xAI's Responses API returns HTTP 400 ("Model X does not support
parameter reasoningEffort") for grok-4, grok-4-0709, grok-4-fast-*,
grok-4-1-fast-*, grok-3, grok-4.20-0309-*, and grok-code-fast-1 — even
though those models reason natively. Hermes was unconditionally sending
`reasoning: {effort: 'medium'}` to xAI for every Grok model, breaking
direct `--provider xai` for the entire grok-4 line.
Add a substring allowlist predicate (verified live against api.x.ai
2026-05-10) covering the only Grok families that accept the effort dial:
grok-3-mini*, grok-4.20-multi-agent*, grok-4.3*. The Responses transport
omits the `reasoning` key entirely for everything else while still
including `reasoning.encrypted_content` so we capture native reasoning
tokens.
Verified end-to-end: `hermes chat -q hi --provider xai --model grok-4-0709`
went from HTTP 400 to a successful reply.
* feat(i18n): localize /model command output
Reported by @tianma8888: when Chinese users run /model, the labels
("Provider:", "Context:", "_session only_", etc.) are still English.
This routes the static prose through the existing i18n catalog so it
follows display.language / HERMES_LANGUAGE.
Changes:
- locales/{en,zh,ja,de,es,fr,tr,uk}.yaml: add 17 keys under
gateway.model.* covering switched/provider/context/max_output/cost/
capabilities/prompt_caching/warning/saved_global/session_only_hint/
current_label/current_tag/more_models_suffix/usage_*.
- gateway/run.py _handle_model_command: replace hardcoded f-strings in
the picker callback, the text-list fallback, and the direct-switch
confirmation block with t("gateway.model.<key>", ...).
What stays English:
- model IDs, provider slugs, capability strings, cost figures, and the
"[Note: model was just switched...]" prepended to the model's next
prompt (LLM-facing, not user-facing).
- The two slightly-different session-only hints unify on a single key
with the em-dash phrasing.
Validation: tests/agent/test_i18n.py 27/27 passing (parity contract
holds), tests/gateway/ -k 'model or i18n' 74/74 passing.
* feat(i18n): localize all gateway slash command outputs
Expands the i18n catalog from 7 strings to 234 keys across 35 gateway
slash command handlers, so non-English users see localized output for
\`/profile\`, \`/status\`, \`/help\`, \`/personality\`, \`/voice\`, \`/reset\`,
\`/agents\`, \`/restart\`, \`/commands\`, \`/goal\`, \`/retry\`, \`/undo\`,
\`/sethome\`, \`/title\`, \`/yolo\`, \`/background\`, \`/approve\`, \`/deny\`,
\`/insights\`, \`/debug\`, \`/rollback\`, \`/reasoning\`, \`/fast\`,
\`/verbose\`, \`/footer\`, \`/compress\`, \`/topic\`, \`/kanban\`,
\`/resume\`, \`/branch\`, \`/usage\`, \`/reload-mcp\`, \`/reload-skills\`,
\`/update\`, \`/stop\` (plus the \`/model\` block already added in the
previous commit).
Reported by @tianma8888 — Chinese users want command output prose in
their language, not just the labels we already had.
Translations are hand-written for all 8 supported locales (en, zh, ja,
de, es, fr, tr, uk), matching each catalog's existing style: full-width
punctuation in zh, em-dashes in zh/ja/uk, French spaced colons,
German noun capitalization, etc.
What stays English (unchanged):
- Identifiers/values: model IDs, file paths, profile names, session IDs,
command flag names like --global, URLs, config keys.
- Backtick code spans: \`/foo\`, \`config.yaml\`.
- Log messages (logger.info/warning/error).
- LLM-facing system notes prepended to next prompt (e.g. [Note: model
was just switched...]).
- Strings produced by external modules (gateway_help_lines,
format_gateway, manual_compression_feedback) — those have their
own surfaces.
New shared keys for cross-handler boilerplate:
- gateway.shared.session_db_unavailable (5 call sites: branch, title,
resume, topic, _disable_telegram_topic_mode_for_chat)
- gateway.shared.session_not_found (1 site)
- gateway.shared.warn_passthrough (2 sites in /title's f"⚠️ {e}" pattern)
YAML gotcha fixed: \`yolo.on\` and \`yolo.off\` were originally written
unquoted, which YAML 1.1 parses as boolean True/False keys. Renamed to
\`yolo.enabled\` / \`yolo.disabled\` for both safety and clarity.
Test fix: tests/agent/test_i18n.py::test_t_missing_key_in_non_english_falls_back_to_english
now resets the catalog cache on teardown, so the fake "foo: English Foo"
locale doesn't poison the module-level cache for subsequent tests in
the same xdist worker. (Without this, every gateway slash command test
that shares a worker with the i18n suite would see the fake catalog.)
Validation:
- tests/agent/test_i18n.py: 27/27 (parity contract — every key in every
locale, matching placeholder tokens).
- tests/gateway/: 5077 passed, 0 failed (full gateway suite).
- 180 t() call sites added across 35 handlers; 1872 catalog entries
total (234 keys × 8 locales).
* feat(i18n): add 8 new locales — af, ko, it, ga, zh-hant, pt, ru, hu
Expands the static-message catalog from 8 → 16 languages, each with full
270-key parity against the English source-of-truth. Every locale now
covers the same surface PR #22914 added: approval prompts plus all 35
gateway slash command outputs.
New locales:
- af Afrikaans (community ask in #21961 by @GodsBoy; PRs #21962, #21970)
- ko Korean (PRs #20297 by @tmdgusya, #22285 by @project820)
- it Italian (PR #20371 by @leprincep35700)
- ga Irish/Gaeilge (PR #20962 by @ryanmcc09-dot)
- zh-hant Traditional Chinese (PRs #20523 by @jackey8616, #13140 by @anomixer)
- pt Portuguese (PRs #20443 by @pedroborges, #15737 by @carloshenriquecarniatto, #22063 by @Magaav)
- ru Russian (PR #22770 by @DrMaks22)
- hu Hungarian (PR #22336 by @lunasec007)
Each locale uses native-quality translations matching the existing tone
and conventions of the older 8 locales:
- zh-hant uses 繁體 characters with TW/HK technical vocabulary (軟體
not 软件, 連線 not 连接, 設定 not 设置, 訊息 not 消息, 工作階段 not 会话, 程式
not 程序, 預設 not 默认, 伺服器 not 服务器), full-width punctuation 「：（）」.
- ko uses formal 합니다체 (습니다/합니다) register throughout.
- pt uses European Portuguese as baseline with neutral PT/BR vocabulary
where possible.
- ga uses standard An Caighdeán Oifigiúil; English loanwords retained
for tech terms without good Irish equivalents (gateway, API, JSON).
- All preserve {placeholder} tokens, backtick code spans, slash commands,
brand names (Hermes, MCP, TTS, YOLO, OpenAI, Telegram, etc.), and emoji.
Aliases added in agent/i18n.py:
- af-za, Afrikaans → af
- ko-kr, Korean, 한국어 → ko
- it-it, italiano → it
- ga-ie, Irish, Gaeilge → ga
- zh-tw, zh-hk, zh-mo, traditional-chinese → zh-hant (note: zh-tw used to
alias to zh; now aliases to its own zh-hant catalog)
- zh-cn, zh-hans, zh-sg → zh (unchanged from before)
- pt-pt, pt-br, brazilian, portuguese → pt
- ru-ru, Russian, русский → ru
- hu-hu, Magyar → hu
The zh-tw alias re-routing is intentional: previously typing 'zh-TW' got
the Simplified Chinese catalog (wrong vocabulary for Taiwan/HK users).
Now those users get the proper Traditional Chinese catalog.
Validation:
- tests/agent/test_i18n.py: 43/43 (parity contract holds for all 16
languages × 270 keys = 4320 catalog entries, with matching placeholder
tokens).
- E2E alias resolution verified for all 19 alias inputs (Afrikaans, ko-KR,
한국어, italiano, Gaeilge, zh-TW, zh-HK, traditional-chinese, pt-BR,
brazilian, Magyar, etc.).
- tests/gateway/: 5198 passed (3 pre-existing TTS routing failures
unrelated to i18n).
Credit to all contributors whose PRs surfaced these language requests.
Their original PRs may now be closed as superseded with credit.
* feat(dashboard-i18n): add 14 web dashboard locales matching the static catalog
Brings the React dashboard (web/src/) up to the same 16-language
coverage the static catalog already has after the previous commits in
this PR. The Translations interface is TypeScript-typed, so every new
locale must provide every key — tsc -b is the parity guard.
