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name: training summary: "Configure and troubleshoot rLLM RL/SFT training backends and gateway-backed rollouts." description: "Use rLLM training APIs and CLI for AgentTrainer, AgentSFTTrainer, Tinker/Verl/Fireworks backends, RL algorithms, SFT data/config, remote runtimes, and model-gateway trace capture." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

rLLM Training

Use this sub-skill when the task mentions rllm train, rllm sft, AgentTrainer, AgentSFTTrainer, BackendProtocol, TinkerBackend, VerlBackend, FireworksBackend, SFTSpec, rollout engines, GRPO/PPO/REINFORCE++/DAPO/CISPO, async_training, remote_runtime, gateway traces, LoRA rank, checkpointing, or backend validation errors.

Start Here

1. Read references/backend-matrix.md before selecting or installing a backend. Tinker/Fireworks are service-backed; Verl is local distributed and GPU-heavy.
2. Read references/training-workflows.md for rllm train, rllm sft, and programmatic AgentTrainer/AgentSFTTrainer patterns.
3. Read references/trainer-api.md for current import locations, constructor signatures, algorithm config notes, and SFT spec fields.
4. Read references/sft-data-and-config.md when SFT files, message rows, eval-to-SFT curation, or tokenization methods are involved.
5. Read references/troubleshooting.md for backend validation errors, gateway trace issues, and required-backend limitations.
6. Use ../evaluation/SKILL.md for AgentFlow/Evaluator implementation and ../datasets/SKILL.md for benchmark/data layout.

Safe Checks

python scripts/check_training_backends.py
python scripts/dump_train_config.py --model-name Qwen/Qwen3-8B --group-size 2 --batch-size 4

check_training_backends.py reports optional dependency and CUDA visibility. dump_train_config.py prints the config produced by the train CLI merger. Neither helper launches training. Missing optional backends are not failures unless the user's selected workflow requires them.

Verification Caveat

CPU/import checks can validate this skill's guidance and config shape, but cannot prove local Verl training, Tinker service training, Fireworks service training, remote AgentCore execution, or long RL/SFT runs. Preserve those as required-backend verification items unless the user explicitly narrows scope.