Profile clones and hand-written minimal configs carry no _config_version
key; check_config_version() coerces that to 0, which wrongly tripped the
v12 floor and left clones unstamped (caught by CI:
test_clone_config_copies_files / test_clone_from_named_profile).
Version-less configs now take the normal ladder + fresh stamp — the
historical behavior; only genuinely ancient explicit-version configs
are refused.
Companion to the no-mutate fix: normalized['models'] retained a
reference to the caller's (possibly cached) models dict, and the
normalized entry escapes into long-lived runtime state
(agent._custom_providers). Shallow-copy so runtime writes can never
reach the shared config cache.
The normalizer writes alias keys into the entry it is given
(entry['key_env'] = entry['api_key_env'] and entry[snake] =
entry[camel]) while building its normalized copy. Two of its three
callers — get_compatible_custom_providers and
providers_dict_to_custom_providers — pass live sub-dicts straight
from load_config_readonly()'s shared cache (only
_custom_provider_entry_to_provider_config defends with dict(entry)).
A config written with the documented camelCase / api_key_env aliases
therefore gets its cached copy polluted with injected duplicate keys,
violating the cache's explicit no-mutation contract; every later
load_config() deepcopy inherits the duplicates, and any
save_config(load_config()) flow (setup wizard, dashboard writes,
model persist) writes them back to config.yaml. The aux-client TLS
resolution runs this on every auxiliary client build, so the
mutation also happens unlocked on worker threads against a shared
object.
Shallow-copy the entry up front; the function's return value is a
separately-built dict, so behavior is otherwise unchanged.
Four hot-path consumers paid a full config deepcopy per read:
- telemetry gate relay_shared_metrics.enabled() — runs 2-3x per agent
turn (2x per API call from lifecycle hooks + 1x per tool call) and
called read_raw_config(), which deepcopies the whole raw config every
call. New read_raw_config_readonly() serves the cached dict directly:
248 us -> 4.6 us per call (54x) on Teknium's real 77-key config.
- interruptible_streaming_api_call local-endpoint stale-timeout branch
called load_config() once per API call for every local-model user.
- gateway get_inbound_media_max_bytes() + _get_ephemeral_system_ttl_default()
called load_config() on per-message paths. All three switched to
load_config_readonly() (345 us -> 12 us; PR #28866 lineage).
Together these account for ~90% of the ~1,900 deepcopy primitives per
turn measured in the 26-call stubbed-LLM profile.
read_raw_config_readonly() keeps the (mtime_ns, size) freshness key so
config edits are picked up next call, and preserves the identity
invariant (cache-miss returns the same object later hits serve) —
regression-tested with 'is', per the PR #28866 identity-bug lesson.
The mutable read_raw_config() is unchanged for save-path callers.
581 targeted tests green (config, relay metrics x2, ephemeral reply,
platform base, new readonly suite).
The disease: ~15 scattered raw yaml.safe_load(config.yaml) reads that
silently miss managed-scope overlay, ${ENV_VAR} expansion, profile-aware
pathing, and root-model normalization. Every new config feature needed an
N-site sweep (incident chain 9cbcc0c9c8 → 732293cf87 → b0e47a98f9 →
1928aa0443). This commit assigns every raw read to an owner and adds a
lint-guard test so the class cannot regrow.
New primitive (additive-only change to hermes_cli/config.py):
read_user_config_raw(path=None) — reads the user file EXACTLY as
written; docstring states it is ONLY legal for write-back round-trips
and raw-file diagnostics. Behavioral reads must use
load_config()/load_config_readonly().
BEHAVIOR FIXES (class-a sites migrated to a canonical loader — these
previously read values that could DIFFER from the effective config):
gateway/run.py _try_resolve_fallback_provider → _load_gateway_runtime_config
keys: fallback_providers/fallback_model (provider, model, base_url,
api_key). Drift fixed: a managed-pinned fallback chain was ignored;
an api_key of "${OPENROUTER_API_KEY}" reached the resolver unexpanded.
gateway/run.py GatewayRunner._load_provider_routing → same loader
key: provider_routing. Drift fixed: managed-pinned routing prefs and
${VAR} templates were ignored.
gateway/run.py GatewayRunner._load_fallback_model → same loader
keys: fallback chain. Same drift as above.
