v0.2.1

[PanAndy]

Hello everyone! Thank you for your interest in ROLL.
ROLL has recently received a large set of new features. Below is a summary of the latest updates. We will continue iterating on ROLL—welcome to join the ROLL community.
#366

🚀 Highlights

• Rollout has been refactored to be scheduled by a router, with support for sglang-router.
• Added training support for [On-Policy Distillation](docs_roll/i18n/zh-Hans/docusaurus-plugin-content-docs/current/User Guides/Pipeline/on_policy_distill_pipeline_start.md).
• Added support for the Qwen3.5 model family: Dense / MoE.

🚀 Major New Features

• Rollout
  • Router scheduling refactor
    • Refactored the sglang strategy to support both engine and server modes.
    • Refactored schedulers (rlvr DynamicScheduler / agentic RolloutScheduler) so that scheduling is now uniformly provided by the Router.
    • Migrated the original LoadBalancer and RequestScheduler to PromptAffinityRouter and EnvAffinityRouter.
    • Added support for sglang-router.
• Pipeline recipes
  • Added On-Policy Distillation training support.
• Models
  • Added support for Qwen3.5 Dense/MoE series models.
• Docker
  • Updated images/environments: torch 2.10, vLLM 0.16.0 nightly, vLLM 0.15.1, mcore 0.16.0.
• Bug fixes
  • Set VLLM_USE_FLASHINFER_SAMPLER=0 by default for vLLM on Torch 2.8.0 to mitigate overly repetitive responses.
  • Fixed occasional port conflicts between sglang and vLLM.
  • Fixed sglang multi-node failures when infer_dp > 1.
  • Fixed reward worker metrics exposure.
  • Fixed a get_node_ip cache issue in model download that could cause deadlock/timeouts.
  • Fixed FSDP2 DCE save when CPU offloading is enabled.
  • Fixed casting during FSDP2 model initialization.

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This discussion was created from the release v0.2.1.