A WebUI/TUI session whose last turn died mid-tool-loop (stale-timeout kill,
interrupt, or process restart before the tool result was written) persists a
dangling assistant(tool_calls) or interrupted assistant->tool tail. The
messaging gateway already strips these tails before replay (the #49201 fix),
but the TUI/WebUI resume path fed db.get_messages_as_conversation() straight
in as the agent's conversation_history with no cleanup. The model re-issued
the unanswered call on every resume -- including after a full WebUI + Gateway
restart, since the poison lives in the SessionDB, not memory -- leaving the
session permanently 'thinking'. Only deleting the session recovered it.
- Extract the two strippers + helper from gateway/run.py into a shared
agent/replay_cleanup.py (sanitize_replay_history wraps both).
- gateway/run.py re-exports under the historical private names; messaging
behavior unchanged.
- Both TUI cold-resume sites now sanitize the model-fed history while leaving
the display transcript untouched, so the user still sees their full history.
Verified E2E against a real SessionDB: dangling and interrupted tails are
stripped from the model feed, healthy mid-progress tool sequences are
preserved, and the display transcript is always the full raw history.
* fix(agent): config-driven intent-ack continuation for all api_modes (#27881)
The agent could end a turn after only stating intent ('I will run a health
check...') without executing the announced tool call, forcing the user to
re-prompt. A continuation guard that catches this and nudges the model to
proceed already existed but was hard-gated to the codex_responses api_mode,
so Gemini/Claude/OpenRouter turns never benefited.
- New agent.intent_ack_continuation config (default 'auto' = codex-only,
byte-stable for existing conversations). 'true'/model-list opts every
api_mode in; 'false' disables. Mirrors agent.tool_use_enforcement's shape.
- looks_like_codex_intermediate_ack gains require_workspace (default True).
The opted-in path drops the codebase/filesystem requirement so general
autonomous workflows (server ops, deploys, API calls) are caught, not just
coding tasks. Future-ack + action-verb + short-content + no-prior-tool
guards still apply; the 2-nudge-per-turn cap is unchanged.
- Resolution centralized in intent_ack_continuation_mode (off/codex_only/all).
* docs(infographic): intent-ack continuation (#27881)
_restore_primary_runtime restored the construction-time api_key snapshot and
never consulted the credential pool. After the pool rotated away from a
revoked/exhausted entry mid-session, every new turn restored the dead key,
re-failed instantly, burned the remaining entries, and fell through to
cross-provider fallback.
After restoring the snapshot, re-select the pool's current best entry and
swap the live credential in via _swap_credential (which already rebuilds the
OpenAI/Anthropic client, reapplies base-url headers, and carries the #33163
base_url / OAuth-detection fixes). Falls back to the snapshot key when the
pool is absent, empty, or the entry has no usable key.
Salvaged from #25206 onto current main: the original targeted the pre-refactor
monolithic method in run_agent.py; the logic now lives in
agent/agent_runtime_helpers.py and is collapsed onto _swap_credential instead
of re-inlining the client rebuild.
Fixes#25205
A document attached alongside an image in the same Discord message was
swept into the vision pipeline and 400'd the whole turn ("Could not
process image"), and was simultaneously never surfaced to the agent as a
readable file. Restores the "any file type works" contract for mixed
messages and fixes the HTTP 400.
Bug 1 — mixed attachments: the inbound routing loop keyed image/audio/video
classification off the message-level type (PHOTO/VOICE/AUDIO), so a doc in
a PHOTO message landed in image_paths and poisoned the vision call. The
document context-note path was gated on message_type == DOCUMENT, so that
same doc never reached the agent at all. Now classification is
per-attachment (trust each attachment's own MIME; fall back to the
message-level type only when MIME is unknown), via shared _event_media_is_*
helpers used by both _build_media_placeholder and the main inbound loop.
The document note now fires for any non-image/audio/video attachment
regardless of message-level type.
Bug 2 — uncommon formats: AVIF/HEIC/BMP/TIFF/ICO produced the same generic
400 because providers only accept PNG/JPEG/GIF/WEBP. image_routing now
transcodes those to PNG via Pillow before declaring media_type, skipping
cleanly (logged) if Pillow/plugins are missing. SVG is vector — Pillow
can't rasterize it — so it's skipped rather than transcoded.
