📄 中文摘要
在快速发展的数字环境中，信息检索和智能自动化变得至关重要。企业通过可扩展且能够高效理解上下文的技术，优化用户互动和提升客户服务体验。大型语言模型（LLMs）与向量数据库的结合，配合微服务和事件驱动架构，能够创建高度可扩展的人工智能解决方案，重新定义常见问题解答及客户查询的处理方式。传统的基于关键词的搜索系统往往无法满足现代用户的需求，因此，采用新技术显得尤为重要。
从数据到对话：利用大型语言模型、Pinecone 和 Kafka 创建智能常见问题解答的技术设计
📄 English Summary
From Data to Dialogue: Creating a Technical Design for Smart FAQs using LLMs, Pinecone & Kafka
In today's rapidly evolving digital landscape, seamless information retrieval and intelligent automation are crucial. Enterprises aim to optimize user interactions and enhance customer service experiences through scalable technologies that understand context with high accuracy. The combination of Large Language Models (LLMs) and vector databases, along with microservices and event-driven architecture, enables the creation of highly scalable AI-powered solutions that redefine the handling of FAQs and customer queries. Traditional keyword-based search systems often fall short of modern user needs, making the adoption of new technologies essential.