v1.0.3

What's Changed

• chore(docker): add openclaw, ironclaw, zeroclaw, and nanobot-ai to runtime image by @garrett4wade in #1051
• feat(agent-service): add Agent Service microservice infrastructure by @CormickKneey in #1048
• feat(gateway): Add rollout gateway infrastructure with controller, router, and data proxy by @nuzant in #1043
• feat: estimators for kl divergence by @NicolasArias in #1060
• test(infra): speed up inference service integration tests by @nuzant in #1068
• fix(infra): simplify RTensor serialization in data proxy by @garrett4wade in #1067
• fix(rpc): resolve connection reset during RTensor fetch with large payloads by @pratyush618 in #1075
• docs: add gitcgr code graph badge by @vitali87 in #1073
• fix(openai): handle streaming responses in chat/completions endpoint by @Zijun9 in #1053
• fix: add PIL image and processor serialization for VLM RPC by @Adiactive in #1070
• refactor(api): migrate allocation_mode to per-engine backend fields by @garrett4wade in #1044
• chore(agents): add Codex harness and align AI workflows by @rchardx in #1082
• feat(platform): add NUMA CPU affinity binding for training engines by @HT-Yuan in #1083
• feat(commands): add fork workflow support to create-pr skill by @guozhihao-224 in #1092
• fix(rpc): batch HTTP RTensor fetches for large multimodal batches by @Wangxiaoxiaoa in #1077
• fix(fsdp): stabilize Qwen-VL rope-index argument binding and dtype by @Adiactive in #1094
• Refactor(vllm): use pause_generation from vllm instead of abort_all_req in areal_vllm_server by @HwVanICI in #1091
• feat: add BailingMoeV2.5 support with Lightning Attention + MLA + MoE + CP by @dingzhiqiang in #1079
• feat：support model training in IPv6-only environment by @TaoZex in #1072
• fix: fix pad_packed_tensor_dict by @HKAB in #1104
• feat: megatron bridge adaptation by @gursimar in #1056
• fix(engine): remove duplicate trust_remote_code kwarg in MegatronBridge init by @rchardx in #1107
• fix(dataloader): prevent data drop and padding during validation for accurate metrics by @Anguo-star in #1100
• fix(archon): add missing POST /data/batch endpoint to data proxy by @rchardx in #1105
• refactor(engine): abstract CUDA calls via current_platform in PerLayerOptimWrapper by @guozhihao-224 in #1108
• perf(fsdp): pipeline distributed weight sync with a single pending bucket by @HT-Yuan in #1074
• fix(engine): restore SGLang VLM training by @garrett4wade in #1098
• feat(archon): add FP8 blockwise training support by @rchardx in #1087
• chore(ci): update GCP CI image by @garrett4wade in #1115
• feat(inference-service): complete vLLM backend support in inference service by @garrett4wade in #1112
• fix(archon): harden FP8 blockwise training for TP and MoE scenarios by @rchardx in #1118
• feat(inference_service): add VLM image input support to OpenAI-compatible API by @garrett4wade in #1119
• feat(utils): add Trackio experiment tracking backend by @guozhihao-224 in #1113
• refactor(infra): decompose rpc_server into shared guard + blueprints by @garrett4wade in #1126
• refactor(agents): redesign review-pr taxonomy and sync flow by @rchardx in #1124
• feat(infra): add client-side fetch buffer for RTensor by @guozhihao-224 in #1122
• chore: fix gcp image to latest by @nuzant in #1130
• docs: add Trackio configuration to CLI reference by @rchardx in #1131
• feat(service): support online inference service by @nuzant in #1121
• fix(engine): for broken tree training due to bad indent in PR #1056 by @gursimar in #1135
• feat(service): add vllm backend support for inference service demo by @nuzant in #1136
• fix(api): add mode validation for WandBConfig and SwanlabConfig by @guozhihao-224 in #1134
• feat: enable LoRA RL-training in Megatron via megatron-bridge by @gursimar in #1123
• fix: harden padded distributed eval across training engines by @rchardx in #1109
• feat(ci): separate vllm and sglang pyproject.toml by @garrett4wade in #1141
• fix(vllm_ext): clear multimodal caches after generation pause by @Adiactive in #1144
• fix(ci): sync uv.vllm.lock with the current pyproject.vllm.toml by @garrett4wade in #1146
• fix(vllm_ext): XCCL lora weights update when PP>1 by buffering and merging PP shards by @gursimar in #1145
• chore: fix pre-commit by @garrett4wade in #1148
• Fix #1040: [Feature] Fixed bugs in Archon LoRA Backend by @JiwaniZakir in #1139
• feat(infra): add distributed data loading service by @garrett4wade in #1120
• refactor(infra): standardize list-first trajectory batch dispatch by @garrett4wade in #1150
• feat(infra): allow colocation with offloading and disk weight updates by @garrett4wade in #1157
• refactor: replace manual JSON parsing with Pydantic models by @koladefaj in #1154
• fix(engine): FSDP compute_logp fails for Qwen3.5 with dict attention_mask by @pratyush618 in #1153
• chore: update readme and enforce license by @garrett4wade in #1170
• chore: ensure SPDX license header in python source files by @garrett4wade in #1171
• fix: add missing pre-commit check file by @garrett4wade in #1173
• chore: add project governance for PyTorch ecosystem by @garrett4wade in #1174
• feat(infra): add microservice-based training service (controller v2) by @garrett4wade in #1169
• chore: renew qrcode by @garrett4wade in #1184
• feat(archon): support multi-node inference in gateway controller by @guozhihao-224 in #1178
• feat(agent-service): add Controller, Guard, and Claude Agent SDK example by @CormickKneey in #1177
• fix _update_weights_from_disk function to prevent training to be stuck by @asif07hossain in #1181
• refactor: mount data blueprint via WSGI and adopt Pydantic in engine blueprint by @koladefaj in #1179
• fix(engine): use meta device for non-rank-0 in FSDP memory_efficient_load by @yulangz in #1182
• ci: parallelize unit and integration tests across 4 GPU instances by @nuzant in #1185
• chore: dump v1.0.3 by @garrett4wade in #1191

