Inspired by Claude Code v2.1.199 (July 2, 2026): stacked slash-skill
invocations load all leading skills (up to 5), not just the first.
- agent/skill_commands.py: split_stacked_skill_commands() consumes leading
/skill tokens (stops at the first non-skill token so slash-path arguments
are never swallowed); build_stacked_skill_invocation_message() composes
the multi-skill turn reusing the existing bundle scaffolding markers so
extract_user_instruction_from_skill_message() keeps memory providers
storing the user's instruction, not N skill bodies.
- cli.py + gateway/run.py: dispatch the stacked path on both surfaces.
- 11 new tests + docs section in skills.md.
Inspired by Claude Code v2.1.199 (July 2, 2026): SSL certificate errors
(TLS-inspecting proxies, missing CA bundles, expired certs) no longer
burn retries before showing actionable guidance — they fail immediately
with the fix hint.
- agent/error_classifier.py: new FailoverReason.ssl_cert_verification +
_SSL_CERT_VERIFY_PATTERNS, checked BEFORE the transient-SSL patterns
(cert-verify messages also contain '[SSL:' and previously retried
forever as timeout). Non-retryable, no compression, no fallback churn.
- agent/conversation_loop.py: dedicated status line + per-cause fix
hints (corporate proxy CA bundle, certifi refresh, self-signed local
endpoints) on the non-retryable abort path.
- 7 new tests incl. regression guards (transient alerts still retry,
large-session cert failure doesn't trigger compression).
format_date() at line 76 still used %-d, which raises ValueError on
Windows strftime. Same class as the axis-label site fixed by #56640;
use dt.day directly. Credit also to @x7peeps (#58480) who flagged both
sites.
`_period_label()` in `learning_graph_render.py` used `%-d %b`
strftime, which is a Linux-only format — the `%-` prefix for
zero-padding suppression doesn't exist on Windows `strftime`, causing
`ValueError: Invalid format string` on `hermes journey`.
Fix by using `dt.day` directly (an integer, no zero-padding by
default) combined with `strftime('%b')` for the month. This is
cross-platform and produces identical output.
Reproduced and tested on Windows 10 with Hermes v0.18.0.
* fix(cli): set correct x-initiator header per Copilot turn
copilot_default_headers() always hardcoded x-initiator: agent, but
GitHub Copilot billing requires "user" for user-initiated prompts and
"agent" for tool/follow-up calls. This caused premium requests to never
be consumed correctly, risking billing issues or account bans.
Adds is_agent_turn param to copilot_default_headers() and injects
extra_headers={"x-initiator": "user"} on the first API call of each
user turn when targeting Copilot URLs. The flag flips to False after
injection so subsequent calls (tool use, streaming fallback) default
back to "agent".
Fixes#3040
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* chore(release): add AUTHOR_MAP entry for @tjp2021 (PR #4097 salvage)
---------
Co-authored-by: Tim <tim@iteachyouai.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
When OpenRouter routes to an endpoint that does not support tool/function
calling, it returns HTTP 404 with the message 'No endpoints found that
support tool use. Try disabling "browser_back".'
The raw error body does not contain 'model not found' or any other
_MODEL_NOT_FOUND_PATTERNS entry, so it falls through to FailoverReason.unknown
with retryable=True. The retry loop wastes 3-5 attempts on the same
deterministic rejection, then surfaces a confusing generic error instead of
automatically failing over to a fallback model or provider.
Adding the OpenRouter phrase to _MODEL_NOT_FOUND_PATTERNS classifies it as
model_not_found (retryable=False, should_fallback=True), which triggers the
client-error fast-fallback path in conversation_loop.py: the agent switches
to a configured fallback model/provider before the user sees the error.
Existing buffered guidance in conversation_loop.py (the 'support tool use'
hint at line ~2967) remains intact and surfaces only if every fallback
exhausts.
_try_anthropic() hard-failed (return None, None) when the anthropic
credential pool was present but had no selectable entry — e.g. the pooled
OAuth token expired and its refresh_token had gone stale, so
_select_pool_entry("anthropic") returned (True, None). This wedged every
auxiliary task routed to Anthropic (goal judge surfaced "no auxiliary
client configured") even when a perfectly valid ANTHROPIC_TOKEN /
credentials-file token was available. The main session stayed healthy
because it resolves the env token directly.
