- Add missing translation keys: skills.resultCount, skills.toolsetLabel
- Replace hardcoded "result(s)" and "toolset" with translated strings
- Fix stale useMemo in SkillsPage allCategories (missing `t` dependency)
causing sidebar category names to stay in English after language switch
Made-with: Cursor
Re-applies changes from #9471 that were overwritten by the i18n PR:
- URL-based routing via react-router-dom (NavLink, Routes, BrowserRouter)
- Replace emoji icons with lucide-react in ConfigPage and SkillsPage
- Sidebar layout for ConfigPage, SkillsPage, and LogsPage
- Custom dropdown Select component (SelectOption) in CronPage
- Remove all non-functional rounded borders across the UI
- Fixed header with proper content offset
Made-with: Cursor
- test_auth_commands: suppress _seed_from_singletons auto-seeding that
adds extra credentials from CI env (same pattern as nearby tests)
- test_interrupt: clear stale _interrupted_threads set to prevent
thread ident reuse from prior tests in same xdist worker
- test_code_execution: add watch_patterns to _BLOCKED_TERMINAL_PARAMS
to match production _TERMINAL_BLOCKED_PARAMS
During rapid tool-calling, the model often emits 1-2 tokens before
switching to tool calls. The stream consumer would create a new message
with 'X ▉' (short text + cursor), and if the follow-up edit to strip
the cursor was rate-limited by the platform, the cursor remained as
a permanent standalone message — reported on Telegram as 'white box'
artifacts.
Add a minimum-content guard in _send_or_edit: when creating a new
standalone message (no existing message_id), require at least 4
visible characters alongside the cursor before sending. Shorter text
accumulates into the next streaming segment instead.
This prevents cursor-only 'tofu' messages across all platforms without
affecting normal streaming (edits to existing messages, final sends
without cursor, and messages with substantial text are all unaffected).
Reported by @michalkomar on X.
Production fixes:
- Add clear_session_context() to hermes_logging.py (fixes 48 teardown errors)
- Add clear_session() to tools/approval.py (fixes 9 setup errors)
- Add SyncError M_UNKNOWN_TOKEN check to Matrix _sync_loop (bug fix)
- Fall back to inline api_key in named custom providers when key_env
is absent (runtime_provider.py)
Test fixes:
- test_memory_user_id: use builtin+external provider pair, fix honcho
peer_name override test to match production behavior
- test_display_config: remove TestHelpers for non-existent functions
- test_auxiliary_client: fix OAuth tokens to match _is_oauth_token
patterns, replace get_vision_auxiliary_client with resolve_vision_provider_client
- test_cli_interrupt_subagent: add missing _execution_thread_id attr
- test_compress_focus: add model/provider/api_key/base_url/api_mode
to mock compressor
- test_auth_provider_gate: add autouse fixture to clean Anthropic env
vars that leak from CI secrets
- test_opencode_go_in_model_list: accept both 'built-in' and 'hermes'
source (models.dev API unavailable in CI)
- test_email: verify email Platform enum membership instead of source
inspection (build_channel_directory now uses dynamic enum loop)
- test_feishu: add bot_added/bot_deleted handler mocks to _Builder
- test_ws_auth_retry: add AsyncMock for sync_store.get_next_batch,
add _pending_megolm and _joined_rooms to Matrix adapter mocks
- test_restart_drain: monkeypatch-delete INVOCATION_ID (systemd sets
this in CI, changing the restart call signature)
- test_session_hygiene: add user_id to SessionSource
- test_session_env: use relative baseline for contextvar clear check
(pytest-xdist workers share context)
Improvements from our earlier #8269 salvage work applied to #7616:
- Platform token lock: acquire_scoped_lock/release_scoped_lock prevents
two profiles from double-connecting the same QQ bot simultaneously
- Send retry with exponential backoff (3 attempts, 1s/2s/4s) with
permanent vs transient error classification (matches Telegram pattern)
- Proper long-message splitting via truncate_message() instead of
hard-truncating at MAX_MESSAGE_LENGTH (preserves code blocks, adds 1/N)
- REST-based one-shot send in send_message_tool — uses QQ Bot REST API
directly with httpx instead of creating a full WebSocket adapter per
message (fixes the connect→send race condition)
- Use shared strip_markdown() from helpers.py instead of 15 lines of
inline regex with import-inside-method (DRY, same as BlueBubbles/SMS)
- format_message() now wired into send() pipeline
- Add Platform.QQBOT to _UPDATE_ALLOWED_PLATFORMS (enables /update command)