New Contributors

• @pratyush618 made their first contribution in #1075
• @vitali87 made their first contribution in #1073
• @Adiactive made their first contribution in #1070
• @guozhihao-224 made their first contribution in #1092
• @TaoZex made their first contribution in #1072
• @HKAB made their first contribution in #1104
• @Anguo-star made their first contribution in #1100
• @JiwaniZakir made their first contribution in #1139
• @koladefaj made their first contribution in #1154
• @asif07hossain made their first contribution in #1181

Full Changelog: v1.0.2...v1.0.3

v1.0.2

Release Note

A massive thank you to our newest contributors who joined us for this release! The strength of this project lies in the collective expertise of the open-source community, and your work is what moves us forward.

🚀 Model & Architecture Updates

• Qwen3.5 Support: Added support for both dense and MoE (Mixture-of-Experts) variants of Qwen3.5 (archon backend, DP-only).

• On-Policy Distillation: Introduced native support for on-policy distillation.

• Added opt-in support for Hugging Face kernels and per-layer optimizer steps with a streaming H2D/D2H pipeline for FSDP.

🛠 Infrastructure & Scalability

• Docker & Runtime: Split Docker images into specialized sglang and vllm variants to allow different torch verions and fast docker image update.

📖 Documentation & Localization

• Bilingual Support: Launched comprehensive bilingual (EN/ZH) documentation, including a new translate-doc-zh command and fixed LaTeX rendering.

• New Guides: Added an online proxy mode training guide and revised existing online RL training tutorials.

