Working with remote large data sets as if they where local.

I made the project public on May, and now as September has arrived, you can work with post production videos anywhere in the world. You can run the daemon on your own NAS and access the data on-demand from your working machines.

The same applies to data acquisition in digital forensics flows.

so yeah.. it builds the stories out of their actual life. their family and friends are in the cast, their dog, the thing they're nervous about this week. the kid doesn't just appear in the story, the story is about their world and imagination and grows with them.

ultimate goal is to keep iterating and get to a level of quality of Bluey, etc but have it actually be the kids world with agency/choices vs. one they have to passively sit back and watch, and that they're not in.

would love any feedback. i know there's been others like Ello shared on here and those threads were really interesting to know HN's opinion on. this does not take an educational and instructional approach. Tella is meant to help develop who they are through stories and be a better screen alternative time to the rest of the algo/curated garbage out there. anyway you guys are a critical and technical bunch and i respect/appreciate that.. especially since this of course leverages multiple AI services to create the stories ~

https://tella.kids/

[1] https://github.com/jha-naman/treetags

[2] https://github.com/jha-naman/treetags/pull/62

Tried to use a generator for automating the bulk of the scanner for a language from `grammar.json` file of a tree-sitter grammar. A runtime engine uses the scanner for a forward only walk on the scanned code and calls the hooks to generate tags.

[3] https://github.com/jha-naman/treetags/pull/56

A complicated mess of a generator that takes a few declarative inputs and tries to generate code for spitting out tags for a given language.

Ai-rganize: Allows AI to identify, classify, and organize local files, making the core workflow naturally reviewable as scan, propose organization, approve, rename or move: https://github.com/adefemi171/ai-rganize

Runeward: Been using this locally myself with hedr to secure all my agents: https://github.com/Runewardd/runeward

Compears: grocery prices are shit now so I designed this to aggregate prices across multiple grocery stores: https://compears.shop/

The basic idea is that ticket (or chat) based workflows loose tons of context over time. During periods of rapid iteration, even the tickets themselves can’t always keep up with changes in the requirements. Goalpost projects are lightly structured documents. Due to that structure, it can easily give you a view of what changed in any particular update, or you can search or browse the overall up to date spec if you are just looking to get context on something.

There are some nice quality of life features. Changes live in batches which can (optionally) be subjected to customizable approval rules. Email notifications to stakeholders when requirements change. The ability to move changes to different batches, pre-approval.

Still WIP, but I’d love any feedback!

https://devorajs-docs-docs.vercel.app https://github.com/hassanalsa3aka/devora.js

AI can make a good one-off character, but keeping that same character consistent across dozens of product illustrations is still surprisingly difficult. That’s the problem I’m trying to solve.

Would love any feedback.