https://ai-blog.noorshomelab.dev/tags/chunking/Recent content in Chunking on AI VOIDHugoenFri, 20 Mar 2026 00:00:00 +0000https://ai-blog.noorshomelab.dev/context-engineering-guide/smart-chunking-strategies/Fri, 20 Mar 2026 00:00:00 +0000https://ai-blog.noorshomelab.dev/context-engineering-guide/smart-chunking-strategies/<h2 id="breaking-down-information-smart-chunking-strategies">Breaking Down Information: Smart Chunking Strategies</h2> <p>Welcome back, future Context Engineering expert! In our previous chapters, we&rsquo;ve explored the critical concept of the LLM context window and the art of designing and structuring information to fit within it. We&rsquo;ve learned that feeding the right information to an LLM is paramount for high-quality, relevant outputs.</p> <p>But what happens when your source material – a massive legal document, a comprehensive research paper, or an entire codebase – far exceeds the LLM&rsquo;s context window? That&rsquo;s where <strong>chunking</strong> comes into play!</p>https://ai-blog.noorshomelab.dev/langextract-guide-2026/12-performance-tuning/Mon, 05 Jan 2026 00:00:00 +0000https://ai-blog.noorshomelab.dev/langextract-guide-2026/12-performance-tuning/<h2 id="introduction-making-your-extractions-fly">Introduction: Making Your Extractions Fly!</h2> <p>Welcome to Chapter 12! So far, you&rsquo;ve learned how to set up LangExtract, define schemas, and perform extractions. Your extractions are working, which is fantastic! But in the real world, efficiency is often just as important as accuracy. Imagine processing thousands of documents or needing near real-time responses – slow extractions can become a major bottleneck, impacting user experience and even racking up significant costs with LLM API usage.</p>