What's Changed

• feat(models): shard vision encoder across Ulysses SP ranks by @aoshen524 in #929
• docs: fix broken documentation links by adding /en/ language prefix by @garrett4wade in #986
• [Feat] Add on-policy distillation support by @HwVanICI in #964
• fix: keep PPO token stats consistent under context parallelism by @yash27-lab in #990
• Upgrade GitHub Actions for Node 24 compatibility by @salmanmkc in #993
• Upgrade GitHub Actions to latest versions by @salmanmkc in #994
• chore: add Python 3.11 support (requires-python >=3.11,<3.13) by @garrett4wade in #991
• chore(ci): replace format-check with pre-commit CI and add commit-msg hooks by @rchardx in #998
• feat(docs): add bilingual documentation with translate-doc-zh command by @ZiyiTsang in #995
• refactor: flatten sub-module imports to use parent package re-exports by @NJX-njx in #996
• feat(infra): split Docker image into sglang and vllm variants by @garrett4wade in #985
• docs: fix broken LaTeX rendering in bilingual docs by @rchardx in #1004
• fix: CPU-only support on macOS by @zhanghaotong in #1003
• feat(archon): add moe_router_dtype config for FP32 router gate GEMM by @rchardx in #1009
• refactor: replace string literals with enums and fix logging issues- … by @HT-Yuan in #1008
• feat(fsdp): add per-layer optimizer step with streaming H2D/D2H pipeline by @aoshen524 in #983
• Update NPU doc for v1.0.1 release by @HwVanICI in #1022
• feat(archon): add Qwen3.5 dense and MoE model support (DP-only) by @rchardx in #1012
• fix: LoRA and XCCL openai_serving_models LoRA versioning bug by @TinLongYu in #1021
• fix: unify RPC error response JSON key to "error" across server and s… by @HT-Yuan in #1019
• fix: close sockets on bind failure, fix exit traceback in trainers by @mango766 in #1032
• fix(vllm): harden runtime LoRA alias handling for XCCL updates by @Wangxiaoxiaoa in #1039
• fix(ci): minor fixing ruff format by @garrett4wade in #1041
• docs(github): improve PR template checklist and type-of-change section by @garrett4wade in #1042
• docs: add online proxy mode training guide by @Zijun9 in #1006
• Add opt-in support for Hugging Face kernels by @lewtun in #1033
• fix(archon): Wrap router gate in nn.Module for DTensor hook compatibility by @fishcrap in #1029
• chore(deps): bump sglang, vllm, megatron-core and restructure Dockerfile by @garrett4wade in #1010
• ci(infra): add GCP image baking workflow for CI acceleration by @garrett4wade in #1045
• refactor(infra): simplify RTensor to single-shard and adopt per-trajectory list pipeline by @fishcrap in #1017
• ci(infra): add GCP image baking workflow and update CI image by @garrett4wade in #1047
• docs: revise online RL training tutorial for EN and ZH by @garrett4wade in #1049
• chore: prepare v1.0.2 release by @garrett4wade in #1050

New Contributors

• @aoshen524 made their first contribution in #929
• @yash27-lab made their first contribution in #990
• @salmanmkc made their first contribution in #993
• @NJX-njx made their first contribution in #996
• @zhanghaotong made their first contribution in #1003
• @HT-Yuan made their first contribution in #1008
• @mango766 made their first contribution in #1032
• @Wangxiaoxiaoa made their first contribution in #1039
• @Zijun9 made their first contribution in #1006
• @lewtun made their first contribution in #1033

Full Changelog: v1.0.1...v1.0.2

v1.0.1

Release Note

A patch release that fixes a dependency issue in the docker image and enriches the documentation and testing of the OpenClaw example.

