Welcome to My Tech-Journal

A space where I share my thoughts, experiences, and learnings on technology, programming, and innovation. Expect in-depth articles, tutorials, and projects that showcase my expertise in web development, cloud computing, machine learning, and more!

Check out the latest posts below!!

INSIDE THE CODEBASE: A DEEP DIVE INTO DRUPAL RAG INTEGRATION

Welcome back! After our first article that showed you our new Drupal Rag Integration app, many of you liked it. Thank you! Today, let’s look at how the code works. Quick Reminder If you missed our first article or need a quick reminder, you can take a look at it here. It’ll help you understand what we’re talking about today. How the App is Built Our integration revolves around a dynamic interaction between a backend designed for intelligent data retrieval and augmentation, and a robust Content Management System (CMS) frontend.

BUILD SMART DRUPAL CHATBOTS WITH RAG INTEGRATION AND OLLAMA

As a Drupal developer who values open-source solutions, I was excited to explore the potential of combining Drupal and Ollama. Drupal is one of the most popular CMS platforms worldwide. Tesla, Nokia, and Oxford University are just a few examples of high-traffic websites powered by Drupal. Among the many reasons why Drupal is used by so many companies, the core one that resonates with me is its open-source nature. Ollama is also open-source and is being used extensively to create applications around LLMs.

DOCUMENTOR: BUILD A RAG CHATBOT WITH OLLAMA, CHROMA & STREAMLIT

In this article, we build a Retrieval-Augmented Generation (RAG) web application called DocuMentor that allows users to upload PDF documents and ask questions about the contents. Let’s understand this with the help of a real-world example. Let’s say you have a web app for your hospital that contains extensive data about doctors—their names, departments, phone numbers, working hours, and more. Now you want to build a chatbot like ChatGPT, but it should address specific queries about your data, such as the details of doctors working at your hospital.

SONG RECOMMENDER: BUILDING A RAG APPLICATION FOR BEGINNERS FROM SCRATCH

Have you been trying to understand RAG and read a bunch of articles, yet feel overwhelmed by how complicated it seems to implement? You’ve just hit the jackpot. In this article, I aim to demystify the RAG concept and demonstrate its utility by building a hands-on song recommender application – all without unnecessary complexity. There’s no need for a deep understanding of AI and machine learning; basic knowledge of Python and a willingness to learn something new are all that’s required.

RETRIEVAL AUGMENTED GENERATION (RAG): A BEGINNER’S GUIDE TO THIS COMPLEX ARCHITECTURE.

“RAG, or Retrieval Augmented Generation, is getting a lot of talk these days. It’s pretty exciting, but also a bit confusing for beginners. In this article I attempt to explain RAG in a way that’s easier to understand, without all the complex tech words.” What is RAG? RAG stands for Retrieval Augmented Generation, an architecture that lets you feed your own content to a generic Large Language Model (LLM) to generate relevant responses.

DRUPAL CODE ASSISTANT: BUILD CHATBOT USING OLLAMA

Introduction: In our previous article, we explored how to create custom models using Ollama. If you haven’t read it yet, I encourage you to start there. Now, let’s expand on that knowledge by crafting a frontend chatbot application for our Drupal Code Assistant. Let’s dive right into coding it. Requirements: We’ll be using Langchain and Streamlit for this tutorial. Langchain: Langchain is a framework designed to simplify the creation of applications using large language models.

AI HELPER: BUILD YOUR OWN CUSTOM LLM MODEL ON OLLAMA

Introduction: In the previous article, we learned how easy it is to use Ollama for running large language models on our own computers. This time around, we’re taking things a step further by creating a custom LLM model tailored just for us. Let’s dive into this hands-on guide! Use Case: As a Drupal Developer, my day includes coding, reviewing, and debugging - all in a day’s work. But what if I had a reliable assistant to help me out?

INTRODUCING OLLAMA: THE LOCAL POWERHOUSE FOR LANGUAGE MODELS

Use Cases: Imagine it’s early in the morning, and you’re thirsty for the latest news on Drupal. You’d usually hop onto Drupal.org or sift through various websites to find quality articles. But you only want the freshest, top-notch reads from this week. ChatGpt, Microsoft Copilot or any other big tech companies’ LLM tool can help with that. But here’s the twist - with Ollama, you can get that, for free and even automate to email you those articles every-day.