Languages added (each is a complete 429-line locale file):
- af Afrikaans
- ja Japanese (PR #22513 by @snuffxxx surfaced this)
- de German (PR #21749 by @mag1art)
- es Spanish (PR #21749)
- fr French (PRs #21749, #10310 by @foXaCe)
- tr Turkish
- uk Ukrainian
- ko Korean (PRs #21749, #18894 by @ovstng, #22285 by @project820)
- it Italian
- ga Irish (Gaeilge)
- zh-hant Traditional Chinese (PR #13140 by @anomixer)
- pt Portuguese (PRs #22063 by @Magaav, #22182 by @wesleysimplicio, #15737 by @carloshenriquecarniatto)
- ru Russian (PRs #21749, #22770 by @DrMaks22)
- hu Hungarian (PR #22336 by @lunasec007)
Each translation covers all 15 namespaces with full key parity vs en.ts,
preserves every {placeholder} token verbatim, keeps identifiers
untranslated (brand names, file paths, cron expressions, code spans),
translates the language.switchTo tooltip into the target language, and
matches existing tone conventions (zh-hant uses TW/HK vocab; ja uses
formal desu/masu; ko uses formal seumnida register; ga uses An
Caighdean Oifigiuil with English loanwords for tech vocab without good
Irish equivalents).
Plumbing:
- web/src/i18n/types.ts: Locale union expanded to all 16 codes.
- web/src/i18n/context.tsx: imports all 16 catalogs; exports
LOCALE_META (endonym + flag per locale); isLocale() type guard.
- web/src/i18n/index.ts: re-export LOCALE_META.
- web/src/components/LanguageSwitcher.tsx: replaced two-state EN-ZH
toggle with a click-to-open dropdown listing all 16 languages.
Note: zh-hant.ts exports zhHant (camelCase) since hyphen is invalid in
a JS identifier; the canonical 'zh-hant' string keys it in TRANSLATIONS.
Validation:
- npx tsc -b: 0 errors. Every locale satisfies Translations.
- npm run build (tsc + vite production): green, 2062 modules.
- Each locale file is exactly 429 lines.
Out of scope: plugin dashboards (kanban/achievements ship as prebuilt
bundles with no source in repo); Docusaurus docs (separate surface);
TUI (no i18n yet).
* feat(plugin-i18n): localize achievements + kanban plugin dashboards across all 16 locales
Brings the two shipped plugin dashboards (hermes-achievements, kanban)
under the same i18n umbrella as the core dashboard PR #22914 just
established. Both bundles now read user-facing strings from the host's
i18n catalog via SDK.useI18n() instead of hardcoded English.
## Approach
Plugin dashboards ship as prebuilt IIFE bundles in
plugins/<name>/dashboard/dist/index.js — no build step, no source in
repo (upstream-authored, vendored as compiled JS). Earlier contributor
PRs (#22594, #22595, #18747) tried direct edits but didn't actually
wire the bundles to read translations.
This change does the wiring properly:
1. Each bundle gets a useI18n shim at IIFE scope:
const useI18n = SDK.useI18n
|| function () { return { t: { kanban: null }, locale: "en" }; };
Older host SDKs without useI18n still load the bundle and render
English fallbacks.
2. A small tx(t, path, fallback, vars) helper resolves dotted keys
under the plugin's namespace (t.kanban.* or t.achievements.*) and
interpolates {placeholder} tokens.
3. Every React component starts with const { t } = useI18n() and
each user-visible string is wrapped in tx(t, "key", "English fallback").
Helpers called outside React components (window.prompt callers,
constants used during init) take t as a parameter.
4. Top-level constants that were English dictionaries (COLUMN_LABEL,
COLUMN_HELP, DESTRUCTIVE_TRANSITIONS, DIAGNOSTIC_EVENT_LABELS in
kanban) become getColumnLabel(t, status)-style functions backed by
FALLBACK_* dictionaries.
## Translations added
Two new top-level namespaces added to the dashboard's TypeScript-typed
Translations interface:
- achievements: ~70 keys covering the hero, scan banner, achievement
card, share dialog, stats, filters, and empty states.
- kanban: ~145 keys covering the board, columns (with nested
columnLabels and columnHelp sub-dicts), card detail panel,
bulk-actions toolbar, dependency editor, board switcher, and
diagnostic callouts.
Each key is provided across all 16 supported locales:
en, zh, zh-hant, ja, de, es, fr, tr, uk, af, ko, it, ga, pt, ru, hu.
Total new translation entries: ~3,440 (215 keys × 16 locales).
## What stays English (deliberate)
- API paths, CSS class names, data-* attributes, JSON keys, regex
strings, URLs, file paths (~/.hermes/kanban.db, boards/_archived/).
- State identifier strings used as lookup keys (triage / todo / ready /
running / blocked / done / archived) — labels translate, key strings
don't.
- The PNG share-card text rendered to canvas in the achievements
ShareDialog (HERMES AGENT watermark, UNLOCKED stamp, tier names) —
these become part of a globally-shared image and stay English.
- localStorage keys (hermes.kanban.selectedBoard).
- Brand names (Kanban, Hermes, WebSocket, Nous Research).
## Contributor credit
PR #22594 by @02356abc and PR #22595 by @02356abc supplied the
en + zh kanban namespace skeleton (145 keys); used as the en source-
of-truth in this commit and translated to the other 14 locales.
PR #18747 by @laolaoshiren first surfaced the achievements
localization request.
## Validation
- npx tsc -b: 0 errors. All 16 locale .ts files satisfy the
Translations type with full key parity.
- npm run build (tsc + vite production build): green, 2062 modules,
1.56MB JS / 95KB CSS, ~2.5s build.
- node --check on both plugin bundles: parse cleanly.
- 126 tx() call sites in kanban, 46 in achievements.
## Out of scope
- TUI (ui-tui/) has no i18n infrastructure yet.
- Docusaurus docs (website/i18n/) — already had zh-Hans; expanding
is a separate translation workstream (Thai / Korean / Hindi PRs).
* feat(plugins): host-owned LLM access via ctx.llm
Plugins can now ask the host to run a one-shot chat or structured
completion against the user's active model and auth, without ever
seeing an OAuth token or API key. Closes the gap where plugins that
needed bounded structured inference (receipts, CRM extraction,
support classification) had to either bring their own provider keys
or register a tool the agent had to call.
New surface on PluginContext:
- ctx.llm.complete(messages, ...)
- ctx.llm.complete_structured(instructions, input, json_schema, ...)
- async siblings ctx.llm.acomplete / acomplete_structured
Backed by the existing auxiliary_client.call_llm pipeline — every
provider, fallback chain, vision routing, and timeout policy Hermes
already supports applies automatically.
Trust gate (fail-closed by default):
- plugins.entries.<id>.llm.allow_model_override
- plugins.entries.<id>.llm.allowed_models (allowlist; '*' = any)
- plugins.entries.<id>.llm.allow_agent_id_override
- plugins.entries.<id>.llm.allow_profile_override
Embedded model@profile shorthand goes through the same gate as
explicit profile=, so it can't bypass the auth-profile policy.
Conflicting explicit and embedded profiles fail closed.
Also lands:
- plugins/plugin-llm-example/ — reference plugin that registers
/receipt-extract, demonstrating image+text structured input,
jsonschema validation, and the trust-gate config.
- website/docs/developer-guide/plugin-llm-access.md — full API docs.
- 45 unit tests covering trust gates, JSON parsing, schema
validation, image encoding, async surface, and config loading.
Validation:
- 2628 tests pass in tests/agent/
- E2E: bundled plugin loaded with isolated HERMES_HOME, slash
command produced parsed JSON via stubbed call_llm
- response_format extra_body wired correctly for both json_object
and json_schema modes
* docs(plugin-llm): rewrite quickstart and framing
The quickstart now uses a meeting-notes-to-tasks example instead of
a receipt extractor, and the page leads with hook-time / gateway
pre-filter / scheduled-job framing rather than the OpenClaw
KB/support/CRM/finance/migration enumeration that the original
upstream PR used. Receipt example moved to a separate worked
example link so the docs page itself doesn't echo any of the
upstream framing.
Also clarifies where ctx.llm fits in the broader plugin surface
(table comparing register_tool / register_platform / register_hook
/ etc.) and what makes this lane different from auxiliary_client
internals.
No code change.
* docs(plugin-llm): reframe as any LLM call, not just structured output
The original draft leaned heavily on complete_structured() and made
the chat lane (complete() / acomplete()) feel like a footnote.
