Tools for using computer algebra systems to solve math problems step-by-step with reinforcement learning
mathy: This removes the MCTS powered agent. It was a nice agent but the pieces required for it to work effectively have been lost. It's not a primary use-case of mine now, so it's better to drop it and remove any confusion.
refactor(agents): move to singular agent with generic names
chore: misc cleanup and fix tests
chore: update tf_siren dep
chore: fix some tests and remove dead ones
refactor(core): use mathy_core for CAS needs
This moves a lot of complexity out to another package, which is desirable for a number of reasons:
chore: fix website build
perf(ci): refactor virtual envs to reduce build time
chore: remove ci specific setup script
chore: remove disk space cleanup step
chore: drop keras-self-attention dep
chore: fix requirements for tf agent
chore: fix requirements for mkdocs plugin
chore: install graphviz on ci build machine
chore: try tensorflow 2.2.0
chore: fix import errors
chore: try to confirm siren fix
chore: remove kwargs from Sine layer
chore: remove second pytest invocation for zero
chore: fix venv path in test scripts
chore: drop example apps from main package
chore: drop reformer test
chore: bump tf_siren to 0.0.5 for tf2.2
chore: drop misc cleanup
test(cli): better coverage for generating problems
chore: cleanup from review
chore: cleanup from review
BREAKING CHANGES: This removes the "zero" agent entirely, and invalidates existing pretrained mathy models.