Task sets for RL / OPD / RL+OPD runs on the Slime agent_envs stack. Rows are stored in the Slime-readable schema so train.py can load them directly with --input-key prompt --label-key label --metadata-key metadata.

Row schema (all configs)

Every row separates the model-input field from the environment-input fields:

prompt (model input, raw text): the fixed instruction the model receives. The live per-turn… See the full description on the dataset page: https://huggingface.co/datasets/huzican/agent_envs.