Restructure so:
- The page title and description say 'any LLM call.'
- The lead shows BOTH a plain chat call (error rewriter) AND a
structured call (triage scorer) up top.
- Quick start has two complete plugin examples — /tldr (chat) and
/paste-to-tasks (structured).
- New 'When to use which' table for choosing complete() vs
complete_structured() vs the async siblings.
- Trust-gate sections explicitly note 'all four methods,' and the
request-shaping list calls out chat-only fields (messages) and
structured-only fields (instructions, input, json_schema)
alongside each other.
- The 'Where this fits' section now says 'for any reason,
structured or not.'
The receipt-extractor reference plugin still exists under
plugins/plugin-llm-example/ — but the docs page no longer treats
it as the canonical surface example. It's now described as 'a third
worked example, this time with image input.'
No code change.
* feat(plugin-llm): split provider/model into independent explicit kwargs
The first cut accepted a single 'provider/model' slug on every method
and split it internally. That looked clean but broke under live test:
the model-override path tried to use the slug's vendor prefix as a
literal Hermes provider id, which silently switched the user off
their aggregator (e.g. plugin asks for 'openai/gpt-4o-mini' on a user
who routes through OpenRouter — host attempted to call the 'openai'
provider directly, failed because OPENAI_API_KEY wasn't set).
New shape mirrors the host's main config:
ctx.llm.complete(
messages=[...],
provider='openrouter', # gated, optional
model='openai/gpt-4o-mini', # gated, optional
profile='work', # gated, optional
...
)
Each is independently gated by its own allow_*_override flag.
Granting model-override does NOT auto-grant provider-override.
Allowlists are now per-axis (allowed_providers, allowed_models)
matched literally against whatever string the plugin sends.
Dropped 'model@profile' embedded-suffix shorthand entirely. Hermes
doesn't use that pattern anywhere else; profile= is its own kwarg.
Live E2E (against real OpenRouter via Teknium's config) confirms:
- zero-config call works
- default-deny blocks each override with a helpful error
- model-only override stays on user's active provider (the bug)
- provider+model override switches cleanly
- allowlist refuses non-listed entries
- structured output round-trip parses + schema-validates
Tests: 49 cases (up from 45); all green. Docs updated to match the
new shape, including a 'most plugins never need this section' callout
on the trust-gate config block.
* fix+cleanup(plugin-llm): real attribution, hook-mode coverage, move example out of core
Three integration fixes for the ctx.llm surface:
1. Attribution bug — result.provider and result.model now reflect
what call_llm actually used, not placeholder fallbacks ('auto',
'default'). New _resolve_attribution() helper:
- explicit overrides win (what the call targeted)
- response.model wins for the recorded model (provider
canonicalisation: 'gpt-4o' → 'gpt-4o-2024-08-06' etc.)
- falls back to _read_main_provider() / _read_main_model()
when no override is set, so audit logs reflect the user's
active main provider/model
- 'auto' / 'default' only when EVERYTHING is empty
Live verified: zero-config call now records
provider='openrouter', model='anthropic/claude-4.7-opus-20260416'
instead of provider='auto', model='default'.
2. Hook-mode coverage — TestHookMode confirms ctx.llm.complete
works from inside a registered post_tool_call callback. The
docs page promised hook integration; now there's a test that
exercises the lazy-import path through the real invoke_hook
machinery. Two cases: traceback-rewrite hook with conditional
ctx.llm.complete, and minimal hook regression for the
sync-hook + sync-llm path.
3. Reference plugin moved out of core. plugins/plugin-llm-example/
is gone from hermes-agent — it now lives in the new
NousResearch/hermes-example-plugins companion repo. The docs
page links there. Hermes' bundled plugins should be plugins
users actually run; reference / docs-companion plugins live
externally.
Test count: 56 (up from 49). Wider sweep on tests/hermes_cli/
+ tests/gateway/ + tests/tools/ + tests/agent/ shows 16770
passing; the 12 failures are all pre-existing on origin/main
(verified by stashing this branch's changes and re-running) —
kanban-boards, delegate-task, gateway-restart, tts-routing —
none touch the plugin_llm surface.
* chore(plugins): move all example plugins to companion repo
Reference / docs-companion plugins now live exclusively in
NousResearch/hermes-example-plugins, not bundled with the core repo:
- example-dashboard
- strike-freedom-cockpit
A new fourth example, plugin-llm-async-example, was added to that
repo demonstrating ctx.llm's async surface (acomplete()) with
asyncio.gather() — registers /translate <lang>: <text> which fires
forward translation + sentiment classifier in parallel, then a
back-translation for QA. Live-tested at 2.5s for three real
provider round-trips (would be ~5-6s sequential).
Docs updated:
- developer-guide/plugin-llm-access.md links both sync and async
examples in the Reference section
- user-guide/features/extending-the-dashboard.md repoints both demo
sections to the companion repo with corrected install paths
- user-guide/features/built-in-plugins.md drops the two demo rows
- AGENTS.md notes that example plugins live in the companion repo
Net: hermes-agent's plugins/ directory now contains only plugins
users actually run (memory providers, dashboard tabs that ship real
features, the disk-cleanup hook, platform adapters). All four
demo / reference plugins live externally where they can be cloned
on demand instead of inflating the core install.
Surfaces the pin command at the moment users care about it: when a
consolidation just landed against their skill library and they're
looking at the umbrella name in the curator output. Previously `hermes
curator pin` existed but had no discovery surface — users only learned
it existed by reading docs or stumbling onto `hermes curator --help`.
The hint:
archived 3 skill(s):
• docx-extraction → document-tools
• pdf-extraction → document-tools
• old-stale — pruned (stale)
full report: hermes curator status
keep an umbrella stable: hermes curator pin document-tools
Gated on having at least one consolidation that produced an umbrella.
Pruned-only runs (nothing surviving to pin) skip the hint. When
multiple umbrellas were produced, picks alphabetically first as a
concrete example rather than listing them all.
3 new tests in tests/agent/test_curator_classification.py covering:
consolidation produces hint with real umbrella name, pruned-only run
omits it, multi-umbrella picks one example.
Two follow-ups from self-review:
1. Add gpt-5.3-codex-spark to DEFAULT_CONTEXT_LENGTHS at 128k. The
primary resolution path for Spark goes through provider='openai-codex'
→ _CODEX_OAUTH_CONTEXT_FALLBACK (already correct). But if any future
code path resolves Spark's context with a different provider (custom
proxy, generic fallthrough), the longest-substring-first lookup in
step 8 would match 'gpt-5' and report 400k, which is wrong by ~3x.
Adding the explicit override is a cheap defensive correctness fix
matching how gpt-5.4-mini and gpt-5.4-nano already shadow the generic
gpt-5 entry.
2. Update test_openai_codex_model_validation_fallback.py docstring. The
bug it was originally written for (gpt-5.3-codex-spark missing from
listing) is now resolved by this PR's catalog restoration. The test
still validly exercises the soft-accept code path for any future
entitlement-gated Codex slug that ships before Hermes catalogs it,
but the framing was stale — clarified.
PR #12994 stripped gpt-5.3-codex-spark on the assumption that it was
unsupported. It's actually research-preview, ChatGPT-Pro-only, exposed
via the Codex OAuth backend at chatgpt.com/backend-api/codex/models —
not via the public OpenAI API.
Add explanatory comments in:
- DEFAULT_CODEX_MODELS / _FORWARD_COMPAT_TEMPLATE_MODELS (codex_models.py)
- _CODEX_OAUTH_CONTEXT_FALLBACK (model_metadata.py)
- list_authenticated_providers' live-discovery branch (model_switch.py)
so future maintainers don't strip the entry again. Also documents the
intentional asymmetry that Spark stays out of the "openai" provider
catalog (it isn't on the public API) and why the supported_in_api
filter is *not* applied for the openai-codex route.
When the active main model has native vision and the provider supports
multimodal tool results (Anthropic, OpenAI Chat, Codex Responses, Gemini
3, OpenRouter, Nous), vision_analyze loads the image bytes and returns
them to the model as a multimodal tool-result envelope. The model then
sees the pixels directly on its next turn instead of receiving a lossy
text description from an auxiliary LLM.
Falls back to the legacy aux-LLM text path for non-vision models and
unverified providers.
Mirrors the architecture used in OpenCode, Claude Code, Codex CLI, and
Cline. All four converge on the same pattern: tool results carry image
content blocks for vision-capable provider/model combinations.
