Recently, LlamaIndex launched a new feature called Workflow in its latest version. This feature helps large language model (LLM) applications achieve event-driven architecture, making the code logic clearer and more independent. This article will take you through a simple practical project to deeply understand this new feature, highlighting its advantages and shortcomings. Without further ado, … Read more
Introduction This article provides an overall introduction to the LlamaIndex framework, including its functions, components, and explanations. LlamaIndex is an open-source LLM application development framework built on large models (including Agents and Workflows) to create context-enhanced generative AI applications. Components of LlamaIndex The following diagram illustrates the overall functional structure of LlamaIndex, abstracted from the … Read more
LLM has become an indispensable productivity tool across various industries, such as text generation, language translation, and knowledge Q&A. Sometimes, the responses from LLMs can be surprising, as they are quicker and more accurate than humans. This demonstrates their significant impact on today’s technological landscape. As we delve deeper into the field of artificial intelligence, … Read more
Are you still troubled by the uneven quality and poor performance of AI in China? Then let’s take a look at Dev 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 You can own them … 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
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
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
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
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