What's Changed

• fix(config): Fix openclaw config typo and increase max_tokens_per_mb by @fishcrap in #959
• docs(openclaw): Replace hardcoded admin key with placeholder in README by @fishcrap in #967
• feat: Fully Support MIS/TIS to stablizing rollout-training mismatch by @ZiyiTsang in #930
• refactor(api): move validation into config post_init methods by @rchardx in #970
• fix(openai-proxy): return None for empty trajectory in online mode by @fishcrap in #971
• Ray placement group refactor and preliminary architecture for multinode inference instances by @hlyli in #966
• feat:Add chinese doc by @ZiyiTsang in #969
• fix(api): replace Literal type with str for SchedulingSpec.ray_placement_strategy by @garrett4wade in #976
• update readme by @xssstory in #974
• test(examples): Add OpenClaw online RL integration test by @fishcrap in #977
• fix: pinning torchao version to 0.15.0 by @garrett4wade in #981
• bump v1.0.1 by @garrett4wade in #982

New Contributors

• @hlyli made their first contribution in #966

Full Changelog: v1.0.0...v1.0.1

v1.0.0

🚀 Key Highlights

Release Notes

Online RL Training

• Seamlessly train any agents by configuring a base_url and api_key—no code changes required and no heavy dependencies.
• Check out the OpenClaw RL training example for more details.

Archon Engine

• A fully working, PyTorch-native 5D parallel training engine.
• Includes features like:
  • Automatic HF format conversion
  • Zero-bubble pipelining
  • torch.compile
  • FSDP (Fully Sharded Data Parallel)
  • Selective activation support

AI-Assisted Coding

• Official commands and skills to streamline development and enable easy customization.

Infrastructure Upgrade

• Transition from the previous SPMD architecture to a more efficient single-controller architecture.

uv Installation Support

• Easily set up training environments by running the simple command: uv sync.