gateway/run.py GatewayRunner._refresh_fallback_model
keeps the raw primitive (its last-known-good-on-parse-failure contract
forbids the fail-open loader, which returns {} on a torn write) but now
applies managed overlay + env expansion inline. Drift fixed: chain
edits under managed scope / env templates were previously frozen out.
tui_gateway/server.py _load_cfg (72 behavioral call sites)
now = raw read + managed overlay (pre-existing) + NEW ${VAR} expansion,
split from a new _load_cfg_raw() write-back primitive. Drift fixed:
e.g. custom_prompt: "hello ${VAR}", agent.system_prompt, model,
api_key/base_url templates reached sessions unexpanded. DEFAULT_CONFIG
is deliberately NOT merged (callers treat missing keys as unset;
`_load_cfg() == {}` sentinels and _save_cfg round-trips depend on it).
tui_gateway/server.py _profile_configured_cwd
keys: terminal.cwd of a NON-launch profile. Drift fixed: managed
overlay + ${VAR} expansion now apply (load_config() would resolve the
wrong profile's home, so the raw primitive + inline pipeline is used).
plugins/platforms/telegram/adapter.py _reload_dm_topics_from_config
→ load_config_readonly(). keys: platforms.telegram.extra.dm_topics.
Drift fixed: managed overlay + profile-aware pathing + expansion.
plugins/memory/holographic _load_plugin_config → load_config_readonly().
keys: plugins.hermes-memory-store.*. Same drift class.
WRITE-BACK ROUND-TRIPS (class-b: stay raw BY DESIGN via read_user_config_raw;
merging defaults/overlay would pollute the saved user file):
gateway/slash_commands.py: model persist x2, _save_gateway_config_key,
memory/skills write_approval toggles
gateway/platforms/yuanbao.py auto-sethome
tui_gateway/server.py _write_config_key + all cfg→_save_cfg blocks
(reasoning show/hide/full/clamp, details_mode[.section], prompt)
→ new _load_cfg_raw()
plugins/memory/holographic save_config
RAW-FILE DIAGNOSTICS + presence-sensitive bridges (class-c: stay raw,
now via the shared primitive with an explanatory comment):
hermes_cli/doctor.py x5 (model validation, stale-root-keys, .env drift,
deprecation sweep, memory-provider probe — the latter two keep their
inline managed overlay where they had one)
gateway/run.py _bridge_max_turns_from_config and the module-level
TERMINAL_*/HERMES_* env bridge (bridging merged defaults would export
all of DEFAULT_CONFIG into the environment; both keep their inline
overlay + expansion)
hermes_cli/send_cmd.py env bridge (same presence-sensitivity)
hermes_cli/gateway.py multiplex-conflict probe (reads the DEFAULT root's
config, not the active profile's — load_config is the wrong owner)
hermes_cli/profiles.py / hermes_cli/web_server.py / tools/wake_word.py
multi-profile reads (load_config targets only the ACTIVE profile home)
cron/jobs.py _resolve_default_model_snapshot and cron/scheduler.py
run_job config read keep their existing inline overlay+expansion but
now share the primitive (their fail-open + last-value semantics and
the deliberate no-defaults merge are preserved exactly).
Failure-semantics audit: every migrated site preserves its exact previous
behavior on missing file ({} / early return) and parse failure (raise into
the caller's existing except, warn, last-known-good, or fail-open) —
read_user_config_raw intentionally mirrors bare open()+safe_load semantics
(raises on parse errors, {} only on FileNotFoundError/non-dict root).
Guard: tests/hermes_cli/test_config_read_guard.py scans the tree for
yaml.safe_load within 6 lines of a 'config.yaml' reference outside an
explicit ALLOWLIST (hermes_cli/config.py, gateway/config.py, gateway/run.py
fallback path, hermes_cli/managed_scope.py which reads the MANAGED file,
gateway/readiness.py parse-health probe) and fails on new offenders.
E2E: tests/hermes_cli/test_config_loader_e2e.py runs a subprocess with a
temp HERMES_HOME (config.yaml containing ${E2E_PROMPT_SUFFIX}) plus a
HERMES_MANAGED_DIR overlay pinning agent.reasoning_effort, asserting
tui _load_cfg resolves "hello world"/"high" while _load_cfg_raw +
_save_cfg round-trip the template and user value verbatim with no
managed/default leakage.