Closes#25935.
Co-authored-by: LeonSGP43 <cine.dreamer.one@gmail.com>
Co-authored-by: cypres0099 <74935762+cypres0099@users.noreply.github.com>
The Anthropic SDK clients were built without max_retries, so the SDK
default (max_retries=2) retried 429/5xx with its own backoff that ignores
Retry-After — double-retrying inside hermes's outer loop and burning
request slots against a bucket that won't refill for minutes. Set
max_retries=0 on all Anthropic/AnthropicBedrock client constructions so
the outer conversation loop (which already honors Retry-After) owns retry.
Also raise the Retry-After cap in the conversation loop from 120s to 600s.
Anthropic Tier 1 input-token buckets reset in ~171s, so the 120s cap made
hermes retry before the reset window and re-trip the limit.
Refs #26293
Claude Code OAuth refresh tokens are single-use; Claude Code refreshes on
its own schedule, so by the time Hermes notices an expired token Claude
Code may have already rotated it. Re-read live credential sources first and
adopt a valid token rather than POSTing a possibly-stale refresh token.
Ports the _refresh_oauth_token hardening from PR #40107 (chazmaniandinkle)
on top of the keychain/file reconciliation from PR #21112 (nodejun).
Adds AUTHOR_MAP entry for nodejun.
read_claude_code_credentials() previously returned the macOS Keychain
entry as soon as one existed, even if its OAuth token was already
expired. Callers then ran is_claude_code_token_valid() on the result
and got False, so resolve_anthropic_token() returned None — surfacing
the misleading 'No Anthropic credentials found' error even when
~/.claude/.credentials.json held a perfectly valid token.
Now reads both sources and prefers the non-expired one. When both are
valid (or both expired), prefers the later expiresAt so any subsequent
refresh uses the freshest refresh_token.
Adds TestReadClaudeCodeCredentialsDesync covering the four reconciliation
cases. The existing 'keychain wins' priority test still passes because
both fixtures share the same expiresAt and the tiebreaker is >=.
_try_openrouter() returned (None, None) whenever an OpenRouter credential
pool existed but was exhausted (_select_pool_entry -> (True, None)), making
the OPENROUTER_API_KEY env-var fallback unreachable. Auxiliary tasks
(compression, vision, web_extract) silently failed even with a valid env key.
Now the pool-present branch only returns early when it successfully builds a
client; an exhausted pool falls through to the env-var path. The final
failure (pool exhausted AND no env var) still marks the provider unhealthy.
Fixes#23452.
Co-authored-by: ambition0802 <noreply@github.com>
When the primary provider returns 401 and the auth-refresh path is
unavailable or fails, both call_llm() and async_call_llm() reached the
should_fallback gate without _is_auth_error in the condition, so the
auxiliary task (e.g. compression) was dropped silently — losing message
history. Add _is_auth_error to should_fallback (NOT is_capacity_error) in
both sync and async paths, plus an 'auth error' reason branch.
Auth stays a non-capacity error: it falls back in auto mode via the
is_auto gate, but on an explicitly-configured provider it still respects
the user's choice and raises rather than silently switching providers.
On a MoA session, auxiliary tasks (title generation, compression, vision, …)
ran through _resolve_auto with provider='moa' / model='<preset>', which sent
the preset name (e.g. 'opus-gpt') as the model id to resolve_provider_client —
producing 'HTTP 400: opus-gpt is not a valid model ID' on every turn (visible
as the title-generation warning).
MoA is a virtual provider with no real HTTP endpoint; aux tasks don't need the
reference fan-out. _resolve_auto now resolves a 'moa' main provider to the
preset's aggregator slot (its acting model) and continues Step 1 with that real
provider+model, dropping the virtual moa://local base_url + placeholder key so
the aggregator resolves via its own provider credentials. Mirrors the MoA
context-length resolution.
Verified live: a MoA turn no longer emits the 'not a valid model ID' warning.
Test: tests/agent/test_auxiliary_main_first.py (19 pass).
A MoA session's model is the preset name (e.g. 'opus-gpt') and its base_url is
the virtual local endpoint, so get_model_context_length() missed every probe
and fell through to the 256K fallback — even when the aggregator is a 1M-context
model. The acting model in MoA IS the aggregator, so resolve the context window
from the aggregator slot's real provider+model.
