horizon-rl/strands-env
Standardizing environment infrastructure with Strands Agents — step, observe, reward.
Treats each environment step as a full multi-turn agent loop with tool use, enabling token-level observations for on-policy RL training. Provides a subclassable `Environment` base with `@tool` decorators for defining custom actions, integrated reward functions, and a CLI-driven evaluator for benchmarking with checkpointing and resume. Directly integrates with Strands Agents SDK and strands-sglang for language model-based RL workflows.
Stars
43
Forks
7
Language
Python
License
Apache-2.0
Category
Last pushed
Mar 13, 2026
Commits (30d)
0
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