The openrouter path (_try_openrouter) and codex path already fall through
to their standalone credential on (True, None); anthropic was the only
provider that hard-failed. Make _try_anthropic fall through to
resolve_anthropic_token() on that branch so the three paths are symmetric:
a temporarily dead pool entry must not block auxiliary tasks when a valid
standalone credential exists.
Adds a regression test covering: (1) pool present + no entry + valid env
token -> client built from the env token, (2) pool present + no entry + no
resolvable token -> clean (None, None), (3) base_url defaults correctly
when falling through with pool_present=True.
'KEY=os.getenv(...)' / 'os.environ[...]' / 'process.env.X' values are
variable-name references in code snippets, not leaked secrets. Masking
them corrupted pasted code in prose/log contexts (issue #2852):
ha_token=os.getenv('HOMEASSISTANT_TOKEN') -> ha_token=os.get...EN').
Skip these values inside _redact_env, which covers all three passes that
share the closure (_ENV_ASSIGN_RE, _CFG_DOTTED_RE, _CFG_ANCHORED_RE).
Real secret values are still masked.
Salvage of PR #2852-fix #2854 — the PR's own placement (an unconditional
pass before the code_file gate) would have reintroduced the code-file
false-positive class; the skip is applied inside the existing gated pass
instead. Tests adapted from the PR.
Co-authored-by: crazywriter1 <sampiyonyus@gmail.com>
Strict providers (DeepSeek) reject a payload where the same tool_call_id
appears more than once with HTTP 400 'Duplicate value for tool_call_id'.
The issue was filed as an 'orphaned tool message' compression bug, but the
pasted error is a DUPLICATE tool_call_id — orphans are already handled on
main; duplicates were not. Reproduced live on main: both shapes leaked
through repair_message_sequence and sanitize_api_messages.
Two chokepoints, two shapes:
- repair_message_sequence: consume the id from known_tool_ids on first
match so a SECOND tool result reusing it falls into the drop branch
(duplicate tool-result shape). This is @Robinlovelace's kernel from
#55436 (applied manually — that PR was ~800 commits stale and bundled
an unrelated duplicate-DB-write change for #860, which is dropped here).
- sanitize_api_messages (final pre-API pass): add a dedup pass covering
BOTH (a) duplicate tool_calls sharing an id WITHIN one assistant message
(the message[6] shape) and (b) later tool result messages reusing an
already-seen id. #55436 covered neither of these at this chokepoint.
Tests: duplicate-tool-result dedup at both functions, duplicate-assistant-
tool_call-id collapse, and a negative control proving distinct ids are
never dropped (no over-dedup).
Credit: @Robinlovelace (#55436) for the repair_message_sequence dedup kernel.
Closes#58327.
Replace the inline dict-copy + _db_persisted pop in
_ensure_compressed_has_user_turn with the canonical
_fresh_compaction_message_copy helper (the same primitive the compressor's
own protected-head/tail assembly uses), so the persistence-marker strip
stays consistent across all compaction copy sites (#57491). Expand the
docstring to record the alternation-safety and end-placement rationale.
22c5048d9 restored Anthropic-style cache_control for two of MoA's three
call paths: the acting aggregator (MoAChatCompletions.create, the
persistent `provider: moa` model) and the advisor fan-out (_run_reference).
aggregate_moa_context() -- the /moa <prompt> one-shot command's synthesis
call -- is the third, independent call path and was never covered: its
call_llm(task="moa_aggregator", ...) sent a single undecorated user message
containing the full joined reference output, re-billing the entire input on
every invocation even when the resolved aggregator slot is a cache-honoring
route (Claude on OpenRouter/native Anthropic, MiniMax, Qwen/DashScope).
- Generalize _maybe_apply_advisor_cache_control to
_maybe_apply_moa_cache_control (it never had advisor-specific logic --
same policy function, same breakpoint layout as the main loop, judged
purely on the passed-in runtime) and reuse it in aggregate_moa_context
the same way _run_reference already does.
