What is the hottest topic in the era of large models? In addition to ChatGPT, tools like LangChain and LlamaIndex, designed for building large model applications, have also been gaining significant attention. To help everyone get started easily, we launched the 【Decoding LangChain】 tutorial series, and now we present the 【Unveiling LlamaIndex】 series, which you … Read more
Source: DeepHub IMBA This article is about 2500 words long and is recommended to be read in 5 minutes. This article will introduce the integration of LLMLingua with the proprietary LlamaIndex for efficient inference. The emergence of large language models (llm) has spurred innovation across multiple fields. However, with strategies driven by chain of thought … Read more
Originally from Akash Mathur’s Blog Abstract: In the field of information retrieval, Retrieval-Augmented Generation (RAG) models signify a paradigm shift, empowering large language models (LLMs) to generate responses that are rich in context and accurate. However, unlocking the full potential of RAG often transcends the limitations of its default query-retrieve-generate framework. This article delves into … Read more
Explanation Querying is the most important part of LLM applications. In LlamaIndex, once you have completed: data loading, building the index, and storing the index, you can proceed to the most crucial part of LLM applications: querying. A simple query is just a prompt call to the large language model: it can be a question … Read more
Preface The internet is a vast sea of information. Humans are intelligent beings that crave information. However, our attention, computational power, and storage capacity are limited. We cannot process all the information on the internet simultaneously, so we invented a “salvaging” tool for information: search engines. Search engines represented by Google remain the most effective … Read more
Selecting the right LLM inference stack means choosing the right model for your task and running appropriate inference code on suitable hardware. This article introduces popular LLM inference stacks and setups, detailing their cost composition for inference; it also discusses current open-source models and how to make the most of them, while addressing features that … Read more
Author: Richard MacManus Translator: Ming Zhi Shan Editor: Tina LangChain is a programming framework that helps use large language models (LLMs) in applications. Like everything in generative AI, this project’s development is very rapid. In October 2022, it started as a Python tool, and then in February this year, support for TypeScript was added. By … Read more
Click the above “Yudao Source Code“, select “Set as Star” What about the previous wave or the next wave? The wave that can roll is the good wave! Every day at 10:33 we update articles, losing a bit of hair every day… Source Code Quality Column Original | The Super Road of Java 2021, very … Read more
It is recommended to click on the original text at the bottom of the article for a better reading experience, including displaying external links and viewing high-definition illustrations. In the article that introduces MCP (Model Context Protocol), we quickly covered the basic concepts of MCP and provided an example to give readers an initial feel … Read more
Introduction to MCP MCP (Model Context Protocol) is a development protocol that standardizes how applications provide context for large models. MCP provides a standardized way to supply data and tools for LLMs, making it easier to build agents or complex workflows based on LLMs. Architecture MCP follows a client-server architecture where an MCP host application … Read more