- model_metadata.get_model_context_length: when provider=='moa', resolve the
preset's aggregator slot through resolve_runtime_provider and recurse with the
aggregator's real provider/model/base_url. Explicit model.context_length still
wins (checked first); falls through to the generic default if resolution fails.
Tests: opus-gpt preset now reports 1M (the aggregator window), config override
still honored.
The secret redactor only matched uppercase env-style keys ([A-Z0-9_]),
so config-file assignments like spring.datasource.password=secret,
app.api.key=xyz, and YAML password: secret leaked verbatim when the
agent ran cat/grep on application.properties or .env files (issue #16413).
Adds three case-insensitive config-key matchers that run only in a
config-file context, preserving the existing #4367 (lowercase code/prose)
and web-URL-passthrough carve-outs:
- _CFG_DOTTED_RE: namespaced keys (contain a dot) — unambiguously config
- _CFG_ANCHORED_RE: bare secret-word keys at line start (incl. export)
- _YAML_ASSIGN_RE: unquoted colon config (password: value)
Value capture stops at whitespace and '&' so form bodies stay pair-wise;
the '://' guard keeps intentional web-URL query-param passthrough intact.
Reported-by: Murtaza1211
Z.AI / Zhipu reuse HTTP 429 for server-wide overload. The 429 status
path classified these unconditionally as rate_limit with
should_rotate_credential=True, so an overloaded provider exhausted the
credential pool after two errors — fatal for a single-key user, who has
nothing to rotate to.
The credential is valid; the server is just busy. Disambiguate the 429
body against a shared _OVERLOADED_PATTERNS list and route overload
language to FailoverReason.overloaded (retryable, no rotation), matching
the existing 503/529 path and the message-only path (#52890). Genuine
rate limits (no overload language) still rotate.
Extracted the inline overloaded tuple #52890 added into the shared
_OVERLOADED_PATTERNS constant so the status-code and message paths use
one list.
Closes#14038.
The curator_env fixture left async review threads (synchronous=False spawns
a daemon 'curator-review' thread that calls save_state() on completion)
running past test teardown. save_state() resolves the state path from
HERMES_HOME at write time, so a straggler could write into the next test's
tmp home, corrupting test_state_file_survives_corrupt_read (and others)
under CI load. Join the thread on teardown while HERMES_HOME is still
pinned to this test's home.
The 'whatsapp' and 'signal' PLATFORM_HINTS told the agent 'Please do not
use markdown as it does not render' — factually wrong. Both adapters
actively convert markdown to native formatting:
- whatsapp_common.format_message(): **bold**, ~~strike~~, # headers,
links, code blocks -> WhatsApp native syntax
- signal_format.markdown_to_signal(): same conversions via bodyRanges,
plus '- item' / '* item' bullets -> '• ' Unicode bullets
The wrong hint made the agent strip bullets and bold the adapter would
have rendered (#12224). Rewrote both hints to mirror whatsapp_cloud:
markdown is auto-converted, bullet lists work, tables are not supported.
Added a contract test asserting markdown-converting platforms never
forbid markdown in their hint.
The verify-on-stop guard fired too eagerly — including on doc/markdown/skill
edits with nothing to verify, where it pushed a pointless /tmp verification
script. Three changes:
1. Default OFF for new installs: agent.verify_on_stop defaults to false
(was the "auto" surface-aware sentinel). _config_version bumped 30 -> 31.
2. One-time migration (v30 -> v31): existing installs are switched off once,
but only when the value is missing or still the "auto" sentinel — an
explicit true/false the user set is preserved.
3. Path filter: build_verify_on_stop_nudge() now drops documentation/prose
paths (.md/.mdx/.rst/.txt/LICENSE/CHANGELOG/...) so even when explicitly
enabled, a doc-only turn never nudges. Mixed doc+code turns still nudge on
the code paths.
The legacy "auto" sentinel is still honored when set explicitly (ON for
interactive coding surfaces, OFF for messaging). HERMES_VERIFY_ON_STOP env
override unchanged.
