benotes VS gnothi

yes indeed it's not possible at the moment and not everyone is happy about that. It will be possible in the future.

I'm working on my web app called Benotes which allows you to organize (text) posts and bookmarks.

Maybe Benotes is something for you. However it needs to be selfhosted.

I use Benotes to organize my bookmarks (and notes), allowing me to add something on the go, while still being able to use it on my desktop. Which is the whole point why I created it in the first place ;)

Thank you so much, removing said mount actually solved it and I have it running now! 😊 (I also had to alter the permission for the persistence folder). I've just noticed there's an open issue about how to run Benotes on Synology; I will post a short how-to (Synology-specific step-by-step) there later this evening on the steps necessary to get it to run.

Look up benotes :3 pretty happy with it

I'm using benotes as a replacement for raindrop.io

Perhaps my application called Benotes might be an option for you. You can share collections (=folders) which contain notes (and bookmarks if you want to).

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.