimensionality reduction for Embeddings to show multiple evaluation Questions and their relationships to source documents with Ragas, OpenAI, Langchain and ChromaDB Retrieval

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How Agentic RAG solves problem with current RAG limitations

How Agentic RAG solves problem with current RAG limitations

In this volume 4 of coffee break concept, we will understand how AgenticRAG helps solve limitations of traditional RAG. RAG Framework The RAG (Retrieval Augmented Generation) framework operates

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How to Improve LLMs with RAG

How to Improve LLMs with RAG

A beginner-friendly introduction w/ Python code This article is part of a larger series on using large language mo

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The Quest for Production-Quality Graph RAG: Easy to Start, Hard to Finish

The Quest for Production-Quality Graph RAG: Easy to Start, Hard to Finish

Overcoming the challenges of productionizing graph RAG When I read the recent article in VentureBeat about how Glean [just secured over $260 million in its latest funding round](https://ve

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Retrieval-Augmented Generation: Approaches, State of the Art, and Optimization Strategies

Retrieval-Augmented Generation: Approaches, State of the Art, and Optimization Strategies

⭐ RAG is particularly useful in knowledge-intensive scenarios or domain-specific applications that require knowledge that’s continually updating. RAG has been popularized recently with its app

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RAG/LLM and PDF: Conversion to Markdown Text with PyMuPDF

RAG/LLM and PDF: Conversion to Markdown Text with PyMuPDF

Data feeding in markdown text format increases generated text quality Introduction In the context of Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) envi

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