When operator config has provider=anthropic with model.base_url pointing
at a non-Anthropic host (e.g. https://openrouter.ai/api/v1 with provider=anthropic),
the auxiliary Anthropic path was unconditionally applying that override.
Main-session traffic routed correctly because the main path attaches the
right credential for the actual destination, but every side-channel call
(memory extractors, reflection, vision, title generation, janus
extractor/promise) sent ANTHROPIC_API_KEY to the foreign host and 401'd.
Gate the override on hostname == api.anthropic.com. Operators routing main
through a non-Anthropic provider must use that provider's own auxiliary
client; the Anthropic aux path now stays pointed at api.anthropic.com.
Regression tests cover openrouter, openai, anthropic-with-path, empty, and
anthropic-default-base_url cases.
Wire get_reasoning_stale_timeout_floor() into both stale detectors so known
reasoning models (Nemotron 3 Ultra, OpenAI o1/o3, Opus 4.x thinking, DeepSeek
R1, Qwen QwQ, Grok reasoning) tolerate multi-minute thinking phases instead of
the upstream gateway idle-killing the socket (BrokenPipeError) before first
token. Applied as max(default, floor) — never overrides explicit user config,
never lowers an existing threshold.
The reasoning_timeouts.py allowlist module already landed on main via #52795,
so this salvage carries only the wiring + tests (the duplicate module and the
stale-base MoA reverts from the original PR branch are dropped).
Salvaged from #52238. Fixes#52217.
The salvaged #51875 added a background-review write guard in skill_manage
that refuses mutations to skills.external_dirs skills — but it only fires
when is_background_review() is true. The curator's LLM review fork ran with
the default _memory_write_origin='assistant_tool', so the guard never
triggered during the exact curation pass it exists to protect against
(GH-47688).
- Set _memory_write_origin='background_review' on the curator review fork so
turn_context binds it onto the write-origin ContextVar and the guard fires.
- Add a regression test asserting the fork runs under the background_review
origin (the invariant linking the fork to the guard).
- AUTHOR_MAP: map yu-xin-c for the salvaged commit.
Force redact_sensitive_text(force=True) on the browser_type text arg so
recognized credentials (API keys, tokens, JWTs) are masked in tool
progress, previews, callbacks, and return payloads even when the global
security.redact_secrets opt-out is set — a typed credential reaching chat
history is a security boundary, not log hygiene. Normal typed text matches
no pattern and stays fully readable for debuggability.
Tests assert the API-key-shaped secret is masked across every surface and
that normal text passes through unchanged.
CredentialPool._sync_device_code_entry_to_auth_store rotated single-use
OAuth refresh tokens but wrote the new chain only into the active profile
store. When a profile resolves a grant from the global-root fallback
(read_credential_pool, #18594) and the pool then refreshes it, root was
left holding a now-revoked refresh token — every other profile reading the
stale root grant subsequently died with refresh_token_reused / invalid_grant
once its access token expired.
This is the credential-pool analog of #43589 (which fixed the non-pool xAI
refresh path in _save_xai_oauth_tokens). Detect the read-from-root case
(profile lacks its own providers.<id> block) BEFORE the profile save and,
after it, write the rotated chain back to the global root via a best-effort,
seat-belted write-through. A profile that genuinely shadows root (owns the
block) is untouched; classic mode (profile == root) is a no-op; a failed root
write never breaks the profile's own save. Covers openai-codex (reported),
xai-oauth, and nous through the shared sync path.
Two-part fix:
Part 1 (classifier override at agent/error_classifier.py:720-738):
A transport disconnect on a reasoning model — even on a large session —
now routes to FailoverReason.timeout instead of context_overflow. Without
this, large-session reasoning-model disconnects route to the compression
branch and silently delete conversation history on a phantom
context-length error. The override is strictly targeted: non-reasoning
models (gpt-4o, claude-3-5-sonnet, llama-3.3-70b, etc.) still route to
context_overflow on large sessions — the existing intentional behavior
for chat models whose proxy doesn't idle-kill during prefill/generation.
Part 2 (new agent/thinking_timeout_guidance.py + integration at
agent/conversation_loop.py:3488-3567):
New is_thinking_timeout() and build_thinking_timeout_guidance() helpers.
