Points the submodule at the vf-nano EnvServer branch so the orchestrator can
build on the env-server abstraction.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

Switch prime-rl's env path to vf-nano: the orchestrator spawns a vf-nano
EnvServer per env (it never loads an environment), dispatches rollouts by task
index, and trains on the returned Trace dicts (branches + renderer tokens).

- pyproject: dep verifiers -> vf-nano; drop v1/research env packages; only the
  vf-nano reverse-text example; override out the transitive v1 verifiers (pulled
  by the prime CLI) so it can't shadow vf-nano's `verifiers` package; add orjson
  /pandas/msgspec (were transitive via verifiers).
- EnvConfig inherits vf-nano's swappable agent/runtime (+ max_turns).
- envs.py: spawn EnvServer child + EnvClient, info() for num_tasks/group-scoring,
  dispatch by task_idx, adapt Trace -> RolloutOutput-shaped dict.
- trajectories.py: trace_to_samples (one sample per Trace branch) + trace_to_output.
- train_source: index sampling; client pool builds vf-nano ClientConfig; lag
  monitor vendored; env-server entrypoint repointed; ~14 files retyped off
  vf.RolloutOutput / vf.ClientConfig.
- configs/debug/vf_nano_reverse_text.toml.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

…er config)

- trace_to_samples stitches each Trace branch's tokens into one TrainingSample
  (prompt = branch start, then each turn's new context [masked] + generated
  tokens [trained]); drop the RolloutOutput adapter — read the Trace's native
  fields directly (reward, error{type,message}, timing generation/scoring,
  num_turns, branches).
- envs returns the raw Trace; eval_sink / train_sink / dispatcher / metrics /
  orchestrator read native Trace fields (no token_usage/completion/timing.total).
- client pool forwards the shared renderers.RendererConfig to the env server's
  renderer client (so it uses qwen3, not the tool-less default fallback).
- debug config: tool_call_parser=hermes (vLLM accepts the agent's tools),
  max_steps=20.
- bump deps/vf-nano.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

…o timeout)

- Env.run_rollout/run_group pass the vf-nano ClientConfig object and a
  SamplingConfig (built from the env's sampling args) directly — no model_dump,
  no per-rollout timeout forwarded to the server.
- debug config: max_steps=20.
- bump deps/vf-nano (typed env-server RPC).

The env server returns a Trace minus its derived fields; the orchestrator resolves
the env's Task subclass (from config.id) and validates the wire dict into a strict
Trace[EnvTask], so the whole orchestrator works with a real, typed vf.Trace —
typed task fields included (e.g. task.answer), nothing subscriptable.

- envs.py: resolve_task_type(env_id); run_rollout/run_group validate -> Trace[EnvTask].
- trajectories/types/dispatcher/train_sink/eval_sink/metrics/filters/advantage/utils
  /orchestrator: attribute access on the typed Trace (reward, error{type,message},
  branches, timing.<span>.duration, num_turns, ...); derived fields recompute on the
  consumer.
- Task/Trace/TimeSpan stay strict (StrictBaseModel) — no extra=ignore anywhere.
- bump deps/vf-nano.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

The orchestrator spawns the env server, so request the serve extra
(zmq/msgpack) explicitly now that vf-nano keeps them out of core.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

`from __future__ import annotations` already defers all annotations to strings,
so the quotes + `# noqa: F821` on the TYPE_CHECKING-only `vf.Trace` / `TrainRollout`
annotations are unnecessary (no import cycle — verifiers.nano never imports prime_rl).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

The field holds a typed vf.Trace, so `trace` reads truer than `raw` (which
suggested an unparsed dict). Renames the field + every `.raw` access, the
`emit_rollout(trace=...)` param/kwarg, the to_dict field filter, and the
dispatcher cancel-path locals.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