- Add 'qqbot' to webhook cross-platform delivery routing
- Add 'qqbot' to hermes dump platform detection
- Fix test_name_property casing: 'QQBot' not 'QQBOT'
- Add _parse_qq_timestamp() for ISO 8601 + integer ms compatibility
(QQ API changed timestamp format — from PR #2411 finding)
- Wire timestamp parsing into all 4 message handlers
- Rename platform from 'qq' to 'qqbot' across all integration points
(Platform enum, toolset, config keys, import paths, file rename qq.py → qqbot.py)
- Add PLATFORM_HINTS for QQBot in prompt_builder (QQ supports markdown)
- Set SUPPORTS_MESSAGE_EDITING = False to skip streaming on QQ
(prevents duplicate messages from non-editable partial + final sends)
- Add _send_qqbot() standalone send function for cron/send_message tool
- Add interactive _setup_qq() wizard in hermes_cli/setup.py
- Restore missing _setup_signal/email/sms/dingtalk/feishu/wecom/wecom_callback
functions that were lost during the original merge
Three improvements to file search based on user feedback:
1. Fuzzy @ completions (commands.py):
- Bare @query now does project-wide fuzzy file search instead of
prefix-only directory listing
- Uses rg --files with 5-second cache for responsive completions
- Scoring: exact name (100) > prefix (80) > substring (60) >
path contains (40) > subsequence with boundary bonus (35/25)
- Bare @ with no query shows recently modified files first
2. Mtime-sorted file search (file_operations.py):
- _search_files_rg now uses --sortr=modified (rg 13+) to surface
recently edited files first
- Falls back to unsorted on older rg versions
3. Improved file-not-found suggestions (file_operations.py):
- Replaced crude character-set overlap with ranked scoring:
same basename (90) > prefix (70) > substring (60) >
reverse substring (40) > same extension (30)
- search_files path-not-found now suggests similar directories
from the parent
Add a second light-mode skin option with warm brown/parchment tones,
adapted from ygd58's contribution in PR #4811. Includes completion
menu and status bar color keys for full light-terminal support.
Co-authored-by: buray <78954051+ygd58@users.noreply.github.com>
Add a lightweight i18n system to the web dashboard with English (default) and
Chinese language support. A language switcher with flag icons is placed in the
header bar, allowing users to toggle between languages. The choice persists
to localStorage.
Implementation:
- src/i18n/ — types, translation files (en.ts, zh.ts), React context + hook
- LanguageSwitcher component shows the *other* language's flag as the toggle
- I18nProvider wraps the app in main.tsx
- All 8 pages + OAuth components updated to use t() translation calls
- Zero new dependencies — pure React context + localStorage
GPT-5.4 supports none/low/medium/high/xhigh but not 'minimal'.
Users may configure 'minimal' via OpenRouter conventions, which would
cause a 400 on native OpenAI. Clamp to 'low' in the codex_responses
path before sending.
* feat(skills): add fitness-nutrition skill to optional-skills
Cherry-picked from PR #9177 by @haileymarshall.
Adds a fitness and nutrition skill for gym-goers and health-conscious users:
- Exercise search via wger API (690+ exercises, free, no auth)
- Nutrition lookup via USDA FoodData Central (380K+ foods, DEMO_KEY fallback)
- Offline body composition calculators (BMI, TDEE, 1RM, macros, body fat %)
- Pure stdlib Python, no pip dependencies
Changes from original PR:
- Moved from skills/ to optional-skills/health/ (correct location)
- Fixed BMR formula in FORMULAS.md (removed confusing -5+10, now just +5)
- Fixed author attribution to match PR submitter
- Marked USDA_API_KEY as optional (DEMO_KEY works without signup)
Also adds optional env var support to the skill readiness checker:
- New 'optional: true' field in required_environment_variables entries
- Optional vars are preserved in metadata but don't block skill readiness
- Optional vars skip the CLI capture prompt flow
- Skills with only optional missing vars show as 'available' not 'setup_needed'
* fix: auto-correct close model name matches in /model validation
When a user types a model name with a minor typo (e.g. gpt5.3-codex instead
of gpt-5.3-codex), the validation now auto-corrects to the closest match
instead of accepting the wrong name with a warning.
Uses difflib get_close_matches with cutoff=0.9 to avoid false corrections
(e.g. gpt-5.3 should not silently become gpt-5.4). Applied consistently
across all three validation paths: codex provider, custom endpoints, and
generic API-probed providers.
