---

name: ui-s1-training description: "Prepare UI-S1 / verl GUI trajectory post-training, SOP evaluation, JSONL validation, Ray/vLLM GRPO commands, and checkpoint merge workflows with backend gating." metadata: disco-role: operating disable-model-invocation: true license: MIT

UI-S1 Training and Evaluation

Use this sub-skill when a task names UI-S1, verl, GUI trajectory RL, GRPO/DAPO/PPO, Ray, vLLM/SGLang rollout, Qwen2.5-VL, AndroidControl/SOP JSONL, eval_qwenvl.py, or model_merger.py.

Route map

Prompt signal	Workflow	Read / run
AndroidControl/SOP trajectory JSONL, missing action_content or check_options	Data validation	references/data-and-action-formats.md, scripts/validate_ui_s1_jsonl.py
GRPO/DAPO training, Ray, vLLM, Hydra overrides, traj_grpo	Training command	references/training-and-evaluation.md, scripts/build_ui_s1_train_command.py
SOP/static evaluation, eval_qwenvl.py, model server calls	Evaluation command	same reference, scripts/build_ui_s1_eval_command.py
FSDP/Megatron checkpoint merge/test/upload	Checkpoint merge	references/checkpoint-and-serving.md, scripts/build_model_merger_command.py
CUDA/Ray/vLLM/flash-attn/checkpoint/data/OOM failures	Troubleshooting	references/troubleshooting.md, references/configuration.md

Safe workflow

1. Validate trajectory data before training/evaluation:

python sub-skills/ui-s1-training/scripts/validate_ui_s1_jsonl.py --jsonl train.jsonl

2. Build a training command without starting Ray/training:

python sub-skills/ui-s1-training/scripts/build_ui_s1_train_command.py \
  --train-files /datasets/android_control_train.jsonl \
  --val-files /datasets/android_control_eval.jsonl \
  --model-path /checkpoints/Qwen/Qwen2.5-VL-7B-Instruct \
  --gpus-per-node 8 \
  --engine vllm

3. Build an SOP evaluation command:

python sub-skills/ui-s1-training/scripts/build_ui_s1_eval_command.py \
  --jsonl-file /datasets/android_control_evaluation_std.jsonl \
  --output-dir /runs/ui-s1-eval \
  --model-name qwen2.5-vl-7b-ui-s1

4. Build checkpoint merge/test commands only after verifying checkpoint layout:

python sub-skills/ui-s1-training/scripts/build_model_merger_command.py \
  --operation merge \
  --backend fsdp \
  --local-dir /runs/checkpoints/global_step_10 \
  --target-dir /runs/merged-hf

Verification stance

Safe validators and builders can run on CPU. Live UI-S1 training/evaluation needs CUDA GPUs, compatible PyTorch, flash-attn, Ray, vLLM/SGLang, checkpoints, datasets, ports, and logging configuration. Do not claim training verified from a laptop/CPU-only command template.

Boundaries

• Live MobileAgent phone/browser/desktop operation belongs to current-gui-owl, mobile-agent-e, pc-agent, or legacy-agents.
• GUI-Critic/AndroidWorld/OSWorld/Web benchmark command preparation belongs to benchmarks-and-evaluation.
• Generic RLHF/verl internals not tied to UI-S1 GUI trajectories may require a broader post-training skill.