- Compute _slot_runtime(aggregator) once and reuse it for both the
decoration call and the call_llm kwargs, instead of calling it twice.
Mutation-verified: reverting the moa_loop.py change makes the new
regression test fail by asserting a plain string aggregator-message
content where the cache-honoring case expects native cache_control
content blocks.
Both wired against features the iron-proxy author (@mslipper) confirmed on
PR #30179 — and both verified present in the pinned v0.39.0 source.
Header-auth providers (match_headers):
- New _HEADER_AUTH_PROVIDERS: Anthropic native (x-api-key), Azure OpenAI
(api-key on *.openai.azure.com / *.cognitiveservices / *.services.ai),
Gemini (x-goog-api-key + ?key= query param via match_query).
- TokenMapping grows match_headers + alias_env_names; per-provider header
sets flow into the secrets rules; mappings.json roundtrips them
(legacy files load with the Authorization default).
- GEMINI_API_KEY / GOOGLE_API_KEY collapse into ONE mapping (two
require-rules on the same host would reject each other); the sandbox
gets the token under both names, and the proxy child env mirrors the
alias into the canonical name when only the alias is set.
- Docker backend injects alias env names alongside canonical ones.
- The fail-closed tier is now empty, so fail_on_uncovered_providers and
discover_blocked_providers are deleted (dead toggle otherwise);
_NON_BEARER_PROVIDERS shrinks to genuinely-unswappable signature auth
(AWS SigV4, GCP service-account OAuth) — warn-only, as before.
Management API (hot reload):
- Generated proxy.yaml enables the v0.39 management listener: loopback
only at tunnel_port+2, bearer key from HERMES_IRON_PROXY_MGMT_KEY.
- Key minted at setup (management.token, 0600); start_proxy injects it
(v0.39 refuses to start when api_key_env is empty).
- hermes egress reload -> POST /v1/reload: re-reads proxy.yaml and
atomically swaps the pipeline; 422 leaves the running ruleset
untouched; actionable errors for not-running / pre-management config /
key mismatch. Secrets changes still require restart (daemon env is
read at spawn) — the CLI says so.
Validation: 218/218 unit+CLI+docker tests; 3/3 gated live E2E against the
real v0.39.0 binary (Authorization swap, x-api-key swap, live reload with
token rotation on the same pid). Docs updated.
Two review findings on the #57922 salvage:
1. Stale inline comment at the login-exchange site still claimed the token
endpoint uses the claude-code/ UA prefix and 404s claude-cli/ — now
contradicts the axios/ fix. Repointed it at _OAUTH_TOKEN_USER_AGENT.
2. The inherited Path.home test isolation on the three TestRefreshOauthToken
tests only stubbed the ~/.claude *file* source, not the macOS Keychain.
_refresh_oauth_token re-reads read_claude_code_credentials() (keychain
first) in its adopt-already-refreshed branch, so on any macOS dev/CI runner
with real Claude Code creds the branch short-circuits and the 3 tests fail.
Stub read_claude_code_credentials -> None so the tests are hermetic.
(The remaining TestResolveAnthropicToken/TestResolveWithRefresh/TestRunOauthSetupToken
failures on macOS are the same pre-existing keychain-leak class on origin/main,
unrelated to this OAuth-UA fix, and pass in CI — left out of scope.)
hermes auth add anthropic fails 100% at token exchange with HTTP 429 while
Claude Code /login succeeds through the same client_id/redirect/scope. The
discriminator is the User-Agent on the /v1/oauth/token request.
Verified live against platform.claude.com (throwaway code, nothing burned):
claude-code/2.1.200 (external, cli) -> 429 rate_limit (Hermes, blocked)
Mozilla/5.0 -> 429 rate_limit
axios/1.7.9 -> 400 invalid_grant (reached validation)
node / empty / SDK-style UAs -> 400 invalid_grant
Anthropic now rate-limits token-endpoint requests whose UA starts with
claude-code/ (the anti-abuse net for Max-sub-as-API-key). This is the same
prefix-block shape that #48534 first hit on claude-cli/, then #56263 dodged by
switching to claude-code/ — which held ~2 weeks and is now blocked too. Bumping
_CLAUDE_CODE_VERSION_FALLBACK cannot help; the gate is prefix-based.
