Stream-Framework VS gnothi

I have looked into a getstream.io integration, however it seems that the Ruby SDK is really treated as a second class citizen. There's bugs with the documented API (I'm having issues even creating users and querying users), the usage of the gem is low and there is an open issue since May that no one has even looked at, which doesn't give me hope for long term support.

An ultralight social media app with no dependencies that can run on shared web hosting. It's an API like Getstream, so F/E is up to you. I've had a fork of it in production for 2.5 years on a subscription site that generates a small income.

Now, I'm seeking your advice and opinions. If you have experience using Stream or MirrorFly for chat implementation, I'd greatly appreciate any insights you can provide. Here are some questions I have:

Think about the edge that you can have over thousands other people looking for a job like you. One of the ways to do it – tailor your (even small) experience to the company you are applying to. E.g. Let's take a company like Stream that have an open-source Swift SDK, try to contribute to their SDK, maybe close some `good-first-issue`s here and there, do some documentation improvements, enrich their example app. So that when you feel like you are ready to knock their door – you already have an edge over others – you don't need onboarding (because you already know most of their codebase, you even completed your first few tasks while yet not being employed!)

This is absolutely absurd. I mean I 100% believe it happens, it's just absurd that the Tier 1 admin bot is this bad.

I too firmly believe the tier 1 admins are just this program - https://getstream.io/ And reddit doesn't want to admit that humans are not actually reviewing things

Really depends on so many variables, and comes down to knowing the audience. I built a lightweight social network api platform to do a lot of what getstream.io and OSSN does, but the way users engaged with it was nothing like what I expected. One use case, for example, would have been mostly satisfied with WordPress and Mailchimp. Forums are very familiar to people and still used by a lot of "I don't do social media" types. At the risk of making a sweeping generalization, if you have an older target audience they will be happy with a forum. If you have a younger target audience they will prefer the sequential post / react style of interacting, like Discord or Instagram.

Ok, glad someone brought this up. Premium uses GPT to generate summary / themes, and it's pretty much perfect every time. Free uses a version of led-16384 trained on booksum, and can.. well.. struggle. A common mistake it will make is to hallucinate content public-domain book type content, especially if the journal entry itself wasn't "meaty" enough to work with. The solution will be to implement a local large language model https://github.com/ocdevel/gnothi/issues/160, so that free users experience similar benefits to premium, if less precise. In the mean time, I'm going to keep fiddling with the summarization model today/tomorrow to see if I can't get it just a bit less book-ish.

Website, Github. My partner u/mVadr and I just launched Gnothi (v1). We’re both psychology/personal development enthusiasts who work in tech. We started Gnothi to get us journaling more, and to leverage machine learning to optimize the process.

Website, Github. Insights & resources include GPT-powered prompt (which uses journal entries as context) behavior analysis, book recommendations, entry summaries, and recurring themes.

I created a GPT journal and am now looking into LocalLLM for the privacy-focused. I gave RedPajama-INCITE a spin, and found it soooo bad! I mean.. really bad. I should note this was about 2 months ago? I did see they released a newer version, I'm assuming there was a data-collection / training process they were waiting on. But I'm wondering: is the magic in the fine-tuning? As in, did you find the model useful before you fine-tuned, and the fine-tuning was just a cherry on top? Or did you have to fine-tune to make it work?

I built a GPT-based Journal. Not a robo-therapist, but there's so much healing in journaling. This has the benefit of maintaining context (your past entries, based on filters). Website, Github

AI Journal. Website, Github. Trying to make an ultra power-tool quantified-self platform, coming from Habitica.

I built an open source robo-journal Gnothi. Started in 2019 with summarization, recurring themes, book recommendations, behavior tracking. Soon as GPT came along, you bet your butt I integrated.