What's Changed

• feat: replace legacy math parsing with math-verify by @rchardx in #739
• Add installation instructions for Ascend NPU by @HwVanICI in #748
• [Bug Fix] Fix Tools compatibility, max_token restrictions, and EOS token issues in Proxy mode by @yulangz in #736
• refactor: modify engine and controllers to support the single-controller mode with the same trainer by @garrett4wade in #753
• VLM Training on NPU by @HwVanICI in #746
• refactor: move device utilities to platform classes and io_struct by @garrett4wade in #757
• Fix: Implement get_device_stats() for train_controller by @HwVanICI in #762
• refactor: single-source task_id generation in submit methods by @garrett4wade in #759
• [Bug Fix] Camel example with wrong and missing agent arguments by @HwVanICI in #766
• feat: use name_resolve for worker discovery and fix perf_tracer in the single-controller mode by @garrett4wade in #764
• [Feature] Implement Single-Controller XCCL Weight Update by @HwVanICI in #754
• feat: Implement slurm scheduler by @garrett4wade in #767
• Ray Scheduler Implementation for Single Controller by @HwVanICI in #741
• refactor: use callbacks to implement xccl weigh transfer and avoid busy waiting during rollout by @garrett4wade in #769
• [Testing] Update GCP image to accelerate CI testing by @nuzant in #772
• refactor: unifying launcher, scheduling spec, yaml configs, and training scripts by @garrett4wade in #770
• feat: improve logging by @garrett4wade in #771
• refactor: separate megatron imports and installation from FSDP by @garrett4wade in #773
• minor fix: vLLM LoRA request cleanup for issue #751 by @TinLongYu in #765
• fix: refactoring proximal logp recompute condition by @garrett4wade in #780
• [Feat] Add FP8 training support by @fishcrap in #758
• Enhance host IP detection in areal.utils.network by @HwVanICI in #778
• chore: remove the ad-hoc should_broadcast parameter in rpc servers by @garrett4wade in #774
• feat: support colocated engines in the single-controller mode by @garrett4wade in #779
• chore: update readme by @garrett4wade in #782
• docs: restructure AGENTS.md and add CLAUDE.md symlink by @rchardx in #783
• chore: Expose error when lauch sglang server by @ZiyiTsang in #781
• refactor: simplifying the implementation of customized workflow with context management by @garrett4wade in #785
• chore: Expose error when launching vllm server by @garrett4wade in #790
• refactor: allow dynamic batch size without the dynamic_filtering function by @garrett4wade in #786
• fix: fix ray scheduler in the single-controller mode by @garrett4wade in #791
• fix inference engine addr resolving logic by @garrett4wade in #792
• chore: minor fix doc formula by @ZiyiTsang in #793
• doc: update docs for grpo and related algorithms by @garrett4wade in #794
• refactor: migrate grouped rollout from customized workflows to inference engines by @garrett4wade in #789
• Single-controller LoRA RL fine-tuning with vLLM by @gursimar in #735
• [Feature] Group-level data redistribution by @nuzant in #800
• critical fix: passing is_eval and group_size from rollout controller to engines by @garrett4wade in #801
• Update NPU doc by @HwVanICI in #803
• feat: add Archon Engine - PyTorch native FSDP2 training backend by @rchardx in #799
• [Feature] Tree training support (Megatron Engine) for agentic RL training by @nuzant in #804
• Add NPU RLVR example by @HwVanICI in #798
• [Bug Fix] XCCL weight synchronization fix for the single controller lora by @gursimar in #796
• [Bug Fix] Fix import error introduced by tree training PR by @nuzant in #808
• chore: remove legacy code, config, and documentation by @garrett4wade in #806
• fix: update tree_attn function name to patch_bridge_for_tree_training by @rchardx in #809
• fix: prevent fake PID killing in LocalScheduler tests by @rchardx in #810
• feat(archon): add torch.compile support and profiling tools by @rchardx in #807
• Add RayScheduler to sft.py by @HwVanICI in #814
• fix: add lm_head.weight into index when index file exists by @jwhj in #816
• feat: use subprocess to fork colocated workers by @garrett4wade in #815
• feat(archon): add Context Parallelism (Ulysses SP) support by @rchardx in #817
• refactor(data): simplify pad_mb_list alignment parameters by @rchardx in #820
• refactor: unify HTTP client management in workflow_context by @garrett4wade in #819
• feat(archon): enable TP + AC + compile compatibility with _WaitAsyncWrapper by @rchardx in #821
• [FEAT] Add direct TE FP8-PyTorch FP8 conversion by @fishcrap in #802
• refactor(core): simplify HTTP client lifecycle with event loop cleanup by @garrett4wade in #823
• feat: Add AgentWorkflow API and migrate workflow resolution to RemoteInfEngine by @garrett4wade in #825
• feat(scheduler): refactor fork_workers to public API with custom command support by @garrett4wade in #826
• [FIX] correct vLLM config defaults for chunked prefill and prefix caching by @fishcrap in #827
• refactor(openai): modularize proxy architecture and add inline mode by @garrett4wade in #829
• chore(doc): update readme by @garrett4wade in #830
• fix(test): Fix math-verify tests by @garrett4wade in #831
• feat(archon): add Expert Parallelism (EP) support for MoE models by @rchardx in #833
• fix(moe): correct histc max param by @rchardx in #835
• feat(archon): add explicit FSDP prefetching for EP by @rchardx in #834
• feat(archon): add EP-aware padding wrapper for MoE grouped_mm by @rchardx in #836
• testing: fix CI, skip tests that cannot run on A100 GPUs by @nuzant in #838
• feat(archon): add Expert Tensor Parallelism (ETP) support for MoE models by @rchardx in #839
• feat: support tree training for FSDP engine by @nuzant in #837
• fix: remove duplicate setup in gsm8k_rl by @v3nividiv1ci in #842
• refactor(archon): cleanup parallel dims and FSDP config for pipeline parallelism by @rchardx in #841
• refactor(tree_attn): decouple FSDP and Megatron implementations by @rchardx in https://github.com/inclusionAI/AReaL/pu...

v1.0.0.rc1

Pre-release for 1.0.0.

v0.5.3

Highlights

This is a patch release primarily for delivering the latest docker image for testing.

We will include well-documented features in the next major release.

v0.5.2

Highlights

This is a patch release primarily for delivering the latest docker image with torch 2.9.1, vllm 0.14.0, and sglang 0.5.7 supports.

We will include well-documented features in the next major release.

v0.5.1

Highlights

This is a patched release upon v0.5.0.

