inclusionAI/AReno v0.0.1

v0.0.1

Repository: inclusionAI/AReno

Tag: v0.0.1

Published: 2026-06-16T03:38:50Z

Prerelease: no

Release notes:

Features

Self-Contained Single-Node RL Training

AReno ships as a single Python package with its own CUDA kernels, tensor-parallel inference engine, and OpenAI-compatible serving — no external training/inference backend to wire together. The RL loop is a short cycle of Trainer calls:

from areno.api import Trainer, ArenoConfig, Areno, SamplingParams, gspo_loss_fn

trainer = Trainer(
world_size=1,
model_path="Qwen/Qwen3-0.6B",
backend_type=Areno,
custom_config=ArenoConfig(tp_size=1),
)
trainer.init()

Or from the CLI:

areno train --ckpt Qwen/Qwen3-0.6B --dataset-path gsm8k:main \
--reward-fn-path examples/math/math_verify_reward.py --algo gspo --tp-size 4

Swap algorithms via --algo: sft, dpo, gspo, grpo, ppo.

Agentic RL with Tool-Calling Trajectories

Built-in support for training agents that call tools and produce multi-turn trajectories. The trainer provides a local OpenAI-compatible proxy during rollout, parses tool calls, logs message-level trajectories, and assigns rewards at token boundaries — no external agent framework needed.

Key design choices:

• Continuous batching: new samples enter as completions finish, maximizing GPU utilization during multi-turn rollout
• Async rollout: separate event loop eliminates GIL contention with the training autograd engine
• Shared tool parser: same parsing logic in training rollout and areno serve, ensuring consistent behavior

OpenAI-Compatible Serving

areno serve provides /v1/chat/completions and /v1/completions with tensor-parallel inference:

areno serve --model-path /path/to/model --tp-size 1 --port 8000

Multi-Model Support

Per-family model adapters for Qwen3, Qwen3.5, LLaMA, Gemma4, Bailing, and MiniCPM-V, registered through areno/models/registry.py. Add a new model family by creating areno/models// — no core changes needed.

PyPI Distribution

Install via pip install areno --no-build-isolation. Automated sdist release workflow publishes from git tags.

Fixes

• Unified reward function contract across all algorithms
• Fixed PPO loss function export missing from public API
• Improved agentic rollout batching and trajectory coalescing
• Fixed CUDA extension build for sdist/metadata-only installs
• Aligned serve sampling defaults with training rollout

Documentation and Examples

• README with installation guide, quick start, and feature highlights
• Developer contributing guide
• CLI and SDK operation guides for training, serving, and agentic rollout
• Agentic rollout examples with rollout sessions

What's Changed

• ci: publish pypi from release tag by @xsuler in 0c476db
• fix: unify reward function contract by @xsuler in 9b46a1e
• docs: update README add acknowledgements and split CLI section by @adohe in 53bd862
• fix: align serve sampling defaults by @xsuler in 1c10882
• feat: share tool parsing in serve by @xsuler in 260c424
• docs: fix agentic rollout examples by @xsuler in dda2ccf
• feat: add agentic trajectories and continuous batching by @xsuler in b745e42
• docs: use rollout session in examples by @xsuler in 1c266c8
• fix: improve agentic rollout batching by @xsuler in f9cb223
• docs: update agentic cli and sdk usage by @xsuler in 53a5c2d
• fix: log agentic message trajectories by @xsuler in 094c840
• feat: improve agentic rollout trajectories by @xsuler in 82b85da
• fix: restore agentic rollout coalesce wait by @xsuler in 5c27fd2
• feat: improve async rollout batching by @xsuler in 30c3064
• feat(agentic): add agentic functionality by @xsuler in 3c71838
• fix: issue and pr template format by @adohe in ebc990f
• chore: add various issue and pr templates by @adohe in 6fb6a32
• chore: update pyproject.toml to add more description and missing dep by @adohe in b47a26a
• chore: enhance git ignore file by @adohe in 1f4756a
• fix(api): add missing ppo loss fn export by @adohe in 07cdc2c
• docs: add developer contributing guide by @adohe in 10f8473
• docs: add operation guides for various agent by @adohe in 8b7ab43
• ci: fix sdist release packaging by @xsuler in 5d9ff5c
• fix(build): skip cuda extensions for sdist metadata by @xsuler in 72cefa0
• docs: add README.md and LICENSE file by @adohe in f2b487c
• ci: add pypi sdist release workflow by @xsuler in 9e002b3

Full Changelog: 3447d53...0c476db