Translations:FACTS About Building Retrieval Augmented Generation-based Chatbots/28/zh: Difference between revisions

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'''Agentic Architectures''': Questions such as ‘compare the revenue of NVIDIA from Q1 through Q4 of FY2024 and provide an analytical commentary on the key contributing factors that led to the changes in revenues during this time’ require complex agents that are capable of query decomposition and orchestration. Figure [[#S3.F2|2]] shows one mechanism we had implemented to deal with such questions in Scout bot. From our experience of building the three bots, we have realized that IR systems and LLMs are insufficient for answering complex queries. Complex agents and multi-agent architectures are needed to handle complex queries.

“代理架构”：诸如“比较NVIDIA在2024财年第一季度至第四季度的收入，并对导致此期间收入变化的关键因素进行分析评论”这样的问题，需要能够进行查询分解和协调的复杂代理。图2展示了我们在Scout机器人中实施的一种机制，用于处理此类问题。通过构建这三个机器人的经验，我们意识到信息检索系统和大型语言模型不足以回答复杂查询。需要复杂的代理和多代理架构来处理复杂查询。