Premise check on live main: barge-in machinery EXISTS for the per-turn
STREAMING pipeline only — cli.py chat() arms _voice_barge_in_monitor and
tui_gateway _tts_stream_begin arms _tts_stream_barge_in_monitor. What was
actually broken for spoken interruptions:
1. CLI whole-file fallback (_voice_speak_response_async — used whenever
streaming TTS cannot start: sounddevice missing, requirement probe
fails): NO monitor was ever armed, so talking over the reply did
nothing. Now arms _voice_barge_in_monitor in continuous voice mode.
2. Gateway fallback speak (tts_queue None → speak_text thread) and the
voice.tts RPC (desktop-triggered speech): speak_text ran bare, and
its internal streaming dispatch created a PRIVATE stop event nothing
could reach — uninterruptible even by stop_playback(). New
_speak_text_with_barge() runs the same barge monitor beside the speak
thread; hermes_cli.voice.speak_text/_speak_text_streaming accept an
external stop_event so a barge cuts the streaming pipeline too.
Stop-phrase handling and voice.transcript submission are inherited
from the shared monitor (merged #73933 behavior preserved).
3. False barge during TTS (the reason interruption "worked" then
self-cancelled or fired randomly): salvaged PR #71083 by @beardedeagle
(previous commit, kept authorship) — rolling-window VAD floor, 8x
multiplier, 4000-RMS trigger ceiling, barge_in_grace_seconds (2s)
before the mic opens, min-floor clamp. barge_in_grace_seconds is now
documented in DEFAULT_CONFIG.
Desktop spoken barge (renderer mic via voice-barge-in.ts) already covers
both its live-stream and fallback speech paths — verified, no change.
Long thinking/tool stretches in a voice conversation are dead air — the
user cannot tell whether the agent is alive. New: quiet, repeating soft
bubble blips while the agent works and no speech audio is flowing.
- tools/voice_mode.py: numpy-synthesized blips (no binary assets) — two
alternating low pitches (G4/E4) with pitch glide + smooth attack/decay
envelopes, ~0.8-1.2s randomized spacing, volume = voice.beep_volume * 0.5.
start_thinking_sound(should_play=...) / stop_thinking_sound() daemon-loop
lifecycle; macOS-TCC-safe (sounddevice output gated there → silent skip,
no per-second afplay churn). New mark_audio_output_active()/
is_audio_output_active() ref-count wraps play_audio_file and the
streaming OutputStream sentence writes so "audio is flowing" is accurate.
- Config: voice.thinking_sound (default true) off-switch.
- cli.py: starts when a voice-mode turn begins, per-blip gate skips while
TTS speaks / mic records / barge capture owns the mic; stopped in the
chat() finally on every exit path.
- tui_gateway/server.py: same lifecycle around _run_prompt_submit turns
(voice mode on), gated on is_audio_output_active + continuous capture.
- Desktop: renderer owns voice-conversation audio, so a matching WebAudio
implementation (src/lib/thinking-sound.ts, same envelope/pitches) runs
while conversation status === "thinking"; honors voice.thinking_sound
(via config store) and the shared sound-mute toggle; stops instantly on
speaking/listening/end.
Follow-ups on top of @DonutsDelivery's salvaged reaper commit (#64141):
- create_from_config() now parses lsp.idle_timeout (invalid values fall
back to DEFAULT_IDLE_TIMEOUT) — previously the constructor knob was
unreachable from config.yaml (config exposure adapted from #36892 by
@0xbWy and #68091 by @9miya20)
- canonical default declared in hermes_cli DEFAULT_CONFIG so config
discovery surfaces the knob (per sweeper review note on #64980)
- reaper loop survives transient sweep errors instead of dying and
silently re-opening the leak (gap flagged in #68091 review)
- eventlog.log_reaped(): one INFO line per sweep + clears the
log_active announce cache so respawns re-announce at INFO
- docs: replace the stale 'no idle-timeout reaper' paragraph with the
new lifecycle description + config reference
- tests: reuse-refresh protection (the regression teknium's sweeper
requested on #64141), reaper-survives-error, config propagation,
invalid-value fallback, DEFAULT_CONFIG/manager-constant sync
Local faster-whisper called model.transcribe with bare {'beam_size': 5}:
no VAD, cross-window conditioning on, no confidence filtering. Pure
silence produced hallucinated tokens (E2E: 5s anullsrc WAV -> 'You',
no_speech_prob=0.705) and noisy clips could produce runs of junk, often
in other languages.
