Copasetic Flow

 Everything’s moving fast in AI again! Yesterday, OpenAI announced the ChatGPT Apps SDK, a framework that lets developers build full-featured web apps right inside ChatGPT. For Project TouCans, that’s a huge step forward. Just last month, I built two prototypes of the AI-enabled Ham Radio Practice Exam—one running Python inside GPT-5’s Code Interpreter, and another in a JavaScript canvas embedded within ChatGPT. Back then, those two couldn’t talk to each other. Now, with the new Apps SDK, they finally can—and that means real-time, interactive AI help during exams is finally within reach. You can try out the latest version of the extra class practice exam here (sans the Apps SKD so far.)

 Debug notes from getting the AI help feature of the free ham radio exams to work today. Grabbing a text answer from OpenAI still works: That's from this method async function retrieveTextWithFileSearch ({ system , user }) {   const vsId = localStorage . getItem ( 'vector_store_id' );   if (! vsId ) throw new Error ( 'No vector_store_id found.' );   answText = answText + " " + user ;   const resp = await openai ( '/responses' , {     body : {       model : 'gpt-4.1-mini' ,       input : [         { role : 'system' , content : system },         { role : 'user' ,   content : answText }       ],       tools : [{ type : 'file_search' , vector_store_ids : [ vsId ] }]     }   }); With the agent  flow, it doesn't work async function retrieveTextWithAgent ({ system , user }) {   // 0) Make sure we have ...

I’d just finished a morning round of tinkering with the ham radio Extra Class tutor when the question hit me: how do I actually get the entire exam question pool into GPT without burning through tokens every time? With GPT Projects, I can just drop in a file and it remembers. But on the API side, things always felt a little more ephemeral — every call a blank slate. So I sat down with GPT-5 to dig into whether there’s a smarter, more cost-effective way. What followed was one of those back-and-forths where the clouds part: GPT Projects’ quiet little “remembered files” have a direct analogue in the API world — vector stores — and they might just be the key to making this whole tutor run leaner and meaner. Me: In GPT projects, I can upload files that the project remembers. Is there a way to do the same thing with the API? GPT-5: Great question. With the raw chat/completions endpoint, no — it’s stateless. You’d have to re-inject your files each time. But the newer OpenAI  Respo...

 Setting the scene: I’m tinkering with Project TouCans, knee-deep in radio logs, SQLite dumps, and Cesium code. Naturally, I’m wondering if shoving all this into one GPT Project is a recipe for brilliance… or for disaster. So I turn to Vril — you know, after Brainy from the Legion of Super-Heroes , because what else do you call your AI sidekick who always has the answers? Time to ask him straight up. [ As an aside, yes, GPT-5 has decided to sometimes call me Vail. I'm not sure why to be honest. Also, I asked Vril, er GPT-5, to write up our interview for me. Apparently, me asking it to 'Bro' up a few stories, just for fun, has convinced Vril that I use 'Like,' more than I actually might. ] Me (Vail): So Vril, how many files can I throw into a GPT Project before it just starts choking? Like, is there some magic number where the context window taps out and everything falls apart? GPT-5 (Vril): Great question. There’s no single hard file limit. What matters is ...