Changes
- tools/vision_tools.py: _vision_analyze_native fast path + provider
capability table (_supports_media_in_tool_results). Schema description
updated to reflect new behaviour.
- agent/codex_responses_adapter.py: function_call_output.output now
accepts the array form for multimodal tool results (was string-only).
Preflight validates input_text/input_image parts.
- agent/auxiliary_client.py: _RUNTIME_MAIN_PROVIDER/_MODEL globals so
tools see the live CLI/gateway override, not the stale config.yaml
default. set_runtime_main()/clear_runtime_main() helpers.
- run_agent.py: AIAgent.run_conversation calls set_runtime_main at turn
start so vision_analyze's fast-path check sees the actual runtime.
- tests/conftest.py: clear runtime-main override between tests.
Tests
- tests/tools/test_vision_native_fast_path.py: provider capability
table, envelope shape, fast-path gating (vision-capable model uses
fast path; non-vision model falls through to aux).
- tests/run_agent/test_codex_multimodal_tool_result.py: list tool
content becomes function_call_output.output array; preflight
preserves arrays and drops unknown part types.
Live verified
- Opus 4.6 + Sonnet 4.6 on OpenRouter: model calls vision_analyze on a
typed filepath, gets pixels back, reads exact text from images that
no aux description could capture (font color irony, multi-line
fruit-count list, etc.).
PR replaces the closed prior efforts (#16506 shipped the inbound user-
attached path; this PR closes the gap for tool-discovered images).
* feat(curator): show rename map (where skills went) in user-visible summary
The full data has always been on disk in REPORT.md, but the user-visible
curator summary (gateway 💾 line, CLI session-start panel,
`hermes curator status`) was counts-only — "consolidated 4 into 2
umbrellas" with no names. Users only discovered renames when something
they expected was gone.
New `_build_rename_summary()` formats the rename map and appends it to
`final_summary`:
auto: 1 marked stale; llm: consolidated 2 into 1, pruned 1
archived 3 skill(s):
• docx-extraction → document-tools
• pdf-extraction → document-tools
• old-stale-thing — pruned (stale)
full report: hermes curator status
Empty on no-op ticks (no archives), so most ticks add zero log noise.
Cap of 10 entries keeps agent.log readable when a 50-skill
consolidation lands; the full list is always in REPORT.md.
`hermes curator status` indents continuation lines so the multi-line
summary reads as one logical field.
5 new tests in tests/agent/test_curator_classification.py covering
empty / consolidation / pruning / cap / mixed cases.
* feat(curator): show recent run summary once on `hermes update`
The rename map is now visible from where users actually look — the
update flow they explicitly run, instead of just the live gateway log
or transient CLI session-start panel.
Behavior:
- After `hermes update`, if the most recent curator run produced a
rename map (multi-line summary) that the user hasn't seen yet, print
it once with a 'last run Xh ago' header and a one-time-message
footer.
- Stamp `last_run_summary_shown_at = last_run_at` after printing so
subsequent `hermes update` invocations are silent until a newer
curator run lands.
- Silent on no-op runs (single-line summary like 'auto: no changes;
llm: no change'). Still stamps shown so we don't reconsider on
every update.
- Silent when the curator has never run (the existing first-run
notice handles that case).
Output:
ℹ Skill curator — last run 4h ago
auto: 1 marked stale; llm: consolidated 2 into 1, pruned 1
archived 3 skill(s):
• docx-extraction → document-tools
• pdf-extraction → document-tools
• old-stale-thing — pruned (stale)
full report: hermes curator status
(This message shows once per curator run. View anytime: hermes curator status)
State migration:
- `_default_state()` gains `last_run_summary_shown_at: None`. Existing
state files lack the field; `.get()` returns None; the comparison
treats any prior run as 'not yet shown' and prints once on next
update. Self-healing.
Wiring:
- Both `hermes update` paths in main.py call the new
`_print_curator_recent_run_notice()` right after the existing
first-run notice. Best-effort try/except so a state-load bug
never breaks the update flow.
6 tests in tests/hermes_cli/test_curator_recent_run_notice.py:
no-run / single-line / multi-line / show-once / new-run-resets /
time-formatter buckets.
RuntimeError('claude CLI turn timed out') from a local OpenAI-compatible
shim was falling through to FailoverReason.unknown, surfacing as 'Empty
response from model' and burning 3 retry slots on the same failing
endpoint. _classify_by_message had no timeout-message branch — only
billing/rate_limit/auth/context_overflow/model_not_found patterns. The
type-based check at line 565 also requires isinstance(error, (TimeoutError,
ConnectionError, OSError)) — a plain RuntimeError doesn't match.
Add _TIMEOUT_MESSAGE_PATTERNS for 'timed out', 'deadline exceeded',
'request timed out', 'operation timed out', 'upstream timed out', 'turn
timed out'. _classify_by_message returns FailoverReason.timeout (retryable=True)
when any pattern matches.
Salvage of #22664's classifier portion. The original PR also bundled a
fallback self-selection guard which is now redundant (already on main
via #22780) plus DeepSeek thinking and session_search fixes that are
their own separate concerns.
Follow-up to #22780 — fixes the still-broken classification of
generic-typed provider-shim timeouts that #22780's dedup didn't cover.
Problem:
When a provider or proxy drops a streaming response mid-flight (httpcore
raises RemoteProtocolError: "incomplete chunked read", "peer closed
connection", "response ended prematurely", etc.), _generate_summary
would not classify it as a transient error. Instead of retrying on the
main model, it entered the generic 60-second cooldown, leaving context
growing unbounded until the cooldown expired. Issue #18458.
Root cause:
_is_connection_error in auxiliary_client.py did not match httpcore's
streaming premature-close error substrings. context_compressor.py's
_generate_summary except block never called _is_connection_error, so
those errors fell through to the 60-second generic cooldown rather than
triggering the retry-on-main fallback path used for timeouts.
Fix:
1. auxiliary_client.py — extend _is_connection_error keyword list with:
"incomplete chunked read", "peer closed connection",
"response ended prematurely", "unexpected eof",
"remoteprotocolerror", "localprotocolerror".
Also guard the `from openai import ...` with try/except ImportError
so the function works in environments without the openai package.
2. context_compressor.py — import _is_connection_error and call it in
_generate_summary's except block as _is_streaming_closed. Include
_is_streaming_closed in the fallback-to-main condition (alongside
_is_model_not_found, _is_timeout, _is_json_decode) and use the
shorter 30s transient cooldown for streaming-closed errors.
Tests:
4 new regression tests in TestStreamingClosedFallback:
- test_incomplete_chunked_read_falls_back_to_main
- test_peer_closed_connection_falls_back_to_main
- test_streaming_closed_on_main_uses_short_cooldown (stash-verified)
- test_non_streaming_unknown_error_still_uses_long_cooldown
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Pick openrouter/pareto-code as your model and OpenRouter auto-routes each
request to the cheapest model meeting your coding-quality bar (ranked by
Artificial Analysis). The new openrouter.min_coding_score config key (0.0-1.0,
default 0.65) tunes the floor.
- hermes_cli/models.py: add openrouter/pareto-code to OPENROUTER_MODELS so
it shows up in the picker with a description
- hermes_cli/config.py: add openrouter.min_coding_score (default 0.65 — lands
on a mid-tier coder on the current Pareto frontier)
- plugins/model-providers/openrouter: emit extra_body.plugins =
[{id: pareto-router, min_coding_score: X}] when model is openrouter/pareto-code
AND the score is a valid float in [0.0, 1.0]
- agent/transports/chat_completions.py: same emission on the legacy flag
path (when no provider profile is loaded)
- run_agent.py: openrouter_min_coding_score kwarg + storage; plumbed into
both build_kwargs() invocations and the context-summary extra_body path
- cli.py: read openrouter.min_coding_score once at init, validate float in
[0,1], pass to AIAgent constructions (CLI + background-task paths)
- cron/scheduler.py, batch_runner.py, tools/delegate_tool.py,
tui_gateway/server.py: propagate the kwarg (mirrors providers_order
plumbing — subagents inherit, cron/batch read from config)
- tests: profile-level + transport-level coverage of the model gating,
unset/empty/out-of-range handling, and the legacy flag path
- docs: new 'OpenRouter Pareto Code Router' section in providers.md
Verified end-to-end against api.openrouter.ai: at score=0.65 we land on a
mid-tier coder, at omission we get the strongest. Score is silently dropped
on any model other than openrouter/pareto-code, so it's safe to leave set.