Fix: shared _OAUTH_TOKEN_USER_AGENT (axios/) on the token endpoint only — the
two refresh POSTs (refresh_anthropic_oauth_pure) and the login exchange POST
(run_hermes_oauth_login_pure). The real Claude Code CLI exchanges the auth code
with a bare axios client, NOT its claude-code/ inference UA.
The INFERENCE client (build_anthropic_kwargs, /v1/messages) is deliberately left
on claude-code/ + x-app: cli — that fingerprint is required there and is NOT
throttled on the messages API. Two endpoints, opposite UA requirements.
Also isolate two _refresh_oauth_token tests from live ~/.claude creds and update
the UA regression tests to assert the split (token endpoint uses a
non-claude-code UA while inference keeps claude-code/).
Verified E2E: Hermes' own login path now returns 400 (past the 429 wall)
instead of 429, using the real _OAUTH_TOKEN_USER_AGENT constant against the live
platform.claude.com token endpoint.
Salvaged from #57922 (authorize-host + scope changes dropped as non-load-bearing;
they only add a redirect hop back to claude.ai and the UA fix alone clears 429).
repair_message_sequence Pass 1 registered only tc.get("id") when building
the set of known assistant tool_call ids, then matched tool results against
it by tool_call_id. In the Codex Responses format an assistant tool_call
carries both id (fc_...) and a distinct call_id (call_...); a tool result's
tool_call_id may be keyed on either depending on which builder produced it.
Registering only id made a valid tool result whose tool_call_id matched
call_id look orphaned, so the pass dropped it and left the assistant
tool_call unanswered -- producing HTTP 400 on strict providers (DeepSeek,
Kimi): 'Messages with role tool must be a response to a preceding message
with tool_calls'. Long-running sessions that persisted such a sequence were
permanently broken, re-sending the orphan every turn.
Register both id and call_id for each assistant tool_call so a result
matching either key is recognized, consistent with
AIAgent._get_tool_call_id_static and the compressor's _sanitize_tool_pairs.
Apply the same call_id||id precedence to the corrupted-args sanitizer's
existing-result scan / stub insertion, which had the identical mismatch.
Adds 3 regression tests covering the codex id!=call_id case (match on
call_id, match on only call_id, match on id when both present).
PR #57601's original branch added a top-level reasoning_effort emit to the
LEGACY build_kwargs path (agent/transports/chat_completions.py), but
provider=custom resolves to CustomProfile (plugins/model-providers/custom/),
so chat_completion_helpers takes the profile path and returns early — the
added branch was unreachable dead code for every custom endpoint.
Move the fix to its real site, CustomProfile.build_api_kwargs_extras(), and
follow the DeepSeek/Zai profile precedent:
- disabled -> extra_body.think = False (unchanged)
- enabled + effort -> TOP-LEVEL reasoning_effort (the OpenAI-compatible
format GLM-5.2/ARK expect), passed through verbatim
incl. max/xhigh
- enabled + no effort -> omit, so the endpoint's server default applies
(avoids silently forcing 'medium' as the original
branch did)
Deliberately does NOT force think=True on enable — that flag is Ollama-only
and risks a 400 on GLM/vLLM endpoints that don't recognize it; thinking is
already server-default-on for these backends.
Verified end-to-end through the real profile dispatch (temp HERMES_HOME):
custom+high -> reasoning_effort=high; custom+max -> reasoning_effort=max;
custom+none -> think=False; custom+unset -> nothing; num_ctx composes.
Adds tests/plugins/model_providers/test_custom_profile.py (13 cases).
Addresses the custom-provider half of #55276.
Co-authored-by: huanshan5195 <huanshan5195@users.noreply.github.com>
- Add 'max' to VALID_REASONING_EFFORTS (GLM-5.2 native parameter)
- Emit top-level reasoning_effort string for custom providers
- Stop hardcoding 'medium' in legacy extra_body.reasoning, use actual effort
Custom providers (e.g. GLM-5.2 on Volcengine ARK) silently dropped
reasoning_effort — the value never reached the upstream API. Kimi,
TokenHub, and LM Studio all had dedicated branches for this, but
custom providers had none.
