| # Mathematics RL |
|
|
| A mathematics RL environment for **Verifiers v1, Harbor, OpenEnv, NeMo Gym and |
| AgentEnv**, covering all **70 modules** of |
| [`d0rj/mathematics_dataset`](https://huggingface.co/datasets/d0rj/mathematics_dataset). |
| The Verifiers API is provided by pinned `verifiers==0.4.0`. Each episode is one |
| tool-less model response followed by a deterministic exact typed reward in `{0, 1}`. |
| English and Russian use the same scoring rules and separate language splits. |
| See [FRAMEWORKS.md](FRAMEWORKS.md) for the four additional adapters, pinned SDK |
| versions, bounded exports, native servers/clients and AgentEnv episode loops. |
| Install each framework in a separate environment: Verifiers' MCP major version |
| conflicts with the other SDKs. The base package contains only the checker/loader. |
|
|
| ## Installation |
|
|
| Commands below run from the package directory: `cd environments/mathematics_rl` |
| in the source checkout, or `cd mathematics-env/rl` after the Hub download. |
|
|
| Full Verifiers execution requires Linux, macOS or WSL: the pinned upstream runtime |
| imports `fcntl`. The standalone checker and its unit tests also work on Windows. |
| Scoring needs no GPU, Docker, hosted sandbox or paid service. |
|
|
| ```bash |
| uv sync --locked --extra verifiers |
| uv run mathematics-rl catalog |
| uv run mathematics-rl grade \ |
| --module arithmetic__div --question 'Divide 1 by 2.' --reference 1/2 --answer '0.5' |
| ``` |
|
|
| For full integration tests from PowerShell (adjust the checkout path): |
|
|
| ```powershell |
| wsl -d Ubuntu-24.04 -- bash /mnt/d/Projects/mathematics_dataset/scripts/run_rl_tests.sh |
| ``` |
|
|
| The script keeps Linux dependencies in `.venv-wsl`, separately from Windows `.venv`. |
|
|
| ## Evaluation |
|
|
| Use an OpenAI-compatible model endpoint. Configure credentials locally through |
| the environment variable named by `--client.api-key-var`. Do not place credentials |
| in commands, TOML files, dataset cards or traces. Local endpoints may accept `EMPTY`. |
|
|
| ```bash |
| uv run --extra verifiers vf-eval mathematics-rl \ |
| --env.taskset.language ru --env.taskset.mode interpolate \ |
| --env.taskset.modules '["arithmetic__add_or_sub"]' \ |
| --model YOUR_MODEL --client.base-url http://127.0.0.1:8000/v1 \ |
| --client.api-key-var LOCAL_LLM_API_KEY -n 20 --no-push |
| ``` |
|
|
| The default `MathematicsEnv` is one agent with the `null` harness, one model turn |
| and local `subprocess` runtime. It provides no tools. Override the runtime with |
| normal Verifiers configuration when needed. Use `--no-push` for local results; |
| upstream otherwise defaults to uploading completed evaluations to Prime Intellect. |
|
|
| `--env.taskset.mode train` selects only `train-easy`, `train-medium`, `train-hard`. |
| `interpolate` and `extrapolate` are separate evaluation modes. For example, |
| `--env.taskset.categories '["train-hard"]'` selects one difficulty within train; |
| cross-mode categories are rejected. See [MODULES.md](MODULES.md) for all module names. |
|
|
| The pinned dataset revision is `d9f78d0665b3a13dad21c6830b9b358c8a25ae74`. |
| Overriding it requires another full commit hash, never a moving branch. The loader |
| uses lazy streaming with Parquet category/module predicate pushdown. Choose modules |
| for small pilots; the existing 125M rows do not need to be rewritten. |
|
|
| ### Bounded sampling and resume |
|
|
| `-n` bounds consumed tasks. Do not use unbounded `-s` over the whole corpus: the |
| framework's exact shuffle materializes its input. Bound it first: |
|
|
| ```bash |
| uv run --extra verifiers vf-eval mathematics-rl \ |
| --env.taskset.language en --select.include.idx 0:1000 -s -n 20 \ |
| --model YOUR_MODEL --client.base-url http://127.0.0.1:8000/v1 --no-push |
| ``` |
|
|
| Alternatively use `--env.taskset.shuffle-buffer 1000 --env.taskset.seed 42` for |
| a bounded approximate streaming shuffle. Preserve revision, filters, seed and |
| buffer size when resuming. IDs combine source/config, source position and content |
| hash: repeated identical rows have distinct keys, and subsequent CLI selection |
| preserves IDs. Changing source filters can change IDs; `content_hash` supports |
| cross-selection duplicate analysis. |
|
|
| ### Offline sources and reference checks |
|
|
| `--env.taskset.source rows.ndjson` (or `.parquet`) reads the same four string |
| columns locally. A local file may include `language`; otherwise it is inferred |
| from the selected language. On the Hub, language comes from the split name. |
| Local examples are marked `local`, not incorrectly attributed to the Hub revision. |
|
|
| ```bash |
| uv run mathematics-rl self-check \ |
| --source tests/fixtures/generated_ru.ndjson \ |
| --language ru --mode all --limit 0 --require-all-modules --output reference-check.json |
| ``` |
|
|
| This checks reference/verifier compatibility, not independent correctness of |
| every reference. Invalid source references fail loudly instead of becoming model |
| errors. Split separation does not prove that duplicate questions or cross-language |
| mathematical overlap are absent. |
|
|
| ## Reward and RL |
|
|
| [GRADING.md](GRADING.md) specifies extraction, accepted notation, form requirements, |
| resource limits and the named-value comparison convention. References stay in |
| immutable `TaskData` on the evaluator and are not inserted into the solver prompt. |
| Traces include `correct` reward, `accuracy`, `parse_error`, `grading_timeout`, |
| answer kind and grading version. |
|
|
| Use the exported environment with a Verifiers v1-compatible trainer and `mode=train`. |
| The trainer supplies trajectories, tokenization, log-probabilities, grouping and |
| weight updates. This package implements no optimizer and claims no training gain. |
| Keep both evaluation categories out of the training mixture. |
|
|
| ## Tests and publication |
|
|
| To check every framework with its pinned SDK in local Linux containers, run |
| `python integrations/docker/run.py --output /absolute/path/to/new-results`. |
| See [DOCKER.md](DOCKER.md) for requirements, native protocol coverage and logs. |
|
|
| ```bash |
| uv run pytest tests -q |
| uv run ruff check src tests |
| uv build . |
| ``` |
|
|
| See [VALIDATION.md](VALIDATION.md) for evidence and fixture provenance. The repository's |
| `scripts/prepare_hf_release.py` builds an allowlisted, hashed release tree with the |
| corrected card and this package under `rl/`. Preparation and the publisher's default |
| dry run do not modify the Hub. See `publication/README.md` in the source checkout. |
|
|
| Apache-2.0; original generator and source data attributed to DeepMind. |
| See [LICENSE](LICENSE) and [NOTICE](NOTICE). |
|
|
