Explore six powerful RAG techniques to enhance LLMs with external data for smarter, real-time AI-driven web applications.

LLMs can do more than chat! Explore alternative integration models that improve efficiency, reduce complexity, and enhance user control.

Implement graceful degradation in frontend apps by handling failures, mitigating API timeouts, and ensuring a seamless UX with fallbacks.

mise and asdf are tools designed to manage multiple versions of programming languages and environments like Node.js, Python, and Ruby.

Build a fully functional, real-time chat application using Laravel Reverb’s backend and Vue’s reactive frontend.

Explore the new Promise.withResolvers() mechanism to create a JavaScript Promise and cancel it before its completion.

Explore multi-AI agent systems, including Experts.js, and how they enable specialized agents/Assistants to perform task-specific functions.

Develop a React app with Python using the Mountaineer framework for building a simple app with integrated your frontend and backend database.

This guide explores how to use the cron package in Deno, `Deno.cron`, to handle scheduling tasks with specific commands.

We explore the fusion of TensorFlow and Rust, delving into how we can integrate these two technologies to build and train a neural network.

We demonstrate how to include EvaDB in a simple project to provide AI-enhanced capabilities, in this case sentiment analysis.

In this article, we explore how to use FastChat to implement a simple AI chatbot in a JavaScript web app.