Three-layer class fix, one shared owner for every local-whisper call
site (build_local_transcribe_kwargs):
1. Silero VAD filter (bundled with faster-whisper) on by default —
silence never reaches the model. stt.local.vad: false restores the
raw behavior for music/ambient transcription.
stt.local.vad_min_silence_ms tunes chunk splitting (default 500).
2. condition_on_previous_text=False — one hallucinated token can no
longer seed a self-reinforcing run; negligible cost for
voice-note-length audio.
3. Segment confidence gate (_join_confident_segments): drop a segment
only when no_speech_prob > 0.6 AND avg_logprob < -1.0 (openai-whisper's
own heuristic shape; both must hit so quiet-but-real speech survives).
Config: stt.local.no_speech_prob_threshold / logprob_threshold.
The WHISPER_HALLUCINATIONS blocklist in voice_mode.py stays as
last-resort defense but should now almost never fire.
E2E (real faster-whisper 'base', CPU int8):
silence.wav before 'You' -> after ''
noise.wav before '' -> after ''
speech.wav before/after 'Hello World, this is a test of the
transcription system.' (unchanged)
Docs (EN + zh-Hans), DEFAULT_CONFIG, cli-config.yaml.example updated;
19 unit tests (kwargs contract, off-switch, confidence gate incl.
quiet-speech survival, _transcribe_local wiring), sabotage-verified.
Adds gpt-transcribe (OpenAI's new file-transcription model, $0.0045/min)
to the OpenAI STT provider:
- OPENAI_MODELS set: gpt-transcribe is recognized so provider
auto-correction keeps it on OpenAI and rejects it on Groq
- Language hint wiring: gpt-transcribe replaces the singular
'language' field with a 'languages' list; the API rejects the legacy
field, so the hint is sent via extra_body {languages: [..]}
- Config comment (DEFAULT_CONFIG), cli-config.yaml.example, desktop
settings enum, and docs (en + zh-Hans) updated
- Tests: model pass-through, languages-list hint shape, legacy singular
hint preserved for gpt-4o-transcribe, Groq auto-correction
gpt-live-transcribe (realtime WebSocket, $0.017/min) is NOT wired here:
the file-based STT pipeline has no realtime session path; it belongs in
a future realtime/voice-mode integration.
Local/self-updated macOS builds were finished with a plain
'codesign --force --deep --sign -', leaving a cdhash-only Designated
Requirement and stripping electron-builder's entitlements. Every rebuild
changes the cdhash, so TCC treats the new bundle as different code and
forgets Full Disk Access, Desktop/Downloads/Documents, Accessibility,
Automation, and microphone grants — users re-approve everything after
every update.
Rework the relaunch fixup to sign inside-out (standalone Mach-O
binaries, nested frameworks/helpers, then the main bundle), preserving
the repo's entitlement plists, and pin an identifier-based Designated
Requirement when signing ad-hoc so TCC has a stable identity to persist.
Opt-in desktop.macos_signing_identity names a persistent keychain cert
(self-signed Code Signing cert works — no Apple Developer account) for a
certificate-anchored DR, the strongest form. An intact Developer ID
signature is detected and never clobbered, callers can pass the
publisher-signing decision explicitly so a later dotenv load can't flip
it, and the legacy deep ad-hoc sign remains the last-resort fallback.
Co-authored-by: lewis4x4 <lewis4x4@users.noreply.github.com>
Co-authored-by: natebransc <natebransc@users.noreply.github.com>
Co-authored-by: caseyanthony <caseyanthony@users.noreply.github.com>
Co-authored-by: gvago <gvago@users.noreply.github.com>
Co-authored-by: twe-cloud <twe-cloud@users.noreply.github.com>
* Revert "fix(credits): remove the 'Grant spent · $X top-up left' notice"
This reverts commit 5dc6a14c14.
