增强型代理RAG：如果聊天机器人能够提供接近人类的精确度，会怎样？

Genie is Uber’s internal on-call copilot, designed to provide real-time support for thousands of queries across multiple help channels in Slack®. It enables users to receive prompt responses with proper citations from Uber’s internal documentation. It also improves the productivity of on-call engineers and subject matter experts (SMEs) by reducing the effort required to address common, ad-hoc queries.

Genie是Uber内部的随叫随到的副驾驶，旨在为Slack®中多个帮助渠道的数千个查询提供实时支持。它使用户能够从Uber的内部文档中快速获得适当引用的响应。它还通过减少处理常见临时查询所需的努力，提高了随叫随到的工程师和主题专家(SMEs)的生产力。

While Genie streamlines the development of an LLM-powered on-call Slack bot, ensuring the accuracy and relevance of its responses remains a significant challenge. This blog details our efforts to improve Genie’s answer quality to near-human precision, allowing SMEs to rely on it for most queries without concern over potential misinformation in the engineering security and privacy domain.

虽然Genie简化了LLM驱动的值班Slack机器人的开发，但确保其响应的准确性和相关性仍然是一个重大挑战。本文详细介绍了我们改善Genie答案质量以接近人类精度的努力，使SME能够在大多数查询中依赖它，而无需担心工程安全和隐私领域可能存在的错误信息。

Genie has revolutionized on-call assistance within Uber by enabling domain teams to deploy an LLM-powered Slack bot overnight using a configurable framework. This framework seamlessly integrates with nearly all internal knowledge sources, including the engineering wiki, Terrablob PDFs, Google Docs™, and custom documents. Additionally, it supports the full RAG  (Retrieval-Augmented Generation) pipeline, covering document loading, processing, vector storage, retrieval, and answer generation.

Genie通过使领域团队能够在一夜之间使用可配置框架部署LLM驱动的Slack机器人，彻底改变了Uber的值班协助。该框架与几乎所有内部知识源无缝集成，包括工程维基、Terrablob PDF、Google Docs™和自定义文档。此外，它支持完整的RAG（检索增强生成）管道，涵盖文档加载、处理、向量存储、检索和答案生成。

While this system is advanced from a machine learning infrastructure perspective, delivering highly precise and relevant responses to domain-specific queries remains an area for improvement. To assess whether the Genie-powered on-call bot was ready for deployment across all Slack channels related to engineering security and privacy, SMEs...