- Drop the FinishedRollout proxy properties (error/reward/is_truncated and the
  example_id field); consumers now read r.trace.{reward,is_truncated,task.idx,...}
  directly. The trace is the single source of truth.
- Use vf.Trace.has_error for existence checks instead of `.error is not None`.
- Replace the prime-rl trace_* token-length utils with vf.Trace.{completion_len,
  total_tokens,has_response} (now on the trace); keep trace_to_samples.
- Carry task_idx end-to-end (GroupState.task_idx, env.run_rollout/run_group(task_idx),
  source dict key) instead of the example/example_id dict carrier; identity comes
  off trace.task.idx.
- Mark the local-package env arrangement as a temporary/experimental TODO.
- Move the debug config to configs/debug/nano/reverse_text.toml.
- Bump deps/vf-nano (Trace/Turn accessors).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

- The env server binds tcp://127.0.0.1:0 and reports its concrete address back
  over a queue; the orchestrator connects to that. Removes _get_free_port and its
  TOCTOU race (the OS assigns the port atomically).
- A spawned server has already bound + loaded by the time it reports its address,
  so the untimed info() is enough — only poll wait_for_server_startup for an
  external (config.address) server, which has no spawn handshake.
- Bump deps/vf-nano (port report + Trace/Branch token-length accessors).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

The Task-subclass introspection now lives in vf-nano (vf.task_type); drop the
prime-rl copy and build the typed Trace via vf.Trace[vf.task_type(env_id)]. Bump
deps/vf-nano.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

SFT trains on a teacher served over the chat client, which returns no token ids,
so the trace's turns have tokens=None and trace_to_samples yields nothing. Restore
backfill: for each tokenless turn, render its prompt + assistant response with the
student chat template and split on the longest common prefix to fill TurnTokens
(masks/logprobs come from trace_to_samples). train_sink.process_rollout backfills
when any turn lacks tokens, before building samples.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

drop_group's error_rollout_output calls omitted the required task_idx, so an
off-policy cancel (on_new_version) raised TypeError. Use the group's task_idx
(or -1 when the group is already gone), mirroring handle_completed_rollout.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

- envs.py: EnvClient now returns Trace[WireTask]; upgrade to this env's real Task
  subclass via self.trace_type.model_validate(wire.to_wire()).
- dispatcher.py: drop the error_rollout_output helper — inline the synthetic error
  Trace at each call site using vf.Error's field names (type/message/traceback); the
  task-exception path carries a real traceback, cancels/empty-trajectory carry none.
- Bump deps/vf-nano.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

…nical

- Spawned env servers now route their output (logging + subprocess-runtime output)
  to <output_dir>/logs/envs/<name>.log via a _run_env_server wrapper that redirects
  stdout/stderr and sets up logging in the child. Previously the orchestrator-spawned
  server logged nowhere.
- Debug config: batch_size 16->128, group_size 8->16, eval num_examples 8->128
  (interval=1), matching configs/debug/training_modes/rl.toml.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

The orchestrator already passes a train/eval-split log_dir (.../logs/envs/train,
.../logs/envs/eval), so _spawn must drop the file directly under it
(<log_dir>/<name>.log) rather than re-adding an envs/ subdir — which had buried the
train/eval split under logs/envs/<kind>/envs/<name>.log.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

Instead of the orchestrator sidecar-spawning each env server as an mp child, the
rl launcher now spawns one `env-server` process per env (train + eval), each on a
free port, with output to logs/envs/{kind}/{name}.log and a crash monitor — same
model as inference/trainer. It sets env.address in the orchestrator config so the
orchestrator attaches (its existing external path) instead of spawning. Envs that
already set address (user-managed external server) are left alone; the orchestrator's
mp sidecar stays as the fallback for running `orchestrator` directly.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

Add RLConfig.env_server_base_port (default 5000); the i-th launcher-managed env binds
base_port + i. Drops the get_free_port dependency in the launcher.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

Train envs bind base_port + i; eval envs bind base_port + ENV_SERVER_KIND_STRIDE + i
(stride 1000), so each kind has headroom for many envs without the blocks colliding
(was a single running index — train and eval sat adjacent).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