* fix(credits): reintroduce grant_spent behind an in-session crossing gate
The removed notice nagged because its condition is a steady state for
accounts living on top-up, the latch is per-session, and the cold-start seed
runs the policy at every session open — every session re-announced
'Grant spent · $X top-up left'. Reintroduce it gated so only a session that
WATCHES the grant run out announces:
- seen_grant_unspent crossing gate, mirroring seen_below_90: opens when the
session observes the grant meaningfully unspent (>= GRANT_UNSPENT_MIN_MICROS,
1 cent — portal-seeded states derive micros from float dollars and can carry
sub-cent residue where headers report exactly spent). Seeds never prime it.
- The gate guards only the show branch and is consumed by the announcement —
one announcement per crossing. Header flicker (used_fraction None and back)
clears the sticky line but cannot re-announce; a renewal re-opens the gate.
- new_credits_latch() centralizes the latch shape (agent build, lazy re-init,
and the policy test helper all build through it).
- Tests: steady-state-open stays silent (seed + policy seams), live crossing
announces once, flicker/renewal/residual cases locked; the rendering test
primes the gate and asserts its leg count so a gate regression cannot
silently shrink coverage.
Closes#55908. The CLI voice-mode beep amplitude is hardcoded at 0.3 inside
tools.voice_mode:play_beep(), which makes the record start/stop cues too
quiet on low-volume systems and headphones. Users couldn't adjust it
without editing source.
Move the literal into a configurable voice.beep_volume setting (clamped to
0.0-1.0, default 0.3 to preserve prior behaviour). The new
_get_beep_volume() helper reads via the same load_config() pattern used by
cli.py's _voice_beeps_enabled() and hermes_cli/voice.py's _beeps_enabled(),
keeps bools / out-of-range / non-numeric / NaN values safely on the default,
and falls back silently if config can't load so the audio cue never breaks
the voice loop on a degenerate config.yaml.
Covered by tests/tools/test_voice_mode.py:
- TestGetBeepVolume (12 cases: missing key, custom value, boundary 0.0/1.0,
out-of-range clamp, type coercion, bool guard, NaN guard, exception
guard, dict-typed voice section)
- TestPlayBeepVolumeWiring (guards against re-introducing a hardcoded 0.3
literal in play_beep)
Docs: website/docs/user-guide/configuration.md mentions the new key.
Other locale translations (zh-Hans etc.) intentionally untouched —
handled by the regular i18n sync pipeline as a separate change.
No change in default behaviour: existing users hear exactly the same beep.
Per-job cron inference pins are now user-owned: the agent-facing cronjob
tool schema no longer exposes model/provider/base_url, and the registered
handler ignores them even if a model hallucinates the old parameters.
Users set pins via the dashboard, hermes cron create/edit --model/--provider,
or jobs.json directly — and once set, a pin sticks until the user changes it.
Existing agent-era pins are grandfathered untouched.
New cron.model / cron.model_provider config keys give the cron fleet its
own default model, independent of the chat model. Fire-time resolution:
per-job pin > cron.model > HERMES_MODEL > model.default. An axis covered
by the explicit cron-fleet default is deliberate routing, not drift, so
the #44585 fail-closed guard skips it — switching your chat model with
/model or hermes model no longer breaks unpinned cron fleets.
- tools/cronjob_tools.py: drop model param from agent schema + handler;
remove now-dead _resolve_model_override
- cron/scheduler.py: cron.model/model_provider resolution + per-axis
drift-guard skip
- cron/jobs.py: snapshot resolution mirrors the new precedence
- hermes_cli/subcommands/cron.py + hermes_cli/cron.py: --model/--provider
on hermes cron create/edit
- hermes_cli/config.py: cron.model / cron.model_provider defaults
- docs: cron.md model-resolution tip rewritten
The grant_spent notice fired for every subscription user with top-up
funds the moment their cap was reached and camped in the CLI/TUI status
bar and desktop toasts with no action to take — the account keeps
working off top-up. Remove it everywhere:
- agent/credits_tracker.py: drop grant_cond + the emit/clear block;
the dev fixture state now (correctly) produces no notice
- TUI: keep the turn-start clear of credits.grant_spent as back-compat
for older backends that still emit the key
- Desktop: drop the demo step and stale comment references
- Docs/config comments: remove grant-spent from credits_notices text
- Tests updated: policy/cold-start now assert the key never fires
Usage bands, depleted, and restored notices are unchanged; /usage still
reports the full balance breakdown.