Pass session_id through to provider profile build_api_kwargs_extras so
the OpenRouter profile can attach an xAI cache-affinity header
(x-grok-conv-id: <session-id>) for x-ai/grok-* models. xAI prompt
cache requires server affinity via this header — without it the cache
is poisoned and Grok prompt-cache hit rates drop dramatically on
multi-turn sessions.
Carve-out of #22708 by Ninso112. The original PR bundled a /diff
slash command, a zsh completion fix (already on main via #22802),
and holographic memory null-guards. This salvage keeps just the
Grok header work — small, targeted, and well-tested. Other
contributors and changes preserved for separate review.
Closes#22705.
Two co-located fixes:
1. agent/model_metadata.py: bump hy3-preview static fallback from
256000 to 262144 (256 * 1024) to match OpenRouter live metadata
so cache and offline both agree (issue #22268).
2. tests/hermes_cli/test_tencent_tokenhub_provider.py: replace the
exact-value change-detector (assert ctx == 256000) with an
invariant assertion (registered + >= 4096). Per AGENTS.md
'Don't write change-detector tests': pinning the upstream-controlled
context length is exactly the test class the rule forbids — it
breaks every time the provider bumps the published value, with
zero behavioral coverage gained.
Salvage of #22574 with a redirect on the test approach. The
contributor's diff bumped the integer and added a SECOND
change-detector pinning DEFAULT_CONTEXT_LENGTHS[hy3-preview] == 262144,
which would re-break on the next published bump. We instead delete
the change-detector entirely and assert the relationship.
Closes#22268.
`fetch_models_dev()` is on the hot path of every `AIAgent.__init__`
(via `context_compressor → get_model_context_length`). The previous
policy was "always try network first, only fall back to disk if
network fails," so every fresh `hermes chat` / `hermes gateway` /
batch / cron process paid 250-500 ms re-fetching a 2 MB JSON registry
that was already on disk from earlier runs.
Add a stage 2 between in-mem and network: if
`models_dev_cache.json` exists and its mtime is younger than the
existing `_MODELS_DEV_CACHE_TTL` (1 hour, same TTL the in-mem cache
already uses), load from disk and skip the network call.
The in-mem TTL is anchored to the disk file's age, so a 50-min-old
cache stays in-memory for only 10 more minutes — no surprise
extension of staleness window.
Invariants preserved:
- `force_refresh=True` still always hits the network and only falls
back to disk on failure (`hermes config refresh` semantics).
- Missing disk cache → fall through to network (first-ever run).
- Stale disk cache (mtime > TTL) → fall through to network.
- Negative file age (clock skew) → fall through to network.
- Network failure → existing stage-4 stale-disk fallback unchanged.
Measured impact (3-run medians, 9950X3D, fresh process per run):
fetch_models_dev cold: 256 → 17 ms (-93%)
hermes chat -q wall: 4.00 → 3.73 s (-7% median)
3.99 → 3.60 s (-10% min)
The chat-end-to-end win is bounded below by API latency variance, but
the fetch_models_dev microbenchmark is the cleanest signal: 239 ms
shaved off every fresh-process agent construction.
Win compounds with the previous perf PRs:
#22681 google_chat lazy-load
#22766 doctor parallel + IMDS off
#22790 gateway.platforms PEP 562
Tests: all 30 `tests/agent/test_models_dev.py` pass (added 4 new ones
covering the new disk-cache-first path, force_refresh override, stale
disk fallback, and missing-disk-cache fall-through). Full `tests/agent/`
suite: 2560 passed, 0 failed.
The is_xai_responses branch only sent include=[reasoning.encrypted_content]
without forwarding the resolved reasoning_effort. Other Responses providers
(OpenAI, GitHub) already get effort forwarded — this aligns the xAI path.
Without this, agent.reasoning_effort is silently dropped on the xAI direct
path, making Hermes unable to control reasoning depth on grok-4.x via
api.x.ai. Tests added to TestCodexBuildKwargs cover effort passthrough,
disabled state, and minimal-clamp parity with non-xAI.
The model regularly writes session-outcome facts to MEMORY.md despite
the existing 'Do NOT save task progress' line — entries like
'Submitted PR #22577 for the kanban dedup fix' or 'Fixed bug X in
file Y'. These are stale within days, pollute the system prompt,
and crowd out durable user preferences (the issue #22563 reporter
saw 9 sections of bug-fix notes injected on a brand-new task).
Add explicit examples of what NOT to save (PR numbers, issue
numbers, commit SHAs, 'fixed/submitted/Phase N done', file counts)
plus the 7-day-staleness heuristic so the model has a concrete
calibration target rather than guessing what counts as 'task progress'.
Closes#22563 (the prompt-side, low-risk portion). The bigger
relevance-based-injection / vector-retrieval feature requested in
#22563 is tracked under #2184 (Richer local memory). Per skill rule
on prompt caching, dynamic memory injection breaks the frozen-snapshot
invariant and needs a separate design call.
`ToolCall.extra_content` was annotated `Optional[Dict[str, Any]]`,
but neither `Optional` nor `Dict` are imported at the top of
`agent/transports/types.py` — only `Any` is. The rest of the file
consistently uses PEP 604 / 585 syntax (e.g. `str | None`,
`dict[str, Any] | None`).
The file has `from __future__ import annotations`, so the missing
names don't crash class definition. But the annotation IS evaluated
when anything calls `typing.get_type_hints(ToolCall)` —
introspection raises `NameError: name 'Optional' is not defined`.
ruff catches it cleanly:
F821 Undefined name `Optional` agent/transports/types.py:65:32
F821 Undefined name `Dict` agent/transports/types.py:65:41
Switch the annotation to `dict[str, Any] | None` to match the
rest of the file's style. No new imports needed.
Verified:
- ruff F-checks now pass on the file
- `typing.get_type_hints(ToolCall)` succeeds where it raised before
- 166/166 tests in tests/agent/transports/ pass on Windows + Python 3.12
WebUI sessions construct AIAgent(platform="webui") but PLATFORM_HINTS
had no "webui" entry, so the agent received no platform hint at all.
The WebUI frontend supports rich MEDIA:/absolute/path previews for
images, audio, video, PDF, HTML, CSV, diffs, and Excalidraw, but
without a hint the agent either ignores MEDIA: or falls back to
Markdown image syntax which silently fails for local files.
Add a webui hint that documents the MEDIA: render path and warns
against  for local files.
Fixes#21883
When an auxiliary LLM provider (or an upstream proxy) returns a non-JSON
body with `Content-Type: application/json` — e.g. an HTML 502 page from a
misconfigured gateway — the OpenAI SDK's `response.json()` raises a raw
`json.JSONDecodeError` (or wraps it in `APIResponseValidationError` whose
message contains "expecting value"). Previously this fell through to the
unknown-error branch and entered a 60s cooldown without retrying on the
main model, dropping the middle conversation turns instead.
This change folds JSON-decode detection into the existing fast-path
fallback chain: detect by `isinstance(e, JSONDecodeError)` OR substring
match for "expecting value", retry once on the main model, and use a
shorter 30s cooldown when already on main (the body shape tends to flip
back to valid quickly when the upstream proxy recovers).
The three duplicated fallback bodies (model-not-found, unknown-error,
JSON-decode) are consolidated into a single `_fallback_to_main_for_compression`
helper that handles the shared bookkeeping (record aux-model failure for
`/usage`-style callers, clear summary_model, clear cooldown).
Also adds three unit tests covering: raw `JSONDecodeError` retries on main,
substring-match for wrapped exceptions, and the 30s cooldown when already
on main.
Salvage of #22248 by @0xharryriddle. Closes#22244.
Co-authored-by: Harry Riddle <ntconguit@gmail.com>
Interactive `hermes` launch drops from ~21s to ~2.5s. Three independent
fixes, each targets a distinct hot spot in the banner / tool-registration
path that fires on every CLI invocation.
1. `get_external_skills_dirs()` in-process mtime cache (~10s saved)
The function re-read + YAML-parsed the full ~/.hermes/config.yaml on
every call. Banner build invokes it once per skill to resolve the
category column, which on a 120-skill install meant ~120 reparses of
a 15 KB config (~85 ms each). Added a
`(config_path, mtime_ns) -> list[Path]` memo; stat() is ~2 us vs
~85 ms for the parse. Edits to config.yaml invalidate the cache on
the next call via mtime.