- env_server entrypoint: intercept vf-nano stdlib logging so the server's own logs
  (EnvServer up, request failures) land in logs/envs/<kind>/<name>.log — previously
  only loguru output was captured, swallowing them.
- envs.py: close the address-handoff mp.Queue after use (no resource_tracker
  leaked-semaphore warning on the sidecar path).
- configs/debug/nano/reverse_text.toml: drop the eval block, mirroring
  examples/reverse_text/rl.toml (train-only smoke; eval path validated separately).
- bump deps/vf-nano (serve/types docstring trim).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

…irectly

The I/O boundary (save_rollouts + monitor sample tables) now dumps the typed
vf.Trace itself (r.trace.model_dump(mode="json")) instead of a Trace+metadata
merge — the on-disk rollout is just the trace.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

vf-nano renamed its rollout-driver abstraction Agent -> Harness. Update the
integration: EnvConfig.agent -> harness (HarnessConfig/DefaultHarnessConfig);
env.run_rollout/run_group spawn forwards harness_config; the env-server entrypoint
passes harness_config/harness_timeout; debug config uses `harness = {...}`. Bump
deps/vf-nano to the renamed branch.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

- v0 configs/rlm_swe/qwen35_4b.toml: restore the train env to r2e and the
  eval env to swebench-verified-quick (as on main), reverting the scaleswe switch
- v1: rename configs/debug/v1/scaleswe.toml -> r2e_gym.toml, point the train env
  at the r2e-gym-v1 taskset, and drop the eval block

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

Apply the edits the prior rename commit missed:
- v0 rlm_swe/qwen35_4b.toml: train -> r2e, eval -> swebench-verified-quick (as on main)
- v1 debug/v1/r2e_gym.toml: taskset -> r2e-gym-v1, eval block removed

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

Env servers spawn their worker pool as fresh `spawn` processes with no logging
handlers (verifiers#1626), so per-rollout logs (rollout start/done, context-exceed
warnings) were silently dropped. Pass `setup_env_server_logging` to verifiers'
`serve_env` as `log_setup`; it runs in the broker and in every worker. A worker
inherits the broker's redirected stdout/stderr, so its logs land in the same
`envs/{train,eval}/<name>.log` as before — no new files or paths.

Bumps deps/verifiers to the worker-logging fix.

Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

Realign the pin onto origin/feat/nano-as-v1 and pick up #1627: the --rich
dashboard's token counts fall back to provider usage when the endpoint returns
no token ids (no more 0/0). The prior pin 3df34ba5 was a pre-rebase #1626
variant; 955b6cdf already contains the equivalent #1626 (env-server worker
logging) plus #1627.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

Picks up the serve_env SIGTERM-teardown fix: pool/in-process env servers no
longer print a spurious KeyboardInterrupt traceback into the env logs on
shutdown.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

Picks up the verifiers floor bump so the renderers offset-tokenizer fix (dev40,
PRs #72/#75) can't be undercut by a pre-fix PyPI resolution. Re-locks uv.lock to
the dev40 specifier.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

Picks up #1628 (reap the whole subprocess tree when a runtime run is cancelled).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

…2774)

* feat(v1): elastic env-server pool (inherit pool config from verifiers)

Companion to verifiers#1629. prime-rl's EnvConfig now extends vf.EnvServerConfig, so
each env inherits the `pool` discriminated union (static{num_workers=4} |
elastic{max_workers=None, multiplex=128}, default elastic) and the orchestrator's env
servers scale workers on demand instead of pre-spawning a fixed `auto` count.

- Drop the per-env / train-group / eval-group `num_workers` fields + the auto-resolution
  (ceil(max_inflight/256)); the elastic pool self-sizes from load.
- envs.py / env_server.py pass `vf.pool_serve_kwargs(env.pool)` to serve_env.
- Bump deps/verifiers to the elastic-pool branch.