• A new docker image with math-verify and the latest ruff.
• Support for PPO critic model support with Megatron engine.
• Refactored FSDP/Megatron engine implementations.
• Implement efficient RPC tensor transfer with RTensor (aka the original DistributedBatch).
• Beam seach support for vLLM.

What's Changed

• fix: change checkpoint cleanup flag to fix update_weights_from_disk in single-controller mode by @HwVanICI in #711
• fix: prevent port overflow in vLLM server with high data parallelism (fixes #652) by @HsiaoTsan in #653
• refactor: refactor train engine high level APIs by @aaaandychen in #658
• [Fix] Fix the bug that experiments cannot properly exit in the TIR example by @nuzant in #712
• chore: print more information in concat mode and handle empty tool calls for easy debugging by @nuzant in #713
• chore: trim tests in CI by @garrett4wade in #714
• refactor: enforce task_id creation, access, and manipulation in inference engines by @garrett4wade in #715
• refactor: redesign TrainEngine API with cleaner abstractions by @rchardx in #719
• [Testing] Add SFT/GRPO integration test for Megatron train engine. by @nuzant in #726
• [FEAT] VLLM support for VLM training by @HwVanICI in #698
• feat: Support beam_search in vllm backend by @ZiyiTsang in #721
• fix: update multi-turn math test configuration by @rchardx in #727
• fix: fix logic error in beam search support check by @rchardx in #728
• feat: add PPO Critic model support for MegatronEngine by @rchardx in #729
• feat: implement RTensor for metadata transfer in the single-controller mode by @garrett4wade in #731
• fix: fix multi-turn proxy example by @dhh1995 in #733
• minor fix: fix openai cache test, add it in CI test suite, and remove OOD todos/fixmes in Megatron engine by @garrett4wade in #732
• [Feat] XCCL-updates for single LoRA functionality for ascend-vLLM by @gursimar in #679
• fix: use group_size=1 for eval in proxy examples by @dhh1995 in #737
• feat: add ignore_eos and skip_special_tokens generation params by @rchardx in #738
• chore: update datasets to version 3.0.0 or higher for inner API compatibility by @ZiyiTsang in #720
• feat: build the docker image with math-verify and the latest ruff by @garrett4wade in #744
• bump v0.5.1 by @garrett4wade in #745

New Contributors

• @HsiaoTsan made their first contribution in #653
• @aaaandychen made their first contribution in #658
• @gursimar made their first contribution in #679

Full Changelog: v0.5.0...v0.5.1

v0.5.0

Highlights

The newly released v0.5.0 of AReaL introduces two core innovations: Seamless Agentic RL and the Single Controller architecture:

• Seamless Agentic RL: AReaL provides a seamless intelligent agent training service via OpenAI-compatible APIs. This facilitates seamless collaboration among environment providers, algorithm developers, and system engineers, forming a zero-friction pipeline in complex engineering workflows and significantly boosting development efficiency and system maintainability.

• Single Controller Architecture: Eliminates long-tail latency and data imbalance issues inherent in SPMD (Single Program, Multiple Data) models. This layered design enhances inference scalability, enables fine-grained system-level control, and preserves algorithmic flexibility while minimizing code migration costs for algorithm developers.

Other changes include:

• Performance & Scalability: Major refactoring to streamline step detection, assignment logic, and workflow batching. Improved distributed training with fixes for NCCL timeouts, Gloo group barriers, and vocab-parallel logprobs for FSDP.

• Model & Hardware Support: Added single LoRA functionality for Ascend-vLLM and improved handling for Vision-Language Models (VLMs).

• Fixes & Refinements: Resolved numerous bugs related to data loading, reward timeouts, interaction caching, process cleanup, and tool call parsing. Significant code refactoring to merge duplicate logic, improve type hints, and centralize asset management. Project-wide code formatting switch to ruff.

Future Work

AReaL currently supports the basic Single Controller mode and Agentic RL training pipeline. Future enhancements include:

• Optimized data flow and distributed launch capabilities under Single Controller mode;
• Automatic scaling, fault recovery, and high-availability training;
• Improved training-inference performance in agent-centric scenarios.

