Source: DeepHub IMBA This article is approximately 1800 words and is suggested to be read in 6 minutes. This article will introduce how to integrate and create a scalable and customizable agent RAG. Building large language model applications can be quite challenging, especially when we have to choose between different frameworks like LangChain and LlamaIndex. … Read more
Overview The Condense Question mode is a simple chat mode built on top of a data query engine. It provides a flexible chat engine by compressing the conversation context and latest message into standalone questions, which are then interacted with the query engine. For each chat interaction: 1. First, generate a standalone question based on … Read more
Overview The Query Engine is a generic interface that allows you to query data. It accepts natural language queries and returns rich responses. It is typically (but not always) built on one or more indexes through a retriever. You can combine multiple query engines to achieve more advanced functionality. Note: If you want to have … Read more
Implementing RAG Queries in LlamaIndex Agent Overview This article explains how to integrate a RAG query engine into an Agent, enabling the Agent to utilize external knowledge bases for data queries, thus enhancing its capabilities. This approach is useful in many scenarios, for instance: often we need to query or compute a specific metric first, … Read more