uv sync                                    # slim
uv sync --group dev                        # + pytest, ruff, pre-commit
uv sync --all-extras                       # + extras (flash-attn, flash-attn-cute, …)
uv sync --all-extras --all-packages        # + all env packages (needed to train on them)
uv sync --package prime-rl --package gsm8k  # core + just one env

uv sync --group dev installs the pre-commit package but leaves the git hook inert until it's wired up — run uv run pre-commit install once per clone (see README.md's Development section).

Environment packages are uv workspace members. Those under deps/prime-envs/environments/*/* are auto-discovered — adding a new env there needs no pyproject.toml change. verifiers' example envs are enumerated explicitly in [tool.uv.workspace].members (only the ones prime-rl trains or tests on) — to use another, add its path to the list. Members are opt-in: a plain uv sync / --all-extras does not install them (and would remove them if already present — re-run with --all-packages, or --inexact to keep them). Install all with --all-packages, or a subset with repeated --package <env> (include --package prime-rl to keep the core). If two envs pin conflicting transitive versions (all members share one lock), add the loser to [tool.uv.workspace].exclude.

When bumping a package past the workspace-wide exclude-newer = "7 days" window, add it (and any newly-required transitives) to [tool.uv.exclude-newer-package] before refreshing uv.lock.

Optional extras

CUDA kernels

Prebuilt wheels, pinned at a release in [tool.uv.sources]:

uv sync --extra kernels

No plain sync compiles CUDA — building from source stays an explicit, manual step (needs nvcc whose CUDA major matches torch's and the deps/prime-kernels submodule initialized), and overrides the wheel until the next sync:

git submodule update --init deps/prime-kernels
uv pip install --no-build-isolation -e deps/prime-kernels

See the kernels skill.

NemotronH (Mamba SSD kernels)

uv sync --extra gpu

Native NemotronH uses Mamba2 Triton SSD kernels and FLA's packed causal convolution. The pinned mamba-ssm source installs without nvcc; no separate causal-conv1d installation is needed. uv sync --all-extras includes these dependencies.

Trainer DeepEP backend

The disagg extra installs the prebuilt DeepEP wheel pinned in [tool.uv.sources]:

uv sync --extra disagg

The prime-kernels repository owns source builds for DeepEP, DeepGEMM, and TorchAO. Use its scripts when a local rebuild is required:

git submodule update --init deps/prime-kernels
bash deps/prime-kernels/scripts/install_ep_kernels.sh --wheel-dir /tmp/prime-kernels-wheels
uv pip install --reinstall --no-deps /tmp/prime-kernels-wheels/deep_ep-*.whl

The build needs a CUDA toolkit whose version matches torch. Set TORCH_CUDA_ARCH_LIST when the build host has no GPU or when the wheel must support more than the local GPU architecture.

Verify: uv run python -c 'import deep_ep; print(deep_ep.__file__)'.

llm-d router backend

Multi-node / disaggregated deployments can route through the upstream llm-d Endpoint Picker instead of vllm-router (set [inference.router] type = "llm-d"). It needs three native binaries — install once:

bash scripts/install_llmd.sh   # builds epp + pd-sidecar from a pinned llm-d-router commit (vendored Go), fetches envoy

Binaries land in third_party/llmd/bin/{epp,envoy,pd-sidecar} (a shared path, so SLURM nodes see them). epp is pinned to the commit that includes the vllmhttp-parser (PR #1248) so prime-rl's renderer/TITO /inference/v1/generate path routes correctly. Override the pin with LLMD_ROUTER_REF=<sha>. The EPP + Envoy + endpoints configs are rendered from templates/llmd/*.yaml.j2 (included into the SLURM script); only the per-node IPv4 addresses are filled in inline at launch time.

Key files

pyproject.toml — dependencies, extras, dependency groups
uv.lock — pinned lockfile (refresh with uv sync --all-extras)
scripts/install.sh — bootstrap installer
deps/prime-kernels/scripts/ — native wheel build scripts

install

Install

Clone + submodules

Sync