📄 中文摘要
在电子商务客户服务中，用户请求往往复杂多样，单一消息可能包含多个意图，并需要协调不同数据源的支持。单智能体架构在处理此类请求时存在明显不足，主要体现在四个方面：无法将复合请求分解为可执行的子任务，导致要么只处理一个意图而忽略其他，要么给出混乱和不完整的回答。此外，单一智能体在处理多任务时的灵活性和效率也受到限制，无法满足现代客户服务的需求。因此，采用多智能体架构能够更有效地应对复杂的客户请求，提高服务质量和响应速度。
基于 LangGraph 构建企业级多智能体客户服务系统
📄 English Summary
Building an Enterprise-Grade Multi-Agent Customer Service System with LangGraph
In e-commerce customer service, user requests are often complex and multifaceted. A typical message may contain multiple intents and require coordination across different data sources. Single-agent architectures exhibit significant shortcomings in handling such requests, primarily in four areas: they cannot decompose compound requests into executable subtasks, leading to either addressing only one intent while ignoring others or providing confused and incomplete responses. Furthermore, the flexibility and efficiency of a single agent in managing multiple tasks are limited, failing to meet the demands of modern customer service. Therefore, adopting a multi-agent architecture can more effectively address complex customer requests, enhancing service quality and response speed.