The validate_requested_model() return dict gains an optional corrected_model
key that switch_model() applies before building the result.
Reported by Discord user — /model gpt5.3-codex was accepted with a warning
but would fail at the API level.
---------
Co-authored-by: haileymarshall <haileymarshall@users.noreply.github.com>
During custom endpoint setup, users are now asked for a display name
with the auto-generated name as the default. Typing 'Ollama' or
'LM Studio' replaces the generic 'Local (localhost:11434)' in the
provider menu.
Extracts _auto_provider_name() for reuse and adds a name= parameter
to _save_custom_provider() so the caller can pass through the
user-chosen label.
Models like MiniMax emit inline <think>...</think> reasoning blocks in
their content field. The CLI already suppresses these via a state machine
in _stream_delta, but the gateway's GatewayStreamConsumer had no
equivalent filtering — raw think blocks were streamed directly to
Discord/Telegram/Slack.
The fix adds a _filter_and_accumulate() method that mirrors the CLI's
approach: a state machine tracks whether we're inside a reasoning block
and silently discards the content. Includes the same block-boundary
check (tag must appear at line start or after whitespace-only prefix)
to avoid false positives when models mention <think> in prose.
Handles all tag variants: <think>, <thinking>, <THINKING>, <thought>,
<reasoning>, <REASONING_SCRATCHPAD>.
Also handles edge cases:
- Tags split across streaming deltas (partial tag buffering)
- Unclosed blocks (content suppressed until stream ends)
- Multiple consecutive blocks
- _flush_think_buffer on stream end for held-back partial tags
Adds 22 unit tests + 1 integration test covering all scenarios.
* feat(skills): add fitness-nutrition skill to optional-skills
Cherry-picked from PR #9177 by @haileymarshall.
Adds a fitness and nutrition skill for gym-goers and health-conscious users:
- Exercise search via wger API (690+ exercises, free, no auth)
- Nutrition lookup via USDA FoodData Central (380K+ foods, DEMO_KEY fallback)
- Offline body composition calculators (BMI, TDEE, 1RM, macros, body fat %)
- Pure stdlib Python, no pip dependencies
Changes from original PR:
- Moved from skills/ to optional-skills/health/ (correct location)
- Fixed BMR formula in FORMULAS.md (removed confusing -5+10, now just +5)
- Fixed author attribution to match PR submitter
- Marked USDA_API_KEY as optional (DEMO_KEY works without signup)
Also adds optional env var support to the skill readiness checker:
- New 'optional: true' field in required_environment_variables entries
- Optional vars are preserved in metadata but don't block skill readiness
- Optional vars skip the CLI capture prompt flow
- Skills with only optional missing vars show as 'available' not 'setup_needed'
* docs: add Hugging Face and Xiaomi MiMo to README provider list
---------
Co-authored-by: haileymarshall <haileymarshall@users.noreply.github.com>
Cherry-picked from PR #9177 by @haileymarshall.
Adds a fitness and nutrition skill for gym-goers and health-conscious users:
- Exercise search via wger API (690+ exercises, free, no auth)
- Nutrition lookup via USDA FoodData Central (380K+ foods, DEMO_KEY fallback)
- Offline body composition calculators (BMI, TDEE, 1RM, macros, body fat %)
- Pure stdlib Python, no pip dependencies
Changes from original PR:
- Moved from skills/ to optional-skills/health/ (correct location)
- Fixed BMR formula in FORMULAS.md (removed confusing -5+10, now just +5)
- Fixed author attribution to match PR submitter
- Marked USDA_API_KEY as optional (DEMO_KEY works without signup)
Also adds optional env var support to the skill readiness checker:
- New 'optional: true' field in required_environment_variables entries
- Optional vars are preserved in metadata but don't block skill readiness
- Optional vars skip the CLI capture prompt flow
- Skills with only optional missing vars show as 'available' not 'setup_needed'
- Add GET /api/model/info endpoint that resolves model metadata using the
same 10-step context-length detection chain the agent uses. Returns
auto-detected context length, config override, effective value, and
model capabilities (tools, vision, reasoning, max output, model family).
- Surface model.context_length as model_context_length virtual field in
the config normalize/denormalize cycle. 0 = auto-detect (default),
positive value overrides. Writing 0 removes context_length from the
model dict on disk.
