Synth AI Environment Framework
Project description
Environments
Synthetic Environments / Long Horizon Tasks / Digital Control Agents
Motivation
- We're building Environments to have key desiderata for long-horizon language agents
- Snapshotting and reproducibility
- Statefulness as a first-class citizen
- Consistent abstractions for engine interaction and state reads across settings
- Environment observability and tracing
- HTTP access for simplified training and evaluation
- Strong data abstractions to enable easily-configurable filtering and curriculum learning
- Simple abstractions for agent-originated tool edits, etc.
User Guide
Note - this repo is under extremely active development. Hic sunt dracones, if not contributing it may be more useful as a reference or development resource than as core code for your production systems.
Supported Environments
[] Sokoban (maturing, not active dev) - This environment is not of our own making! Please credit the great researchers at Deepmind and Ragen, among others. - Checkout test_synth_react.py for a hello world example! [] Hendryks Math [] (maturing) [] Crafter-Classic (maturing) [] EnronBench (active dev) [] SWE-Bench (active dev - do not attempt) [] NMMO (active dev - do not attempt) [] Red (active dev) [] Verilog (maturing)
...
Development
To use the Astral suite of devtools: package management: uv sync, uv add, uv remove linting: ruff format . type(hint) checking: uvx ty check
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