When a known reasoning model (NVIDIA Nemotron 3 Ultra, OpenAI o1/o3,
Anthropic Opus 4.x thinking, DeepSeek R1, Qwen QwQ, xAI Grok reasoning)
hits a transport-kill on a small session (classifier says timeout
directly) or after Part 1 routes correctly (large session), the user
now sees reasoning-specific guidance with three actionable workarounds
in priority order:
1. Set providers.<provider>.models.<model>.stale_timeout_seconds: 900
in ~/.hermes/config.yaml (Hermes's built-in floor is already 600s
for known reasoning models; raise further if upstream is even
tighter).
2. Lower reasoning_budget or set reasoning_effort: medium on this
model if the provider supports it.
3. Use a smaller / faster reasoning model if the task doesn't
require deep thinking.
The new guidance takes precedence via if/elif over the existing
_is_stream_drop block, so a reasoning-model user with a transport-kill
message sees actionable advice instead of the misleading "try
execute_code with Python's open() for large files" advice (which is
correct for the unrelated large-file-write stream-drop case but
actively wrong for the thinking-timeout case).
Verified:
- 478 tests passing across 9 directly-relevant files (49 new + 429
existing, zero regressions).
- Ruff lint clean on all 4 modified/new files.
- Negative test: 6 parametrized regression guards confirm non-reasoning
models still route to context_overflow on large sessions; 4
parametrized gates confirm non-timeout classifier reasons never
trigger the guidance; 5 parametrized cases confirm non-transport
messages never trigger it.
- Regression guard: new guidance message does NOT contain
"execute_code" or "open()" — the misleading advice is fully
replaced, not appended alongside.
- Cross-vendor dual review via agy -p:
- Gemini 3.5 Flash (Medium) — passed: true, zero blockers, one
SHOULD-FIX (vprint block duplication — fixed by extracting
detection into a helper module).
- GPT-OSS 120B (Medium) — passed: true, zero blockers, two nits
(test placement — adopted at tests/agent/test_thinking_timeout_guidance.py;
primary-model capture — accepted as non-issue per Flash's nit).
Dependency note for maintainers:
This PR includes agent/reasoning_timeouts.py (the reasoning-model
allowlist module from PR #52238) because the Layer 1 override is
load-bearing on get_reasoning_stale_timeout_floor(). After PR #52238
lands on main, this PR's duplicate agent/reasoning_timeouts.py should
be rebased away. Either PR can land first; the other rebase is
mechanical.
Fixes#52271.
The salvaged context-window screen (#52392) skips fallback candidates that
are too small, and the rate-limit/403 fixes skip candidates that are at
capacity. A third hard failure remained uncovered: a fallback that builds a
client fine but returns a 400 because it structurally cannot run the model.
The canonical case is a configured openai-codex / ChatGPT-account fallback
asked to compress a glm-5.2 conversation:
400 - {'detail': "The 'glm-5.2' model is not supported when using
Codex with a ChatGPT account."}
This is a request-validation error, so should_fallback was False and the
explicit-provider gate blocked it — the auxiliary task (compression) aborted
every turn, dropping middle turns without a summary and churning the session,
which is exactly what destroys the prompt cache.
Adds _is_model_incompatible_error() (400 + capability phrasing, excluding
not-found and billing 400s which the sibling predicates own) and treats it as
a fallback-worthy capacity error in both sync and async call_llm, so the chain
skips the incapable route and continues to the next viable candidate.
The runtime auxiliary fallback chain (_try_configured_fallback_chain and
_try_main_fallback_chain) returned the first reachable candidate without
checking whether the candidate's context window was large enough for the
task. For task='compression' this meant a reachable but undersized
fallback (e.g. 32K) could be selected and then fail, even when a later
larger-context fallback was available.
This adds two small helpers:
_task_minimum_context_length(task)
Returns MINIMUM_CONTEXT_LENGTH (64K) for compression, None for
other tasks (vision, web_extract, etc.).
_candidate_context_window(provider, model, ...)
Thin wrapper around get_model_context_length that returns None on
probe failure so unknown/custom endpoints pass through unchanged
(preserves the existing fallback surface).
Both fallback loops now skip reachable candidates whose resolved context
is below the task minimum and continue iterating. The success path
(first viable candidate wins) is unchanged. Return shape and ordering
for healthy candidates are preserved.
