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Understanding the Browsing Tool Used by ChatGPT

  Introduction ChatGPT is a powerful AI capable of answering questions, assisting with coding, summarizing articles, and much more. However, its pre-trained knowledge is static and has a cutoff date. This means it does not automatically know real-time information. To overcome this limitation, ChatGPT uses a browsing tool that allows it to fetch the latest information from the web. What is the ChatGPT Browsing Tool? The browsing tool is an integrated feature that allows ChatGPT to perform real-time web searches and retrieve up-to-date information. It acts as an automated search engine that fetches data from trusted online sources when a user’s query requires fresh or live data. How Does It Work? User Asks a Query : When a user asks about current events, live prices, or the latest tech updates, ChatGPT first checks its pre-existing knowledge. Decision to Use the Browser : If the information is not available in its static knowledge, ChatGPT decides to trigger a web search. Fetchi...
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Sentry in React applications

 What is Sentry "If you've ever shipped a React app to production, you know things can — and will — go wrong. But how do you find out when they do? That’s where Sentry comes in. Sentry is a powerful open-source tool for real-time error tracking and performance monitoring. It helps you identify, prioritize, and fix bugs faster by providing visibility into the stack trace, affected users, and the context around the issue.  Installing Sentry in a React App npm install @sentry/react @sentry/tracing "To get started, install the official Sentry packages. Once that’s done, head to your entry point — usually index.js or main.jsx — and initialize Sentry like this:" import * as Sentry from "@sentry/react"; import { BrowserTracing } from "@sentry/tracing"; Sentry.init({   dsn: "https://your-public-dsn@sentry.io/project-id",   integrations: [new BrowserTracing()],   tracesSampleRate: 1.0, // Adjust for performance monitoring }); Sentry automatic...

Training a Custom LLM with Your Data Using LLaMA and LangChain

 In this blog, we’ll walk through a step-by-step guide to building an AI application that can intelligently answer questions based on your website’s content using LangChain , Ollama , and ChromaDB . This approach leverages Retrieval-Augmented Generation (RAG) , enabling you to use a pre-trained language model while grounding its responses in your own data — without needing to fine-tune the model. What We'll Use LangChain – for chaining together data loading, embedding, retrieval, and prompt logic Ollama – to run open-source LLMs (like LLaMA or Mistral) locally ChromaDB – as an efficient vector store WebsiteLoader – to extract data directly from your website RecursiveTextSplitter – for clean and structured chunking of long web content Step 1: Install Dependencies pip install langchain chromadb beautifulsoup4 unstructured requests tiktoken Step 2: Load Website Content from langchain_community.document_loaders import WebBaseLoader urls = [     "https:/...

The Rise of Agentic AI: Unlocking the Next Frontier of Autonomy

  Introduction The evolution of Artificial Intelligence (AI) has witnessed remarkable advancements, from simple rule-based systems to deep learning models that power today's intelligent applications. However, a new paradigm is emerging that promises to redefine how AI systems interact with their environments: Agentic AI. This concept introduces AI models capable of autonomy, decision-making, and goal-driven behavior, pushing the boundaries of what machines can achieve independently. What is Agentic AI? Agentic AI refers to artificial intelligence systems designed to operate autonomously by setting objectives, making decisions, and executing tasks without direct human intervention. Unlike traditional AI, which requires predefined inputs and outputs, agentic AI can: Set and pursue goals based on high-level instructions. Adapt to dynamic environments by learning and evolving from interactions. Self-correct and optimize through feedback loops and reinforcement learning. Coordinate w...

Introduction to Stencil.js: A Modern Web Component Compiler

  Introduction to Stencil.js: A Modern Web Component Compiler In the ever-evolving world of frontend development, performance, reusability, and flexibility have become key considerations when building web applications. Stencil.js, a modern Web Component compiler, offers a powerful way to create highly optimized, reusable components with minimal runtime overhead. This blog explores what Stencil.js is, its key features, and why it is an excellent choice for modern web development. What is Stencil.js? Stencil.js is an open-source compiler for building standard-based Web Components. Developed by the team behind the Ionic Framework, Stencil.js enables developers to write modern, framework-agnostic UI components that can be used in any JavaScript framework, including React, Angular, Vue, and even plain HTML. Unlike traditional frontend frameworks, Stencil does not provide a complete application development structure. Instead, it focuses on compiling high-performance, lightweight Web ...

Creating Custom Hooks in React

  Introduction to Custom Hooks in React React, the renowned JavaScript library for building user interfaces, has continuously evolved to simplify developers' workflows. One of the most significant additions in recent years is the introduction of hooks in React 16.8. Hooks enable developers to utilize state and other React features without writing class components. Among these hooks, custom hooks stand out as a powerful tool for encapsulating logic and promoting code reuse. Custom hooks are JavaScript functions whose names start with "use" and which may call other hooks. They allow developers to extract component logic into reusable functions. This not only reduces redundancy in the codebase but also enhances readability and maintainability, making the development process more efficient. Understanding the Basics of React Hooks Before delving into custom hooks, it is essential to understand the basic hooks provided by React: useState : This hook allows you to add state to f...

The Power of Logic Apps in Azure: A Comprehensive Guide

  What are Azure Logic Apps? Azure Logic Apps is a cloud-based service designed to help organizations automate workflows and integrate services with minimal code. This powerful tool allows users to create complex workflows that can connect to various services, both within the Microsoft ecosystem and beyond. With its user-friendly visual designer, Logic Apps makes it possible for both developers and non-developers to build and manage workflows efficiently. The platform's serverless architecture ensures that users do not need to worry about the underlying infrastructure. Microsoft handles all aspects of scalability, availability, and reliability, allowing users to focus entirely on designing and executing their workflows. This approach not only simplifies the development process but also ensures that Logic Apps can handle varying loads and manage errors effectively, providing a robust solution for business process automation. One of the standout features of Azure Logic Apps is its ex...