This started as a small experiment in structural rewriting. The basic idea is
that you give the system two or three before and after examples, press Teach,
and it learns that transformation and applies it to new inputs.
It is not an LLM and it is not a template system. There is a small learned
component that decides when a rule applies, and the rest is a deterministic
structural rewrite engine.
There are a few demo modes:
TEACH: learn a structural rule from examples
COMPOSE: apply several learnt rules together
TRANSFER: use the same rule in different symbolic domains
SIMPLIFY: multi step rewriting
CODEMOD: for example you can teach lodash.get to optional chaining from two examples
Once a rule is learnt it generalises to inputs that are deeper or shaped
differently from the examples you gave. Everything runs on CPU and learning
happens in real time.
This started as a small experiment in structural rewriting. The basic idea is that you give the system two or three before and after examples, press Teach, and it learns that transformation and applies it to new inputs.
It is not an LLM and it is not a template system. There is a small learned component that decides when a rule applies, and the rest is a deterministic structural rewrite engine.
There are a few demo modes:
TEACH: learn a structural rule from examples COMPOSE: apply several learnt rules together TRANSFER: use the same rule in different symbolic domains SIMPLIFY: multi step rewriting CODEMOD: for example you can teach lodash.get to optional chaining from two examples
Once a rule is learnt it generalises to inputs that are deeper or shaped differently from the examples you gave. Everything runs on CPU and learning happens in real time.
Demo: https://re.heavyweather.io