Self-review (hermes-pr-review Phase 2) flagged the mid-turn pre-API
compaction for reuse/duplication (W1/W2); fixing that surfaced a
regression against a deliberate existing feature, now also fixed.
The block now mirrors the turn-prologue preflight's guard chain exactly
(agent/turn_context.py) instead of a hand-rolled pressure limit:
1. should_defer_preflight_to_real_usage(rough) — defer when the rough
estimate is known-noisy vs a recent real provider prompt that fit
under threshold (schema overhead / post-compaction over-count, #36718).
2. get_active_compression_failure_cooldown() — skip during a same-session
compression-failure cooldown.
3. should_compress(rough) — reuses the canonical threshold_tokens (output
room already reserved by _compute_threshold_tokens) plus its summary-LLM
cooldown + anti-thrash guards (#11529).
Dropped the seven inline _reserve/_output_pressure locals (W2: they
re-derived _compute_threshold_tokens and omitted its 85% degenerate-window
fallback). compression_attempts stays as the hard per-turn backstop.
Without guard (1) the block fired a compaction the preflight deliberately
defers, breaking test_413_compression::test_preflight_defers_when_recent_
real_usage_fit (ValueError from the mocked _compress_context). Verified:
test_413_compression 26/26, codex 82/82, and anti-thrash engaged
(_ineffective_compression_count=2) still suppresses the block (0 calls).
The salvaged max-output/pressure fix set conversation_history=None after
the new pre-API compaction. That is only correct for legacy session-
rotation. Under the default in-place compaction (compression.in_place:
True), archive_and_compact inserts the compacted rows into the session DB
directly without stamping them with the intrinsic persisted-marker, so a
subsequent flush with conversation_history=None re-appends them — doubling
the active context and retriggering compression (the early-persist
duplicate-row trap).
Use conversation_history_after_compression(agent, messages), matching the
two existing compaction sites (post-response should_compress and the
turn-prologue preflight), which returns None for rotation and
list(messages) for in-place so the compacted dicts are skipped by identity.
Adds a regression test with a real SessionDB + real archive_and_compact
that asserts the compacted summary row is persisted exactly once (fails
with 2 copies on the None variant).
Follow-up to the salvaged #57845 fix. _can_carry_marker used
any(isinstance(part, dict)) but _apply_cache_marker only marks the LAST
content part, so a list whose last element is a non-dict passed the carrier
gate yet received no marker — wasting one of the four breakpoints. Tighten
the predicate to require content[-1] to be a dict (mirroring the apply
logic) and add a regression test. Flagged by a 3-agent review.
Follow-up to the per-provider guards. Three improvements from review:
1. Extract agent.file_safety.raise_if_read_blocked() as a single shared
chokepoint and route the OpenAI, OpenRouter, and (newly) xAI image
providers through it, replacing the 3x-duplicated inline try/except.
Fixes the whole bug class: xai/_xai_image_field read a model-supplied
local path via open() with no guard — the same vulnerability the PR
fixed for OpenAI/OpenRouter, in a sibling provider it missed.
2. Strengthen the regression tests from pass-on-any-ValueError to true
security invariants: spy open()/read_bytes() and assert the blocked
credential is NEVER read; add negative controls (legit local image
still loads; remote/data: URIs pass through unguarded) so a
block-everything regression can't pass.
3. Guard is best-effort by design (defense-in-depth, not a security
boundary) — documented on the shared helper.
- agent/file_safety.py: raise_if_read_blocked()
- plugins/image_gen/{openai,openrouter,xai}: route through helper
- tests: no-read spies + negative controls across all three providers
Two caching holes made MoA re-bill essentially its entire input stream:
1. AGGREGATOR: anthropic_prompt_cache_policy() judged the agent's own
model/provider — on the MoA path those are the virtual preset name and
'moa', which match no caching branch, so _use_prompt_caching was False
and the acting aggregator (Claude on OpenRouter) ran with ZERO
cache_control breakpoints. Measured on identical opus-4.8 sessions:
85% cache share solo vs 2% via MoA — ~30M re-billed input tokens on one
132-task benchmark run. Fix: when provider == 'moa', resolve the policy
from the preset's real aggregator slot (provider/model/base_url/api_mode
via resolve_runtime_provider).
