map-verl-config

name	map-verl-config
description	Map VERL training configuration to AgentJet configuration. Find VERL config in verl_default.yaml, check for existing mappings in config_auto_convertion_verl.jsonc, add new mappings to ajet_default.yaml and the conversion schema, and optionally add parameters to AgentJetJob.
license	Complete terms in LICENSE.txt

1. find user requested verl config in codebase/agentjet/ajet/default_config/verl/verl_default.yaml

2. check codebase/agentjet/ajet/default_config/verl/config_auto_convertion_verl.jsonc, whether a mapping to this config already exists.

3. if not, add a config under ajet field in codebase/agentjet/ajet/default_config/ajet_default.yaml, and add a mapping in codebase/agentjet/ajet/default_config/verl/config_auto_convertion_verl.jsonc

4. double check, confirm that default value in ajet_default.yaml is the same as verl config in verl_default.yaml, and the mapping is correct in config_auto_convertion_verl.jsonc

5. ask user whether to add to AgentJetJob (ajet/copilot/job.py), if the user confirms:

• learn how other config is added in ajet/copilot/job.py
• add to init signature (with type hint and default None)
• update docstring with parameter description
• add instance attribute assignment with cast()
• add mapping to overrides dict

6. CRITICAL: update ajet/default_config/ajet_config_schema.py

• the schema must have a dataclass for EVERY nested level in the config path
• e.g., for ajet.trainer_common.optim.lr, need:
  • AjetOptim dataclass with lr: float = 1e-6
  • AjetTrainerCommon must have optim: AjetOptim = field(default_factory=AjetOptim)
• if parent dataclass is missing the nested field, config loading will store it as a raw dict instead of a typed dataclass, causing getattr() to fail at runtime