'hey hor' triggered the wake word: the default sensitivity was 0.5, which
for openWakeWord IS the raw per-frame score threshold — openWakeWord's own
permissive baseline that near-misses clear. Raised the default to 0.6 so
phonetic near-misses fall short while real 'hey hermes' (typically 0.9+)
still fires easily.
Also fixed a real cross-engine inconsistency found while checking: the
sensitivity knob is documented 'higher = stricter' and behaves that way
for openWakeWord (threshold = sensitivity) and sherpa (0.05 + 0.4*s), but
Porcupine's own 'sensitivities' param runs the opposite way (higher = MORE
false alarms, per Picovoice). Turning sensitivity up made Porcupine looser
— backwards. Now inverted (1 - sensitivity) so 'higher = stricter' holds
for every engine.
- tools/wake_word.py: default 0.6; _sensitivity fallback uses _DEFAULTS;
Porcupine sensitivity inverted with rationale
- hermes_cli/config.py + docs: default + consistent-direction note
- tests: Porcupine inversion, default>=0.6 regression, fallback-to-default
openWakeWord scores one ~80ms frame at a time and the detector fired the
instant a SINGLE frame crossed threshold — so a stray phoneme in background
conversation could trigger the wake word unintentionally (reported in
testing). A real utterance of the phrase holds a high score across several
consecutive frames; an ambient blip spikes just one.
_OpenWakeWordEngine now requires N consecutive over-threshold frames
(wake_word.confirmation_frames, default 3) before firing. The streak resets
on any sub-threshold frame and on engine reset() (pause/resume), so a
pre-pause frame can't count toward a post-resume fire. confirmation_frames=1
restores the old single-frame behavior; clamped 1..10.
Only openWakeWord is affected — sherpa (streaming transducer) and porcupine
decode the whole phrase internally and already reject single-frame spikes.
- tools/wake_word.py: _confirmation_frames() accessor, streak logic in
process()/reset(), config default
- hermes_cli/config.py: wake_word.confirmation_frames documented default
- tests: 5 new (spike rejected, sustained fires once, =1 legacy behavior,
reset clears streak, config clamp) — 58 wake tests green
- docs: 'Reducing false triggers on ambient speech' section
openWakeWord's ONNX backend returns near-zero scores on Apple Silicon
(dscripka/openWakeWord#336), so "Hey Hermes" never crossed the 0.5
threshold: the listener armed, the microphone worked, and nothing fired.
Bisecting the pipeline puts the fault in exactly one stage — feeding the
same audio through both backends, the melspectrogram front-end is
bit-identical (maxdiff 0.00000) and the wake classifier agrees on
identical features, while the shared embedding model diverges by 45.44.
Cross-feeding confirms it: tflite features scored through the *onnx*
classifier give 0.9948 vs 0.000009 for onnx features. A telling
secondary symptom is that scores fall as input gets louder (0.5x ->
0.00031, 8x -> 0.000066), which is garbage inference rather than a weak
detection.
Selecting tflite in config alone does not fix it. openWakeWord hardcodes
`import tflite_runtime.interpreter` but declares tflite-runtime for
`platform_system == "Linux"` only; on macOS the equivalent wheel is
ai-edge-litert, so that import always fails and model.py silently
downgrades back to onnx. The result is a detector that reports itself
listening and can never fire.
- default the backend per platform (tflite on macOS ARM64, onnx
elsewhere) instead of hardcoding onnx, and pick the matching bundled
model artifact
- bridge tflite_runtime -> ai_edge_litert through sys.modules, in-process,
with no writes to site-packages
- refuse the silent onnx downgrade on macOS ARM64 and report the missing
runtime through check_wake_word_requirements() so the GUI surfaces an
actionable hint rather than arming a dead ear
- lazy-install ai-edge-litert via its own feature key, because lazy-dep
specs cannot carry PEP 508 markers (_spec_is_safe rejects ";")
An explicit `inference_framework` in config still wins, so anyone pinning
a backend keeps it.