2. ADVISORS: _run_reference never applied cache_control at all, and
Anthropic caching is opt-in per request — Claude advisors served 0
cache reads across 1,227 benchmark calls (11.5M re-billed input tokens)
even though the advisory view is append-only across iterations (stable
prefix; the synthetic end marker is last so it never pollutes it). Fix:
_maybe_apply_advisor_cache_control() reuses the SAME policy function and
SAME system_and_3 layout as the main loop, judged on the advisor slot's
own resolved runtime — advisor requests are now decorated exactly like
an acting agent on that provider. Auto-caching routes (OpenAI-family)
are left untouched by policy.
Live-verified on the wire (per-iteration opus+gpt5.5 preset, 4 fan-outs):
claude advisor fan-out 2-3 cache_write=2161/2344, fan-out 4
cache_read=2206 / fresh_in=2; aggregator session cache share 84%/77%
(vs 2%/0% before). Sub-1024-token prompts correctly stay uncached
(Anthropic minimum).
A custom:<name> main provider resolves at runtime to the bare provider id
"custom". In the vision auto-detect chain, the main-provider branch called
resolve_provider_client("custom", ...) WITHOUT explicit_base_url/api_key,
so it returned (None, None) ("no endpoint credentials found") and the whole
chain fell through to OpenRouter/Nous. A user on a custom endpoint with no
aggregator configured then got "No LLM provider configured for task=vision
provider=auto" on every image, even though their main model fully supports
vision.
Recover the live endpoint that set_runtime_main() records each turn
(_RUNTIME_MAIN_BASE_URL/_API_KEY/_API_MODE) and forward it to Step 1, with
a fallback to _resolve_custom_runtime() for non-gateway callers. Mirrors the
existing explicit-base_url branch directly above.
Adds TestResolveVisionCustomProvider covering custom, custom:<name>, and the
no-runtime fallback path.
When model.provider is set to custom:<name>, _supports_vision_override()
previously tried only the runtime provider key ('custom') and the raw
config value ('custom:my-proxy'). It did not try the stripped name
('my-proxy'), which is the actual key under providers: in config.yaml.
This caused native image routing to fall back to text mode even when the
user explicitly declared supports_vision: true on the named provider's
model entry.
Fixes#39963
The advisory view appends a synthetic user marker when it ends on an
assistant turn (Anthropic end-on-user rule) — i.e. on every tool iteration
after the first. The user_turn prefix hash treated that marker as the last
user message, so the hashed prefix included the grown mid-turn context and
the signature changed every iteration: advisors re-ran per iteration,
silently defeating the once-per-turn cadence (live smoke test: 2 fan-outs
for a 2-iteration task; expected 1). Hoist the marker to a module constant
and skip it when locating the last REAL user message. Verified: iteration-2
signature now equals iteration-1 (cache HIT); a new real user message still
re-triggers the fan-out.
New preset key 'fanout': 'per_iteration' (default, unchanged behavior)
re-runs the reference fan-out whenever the advisory view changes — every
tool iteration. 'user_turn' runs the advisors ONCE per user turn and lets
the aggregator act alone for the rest of the tool loop — the original MoA
shape (upfront multi-model synthesis, then a single acting model), and the
obvious lever on MoA's wall/cost multiplier (advisor generation dominates
per-turn latency).
Implementation reuses the existing turn-scoped reference cache: in
user_turn mode the cache signature hashes only the prefix up to the LAST
user message, so mid-turn advisory-view growth doesn't change the key and
iteration 2+ is a cache HIT (advice reused, zero advisor spend, no
re-trace). A new user message changes the prefix and re-triggers the
fan-out. Unknown fanout values normalize to per_iteration.
A single-model Hermes agent never sends temperature; the provider default
applies. MoA hardcoded reference_temperature=0.6 / aggregator_temperature=0.4,
and the coercion float(preset.get(key, 0.6) or 0.6) made unset IMPOSSIBLE to
express: absent, null, empty, and even an explicit 0 all collapsed to the
baked-in default. Every MoA advisor and aggregator therefore ran at 0.6/0.4
while the same model running solo used the provider default — silently
skewing solo-vs-MoA comparisons and overriding provider-tuned defaults.
