prime-runs

docs/training.md

@@ -384,9 +384,9 @@ Or set it in TOML:
 name = "my-experiment"
 ```
 
-Every 10th step the orchestrator uploads the step's episodes (full conversations with rewards and advantages) to the run's sample viewer.
+The monitor is a thin layer over the [`prime-runs`](https://github.com/PrimeIntellect-ai/prime/tree/main/packages/prime-runs) SDK (installed as `prime-runs[train]`): it registers the run, streams per-step metrics, uploads every 10th step's episodes (full conversations with rewards and advantages) to the run's sample viewer, and closes the run out. A process that exits without finishing is reported as crashed. Uploaded episodes are keyed to the platform run by the SDK; the orchestrator's own run id (the launcher's `PRL_RUN_ID`) stays on W&B and in the local records.
 
-Requires `PRIME_API_KEY` (set via `prime login` or env var) and an allowlisted team. Currently internal-only.
+Requires `PRIME_API_KEY` (`prime login` or the env var) and a team (`PRIME_TEAM_ID`, or the team selected with `prime login`) enabled for external runs. A configured monitor must work: a missing key or a team outside the allowlist fails the launch. `PRIME_RUNS_MODE=disabled` keeps the monitor configured but opens no platform run; `RUN_ID=<id>` attaches to an external run a launcher already created instead of registering a new one. Currently internal-only.
 
 ## Rules of Thumb
 

pyproject.toml

@@ -17,6 +17,7 @@ dependencies = [
     "wandb>=0.26.1",
     "wandb-workspaces>=0.4.3",
     "prime>=0.6.19",
+    "prime-runs[train]>=0.1.0",
     "pyzmq>=27.1.0",
     "aiolimiter>=1.2.1",
     "tenacity>=8.2.0",
@@ -221,6 +222,8 @@ flash_attn_3 = false
 # appear in `uv tree` need to be listed; the resolver ignores entries for
 # packages it never sees.
 prime = false
+prime-runs = false
+prime-traces = false
 prime-sandboxes = false
 prime-tunnel = false
 prime-evals = false