Verified on macOS 26.5.2 / M-series: "hey hermes" scores 0.0005 on onnx
and 0.9423 on tflite from the same clip, with cross-phrase controls at
0.0003. Live over-the-air through the real microphone fires 4/4
utterances (peak 0.9532).
One sherpa listener now enrolls every wake-enabled profile's phrase
(defaulting to "hey <profile name>") and reports WHICH phrase fired.
wake.detected gains a profile field; the desktop live-switches to the
matching profile (same path as the profile rail), opens a fresh session
there, and starts hands-free voice. The single-profile CLI/TUI print the
hermes -p switch command for foreign-profile phrases instead of
answering as the wrong profile. Opt out per listener with
wake_word.profile_routing: false.
New "sherpa" wake_word provider: the configured phrase is BPE-tokenized
at runtime against a small streaming zipformer KWS model (~13 MB English,
one-time download cached under HERMES_HOME), so ANY typed phrase works
with zero training — including per-profile phrases like "hey coder".
wake.sherpa lazy-dep group + [wake] extra grow sherpa-onnx/sentencepiece;
requirements probe routes per provider; sensitivity maps onto sherpa
keywords_threshold. E2E-verified on real audio (target phrase fires,
foreign phrase stays silent, reset drops buffered state).
From #53378: ships hey_hermes.onnx/.tflite (openWakeWord pipeline,
Apache-2.0) under tools/wakewords/, resolves the default (and hey_hermes
aliases) to the bundled file, ensures openWakeWord base feature models
are fetched for custom paths too, and updates config defaults + docs
from hey_jarvis to hey hermes.
Makes the wake word a tri-surface feature with one configurable owner.
- wake_word.surface ("auto" | "cli" | "tui" | "gui") + shared
wake_surface_enabled() gate consulted by every surface, so exactly one
place owns the listener and the new session it opens.
- tui_gateway: wake.start/stop/pause/resume/status RPCs + a wake.detected
event, sharing one server-side detector for both TUI and desktop. The
detector yields the mic to voice.record (pause on capture start, resume
on terminal) and to the desktop's browser mic (wake.pause/resume).
- TUI (Ink): arm wake.start on gateway.ready; on wake.detected open a
fresh session and start voice capture.
- Desktop (Electron): arm wake.start on connect; on wake.detected open a
fresh session.
- CLI now gates on wake_surface_enabled("cli"); /wake status shows surface.
- Tests for the surface gate; docs cover the surface knob + cross-surface.
Adds an opt-in, on-device hotword listener for the CLI. With
wake_word.enabled (or /wake on), Hermes listens in the background for a
wake phrase; on detection it starts a fresh session, captures one
utterance through the existing voice pipeline, and answers — the
"Hey Siri" pattern.
- tools/wake_word.py: provider-pluggable detector (openWakeWord, free
local default; Porcupine, premium) over the shared 16 kHz sounddevice
capture path. Background daemon thread with pause/resume so it yields
the mic during a voice turn.
- CLI wiring: startup listener (off-thread), on-wake flow, an idle
watchdog that resumes the detector after each turn, cleanup hook, and
a /wake [on|off|status] command.
- config.yaml wake_word section; PORCUPINE_ACCESS_KEY as an optional
secret. Engines lazy-install via the [wake] extra.
- Hands a transcript to the input queue exactly like voice mode, so no
system-prompt/cache mutation. No new core model tool.
- Tests (mocked, no live audio/network) + feature docs.
- Replace _load_cron_jobs_for_config_warning with lazy import of
cron.jobs.load_jobs — picks up BOM handling, corruption repair,
and context-local store resolution for free
- Re-add model.name to axis mapping (was dropped during merge);
model.name is a legacy alias for model.default
- Fix grammar: '1 enabled unpinned cron job have' -> 'has'
- Pass user_config to cron_model_drift_guard_enabled in set_config_value
to avoid a redundant load_config() re-read of the file just written
When an operator changes the global model/provider config, warn that
unpinned cron jobs with stored snapshots will fail-closed on their next
run. Adds a cron.model_drift_guard config opt-out (default true) for
fleets that should deliberately track changing global defaults.
Addresses #59031. Original PR #59177 by @doncazper.
