Translations:FACTS About Building Retrieval Augmented Generation-based Chatbots/14/zh: Difference between revisions

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Our company’s content landscape includes both authoritative knowledge and unauthoritative content. Authoritative content encompasses IT help articles, HR resources in platforms like ServiceNow, and project documentation on Confluence, SharePoint, Google Drive, and engineering tools like NVBugs and GitHub. Employee-generated content complements these sources on platforms such as Slack and MS Teams. In this paper, we present three bots that we have built at NVIDIA using RAGs and LLMs. These bots are briefly introduced below. All three bots are built on our in-house built generative-AI chatbot platform called NVBot platform. Some of the queries that our bots are capable of answering are shown in Table [[#S1.T1|1]].

我们公司的内容领域包括权威知识和非权威内容。权威内容包括 IT 帮助文章、ServiceNow 等平台上的人力资源资源，以及 Confluence、SharePoint、Google Drive 和 NVBugs、GitHub 等工程工具上的项目文档。员工生成的内容在 Slack 和 MS Teams 等平台上补充了这些来源。在本文中，我们介绍了 NVIDIA 使用 RAGs 和 LLMs 构建的三个机器人。以下是对这三个机器人的简要介绍。所有三个机器人都基于我们内部构建的生成式 AI 聊天机器人平台 NVBot 平台构建。我们的机器人能够回答的一些查询显示在表 1 中。