What's Changed

• update readme for qwen3-vl by @garrett4wade in #578
• [FIX] add recipe directory to pre-commit checks by @fishcrap in #580
• [FIX] reduce reward timeout warning by @fishcrap in #579
• [FIX] fix compute logp temperature by @fishcrap in #581
• feat: rebuild step detection around global batches by @rchardx in #583
• chore: extend wait timeout and hardens config checks by @rchardx in #585
• feat: streamline step assignment logic by @rchardx in #584
• fix: Use background threads to commit tasks and fetch results in workflow executor by @garrett4wade in #587
• fix: reuse aiohttp.ClientSession in agenerate by @garrett4wade in #589
• chore: automates session tracing context by @rchardx in #591
• [feat] add Serializer for rpc server by @CormickKneey in #566
• doc: improve tracer documentation with custom phase support and improved plotting by @rchardx in #594
• [feature] Support concat export completions in proxy mode by @yulangz in #582
• Fix trainer to use backend information from allocation mode by @dhh1995 in #596
• fix: fix the stucking issue of rollout_batch by @garrett4wade in #595
• fix: extends NCCL group timeout coverage by @rchardx in #598
• chore: use typevar to type hint loaded config by @dhh1995 in #603
• fix: safely close all ClientSessions with ContextVar by @garrett4wade in #605
• chore: remove requirements.txt by @garrett4wade in #604
• [Feat] Add train/rollout offload support by @fishcrap in #590
• [FIx] Use gloo group barriers for distributed synchronization by @fishcrap in #607
• feat: adds scheduled profiler tracing by @rchardx in #608
• refactor: let WorkflowExecutor.wait return a list with None by @garrett4wade in #612
• [feat] add local scheduler for single controller mode by @daihaowz in #610
• refactor: separate BatchTaskDispatcher from WorkflowExecutor by @garrett4wade in #613
• chore: upload paper to the repo by @garrett4wade in #616
• chore: clarifies agent onboarding guide by @rchardx in #617
• refactor: improves async coordination by @rchardx in #618
• [FIX] fix enable_offload break change and add offload/onload API by @fishcrap in #625
• refact: update gconfig to update stop token ids in workflows instead of in example scripts by @dhh1995 in #626
• chore: improve workflow batching safeguards by @rchardx in #624
• chore: ensures worker threads exit cleanly by @rchardx in #630
• bug fix: correctly shuffling data with distributed sampler by @garrett4wade in #632
• rename CompletionCache to InteractionCache by @dhh1995 in #631
• refactor: merge base_hf_engine with fsdp_engine for code cleanup by @garrett4wade in #629
• chore: format all files under areal/utils with ruff by @garrett4wade in #635
• chore: format all tests with ruff by @garrett4wade in #636
• chore: format remaining files under areal/ with ruff by @garrett4wade in #637
• ci: update ci formatter to ruff by @garrett4wade in #638
• chore: tunes NCCL IB settings by @rchardx in #640
• [feat] implement train controller for single controller by @daihaowz in #614
• fix: modify the default value of "shuffle" and "drop_last" for validation datasets by @garrett4wade in #633
• [Feat] Single LoRA functionality for ascend-vLLM by @HwVanICI in #621
• fix: prevent zombie vLLM processes when Ray launcher kills tasks by @zhshgmail in #623
• refactor: add export_stats as engine's method by @garrett4wade in #643
• [feat] impl rollout controller for single controller by @dingzhiqiang in #611
• feat: implement proximal log-probability approximation for decoupled PPO by @zhshgmail in #600
• fix: fixes CLI docs import order by @rchardx in #646
• refactor: refines PPO/GRPO loss by @rchardx in #650
• refactor: merge duplicate process termination functions into unified kill_process_tree by @garrett4wade in #648
• feat: simplify openAI agent integration and allow training with any customized agent by @garrett4wade in #657
• fix: tear down local inference servers when caling destroy by @garrett4wade in #659
• fix: vlm input slicing by @HwVanICI in #651
• refactor: move logprob and value computation into TrainEngine by @rchardx in #663
• fix: fix drop last for data loader with distributed sampler by @dhh1995 in #665
• [FIX] Initialize llm_addrs in Slurm launcher for SFT jobs by @fishcrap in #662
• refactor: apply PPOTrainer and SFTTrainer in example scripts by @garrett4wade in #660
• feature: implement vocab-parallel logprobs for FSDP by @rchardx in #667
• refact: expose workflow executor in inference engine by @dhh1995 in #676
• fix: raise AttributeError instead of returning None in Platform.getattr by @rchardx in #672
• fix: add missing device_control_env_var to CpuPlatform by @rchardx in #681
• fix: override workflow_executor property in MockInferenceEngine by @rchardx in #682
• refactor: make processing multi_modal_input generic by @HwVanICI in #678
• refactor: refactor attention mask generation logic for clarity by @rchardx in #685
• [Feat] Implement GRPO trainer and weight exchange for single-controller mode by @dingzhiqiang in #666
• refact: rename set_final_reward to set_last_reward, also fix openai gen args by excluding lora_name by @dhh1995 in #675
• fix: fix CPU offloading in FSDP grad clipping and weight updates by @rchardx in https://github.com/inclus...

