Hey all! Firstly a huge thanks in advance to anyone who spends time responding to this.

So I’m working on my MVP which I’m about to launch (in its simplest form this is an AI based news aggregator)

To date my server set up has been:

  1. data storage, scraping, and app API calls to my digital ocean server. This is a 2GB memory, 1 AMD vCPU 50 GB disk server running LAMP on Ubuntu 20.04

  2. All my AI LLM work where I preprocess and clean text, locally run LLMs from hugging face is done through a Scaleway PLAY2-PICO instance.

A few issues I’m facing:

  1. The api calls to the digital ocean server are incredibly slow. Takes 5 seconds to load posts and I’m the only one using the app.

  2. The scaleway server processes for LLMs just get killed I assume due to memory issues or whatever it is.

So now to the question. What is the server architecture / providers you guys use? It needs to be able to deal with large data tables in MYSQL quickly as well as run large LLM models as well (the two don’t need to be the same set up)

Much appreciated!

  • EveryThingPlay@alien.topB
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    1 year ago

    Agreed with you, profiling is really needed to see where the bottleneck is - my suggestion is in LLM itself (because some of them are really heavy stuff), but it actually maybe just because of the wrong server settings. And yeah running the whole neural network inside of the flask app is a bad idea not only for performance, but for stability (cuz if something gets crashed in model, then it would be high risk for something to get crashed in Flask app, and whole application get stuck)