`_module_registers_tools()` reads each `tools/*.py` file and fully
AST-parses it to check for a top-level `registry.register()` call.
90 files are scanned on every process start — but only 32 actually
register tools.
Add a cheap text prefilter: after reading the file (which we need to
do anyway for AST), check that both `"registry"` and `"register"`
appear in the source before calling `ast.parse`. A file with a
top-level `registry.register()` call must contain both strings, so
this is a perfect superset — zero false negatives. 50 of 90 files
skip the AST parse entirely.
The `source=` parameter is not threaded through `discover_builtin_tools`;
the prefilter lives entirely inside `_module_registers_tools`, keeping
the public API unchanged.
Benchmark (median of 10 runs, scanning 90 files):
before (read + ast.parse all): 305.9ms
after (text prefilter + ast): 187.8ms
speedup: 1.6x (118ms saved)
Identical module set: 32 modules, same names, same order.
The _PROVIDER_PREFIXES frozenset in agent/model_metadata.py is static
and does not auto-extend from ProviderProfile. Removing deepinfra and
deep-infra from it broke provider:model prefix stripping for DeepInfra.
Preserve one durable staged input across terminal close and the worker's early turn flush, without duplicating resumed transcripts or creating a session with a null prompt. Fixes#63766.
Retain a distinct CLI history baseline during the signal window before a turn's normal persistence flush. When CLI history aliases the live agent list, use marker-only persistence so a genuinely unflushed tail is written.
Salvage of #63935. The original fix read HERMES_CRON_SESSION_DB_TIMEOUT
from a bare env var, but AGENTS.md requires non-secret behavioral
settings to live in config.yaml with an env var bridge only for
backward compatibility.
Changes:
- Add cron.session_db_timeout_seconds to DEFAULT_CONFIG (default 10s)
- Resolution order: HERMES_CRON_SESSION_DB_TIMEOUT env override →
cron.session_db_timeout_seconds in config.yaml → 10s default
(mirrors the existing script_timeout_seconds pattern)
- 0 = unlimited (opt-in for debugging, skips the bound)
- Strengthen test: assert the warning is logged on invalid env value
(caplog was taken but never asserted)
- Add test: verify config.yaml resolution path works end-to-end
Co-authored-by: LoicHmh <26006141+LoicHmh@users.noreply.github.com>
run_job() constructs SessionDB() synchronously with no timeout of its
own, unlike the agent's run_conversation call further down, which is
already bounded by HERMES_CRON_TIMEOUT. A wedged sqlite3.connect (e.g.
a stale flock from a crashed sibling process) hangs this call
indefinitely.
That hang is invisible to every existing cron safeguard because it
happens before _submit_with_guard's future exists: the finally block
that discards the job ID from _running_job_ids never runs. The job
stays wedged "running" — every later tick logs "already running —
skipping" — until the whole gateway process is restarted.
Observed in production: a cron job's worker thread was confirmed via
a live py-spy thread dump to be parked inside SessionDB.__init__'s
sqlite3.connect for 3+ days, silently skipping every scheduled fire
in between across a gateway process that otherwise stayed healthy.
Bound the SessionDB() construction with its own timeout
(HERMES_CRON_SESSION_DB_TIMEOUT, default 10s), following the same
bounded-thread-pool pattern already used elsewhere in this file (the
delivery retry path, and the agent inactivity watchdog just below).
On timeout, log at ERROR and proceed with session_db=None instead of
degrading silently to debug level, since an actual hang here is a new
condition worth surfacing.
Adds tests/cron/test_sessiondb_init_hang.py, including an end-to-end
regression proving the dispatch guard is released and a subsequent
tick can fire the same job again after a simulated hang.
The Thinking disclosure rendered blank for every reasoning-emitting model
(Fable, DeepSeek, GPT-5.5, ...). Two causes:
1. ReasoningTextPart read a `text` prop that assistant-ui never populates —
reasoning parts arrive via context, same as text parts — so it always got
an empty string. Read the text via useMessagePartReasoning() instead,
mirroring how MarkdownText uses useMessagePartText().