- moa_config normalization: temperatures coerce to None when absent/blank/
invalid (new _coerce_float_or_none); explicit values incl. 0 honored.
- moa_loop: _preset_temperature() resolves preset values; None flows to
call_llm, which already omits the parameter when None (same contract as
max_tokens). Aggregator still inherits the acting agent's own configured
temperature when the preset doesn't pin one.
- conversation_loop (context-mode MoA): same resolution, no more hardcoded
0.6/0.4 at the call site.
- DEFAULT_CONFIG preset + web_server payload models + docs updated: unset
is the default, pinning stays available.
Follow-up to the per-site strips from the review gate. The two copy-site
strips are correct but positional — a copy site added after the assembly
loops would re-leak _db_persisted into the child-session flush. Add a single
terminal sweep (_strip_persistence_markers) run once on the fully-assembled
compressed list so the invariant 'no compacted message leaves compress()
carrying a persistence marker' is structural, not dependent on copy-site order.
- agent/context_compressor.py: _strip_persistence_markers() called before
compress() returns; helper docstring notes the sweep is the authoritative guard
- tests/agent/test_context_compressor.py: structural regression — neuter the
per-site helper to a leaking copy, assert the terminal sweep still strips
- tests/run_agent/test_compression_persistence.py: pin the fixture assumption
behind the exact-equality row-count assertion
Shallow messages[i].copy() during context compression propagated the
_db_persisted marker from cached gateway incremental flushes into the
post-rotation compressed list. _flush_messages_to_session_db then skipped
every row when writing to the new child session, so gateway restarts
lost the compacted transcript (severe amnesia).
Strip the marker in _fresh_compaction_message_copy() and add regression
tests for rotation flush + compressor assembly.
Fixes#57491
Self-review (ruff+ty lint diff = 0 net-new; 2-agent deep review) surfaced one
Warning + comment-accuracy nits; no Critical:
- W1: the local-probe TTL cache memoized None (probe failure) for 30s, so a
probe that failed during a startup race would suppress a legit retry once
the server came up. Cache only positive results — still fully bounds the
hot-path probe rate (reachable servers cache their value) while an
unreachable one re-probes on the next call. Add a regression test asserting
a None result is NOT cached (retry re-probes); mutation-verified.
- Tighten the platform-guard comment: gateway/TUI/cron already construct with
quiet_mode=True (gated by `not agent.quiet_mode`), so the guard's active job
is CLI dedup vs show_banner, not "filling the gateway/TUI gap" as originally
worded.
Verified not-issues (per review): positive-value 30s cache does not break the
reconcile-after-restart freshness contract (restart = fresh process, empty
cache); cache key is collision-safe; platform guard is correct in both
directions (no runtime path leaves platform None on a non-CLI surface).
Tests: 149 passed. ruff clean; ty 0 net-new vs base.
Salvage review of #56431 surfaced one Critical + two Warning issues; fix
them on top of the contributor's cherry-picked commits:
1. Critical — duplicate non-agentic warning on the interactive CLI. The new
agent_init warning fires on every platform, but cli.py show_banner()
already warns on CLI (richer output + /model hint), so a CLI user saw the
warning twice per startup. Guard the agent_init emit to skip platform=="cli"
— it now fills exactly the gateway/TUI gap the PR intended, no duplication.
2. Warning — vLLM error-parse regex under-matched. The patterns required a
literal space before the number, so "max_model_len: 32768", "=32768",
"(32768)", and "... is 32768" all returned None. Broaden both patterns to
accept :/=/(/ 'is' delimiters. Add a parametrized test over all delimiter
variants.
3. Warning — per-call live probe latency on local endpoints. The new
reconcile-on-hit + pre-defaults step-7 probe made every local resolution
fire a synchronous network probe (banner + /model switch + compressor
update_model each within one startup). Add a 30s in-process TTL cache
keyed by (model, base_url) around _query_local_context_length so back-to-
back resolutions reuse one round-trip; not persisted to disk, so the
reconcile freshness contract (re-probe after restart) is preserved. Add an
autouse fixture clearing the cache between tests + TTL coverage.