Saying EXACTLY a configured stop phrase (default: 'stop') and nothing
else now ends the voice conversation instead of being sent to the agent
as a prompt. Match is deliberately strict — whole utterance,
case-insensitive, surrounding punctuation stripped — so 'stop doing
that and try X' still reaches the agent.
- tools/voice_mode.py: is_voice_stop_phrase() + voice.stop_phrases
config loader (default ['stop'], [] disables, malformed config falls
back safely).
- hermes_cli/voice.py: shared continuous loop (TUI + desktop) halts on
a stop phrase exactly like the silent-cycle limit (fires
on_silent_limit so every UI turns voice off); stop_continuous
force-transcribe path swallows the phrase without counting a silent
cycle.
- cli.py: classic CLI push-to-talk/continuous path and barge-in
utterance path disable voice mode on a stop phrase.
- Config default voice.stop_phrases: ['stop']; docs updated.
Tests: tests/tools/test_voice_stop_phrase.py (27 tests,
sabotage-verified: loop test fails when detection is disabled);
voice suites green (110 + 44 passed).
Whisper auto-detection frequently misidentifies short/accented clips,
which users experience as voice notes transcribed in the wrong language
(Teknium + CTO both hit this). The unified resolver from #73067 made a
global hint possible; this makes it the DEFAULT so stock installs stop
guessing. Non-English users set stt.language once; '' restores
auto-detect for multilingual use.
Deep-merge gives existing configs the new default automatically (no
_config_version bump needed); any explicit per-provider or global
language setting still wins.
Class-level fix for the 'STT transcribes the wrong language' issue family
(#55551, #50181 and siblings). Previously language handling was per-provider
chaos: local honoured stt.local.language, Groq/OpenAI/Mistral/DeepInfra sent
no language hint at all, xAI silently forced 'en', ElevenLabs used its own
language_code key, and there was no global setting.
- New _resolve_stt_language() helper: stt.<provider>.language >
stt.language (new global key) > HERMES_LOCAL_STT_LANGUAGE > auto-detect.
- Threaded through ALL providers: local, local_command, groq, openai,
mistral, xai, elevenlabs, deepinfra (shared OpenAI handler), command
providers, and plugin dispatch.
- xAI no longer forces English when nothing is configured (auto-detect).
- Mistral Voxtral now receives a language hint when configured.
- stt.groq.model is now honoured from config (previously env-only).
- DEFAULT_CONFIG gains stt.language, stt.groq, stt.xai, stt.mistral.language.
- Tests: tests/tools/test_stt_language_resolution.py (11 tests, sabotage-
verified) + full transcription suite green (236 passed).
Builds on cherry-picked contributor work from #19786 (@zombopanda),
#23161 (@materemias), #50684 (@BlackishGreen33).
Add optional stt.openai.language config for OpenAI transcription. Forward non-empty hints to the API while preserving auto-detection when unset. Document the config-only setting, add its default, and cover configured and unset request arguments.
Per Teknium: the caps should bound a single agent loop, not accumulate
over the whole session. Rename SessionCapConfig -> LoopCapConfig and the
config section session_caps -> loop_caps; move the counters into
reset_for_turn (invoked per turn via turn_context) so each turn starts
with a fresh budget; retune defaults 200 -> 50 (a single turn issuing 50
web searches / spawning 50 subagents is already pathological). Block
codes session_*_cap -> loop_*_cap and messages updated to drop the
/new-resets-the-budget guidance (irrelevant now that it resets per turn).
Tests flipped: the old persists-across-turn-resets assertion becomes
resets-each-turn.
Add per-session lifetime caps on web_search calls and subagent spawns
(defaults 200/200, matching Claude Code v2.1.212). Unlike the existing
per-turn tool-loop guardrails, these count over the whole session and
reset only when a fresh agent is built (/new, /clear). Hitting a cap
blocks the offending call and halts the turn cleanly.
- agent/tool_guardrails.py: SessionCapConfig + session counters on the
controller (in __init__, not reset_for_turn, so they persist across
turns). before_call() enforces caps first, independent of
hard_stop_enabled. delegate_task batches count each task.
- hermes_cli/config.py: tool_loop_guardrails.session_caps defaults.
- docs + tests (unit + E2E validated against a real AIAgent).
