Zeno

Verifiable RL rewards for LLMs that actually make sense.

Why Zeno?

• Provides verifiable, interpretable reward functions for finetuning LLMs, especially for code, and soon, other domains.
• Keeps all rewards transparent and hackable.
• No secret sauce. No LLM-as-a-judge. No magical "alignment". Just actual auditable rules.

If you care about trusting your rewards, and being able to debug them, start with Zeno.

Installation

git clone https://github.com/think-a-tron/zeno.git
cd zeno
uv add ./zeno

What do you get?

Zeno ships with a set of plug-and-play reward functions for Python code completions for now. All rewards are stateless, verifiable, and don't require extra config or setup.

Reward	What it rewards or penalizes	Score Range
reward_docstrings	Proportion of functions/classes with docstrings	0.0 to 1.0
reward_lint	Fewer lint errors (via ruff), normalized per line	0.0 to 1.0
reward_direct_recursion	Presence/absence of direct recursion (configurable)	1.0 / 0.0 / -1.0
reward_list_comprehension	Use (or avoidance) of list comprehensions	1.0 / 0.0 / -1.0
reward_type_hints	Fraction of args/returns with type hints	0.0 to 1.0
reward_exception_handling	Has at least one try/except (reward) or none (penalize)	1.0 / -1.0
reward_functional	Prefers functional (no class) over OOP style	1.0 / -1.0

Usage with trl

You can plug them directly into trl as your reward function.

from trl import GRPOTrainer
from zeno.code.python import reward_lint

trainer = GRPOTrainer(
    model="Qwen/Qwen3-0.6B",
    reward_funcs=[reward_lint],
)

Contributing

Want to add more rewards? PRs welcome, but keep it verifiable and explainable. No black-box models.

Roadmap

• Stepwise rewards for math reasoning.
• Multi turn rewards for tool use.

License

MIT