开发者在生产环境中遇到了大型语言模型 (LLM) 的挑战，特别是在成本管理和可靠的输出格式化方面。一个常见的问题是未跟踪的运行成本，这并非直接与模型定价相关，而是与未受监控的使用有关。此外，LLM 可能产生无法在生产环境中正确解析的 JSON 输出，这需要强大的错误处理策略。这些问题凸显了将 LLM 集成到软件开发工作流程中的复杂性。 AI
影响 强调了部署 LLM 的实际挑战，重点关注开发者的成本控制和输出可靠性。
排序理由 该集群讨论了在软件开发中使用 LLM 的工具和技术，而不是新的模型发布或前沿研究。
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