v0.4.1

What's Changed

• feat: add raise_timeout parameter to allow quiet waiting for inference results by @garrett4wade in #547
• Fix batch size in example examples/vlm/clevr_count_70k_grpo.yaml by @wangruohui in #549
• chore: format dataset and reward folders with ruff by @garrett4wade in #551
• refactor: rename the should_accept argument in rollout/prepare_batch to should_accept_fn by @garrett4wade in #555
• chore: delete not-planned experimental features by @garrett4wade in #554
• feat: add grpo trainer and simplify gsm8k grpo example by @dhh1995 in #552
• feat: add launch_server and teardown_server in inference engine api by @garrett4wade in #550
• [Refactor] refactor stats_tracker usage in engines and examples by @nuzant in #556
• refactor: allow passing string paths and init kwargs as rollout workflows by @garrett4wade in #525
• feat: introduces session-centric tracing APIs by @rchardx in #539
• doc: Add notes about asynchronous RL training by @garrett4wade in #558
• format: ruff format examples directory by @fishcrap in #559
• feat: support proxy server and client for training openai-compatible agents by @dhh1995 in #500
• chore: change type annotations and minor fixes for single-controller mode by @garrett4wade in #560
• docs: add "Performance Profiling" guide to best practices by @rchardx in #538
• add README for proxy_agent by @yulangz in #561
• chore: extends engine perf instrumentation by @rchardx in #562
• [FEAT] add pause/resume generation for vLLM server by @fishcrap in #563
• doc: update AReaL design doc with the current dev status by @garrett4wade in #568
• doc: update documentation to align the current dev status by @garrett4wade in #570
• refactor: extend allocation mode to support allocation naming and composition by @garrett4wade in #565
• feat: align perf_tracer with task hierarchy by @rchardx in #569
• chore: add hint for the breaking change of allocation mode by @garrett4wade in #572
• [FIX] fix atrace_session_phase in workflow by @fishcrap in #573
• chore: Quick fix for GSPO missing in doc by @ZiyiTsang in #576
• ci: build docker images with GCP by @garrett4wade in #564
• refactor: restrict the usage scope of the rollout_batch method by @garrett4wade in #567
• chore: add issue template for questsions by @garrett4wade in #571
• ci: automatically tag the dev image upon new releases by @garrett4wade in #574
• chore: remove the old script used for validating installation by @garrett4wade in #575
• [FEAT] Add Qwen3-VL model support for fsdp by @fishcrap in #557
• bump v0.4.1 by @garrett4wade in #577

New Contributors

• @wangruohui made their first contribution in #549

Full Changelog: v0.4.0...v0.4.1