Six regression tests cover:
L2 configured chain skips too-small candidate
L2 chain continues after skipping, returns last viable
L3 main chain skips too-small candidate
L4 unknown-context candidate passes through
L5 non-compression task is not filtered
L6 minimum constant matches MINIMUM_CONTEXT_LENGTH (64K)
3/6 fail on upstream/main without the production change (verified); all
6 pass with the fix. Full test_auxiliary_client.py suite (231 tests)
and related compression tests (130 tests) remain green.
When an explicit aux provider cannot build a client before any request is
sent (missing raw env key, exhausted/unavailable OAuth or credential-pool
auth, resolver returning (None, None)), call_llm raised a misleading
"no API key was found" error and bypassed the configured fallback_chain
entirely. A provider authenticated through Hermes auth / the credential
pool (e.g. ollama-cloud) whose pool entry is exhausted hit this path, so
compression failed instead of routing to the configured fallback.
Adds _try_configured_fallback_for_unavailable_client() and wires it into
both sync and async call_llm before the raise, and into the startup
compression feasibility check.
Salvaged from #51835 by @herbalizer404.
Rate-limit (429) errors on explicit-provider auxiliary tasks were
silently failing instead of triggering the fallback chain. The
is_capacity_error gate only checked payment and connection errors,
excluding rate limits — so when a configured provider like
openai-codex hit its rate limit, auxiliary tasks (kanban_decomposer,
vision, web_extract, approval, etc.) had zero resilience.
Add _is_rate_limit_error() to is_capacity_error at both call sites
(sync and async paths) so rate limits trigger fallback regardless
of whether the provider was auto-detected or explicitly configured.
Fixes#52228
Ollama Cloud (and similar) return 403 with bodies like "this model requires
a subscription, upgrade for access" or "you have reached your session usage
limit, upgrade for higher limits". These are capacity/billing conditions
semantically identical to credit exhaustion, but _is_payment_error() did not
recognize them (403 missing from the status set; keywords missing), so the
configured fallback_chain was never tried and compression failed outright.
Adds 403 to the status set and the subscription/session-usage keywords.
Salvaged from #49076 by @herbalizer404.
These 7 test sites assert rotation behavior (fork, child sessions, lock
contention, logging session-context follows id rotation, boundary hooks fire
on rotation). Pin each builder to in_place=False explicitly so they keep
exercising the retained rotation fallback regardless of the global default
(flipped to True in #38763). Rotation stays a working opt-out fallback and
deserves continued coverage — these are NOT deleted.
Pinned sites:
- test_compression_concurrent_fork._build_agent_with_db
- test_compression_logging_session_context._build_agent_with_db
- test_compression_rotation_state._build_agent_with_db
- test_compression_boundary_hook._make_agent (2 helpers: CompressionBoundaryHook + SessionCompressEvent)
- test_compression_concurrent_sessions._build_agent_with_db
build_turn_context() created the DB session row via _ensure_db_session()
before the system prompt was restored/built, so a fresh API/gateway agent
carrying client-managed history inserted a row with system_prompt=NULL. That
tripped the misleading 'stored system prompt is null; rebuilding from scratch
... investigate the previous turn's write path' warning and a guaranteed
first-turn prefix cache miss. Move row creation to after _cached_system_prompt
is populated.
Verified live (OpenRouter + claude-sonnet-4.5): persistent-agent turns show
cache_read jumping to the full prefix on turn 2+ (write 24411 -> read 24411),
and the persisted system_prompt is non-NULL so fresh-agent restore keeps the
prefix cache warm.
Tests: turn-context ordering regression asserting _ensure_db_session runs
after _cached_system_prompt is populated.
/learn told the agent to fill the skill `author` field, and the system
prompt environment probe surfaces the OS login name (user=$(whoami) in
prompt_builder.py), so the model wrote the host username into published
SKILL.md frontmatter — a privacy leak the user never opted into, and
inconsistent run to run as the most-salient identity changed.
The /learn authoring prompt now sets `author` to the literal value
`Hermes` and explicitly forbids deriving it from the host environment
(OS/login user, git config, or any probeable identity). The skill names
itself as the tool that wrote it.
Closes#52368.
