<?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/7a1165e14d884429a4a423c9097db022&quot; frameborder=&quot;0&quot; width=&quot;1664&quot; height=&quot;1248&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>1248</height><width>1664</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>1248</thumbnail_height><thumbnail_width>1664</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/7a1165e14d884429a4a423c9097db022-6b7131254f13e0d3.gif</thumbnail_url><duration>277.5574</duration><title>Presenting an Effective Data Collector Application for Chat Feedback</title><description>In this video, I showcase our LLM data collector application that we quickly built and refined over a weekend. The app features a simple chat interface for collecting user feedback, which we can analyze through a dashboard that tracks various metrics like ratings and comments. I explain how easy it is to deploy the app with just a single command and how you can customize it to use your own model provider. I encourage you to check out the documentation and consider building your own feedback collector on top of our API. Please let me know if you have any questions or need further assistance!</description></oembed>