One of the very first experiments I did with AI was trying to build a browser based filesystem interface and general API provider. I think the first attempts were with ChatGPT 3.5 . I pretty quickly hit a wall, but Gpt4 got me quite a lot further.
I see the datestamp on this early test https://fingswotidun.com/tests/messageAPI/ is 2023-03-22 Thinking about the progress since then I'm amazed I got as far as I did. (To get the second window to run its test you need to enter aWorker.postMessage("go") in the console)
The design was using IndexedDB to make a very simple filesystem, and a transmittable API
The source of the worker shows the simplicity of it once set up. https://fingswotidun.com/tests/messageAPI/testWorker.js in total is just
importScripts("MessageTunnel.js"); // the only dependency of the worker
onmessage = function(e) {
console.log(`Worker: Message received from main script`,e.data);
if (e.data.apiDefinition) {
installRemoteAPI(e.data.apiDefinition,e.ports[0])
}
if (e.data=="go") {
go();
return;
}
}
async function go() {
const thing = await testAPI.echo("hello world")
console.log("got a thing back ",thing)
//fs is provided by installRemoteAPI
const rootInfo = await fs.stat("/");
console.log(`stat("/") returned `,rootInfo)
// fs.readDir returns an async iterator that awaits on an iterator on the host side
const dir = await fs.readDir("/")
for await (const f of dir) {
const stats = await fs.stat("/"+f.name);
console.log("file " +f,stats)
}
}
I distinctly remember adding a Serviceworker so you could fetch URLs from inside the filesystem, so I must have a more recent version sitting around somewhere.
It wouldn't take too much to have a $PATH analog and a command executor that launched a worker from a file on the system if it found a match existed on the $PATH. Then a LLM would be able to make its own scripts from there.
It might be time to revisit this. Polishing everything up would probably be a piece of cake for Claude.