2. The reasoning-only SmoothStreamingText / useSmoothReveal layer stalled at
revealed="": the reasoning part stays isRunning for the whole message while
the answer streams and thrashes re-renders, so the char-reveal never
advanced past 0. Render reasoning through the same DeferStreamingText →
surface path the assistant answer uses, and drop the dead smoothing code.
Baseline bars were positioned at their absolute timeline offset, which
included the baseline run's own wait time — making duration comparisons
hard since the bars were visually offset. Now each baseline bar starts
at the same left position as its corresponding current job, so the two
bars directly overlap for at-a-glance duration comparison.
Also removed the now-unused bl_t0 / bl_max / bl_jobs_timed variables
that tracked the baseline timeline position.
Add wait time computation: for each job, wait_s = started_at - max(completed_at
of all jobs that finished before it started). This is a timestamp heuristic
(no workflow YAML dependency parse needed) that's accurate for pipeline-shaped
CI where the critical path is linear at each stage.
Shows up in:
- Job table: new Wait + Δ Wait columns
- Gantt chart: hatched bar segment before the run bar
- Step details: '(wait Xs)' annotation in the summary line
- Markdown summary: Total wait row with delta vs baseline
- Stats: total_wait / bl_total_wait in compute_stats
Also completes the skipped-jobs UI:
- Skipped stat card in stats cards
- Skipped row in markdown summary table
Backward compatible: old cached baselines without wait_s annotate on load.
Skipped jobs (conclusion == 'skipped') have null/zero-duration timestamps
that polluted every downstream computation: they counted as 'unchanged'
(0 vs 0) in faster/slower tallies, showed meaningless '0.0s (0%)' deltas
in the job table, rendered phantom gantt bars, and inflated wall/compute
totals.
Add is_skipped() helper and apply it consistently:
- compute_stats: exclude from wall/compute + faster/slower/unchanged;
add 'skipped' and 'bl_skipped' counts
- _gantt_bars: filter from current bars, baseline bars, and axis calc
- _job_table: show 'skipped' label instead of durations/deltas
- _step_details: skip entirely (no meaningful step data)
- _regressions: exclude from both current and baseline sides
alelpoan's fix (emit hermes:zoom:changed after restore) is correct, but the
bug's root is duplication: setAndPersistZoomLevel and restorePersistedZoomLevel
each independently did setZoomLevel + send, and restore forgot the send.
Collapse both (and the lifecycle re-assert) into a single applyZoomLevel()
helper in zoom.ts that always applies-then-notifies — the regression can't
recur by omitting a send. Replace the source-grep test (which broke on main:
the sibling source-assertion pet test it copied was refactored to a behavioral
one, dropping the fs/path imports it relied on) with behavioral coverage of the
funnel, matching zoom.ts's "unit-testable without booting a BrowserWindow"
convention.
Co-authored-by: alelpoan <alelpoan@proton.me>
classifyNativeBinary only checked big-endian Mach-O/Fat magic bytes
(feedfacf, feedface, cafebabe). Real Darwin .node files from node-pty
prebuilds are stored little-endian on disk (cffaedfe = MH_CIGAM_64),
so every Darwin prebuild classified as null, and validateStagedBinaries
threw a platform mismatch on macOS — breaking npm run check for every
macOS contributor. CI didn't catch it because runners are Linux (ELF
path was correct) and tests only planted big-endian fake headers.
Add recognition for all six Mach-O/Fat byte orderings:
- MH_CIGAM (cefaedfe) — LE 32-bit
- MH_CIGAM_64 (cffaedfe) — LE 64-bit [the one real prebuilds use]
- FAT_CIGAM (bebafeca) — LE universal
Update makeFakeNode to write LE CIGAM_64 bytes for the darwin fixture
(matching real on-disk format) and add regression tests for all new
magic forms.
