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Hbp100

By @Erox

  • 7 Devlogs
  • 26 Total hours

Imagine someone just got released form hospital with a bunch of medical documents , prescriptions and now he is unable to read those all(might be due to different native language or low english proficiency or even too much papers), so they wd like to rely on a llm . Same goes for insurance , business logs or even a dev like me but it is scary to thing abt all our private data is directly sent to the llm, i mean real humans will review the data for preparing better dataset, i felt uncomfortable so i build hbp100. Its a ai to save privacy from ai .It is a ml model built with thousands of examples and it just swaps private data with place holders like [email protected] with [EMAIL_1] , the llm gets enough context(and if using the placeholder kills context my ml is designed not to mask or mask based on confidence ) to work without using users real data and after response my engine again swaps the place holder with the real data and as it runs on the users device .

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@Erox on Hbp100

3h 12m 58s logged

This time i removed all the extractors , and made a new impl to add config from json files or code in python and rust both , it took me a lot of time also i added a website built on hbp100 this time for easier review but dont forget me crate

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@Erox on Hbp100

2h 9m 25s logged

This time i fixed the session issue and wrote THE README MYSELF ,took me a lot of time still worth it

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Ship #1 Pending review

@Erox on Hbp100

Hbp100

After all the debugging, rewrites, benchmarks, broken builds now Hbp100 v3.1.1 is now release d..

What started as a small python privacy project eventually and became a full Rust implementation with a Python interface.
The current version has:

  • A native Rust core
  • Python support through PyO3
  • Ml-powered contextual privacy decisions
  • Reversible placeholder masking
  • Session-based metadata
  • Extremely low processing latency
  • Releases on GitHub and crates.io

There are still edge cases, the extractor can still be improved, and there are plenty of things I want to build next like rayon and multi threaded performance for more speed . It is not like , i have less speed(the current speed is enough to make flash accept defeat) but why not , i use arch btw.

and now i can finally sleep at ease .

  • 5 devlogs
  • 20h
Try project → See source code →
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@Erox on Hbp100

2h 2m 11s logged

Finally session based metadata added now i can sleep in ease also it is v3.1.1 both on crates and github

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@Erox on Hbp100

6h 55m 36s logged

This is probably the most hardcore devlog in this whole session, my task was simply write debug , ask gpt why it didnt work , then deepseek wrote code still didnt work and thts how 7 hrs passed me adding session with persistent memory also with a lot of optimizations , also v3.1.0 is on cargo now , go ahead and check it up for me uWu.

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@Erox on Hbp100

3h 17m 54s logged

This time it is a huge improvement , it looks like v3 to v3.0.1 but i added pyo3 and python api’s , i mean now even python can use my rust package with rust like speed + safety in python , also i fixed some small bugs in extractor , also added benchmarks (the speed is insane , see on the tagged screenshot ) also the ml is hella fast , in python the ml model only took 3x time than a whole iteration in rust with extractors and pyo3 overhead , also now i have got some more ideas to add in my hbp100 i think those will make it even better and polished..

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@Erox on Hbp100

5h 6m 45s logged

today finally i shipped hbp100 v3 on crates “https://crates.io/crates/hbp100/3.0.0” , this time no python runtime full rust even ml in rust thx to lightgbm3 , now it is far faster than the python pkl one , it took me 3+hrs just to train the model and to convert my old python logic into rust , then i had to do the dual readme setup to prevent the bug i came to meet on my last project too , now its fine i made a release on github too , in the crates release there is no “test.rs” but in git release i added tht , the tagged screenshot is result of test

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@Erox on Hbp100

2h 50m logged

actually when i started the project i didnt knew abt stardance , still after v2.2 i used it , v2.2 was pure python and really fast but still it didnt convince me , so i went to v3 rust and i tried rust and python hybrid it sucked i am unable to debug the mess i made so i am thinking to write the ml portion in rust too , i have a live website for v2.2 too , i am new to onnx so it might take some time debugging , still my v2.2 was pretty much successful , one can try tht on “https://github.com/Erox-02/humming-bird-v3/releases/tag/v2.0.0” , so next will be v3.0 and i intend to ship the live website as a other project

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