AI knowledge Page 3

Long Text Vector Modeling The ability to encode ten pages of text into a single vector sounds powerful, but is it really practical? Many people think... Not necessarily. Is it okay to use it directly? Should it be chunked? How to divide the most efficient? This article will take you in-depth discussion of different chunking strategies for long text vector models, analyzing the pros and cons...

  I. The Root Cause of Testing Prompts: LLM is highly sensitive to prompts, and subtle changes in wording can lead to significantly different outputs Untested prompts can produce: Factually incorrect information Irrelevant replies Unnecessary wasted API costs II. Systematic Optimization of Prompts ...

Overview This guide will walk you through creating a simple Retrieval Augmentation Generation (RAG) system using pure Python. We will use an embedding model and a large language model (LLM) to retrieve relevant documents and generate responses based on user queries. https://github.com/adithya-s-k/A...

Introduction Retrieval-enhanced generation (RAG) is a powerful technique that combines the benefits of large language models with the ability to retrieve relevant information from a knowledge base. This approach improves the quality and accuracy of generated responses by basing them on specific retrieved information.a This notebook aims ...

INTRODUCTION BM25 Retrieval Augmented Generation (BM25 RAG) is an advanced technique that combines the BM25 (Best Matching 25) algorithm for information retrieval with a large language model for text generation. By using a validated probabilistic retrieval model, this method improves the accuracy and relevance of the generated responses....

INTRODUCTION Data chunking is a key step in Retrieval Augmented Generation (RAG) systems. It breaks large documents into smaller, manageable pieces for efficient indexing, retrieval, and processing. This README provides an overview of the various chunking methods available in the RAG pipeline. https://github.com/adithya-...

One of the biggest breakthroughs in the field of AI this year should be in the field of programming, AI programming tools like Cursor and v0 dev have not only drastically lowered the threshold of programming for the average person, but also allowed professional programmers to dramatically increase their development efficiency. But all the news we hear is about high school students who can't program,...

Introduction Evaluation is a key component in the development and optimization of Retrieval Augmentation Generation (RAG) systems. Evaluation involves measuring the performance, accuracy, and quality of all aspects of the RAG process, from retrieval effectiveness to the relevance and authenticity of generated responses. Importance of RAG Evaluation An effective RAG system...