{"version":"1.0","generated_at":"2026-10-08T01:14:12.318159","id":195,"slug":"speeding-up-agentic-workflows-with-websockets-in-the-responses-api","title":"趋势解读：Speeding up agentic workflows with WebSockets in the，聚焦 Agent 工作流自动化","summary":"深入探讨Codex代理循环，展示WebSockets和连接范围缓存如何减少API开销并改善模型延迟。","abstract":"趋势解读：Speeding up agentic workflows with WebSockets in the，聚焦 Agent 工作流自动化 深入探讨Codex代理循环，展示WebSockets和连接范围缓存如何减少API开销并改善模型延迟。 OpenAI发布WebSocket优化Agent工作流方案 连接范围缓存减少API调用开销 该技术可降低模型推理延迟 开发者需评估集成复杂度与收益 深入探讨了Codex代理循环，展示了WebSockets和连接范围缓存如何减少API开销并改善模型延迟。 信号解读： OpenAI官方发布了一篇关于如何利用WebSockets和连接范围缓存加速Agent工作流的技术深度文章，聚焦Codex代理循环。这表明OpenAI正在系统性地优化AI Agent的执行效率，尤其是减少API调用开销和降低模型推理延迟。 为什么重要： Agent工作流是当前AI应用从单次问答转向多步骤自主执行的关键范式。降低API开销和延迟直接影响Agent的响应速度和成本，这对于实时交互、高并发场景（如客服、编程助手）至关重要。此次优化可能成为Agent基础设施的标准实践，推动更复杂的Agent任务落地。 对谁有价值： 主要面向AI开发者、企业技术决策者、以及构建Agent应用的团队。对于正在使用或计划接入OpenAI Codex、GPT模型的开发者，此方案可提供明确的性能提升路径。对于关注Agent架构的技术社区，这也是一次重要的工程最佳实践分享。 可以怎么行动： 1. 深入阅读原文，理解WebSocket连接管理和缓存策略的具体实现。2. 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