Breaking: `num_workers` is replaced by `pool`. Configs set `pool = { type = "elastic",
multiplex = N }` or `{ type = "static", num_workers = N }`; the rlm_swe + r2e debug
configs are migrated.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* fix(v1): back-compat shim mapping legacy num_workers -> pool

EnvConfig forbids extra fields, so configs still setting the removed `num_workers`
would hard-fail. Add a `model_validator(mode="before")` that maps it onto `pool`:
an int -> a fixed `static` pool, `"auto"` -> the default `elastic` pool; an explicit
`pool` always wins. Keeps existing (incl. out-of-tree) configs parsing without edits.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* chore(v1): drop num_workers from rlm_swe + r2e configs (use default elastic pool)

The default `pool` is already elastic (multiplex 128), so an explicit `pool` here was
redundant — just remove the legacy `num_workers` and inherit the default.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

Realign the pin onto origin/feat/nano-as-v1: the prior pin d0c5bc98 was the
unsquashed #1629 feature branch, now squash-merged as f404e97f
(content-identical). Picks up #1629 (static/elastic env-server pool config).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

Picks up #1631 (per-rollout setup timing as a distinct phase) and #1632
(per-call model + runtime retries).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

…_wire validation)

Fixes RunRolloutResponse ValidationError 'trace.timing.setup.duration: Extra
inputs are not permitted' that crashed every rollout (#1636 drops computed
durations from to_wire).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

Picks up #1638 (add --resume for evals: re-run a previous run's
missing/errored rollouts).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

…[WireTask]) (#2781)

* chore(v1): stop importing env modules in the orchestrator

The orchestrator built its per-env trace_type as Rollout[vf.task_type(env_id)] for v1 envs, and
vf.task_type imports the env package just to read its Task subclass for typing the wire trace.
Nothing reads typed env task fields - only task.idx and a full task.model_dump - and WireTask
(extra="allow") preserves those fields (incl. on disk). Always use Rollout[vf.WireTask], so the
orchestrator never imports an env package: the env's type and runtime both live only in the
server process.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* chore(v1): hoist the constant Rollout[WireTask] to a module-level ROLLOUT_TYPE

It no longer varies per env, so it doesn't belong as a per-instance attribute set in
Env.__init__ - lift it to a module constant used directly in run_rollout/run_group.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

…mports (#2792)

Bump deps/verifiers to feat/nano-as-v1 HEAD (8873a740), which includes verifiers#1654 — the v1
interception rework: role-named clients (EvalClient/TrainClient), route-detected wire dialects
(chat/responses/anthropic), 1:1 relay + streaming, reasoning preserved.

Adopt the renamed client config classes in prime_rl/utils/client.py:
OpenAIClientConfig -> EvalClientConfig, RendererClientConfig -> TrainClientConfig.

Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

…ts, #1660)

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

It was only a manual editable install, so `uv sync` pruned it. Add it to the env dependency
group + [tool.uv.sources] (mirroring r2e-gym-v1) so it persists across syncs and is available
out of the box.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

verifiers#1653 (carry mm tensors across the env-server wire) is merged and pinned, so
`MessageNode.multi_modal_data` is no longer `exclude=True` — `model_dump(mode="json")` now
serializes the base64 pixel tensors into `train_rollouts.jsonl` and the wandb sample tables,
bloating every line. They're the training `mm_kwargs` carrier, not part of the rollout
record, so exclude them at the dump boundary (train + eval paths).

Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

Declare the remaining 7 verifiers v1 example tasksets (code-golf, deepwiki,
glossary, swelego, wiki-search, wikispeedia, wordle) as editable deps so uv sync
installs every example, matching the verifiers examples set. chromadb/textarena
were already present via the v0 wiki-search/wordle envs.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

The example harness (examples/harnesses/compact) was missing from prime-rl deps,
so the documented --harness.id compact branching example failed to resolve
(ModuleNotFoundError: harness compact not found). Declare it like the example
tasksets so uv sync installs it.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>