Are you still troubled by the mixed quality of AI in China and its poor performance? Then let’s take a look at Developer Cat AI (3in1)! This is an integrated AI assistant that combines GPT-4, Claude3, and Gemini. It covers all models of the three AI tools. Including GPT-4o and Gemini flash Now you can … Read more
Click 👇🏻 to follow, article from “ With the expanding application of large language models (LLMs), Retrieval-Augmented Generation (RAG) has become a mature technology. The popularity of products like txt2sql and ChatBI highlights the increasing importance of query construction techniques. This article analyzes the process of query construction and illustrates, through examples, how to transform … Read more
LLM (Large Language Model) is a powerful new platform, but they are not always trained on data that is relevant to our tasks or the most recent data. RAG (Retrieval Augmented Generation) is a general method that connects LLMs with external data sources (such as private data or the latest data). It allows LLMs to … Read more
Source: Deep Learning and Large Models (LLM) This article is approximately 3500 words long and is recommended for a 9-minute read. This article delves into the development of Retrieval-Augmented Generation (RAG), from basic concepts to the latest technologies. 4. Overview of Existing RAG Frameworks Agent-Based RAG A new agent-based Retrieval-Augmented Generation (RAG) framework adopts a … Read more
LLM (Large Language Model) is a powerful new platform, but they are not always trained on data relevant to our tasks or the latest data. RAG (Retrieval Augmented Generation) is a general method that connects LLMs with external data sources (such as private or up-to-date data). It allows LLMs to use external data to generate … Read more
Machine Heart Report Editor: Rome Retrieval-Augmented Generation (RAG) and Fine-tuning are two common methods to enhance the performance of large language models. So, which method is better? Which is more efficient when building applications in specific domains? This paper from Microsoft serves as a reference for your choice. When constructing large language model applications, there … Read more
A Survey of Query Optimization in Large Language Models Paper Link:https://arxiv.org/pdf/2412.17558 Published by: Tencent Large Language Models (LLMs) are becoming increasingly popular, but they also face challenges such as “hallucination” when dealing with domain-specific tasks or those requiring specialized knowledge. Retrieval-Augmented Generation (RAG) technology has emerged as a key method for enhancing model performance, with … Read more
Hi, I’m GuiGui, exploring AI. If you like the content here, please follow to stay updated! Slash Little Ghost Have you ever encountered a situation where you eagerly ask AI a question, only for it to provide a completely absurd answer? For instance, if you ask, “What is Python?” and it responds, “Python is a … Read more
Recently, while reading some materials about RAG systems, I discovered an interesting phenomenon: the relevance issue of RAG is far more complex than we imagine. Whether from the perspective of data retrieval or the understanding of relevance by large models, the performance of RAG is filled with challenges and opportunities. Today, I would like to … Read more
RAG Logger is a logging tool for RAG applications, a lighter open-source alternative to LangSmith. It comprehensively records, queries tracking, retrieves results, logs LLM interactions, and monitors performance step by step. It features structured log storage, organizes log files by day, automatically manages log files, and preserves detailed metadata such as timestamps and execution duration. … Read more