Tests: 148 passed (was 138). ruff clean.
Reconcile stale local disk cache against live vLLM/Ollama max_model_len
probes, probe local servers before the llama hardcoded default, parse
vLLM max_model_len overflow errors, and surface the non-agentic Hermes 3/4
warning at agent init on gateway/TUI.
Sub-64K live probes are returned for startup rejection but are not
persisted to the context cache — preserving the 64K minimum-context
contract instead of normalizing undersized windows as valid config.
(cherry picked from commit c3a02db4fd)
normalize_usage only read output_tokens_details.reasoning_tokens (the
Responses API shape). Chat Completions providers — OpenAI, OpenRouter,
DeepSeek, and every OpenAI-compatible proxy — report it under
completion_tokens_details.reasoning_tokens, so reasoning_tokens was 0 for
every chat_completions reasoning model: hidden thinking was invisible in
session accounting, MoA traces, and the eval's per-task token columns.
Measured impact (HermesBench MoA run on deepseek-v4-flash, 4,828 advisor
calls): reasoning_tokens showed 0 everywhere while individual calls burned
up to 21.5K hidden thinking tokens to emit ~500 visible tokens. Verified
live against OpenRouter: deepseek-v4-flash returns
completion_tokens_details.reasoning_tokens=61 for a 74-completion-token
call; the field was simply never read.
Responses-shape reads are unchanged; the new read only fires when the
Responses shape yielded nothing.
The terminal-refresh quarantine filtered in-memory entries on
source == "device_code" but built removed_ids from the deleted
"loopback_pkce" source name, so the revoked device-code entry was
never pruned from the persisted pool in auth.json. Also restores the
_print_loopback_ssh_hint test suite scoped to Spotify (the helper's
remaining caller) instead of deleting it wholesale.
Replace the loopback/PKCE-callback server and manual-paste fallback with
the RFC 8628 device-code flow as the only xAI Grok OAuth login path. The
flow works in headless/SSH/container sessions with no 127.0.0.1 listener,
shrinking the local attack surface.
- Poll the token endpoint with server-provided interval, honoring
slow_down and expires_in; store tokens with auth_mode
oauth_device_code.
- Adaptive proactive refresh skew for short-lived device-code JWTs;
rotated tokens sync back to auth.json, the global root store, and the
credential pool (no refresh-token replay).
- Clear source suppression on successful re-login (CLI + dashboard) and
drop the duplicate dashboard pool entry so exactly one seeded
device_code entry exists.
- Use the shared device_code source name for consistency with the
nous/codex device-code providers.
- Desktop: remove the loopback OAuth flow states and dead type variants;
pkce providers' sign-in URL selection is unchanged.
- Docs (EN + zh-Hans) rewritten for device-code login; drop the deleted
--manual-paste flag from documented commands.
Named providers / custom_providers entries in config.yaml now accept an
extra_headers dict scoped to that endpoint — for reverse proxies, API
gateways, and custom auth schemes (e.g. Cloudflare Access service tokens).
- hermes_cli/config.py: normalize extra_headers on provider entries
(_normalize_custom_provider_entry + providers-dict translation), add
get_custom_provider_extra_headers /
apply_custom_provider_extra_headers_to_client_kwargs helpers keyed on
base_url (case/trailing-slash insensitive, no substring bypass —
mirrors the TLS helpers)
- hermes_cli/runtime_provider.py: surface extra_headers in the resolved
runtime for named custom providers (providers dict, legacy
custom_providers list, and the credential-pool path)
- run_agent.py / agent/agent_init.py: merge per-provider extra_headers
onto the OpenAI client default_headers at construction and on every
_apply_client_headers_for_base_url re-application (credential swaps,
rebuilds), most-specific level wins; OpenAI-wire only (native
Anthropic/Bedrock scoped out)
- agent/auxiliary_client.py: accept model.extra_headers as an alias of
model.default_headers for the global variant
- cli-config.yaml.example: documented commented example
- Header values are treated as secrets and never logged
Salvaged from PR #3526 by @jneeee, reimplemented against current main.
Co-authored-by: Teknium <127238744+teknium1@users.noreply.github.com>
