agentic-rl
Agentic RL 中文零基础教程（33 章）：从概念到 GRPO 实战，含 TRL 最小可跑示例；26–33 章附一套可运行的三方判别模型实证工程（encoder vs LLM-LoRA vs 规则基线）。第 25 章讲清 Jev / TypeSafe System One 与 RL 的能力边界 | Chinese Agentic RL tutorial (33 chapters) + a reproducible discriminative-model benchmark
139 ★ on GitHub
What it is
面向小白的 Agentic RL（智能体强化学习）系统教程 — 33 篇中文 Markdown + 两套可运行工程： TRL 最小示例（minimal-verl/）与判别模型三方对照实证（minimal-decision-bench/）。 搜「Agentic RL 教程」「GRPO 入门」「LLM 强化学习」「verl TRL 实战」「Jev 与 RL 的边界」「System One 判别模型」「判别能力外置」都能找到这里。
Where the decision sits
agentic-rl runs its own weights or its own runtime rather than calling a hosted API, so its decisions do not depend on a vendor being up or on a key being funded. The trade is that the model is now yours to keep current.
How active it is
Created 2026-06-03, last pushed 2026-10-26, 139 stars and 13 forks when we read it on 2026-11-02. Everything in this category is weeks old at most, so a stale push date means something different here than it would on a mature project. Check the repository before you depend on it.
Find out what your data actually supports
We turn your historical decisions into a frozen test set, then tell you which model, which threshold, and how much of it you can safely automate.