AI网关可以通过充当中介层，显著提高大型语言模型（LLM）在生产应用中的可靠性。这些网关提供诸如在服务中断期间自动故障转移到备用提供商、防止过载的智能负载均衡以及基于性能或成本的高级模型路由等功能。此外，它们还有助于管理LLM提供商施加的速率限制，防止应用程序停机并确保一致的性能。对于开发AI MVP的开发人员来说，专注于结构化输出和单元测试提示对于可靠性至关重要，可以防止出现幻觉数据等问题，并确保一致、可信的结果。 AI
影响 提高了在生产应用中部署LLM的稳定性和成本效益。
排序理由 该集群讨论了提高LLM可靠性的工具和技术，而不是新的模型发布或重大的行业事件。
AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →
<p><a class="article-body-image-wrapper" href="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.us-east-2.amazonaws.com%2Fuploads%2Farticles%2Frp4yqktt436b7wu1fox2.png"><img alt="9 Ways an AI Gat…
<p>I once built an AI pipeline that was shut down after a single month. The LLM costs were unsustainable, and worse, the outputs were unreliable enough that we couldn't trust them in production. That failure taught me something I still use today: evaluation isn't a phase you add …