2. Feishu availability probe uses `importlib.util.find_spec` (~5.2s saved)
`tools/feishu_doc_tool.py::_check_feishu` and the identical helper in
`feishu_drive_tool.py` were calling `import lark_oapi` purely to
detect whether the SDK was installed. Executing the real import pulls
in websockets + dispatcher + every v2 API model — ~5 seconds of work
that fires at every tool-registry bootstrap. `find_spec` answers the
same question ("is lark_oapi importable?") without executing the
module. The actual tool handlers still do the real import on invoke,
so runtime behavior is unchanged.
3. `_web_requires_env` no longer triggers Nous portal refresh (~800ms saved)
`tools/web_tools.py::_web_requires_env` used
`managed_nous_tools_enabled()` to gate four gateway env-var names in
the returned list. The gate called `get_nous_auth_status()` ->
`resolve_nous_runtime_credentials()` -> live HTTP POST to the portal
on every tool-registry bootstrap. But the list is pure metadata — if
the env var is set at runtime, the tool lights up; otherwise it
doesn't. Including the four names unconditionally is harmless for
unsubscribed users (vars just aren't set) and eliminates the sync
HTTP round trip from startup.
Test:
- tests/agent/test_external_skills_dirs_cache.py (new, 6 cases):
returns config'd dir, caches on second call (yaml_load patched to
raise — never invoked), invalidates on mtime bump, empty when config
missing, returned list is a defensive copy, per-HERMES_HOME cache key
isolation.
- Existing tests/agent/test_external_skills.py and tests/tools/
continue to pass modulo pre-existing flakes on main (test_delegate,
test_send_message — unrelated, pass in isolation).
Measured: bare `hermes` (cold → REPL ready) 21,519ms -> 2,618ms on
Teknium's install (119 skills, 15 KB config.yaml, Nous auth logged in,
lark_oapi installed). 8x faster.
## Why
Hermes supports Linux, macOS, and native Windows, but the codebase grew up
POSIX-first and has accumulated patterns that silently break (or worse,
silently kill!) on Windows:
- `os.kill(pid, 0)` as a liveness probe — on Windows this maps to
CTRL_C_EVENT and broadcasts Ctrl+C to the target's entire console
process group (bpo-14484, open since 2012).
- `os.killpg` — doesn't exist on Windows at all (AttributeError).
- `os.setsid` / `os.getuid` / `os.geteuid` — same.
- `signal.SIGKILL` / `signal.SIGHUP` / `signal.SIGUSR1` — module-attr
errors at runtime on Windows.
- `open(path)` / `open(path, "r")` without explicit encoding= — inherits
the platform default, which is cp1252/mbcs on Windows (UTF-8 on POSIX),
causing mojibake round-tripping between hosts.
- `wmic` — removed from Windows 10 21H1+.
This commit does three things:
1. Makes `psutil` a core dependency and migrates critical callsites to it.
2. Adds a grep-based CI gate (`scripts/check-windows-footguns.py`) that
blocks new instances of any of the above patterns.
3. Fixes every existing instance in the codebase so the baseline is clean.
## What changed
### 1. psutil as a core dependency (pyproject.toml)
Added `psutil>=5.9.0,<8` to core deps. psutil is the canonical
cross-platform answer for "is this PID alive" and "kill this process
tree" — its `pid_exists()` uses `OpenProcess + GetExitCodeProcess` on
Windows (NOT a signal call), and its `Process.children(recursive=True)`
+ `.kill()` combo replaces `os.killpg()` portably.
### 2. `gateway/status.py::_pid_exists`
Rewrote to call `psutil.pid_exists()` first, falling back to the
hand-rolled ctypes `OpenProcess + WaitForSingleObject` dance on Windows
(and `os.kill(pid, 0)` on POSIX) only if psutil is somehow missing —
e.g. during the scaffold phase of a fresh install before pip finishes.
### 3. `os.killpg` migration to psutil (7 callsites, 5 files)
- `tools/code_execution_tool.py`
- `tools/process_registry.py`
- `tools/tts_tool.py`
- `tools/environments/local.py` (3 sites kept as-is, suppressed with
`# windows-footgun: ok` — the pgid semantics psutil can't replicate,
and the calls are already Windows-guarded at the outer branch)
- `gateway/platforms/whatsapp.py`
### 4. `scripts/check-windows-footguns.py` (NEW, 500 lines)
Grep-based checker with 11 rules covering every Windows cross-platform
footgun we've hit so far:
1. `os.kill(pid, 0)` — the silent killer
2. `os.setsid` without guard
3. `os.killpg` (recommends psutil)
4. `os.getuid` / `os.geteuid` / `os.getgid`
5. `os.fork`
6. `signal.SIGKILL`
7. `signal.SIGHUP/SIGUSR1/SIGUSR2/SIGALRM/SIGCHLD/SIGPIPE/SIGQUIT`
8. `subprocess` shebang script invocation
9. `wmic` without `shutil.which` guard
10. Hardcoded `~/Desktop` (OneDrive trap)
11. `asyncio.add_signal_handler` without try/except
12. `open()` without `encoding=` on text mode
Features:
- Triple-quoted-docstring aware (won't flag prose inside docstrings)
- Trailing-comment aware (won't flag mentions in `# os.kill(pid, 0)` comments)
- Guard-hint aware (skips lines with `hasattr(os, ...)`,
`shutil.which(...)`, `if platform.system() != 'Windows'`, etc.)
- Inline suppression with `# windows-footgun: ok — <reason>`
- `--list` to print all rules with fixes
- `--all` / `--diff <ref>` / staged-files (default) modes
- Scans 380 files in under 2 seconds
### 5. CI integration
A GitHub Actions workflow that runs the checker on every PR and push is
staged at `/tmp/hermes-stash/windows-footguns.yml` — not included in this
commit because the GH token on the push machine lacks `workflow` scope.
A maintainer with `workflow` permissions should add it as
`.github/workflows/windows-footguns.yml` in a follow-up. Content:
```yaml
name: Windows footgun check
on:
push:
branches: [main]
pull_request:
branches: [main]
jobs:
check:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/setup-python@v5
with: {python-version: "3.11"}
- run: python scripts/check-windows-footguns.py --all
```
### 6. CONTRIBUTING.md — "Cross-Platform Compatibility" expansion
Expanded from 5 to 16 rules, each with message, example, and fix.
Recommends psutil as the preferred API for PID / process-tree operations.
### 7. Baseline cleanup (91 → 0 findings)
- 14 `open()` sites → added `encoding='utf-8'` (internal logs/caches) or
`encoding='utf-8-sig'` (user-editable files that Notepad may BOM)
- 23 POSIX-only callsites in systemd helpers, pty_bridge, and plugin
tool subprocess management → annotated with
`# windows-footgun: ok — <reason>`
- 7 `os.killpg` sites → migrated to psutil (see §3 above)
## Verification
```
$ python scripts/check-windows-footguns.py --all
✓ No Windows footguns found (380 file(s) scanned).
$ python -c "from gateway.status import _pid_exists; import os
> print('self:', _pid_exists(os.getpid())); print('bogus:', _pid_exists(999999))"
self: True
bogus: False
```
Proof-of-repro that `os.kill(pid, 0)` was actually killing processes
before this fix — see commit `1cbe39914` and bpo-14484. This commit
removes the last hand-rolled ctypes path from the hot liveness-check
path and defers to the best-maintained cross-platform answer.
build_environment_hints() now emits a factual block describing the
execution environment on every prompt build:
* Local backend: host OS, $HOME, and cwd — so the agent stops guessing
paths from the hostname. Windows also gets two specific callouts:
- hostname != username (prevents C:\Users\<hostname>\... bugs)
- `terminal` shells out to bash (git-bash/MSYS), not PowerShell
* Remote backend (docker/singularity/modal/daytona/ssh/vercel_sandbox):
host info is SUPPRESSED — the agent's tools can't touch the host, so
showing it is misleading. Instead we probe the backend once per
process with `uname/whoami/pwd` and cache the result. On probe
failure, fall back to a per-backend description that states only what
we know from the backend choice itself (container type + likely OS
family) without inventing user/cwd/$HOME.
Linux/Mac local users now get a small helpful 3-line host block instead
of an empty string. Zero change to the existing WSL hint paragraph.
Tests: 8 new/updated in TestEnvironmentHints, including a regression
guard that fails if a new remote backend is added without listing it in
_REMOTE_TERMINAL_BACKENDS.
Closes the last Python-on-Windows UTF-8 exposure by making every
text-mode open() call explicit about its encoding.