#48879 closed the tool-call sequence on interrupt inside finalize_turn so a
/stop after a tool no longer persists a `tool` tail that the next user message
turns into a `tool -> user` role-alternation violation (which strict providers
like Gemini/Claude react to by hallucinating a continuation and ignoring prior
context — what users see as "lost context after stop").
But the retry-wait, error-handling, and post-error retry-wait interrupt aborts
in conversation_loop return early and never reach finalize_turn, so they still
persisted and returned a raw `tool` tail. Interrupting during provider
backoff/rate-limiting (common under heavy work) hit exactly this path.
Extract the close into a shared close_interrupted_tool_sequence helper and apply
it at every interrupt abort (finalize_turn + the three early returns) so the
whole bug class is fixed, not just the one site.
The verify-on-stop guard (PRs #52296, #52297) defaulted ON for every
session, so on gateway messaging surfaces (Telegram, Discord, etc.) the
model complied with the nudge by writing a hermes-verify temp script and
emitting an ad-hoc verification summary, which the gateway delivered to
the end user as chat noise.
Resolve a surface-aware default instead. The DEFAULT_CONFIG value becomes
the sentinel "auto", which verify_on_stop_enabled() resolves to ON for
interactive coding surfaces (CLI, TUI, desktop) and programmatic callers,
and OFF for conversational messaging surfaces. The surface is read from
HERMES_SESSION_PLATFORM (what the gateway actually binds), with
HERMES_SESSION_SOURCE and HERMES_PLATFORM as fallbacks, matching the
sibling resolution in skill_commands.py and prompt_builder.py. An explicit
HERMES_VERIFY_ON_STOP env var or a boolean agent.verify_on_stop config
still overrides in either direction.
The passive evidence ledger and the call site are untouched.
The /learn authoring prompt taught a subset of the HARDLINE skill rules,
and stated the <=60-char description rule without making the model enforce
it — so generated descriptions overshot (up to 202 chars), which the
60-char system-prompt skill index then silently truncates.
- description: add the index-truncation rationale, a count-and-trim
self-check, and a good/bad length example so the model actually hits <=60.
- add platforms-gating rule (OS-bound primitives -> declare platforms:).
- add author-credits-human-first rule.
- round out the Hermes-tool framing with the full wrapped-tool mapping and
references/templates layout.
Closes#52367.
Move terminal/execute_code/read_file preview compaction into agent.display so CLI, gateway, and Ink TUI all inherit the same labels that desktop introduced in #52321.
The shared preview keeps raw args intact while trimming display-only shell plumbing (`cd`, pipe tails, banner/status echoes) and read_file line ranges. Desktop now prefers backend `context` for live rows and keeps its TypeScript fallback only for hydrated history.
The pet generation image-processing suite is deterministic but expensive enough
to blow the per-file CI timeout on Linux (140s), and it is not relevant to the
fast timeout PR's normal signal. Keep it available for manual validation, but do
not run it by default.
Set HERMES_RUN_SLOW_PET_TESTS=1 to enable the suite. The canonical test wrapper
now preserves that opt-in variable through its hermetic env.
Recurring cron jobs were prompt-cache-cold on every fire. session_id is
built as cron_<job_id>_<timestamp>, and the Codex/Responses transport used
session_id directly as prompt_cache_key — so the timestamp changed the cache
key on every run and the static prefix (agent identity + tool schemas) was
re-paid each tick.
Derive prompt_cache_key from a SHA-256 of the static prefix (instructions +
sorted tool schemas) instead. Repeated fires of the same job share one
content-addressed key (pck_<hash>) and reuse the warm prefix within the
provider's cache TTL. The key changes exactly when the prefix changes —
edit the job's prompt or toolset and it re-keys; leave it alone and it stays
stable.
session_id is left untouched for transcript isolation, log correlation, and
the Codex/xAI session-scope routing headers (session_id, x-client-request-id,
x-grok-conv-id) — those are the per-fire identity, not the cache key. Only the
prompt_cache_key body field (standard OpenAI/Codex path and the xAI extra_body
field) is content-addressed.
Closes#51395.
Co-authored-by: spiky02plateau <spiky02plateau@users.noreply.github.com>
Co-authored-by: JoaoMarcos44 <JoaoMarcos44@users.noreply.github.com>
