Code Explanation: RAG with FAQ and OpenAI This Python code implements a Retrieval Augmented Generation (RAG) system specifically designed to answer questions from an FAQ dataset using OpenAI’s…
Sample code to enable running the LLM locally. This will involve using a local LLM instead of OpenAI. Key Changes: To run this code with a local LLM:…
Explanation: Key Points: Remember to:
Retrieval Augmented Generation (RAG) is a technique that enhances the capabilities of Large Language Models (LLMs) by enabling them to access and incorporate information from external sources during…
The introduction of React Hooks in React 16.8 marked a significant shift in how React developers manage state and side effects. Here’s a breakdown of the key differences…
To understand Redux “under the hood,” let’s break down its core principles and how they work together: 1. The Store: 2. Actions: 3. Reducers: 4. The Data Flow:…