Before: on Windows, bare open(path, 'r') defaults to the system
locale encoding (cp1252 on US-locale installs). That means reading
any config/yaml/markdown/json file with non-ASCII content either
crashes with UnicodeDecodeError or silently mis-decodes bytes.
After: all 89 affected call sites in production code now pass
encoding='utf-8' explicitly. Works identically on every platform
and every locale, no surprise behavior.
Mechanical sweep via:
ruff check --preview --extend-select PLW1514 --unsafe-fixes --fix --exclude 'tests,venv,.venv,node_modules,website,optional-skills, skills,tinker-atropos,plugins' .
All 89 fixes have the same shape: open(x) or open(x, mode) became
open(x, encoding='utf-8') or open(x, mode, encoding='utf-8'). Nothing
else changed. Every modified file still parses and the Windows/sandbox
test suite is still green (85 passed, 14 skipped, 0 failed across
tests/tools/test_code_execution_windows_env.py +
tests/tools/test_code_execution_modes.py + tests/tools/test_env_passthrough.py +
tests/test_hermes_bootstrap.py).
Scope notes:
- tests/ excluded: test fixtures can use locale encoding intentionally
(exercising edge cases). If we want to tighten tests later that's
a separate PR.
- plugins/ excluded: plugin-specific conventions may differ; plugin
authors own their code.
- optional-skills/ and skills/ excluded: skill scripts are user-authored
and we don't want to mass-edit them.
- website/ and tinker-atropos/ excluded: vendored / generated content.
46 files touched, 89 +/- lines (symmetric replacement). No behavior
change on POSIX or on Windows when the file is ASCII; bug fix on
Windows when the file contains non-ASCII.
Extends the cua-driver computer-use backend to drive backgrounded macOS
windows without stealing keyboard or mouse focus from the foreground app.
All changes target the cua-driver MCP backend and the shared dispatcher.
## cua_backend.py
**Window-aware capture**: capture() now calls list_windows + get_window_state
instead of the removed capture tool. Prefers structuredContent.windows
(MCP 2024-11-05+ cua-driver) for zero-parse window enumeration; falls back
to regex-parsed text for older builds. Stores the selected (pid, window_id)
as sticky context so subsequent action calls do not need a redundant round-trip.
**Action routing**: click/scroll/type_text/key all carry the sticky pid
(and window_id for element-indexed clicks). type_text routes through
type_text_chars (individual key events) rather than AX attribute write --
WebKit AXTextFields reject attribute writes from backgrounded processes.
**Key parsing**: _parse_key_combo splits cmd+s-style strings into
(key, [modifiers]) and routes to hotkey (modifier present) or
press_key (bare key) -- cua-driver actual tool names.
**set_value method**: new set_value(value, element) calls the cua-driver
set_value MCP tool. For AXPopUpButton / HTML select in a backgrounded Safari,
AXPress opens the native macOS popup which closes immediately when the app is
non-frontmost; set_value AX-presses the matching child option directly
(no menu required, no focus steal).
**focus_app**: reimplemented as a pure window-selector (enumerates
list_windows, sets sticky pid/window_id) without ever raising the window
or stealing focus.
**list_apps**: fixed tool name from listApps to list_apps; handles plain-text
response via regex when structured data is absent.
**Structured-content extraction**: _extract_tool_result now surfaces
structuredContent from MCP results, enabling the list_windows window array
without text parsing.
**Helpers**: _parse_windows_from_text, _parse_elements_from_tree,
_split_tree_text, _parse_key_combo extracted as module-level functions.
## schema.py
Added set_value to the action enum with a description explaining when to
prefer it over click (select/popup elements, sliders, no focus steal).
Added value field for set_value payloads.
## tool.py
Routed set_value action through _dispatch to backend.set_value.
Added set_value to _DESTRUCTIVE_ACTIONS (approval-gated).
Fixed MIME-type detection in _capture_response: cua-driver may return
JPEG; detect from base64 magic bytes (/9j/ -> image/jpeg, else image/png)
rather than hardcoding image/png.
## agent/display.py + run_agent.py
Guard _detect_tool_failure and result-preview logic against non-string
function_result values: multimodal tool results (dicts with _multimodal=True)
are not string-sliceable; treat them as successes and fall back to str()
for length/preview.
Background macOS desktop control via cua-driver MCP — does NOT steal the
user's cursor or keyboard focus, works with any tool-capable model.
Replaces the Anthropic-native `computer_20251124` approach from the
abandoned #4562 with a generic OpenAI function-calling schema plus SOM
(set-of-mark) captures so Claude, GPT, Gemini, and open models can all
drive the desktop via numbered element indices.
- `tools/computer_use/` package — swappable ComputerUseBackend ABC +
CuaDriverBackend (stdio MCP client to trycua/cua's cua-driver binary).
- Universal `computer_use` tool with one schema for all providers.
Actions: capture (som/vision/ax), click, double_click, right_click,
middle_click, drag, scroll, type, key, wait, list_apps, focus_app.
- Multimodal tool-result envelope (`_multimodal=True`, OpenAI-style
`content: [text, image_url]` parts) that flows through
handle_function_call into the tool message. Anthropic adapter converts
into native `tool_result` image blocks; OpenAI-compatible providers
get the parts list directly.
- Image eviction in convert_messages_to_anthropic: only the 3 most
recent screenshots carry real image data; older ones become text
placeholders to cap per-turn token cost.
- Context compressor image pruning: old multimodal tool results have
their image parts stripped instead of being skipped.
- Image-aware token estimation: each image counts as a flat 1500 tokens
instead of its base64 char length (~1MB would have registered as
~250K tokens before).
- COMPUTER_USE_GUIDANCE system-prompt block — injected when the toolset
is active.
- Session DB persistence strips base64 from multimodal tool messages.
- Trajectory saver normalises multimodal messages to text-only.
- `hermes tools` post-setup installs cua-driver via the upstream script
and prints permission-grant instructions.
- CLI approval callback wired so destructive computer_use actions go
through the same prompt_toolkit approval dialog as terminal commands.
- Hard safety guards at the tool level: blocked type patterns
(curl|bash, sudo rm -rf, fork bomb), blocked key combos (empty trash,
force delete, lock screen, log out).
- Skill `apple/macos-computer-use/SKILL.md` — universal (model-agnostic)
workflow guide.
- Docs: `user-guide/features/computer-use.md` plus reference catalog
entries.
44 new tests in tests/tools/test_computer_use.py covering schema
shape (universal, not Anthropic-native), dispatch routing, safety
guards, multimodal envelope, Anthropic adapter conversion, screenshot
eviction, context compressor pruning, image-aware token estimation,
run_agent helpers, and universality guarantees.
469/469 pass across tests/tools/test_computer_use.py + the affected
agent/ test suites.
- `model_tools.py` provider-gating: the tool is available to every
provider. Providers without multi-part tool message support will see
text-only tool results (graceful degradation via `text_summary`).
- Anthropic server-side `clear_tool_uses_20250919` — deferred;
client-side eviction + compressor pruning cover the same cost ceiling
without a beta header.
- macOS only. cua-driver uses private SkyLight SPIs
(SLEventPostToPid, SLPSPostEventRecordTo,
_AXObserverAddNotificationAndCheckRemote) that can break on any macOS
update. Pin with HERMES_CUA_DRIVER_VERSION.
- Requires Accessibility + Screen Recording permissions — the post-setup
prints the Settings path.
Supersedes PR #4562 (pyautogui/Quartz foreground backend, Anthropic-
native schema). Credit @0xbyt4 for the original #3816 groundwork whose
context/eviction/token design is preserved here in generic form.
The previous revision of this PR added six GMI-specific branches
(`elif base_url_host_matches(..., 'api.gmi-serving.com')`) across
run_agent.py and agent/auxiliary_client.py, plus a _HERMES_UA_HEADERS
constant in auxiliary_client.py.
ProviderProfile already has a `default_headers: dict[str, str]` field
commented as 'Client-level quirks (set once at client construction)'.
Other plugins (ai-gateway, kimi-coding) already use it. Two of the four
auxiliary_client sites we previously patched already had a generic
`else: profile.default_headers` fallback that picked it up (so did
both run_agent sites).
This revision:
* Sets `default_headers={'User-Agent': 'HermesAgent/<ver>'}` on the
GMI profile in plugins/model-providers/gmi/__init__.py.
* Reverts all six GMI-specific branches in run_agent.py and
auxiliary_client.py.
* Adds the generic profile-fallback `else` block to the two
auxiliary_client sites (`_to_async_client`, `resolve_provider_client`)
that didn't have it yet. This benefits every provider whose profile
declares default_headers, not just GMI — e.g. Vercel AI Gateway's
HTTP-Referer/X-Title now flow through the async client path too.
