<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>LLM API Calls on AI VOID</title><link>https://ai-blog.noorshomelab.dev/tags/llm-api-calls/</link><description>Recent content in LLM API Calls on AI VOID</description><generator>Hugo</generator><language>en</language><lastBuildDate>Tue, 30 Dec 2025 00:00:00 +0000</lastBuildDate><atom:link href="https://ai-blog.noorshomelab.dev/tags/llm-api-calls/index.xml" rel="self" type="application/rss+xml"/><item><title>Asynchronous Operations for Performance</title><link>https://ai-blog.noorshomelab.dev/any-llm-guide-2025/async-operations/</link><pubDate>Tue, 30 Dec 2025 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/any-llm-guide-2025/async-operations/</guid><description>&lt;h2 id="introduction-to-asynchronous-operations"&gt;Introduction to Asynchronous Operations&lt;/h2&gt;
&lt;p&gt;Welcome back, future AI architect! In our journey with &lt;code&gt;any-llm&lt;/code&gt;, we&amp;rsquo;ve learned how to connect to various LLM providers and get intelligent responses. So far, our interactions have been synchronous, meaning one operation completes entirely before the next one begins. While this is straightforward, it&amp;rsquo;s not always the most efficient, especially when dealing with tasks that involve waiting.&lt;/p&gt;
&lt;p&gt;Think about ordering coffee. If you order, then wait for your coffee to be made, then order a pastry, then wait for that to be ready, that&amp;rsquo;s synchronous. What if you could order both at once, and while the coffee is brewing, the barista starts preparing your pastry? That&amp;rsquo;s closer to asynchronous!&lt;/p&gt;</description></item></channel></rss>