gZany is it using a backend as i assume, or is it using CDO's inbuilt AI feature? of which i have been meaning to look into but don't know how to structure the training data to be effective for CDO's models and or don't have any big enough csv data to throw into it for actual results
MonsterYT_DaGamer I send a request to my server, my server sends a request to huggingface, huggingface returns the data, my server then returns the data as an image which can be parsed by the cdo project.
DragonFireGames considering i built the fetch library lmao (well a baseline version of it anyways) seems you've vastly improved it for modular usage,
also you may be able to generate results on your server end, from my results they've been pretty good at least while using nodejs so that's most likely what i will do later on rather than key chaining
oh also update on the CDO AI model stuff very weird and can only do predictions with limited data, so generating results will most likely be very tedious with probably needing model chaining to get anywhere near the performance of other stuff
The main difference is that I can send and receive data easily using the new version of fetch. I also use Owokoyo's method of parsing the image which is like 100x faster. The fetched content doesn't have to be text or json either, you can also just fetch an image directly.
https://cdo-backend.onrender.com/fetch?url=<insert url here>&data=<json for 2nd parameter of fetch>
you can also add &proxy=1 if you want to just see the unencoded data using your browser
DragonFireGames ah yea the biggest jump for it is probably using fromCharCode and passing through an array through it though seems like it'd be much faster, though i don't think there's really a need to fetch an image directly because then it just takes longer because it needs to pass through your proxy, unless your storing cached results which can be beneficial.... though i may update my library to include the method sooner or later