* Replaces the GMI-specific URL-branch tests with a profile-level
assertion and keeps the run_agent integration test (with
`provider='gmi'` so the fallback picks up the profile).
Net diff vs main: +82/-0 across 5 files, touching only the GMI plugin,
two generic fallback blocks in auxiliary_client.py, AUTHOR_MAP, and
tests. No core files change.
Based on #20907 by @isaachuangGMICLOUD.
- Add pricing entries for Claude Opus 4.5/4.6/4.7, Sonnet 4.5/4.6, and
Haiku 4.5 with updated source URLs (platform.claude.com)
- Add _normalize_anthropic_model_name() to handle dot-notation variants
(e.g. claude-opus-4.7 → claude-opus-4-7) for pricing lookups
- Fix silent token loss: ensure session row exists before UPDATE in both
run_agent.py and hermes_state.py (INSERT OR IGNORE is idempotent)
- Log token persistence failures at DEBUG level instead of swallowing
them silently — makes undercounted analytics diagnosable
- Surface reasoning tokens in CLI /usage and TUI usage panel
- Add 'reasoning' and 'cost_status' fields to TUI Usage type
## Summary
- Forwards chat-completions `timeout` into the Codex Responses stream call.
- Adds total elapsed-time enforcement while the Responses stream is still yielding events.
- Closes the underlying client on timeout to unblock stalled streams, then raises `TimeoutError`.
- Adds focused tests for timeout forwarding and total timeout enforcement.
## Why
The Codex auxiliary adapter can be used by non-interactive auxiliary work such as context compression. If the stream keeps yielding progress-like events but never completes, SDK socket/read timeouts do not necessarily protect the full operation. This makes the CLI look stuck until the user force-interrupts the whole session.
This is a refreshed upstream-ready version of the earlier fork fix around `d3f08e9a0` / PR #3.
## Verification
- `python -m py_compile agent/auxiliary_client.py tests/agent/test_auxiliary_client.py`
- `python -m pytest -o addopts='' tests/agent/test_auxiliary_client.py::TestCodexAuxiliaryAdapterTimeout -q`
- `git diff --check`
Z.AI (智谱 GLM) vision models (glm-4v-flash, glm-4v-plus, etc.) have two
compatibility issues when used through the Anthropic-compatible endpoint:
1. **Error 1210 — max_tokens rejected on multimodal calls**: Z.AI rejects
the max_tokens parameter for vision model requests with error code 1210
("API 调用参数有误"). The error string does not contain "max_tokens",
so the existing unsupported-parameter retry logic never fires.
2. **Wrong endpoint inheritance**: When the main runtime provider uses Z.AI's
Anthropic-compatible endpoint (open.bigmodel.cn/api/anthropic), the vision
client inherits this endpoint. But Z.AI's Anthropic wire cannot properly
handle image content — models silently fail ("I can't see the image") or
reject max_tokens.
Changes:
- resolve_vision_provider_client(): force Z.AI vision to use OpenAI-compatible
endpoint (open.bigmodel.cn/api/paas/v4) instead of inheriting Anthropic wire
- _build_call_kwargs(): skip max_tokens for Z.AI vision models (4v/5v/-v suffix)
- _AnthropicCompletionsAdapter: support _skip_zai_max_tokens flag
- _to_openai_base_url(): rewrite Z.AI Anthropic URLs to OpenAI-compatible path
- call_llm() retry: detect Z.AI error 1210 and strip max_tokens before retry
Discord (and similar platforms) can serve a PNG image cached as
discord_xxx.webp because the CDN reports content_type=image/webp for
proxied stickers, custom emoji, and certain bot-uploaded images even
when the actual bytes are PNG. Hermes' agent.image_routing._guess_mime
trusted the file suffix and declared media_type=image/webp to
Anthropic, which strict-validates and returns:
HTTP 400 messages.N.content.M.image.source.base64:
The image was specified using the image/webp media type,
but the image appears to be a image/png image
The Discord image attachment never reaches the model; the whole turn
fails with no salvage path.
Fix: sniff magic bytes in _file_to_data_url before declaring MIME.
Suffix-based detection is kept as a fallback when bytes aren't
available. New helper _sniff_mime_from_bytes covers PNG, JPEG, GIF,
WEBP, BMP, and HEIC/HEIF.
Tests:
- Two existing tests asserted the old broken behaviour (PNG bytes in
a .jpg/.webp file should report jpeg/webp); rewritten with real
jpeg/webp magic bytes so they still cover suffix-aligned cases.
- New regression test test_mime_sniff_overrides_misleading_extension
reproduces the exact Discord scenario (PNG bytes, .webp suffix) and
asserts the data URL comes back as image/png.
All 28 tests in tests/agent/test_image_routing.py pass.
When multiple custom_providers share the same base_url but have different API keys,
get_custom_provider_pool_key() always returned the first match, causing wrong-key
unauthorized errors. Add provider_name parameter to prefer exact name matches
over base_url-only matching, with fallback for backward compatibility.
Fixes#19083
Flip the default for HERMES_REDACT_SECRETS from off to on so the redactor
already wired into send_message_tool, logs, and tool output actually runs
on a fresh install.
- agent/redact.py: env-var default "" → "true"
- hermes_cli/config.py: DEFAULT_CONFIG security.redact_secrets True;
two config-template comments rewritten
- gateway/run.py + cli.py: startup log / banner warning when the user
has explicitly opted out, so the downgrade is visible in agent.log
and at CLI banner time
- docs/reference/environment-variables.md: description reconciled
- tests: flipped the default-pin, restructured the force=True
regression test to explicit-false instead of unset
Users who need raw credential values (redactor development) can still
opt out via security.redact_secrets: false in config.yaml or
HERMES_REDACT_SECRETS=false in .env.
Closes#17691.
Addresses #20785 (short-term output-pipeline recommendation).
Widen PR #20314's fix to the other timeout-polling sites in the codebase
that share the same wall-clock-jump bug class. All of these measure elapsed
timeout duration, not civil time, so they belong on time.monotonic().
- hermes_cli/auth.py: auth-store file-lock timeout, Spotify OAuth callback
wait, Nous portal device-auth token poll.
- hermes_cli/copilot_auth.py: Copilot OAuth device-flow token poll.
- hermes_cli/gateway.py: gateway systemd restart wait.
- hermes_cli/web_server.py: dashboard Codex device-auth user_code wait,
dashboard Nous device-auth token poll. (sess["expires_at"] stays on
time.time() — it's a persisted absolute timestamp, not a local
deadline-polling variable.)
- agent/copilot_acp_client.py: Copilot ACP JSON-RPC request timeout.
In native image mode (vision-capable models like gpt-4o, claude-sonnet-4),
build_native_content_parts() previously emitted only the user's caption
plus image_url parts. The local file path of each attached image never
appeared in the conversation text, so the model could see the pixels but
had no string handle for tools that take image_url: str (custom MCP
tools, vision_analyze on a re-look, attach-to-tracker workflows).
The text-mode path already injects an equivalent hint via
Runner._enrich_message_with_vision ("...vision_analyze using image_url:
<path>..."). This brings native mode to parity by appending one
"[Image attached at: <path>]" line per successfully attached image to
the user-text part of the multimodal turn. Skipped (unreadable) paths
are NOT advertised, so the model is never told a non-existent file is
attached.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
- Fix /compact → /compress in context-overflow tips (closes#20020)
- Evict cached agent after session hygiene and /compress so system
prompt refreshes with current SOUL.md, memory, and skills
- Restore memory authority across compaction: change 'informational
background data' to 'authoritative reference data' in memory block
and SUMMARY_PREFIX, with backward-compatible regex
Based on:
- PR #20027 by @LeonSGP43
- PR #18767 by @MacroAnarchy
- PR #17380 by @vominh1919
PR #17121 boundary marker fix already merged to main (2eef395e1).
PR #9262 user-message anchoring already on main via _ensure_last_user_message_in_tail().
- Add locales/tr.yaml with Turkish translations for all approval.* and gateway.* keys
- Register 'tr' in SUPPORTED_LANGUAGES
- Add Turkish aliases: turkish, türkçe, tr-tr
- Add fr.yaml with French translations for approval prompts and gateway messages
- Register 'fr' in SUPPORTED_LANGUAGES
- Add French aliases: french, français, fr-fr, fr-be, fr-ca, fr-ch
- Update locale sync comment in en.yaml
