<?xml version="1.0" encoding="UTF-8"?><oembed><type>video</type><version>1.0</version><html>&lt;iframe src=&quot;https://www.loom.com/embed/458f9b6679b740f0a5c78a33fffee3dc&quot; frameborder=&quot;0&quot; width=&quot;1730&quot; height=&quot;1297&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>1297</height><width>1730</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>1297</thumbnail_height><thumbnail_width>1730</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/458f9b6679b740f0a5c78a33fffee3dc-00001.gif</thumbnail_url><duration>86.69999999999997</duration><title>Axilla: an end-to-end open source TypeScript framework for LLMs</title><description>In this video, I introduce Axilla&apos;s open-source TypeScript framework for working with LLMs. The first module, axgen, focuses on data loading and retrieval of questions with augmented context. 

Star axgen on github: https://github.com/axilla-io/ax

I will demonstrate a demo UI that showcases the capabilities of this framework, which is fully configurable. We will use GPT4 and ingest the San Francisco Wikipedia page as an example. I will also show you how to ask questions to the LLM, both with and without passing context documents. Join me in exploring this powerful framework!</description></oembed>