- Add ModelInfoCard component showing resolved context window (e.g. '1M
auto-detected' or '500K override — auto: 1M'), max output tokens, and
colored capability badges (Tools, Vision, Reasoning, model family).
- Inject ModelInfoCard between model field and context_length override in
ConfigPage General tab. Card re-fetches on model change and after save.
- Insert model_context_length right after model in CONFIG_SCHEMA ordering
so the three elements (model input → info card → override) are adjacent.
Plugins can now return {"action": "block", "message": "reason"} from
their pre_tool_call hook to prevent a tool from executing. The error
message is returned to the model as a tool result so it can adjust.
Covers both execution paths: handle_function_call (model_tools.py) and
agent-level tools (run_agent.py _invoke_tool + sequential/concurrent).
Blocked tools skip all side effects (counter resets, checkpoints,
callbacks, read-loop tracker).
Adds skip_pre_tool_call_hook flag to avoid double-firing the hook when
run_agent.py already checked and then calls handle_function_call.
Salvaged from PR #5385 (gianfrancopiana) and PR #4610 (oredsecurity).
* Add hermes debug share instructions to all issue templates
- bug_report.yml: Add required Debug Report section with hermes debug share
and /debug instructions, make OS/Python/Hermes version optional (covered
by debug report), demote old logs field to optional supplementary
- setup_help.yml: Replace hermes doctor reference with hermes debug share,
add Debug Report section with fallback chain (debug share -> --local -> doctor)
- feature_request.yml: Add optional Debug Report section for environment context
All templates now guide users to run hermes debug share (or /debug in chat)
and paste the resulting paste.rs links, giving maintainers system info,
config, and recent logs in one step.
* feat: add openrouter/elephant-alpha to curated model lists
- Add to OPENROUTER_MODELS (free, positioned above GPT models)
- Add to _PROVIDER_MODELS["nous"] mirror list
- Add 256K context window fallback in model_metadata.py
Adds a CI workflow that blocks PRs introducing commits with
unmapped author emails. Checks each new commit's author email
against AUTHOR_MAP in scripts/release.py — GitHub noreply emails
auto-pass, but personal/work emails must be mapped.
Also adds --strict and --diff-base flags to contributor_audit.py
for programmatic use. --strict exits 1 when new unmapped emails
are found; --diff-base scopes the check to only flag emails from
commits after a given ref (grandfathers existing unknowns).
Prevention for the 97-unmapped-email gap found in the April 2026
contributor audit.
Audit of all external contributor PRs revealed 97 commit emails
not mapped in AUTHOR_MAP, meaning contributors weren't properly
credited in release notes. Cross-referenced via:
- GitHub API email search (9 resolved before rate limit)
- Salvage PR body mentions (@username in descriptions)
- Git noreply email cross-reference (same person, both emails)
- GH contributor list username matching
Also adds .mailmap for git shortlog/log display consistency.
Remaining 22 unmapped emails need GH API resolution when rate
limit resets — the contributor_audit.py script will flag them.
Addresses ColourfulWhite's report about missing contributor tags.
When the 5-second stream_task timeout in gateway/run.py expires (due to
slow Telegram API calls from rate limiting after several messages), the
stream consumer is cancelled via asyncio.CancelledError. The
CancelledError handler did a best-effort final edit but never set
final_response_sent, so the gateway fell through to the normal send path
and delivered the full response again as a reply — causing a duplicate.
The fix: in the CancelledError handler, set final_response_sent = True
when already_sent is True (i.e., the stream consumer had already
delivered content to the user). This tells the gateway's already_sent
check that the response was delivered, preventing the duplicate send.
Adds two tests verifying the cancellation behavior:
- Cancelled with already_sent=True → final_response_sent=True (no dup)
- Cancelled with already_sent=False → final_response_sent=False (normal
send path proceeds)
Reported by community user hume on Discord.
The generic 'gpt-5' fallback was set to 128,000 — which is the max
OUTPUT tokens, not the context window. GPT-5 base and most variants
(codex, mini) have 400,000 context. This caused /model to report
128k for models like gpt-5.3-codex when models.dev was unavailable.
Added specific entries for GPT-5 variants with different context sizes:
- gpt-5.4, gpt-5.4-pro: 1,050,000 (1.05M)
- gpt-5.4-mini, gpt-5.4-nano: 400,000
- gpt-5.3-codex-spark: 128,000 (reduced)
- gpt-5.1-chat: 128,000 (chat variant)
- gpt-5 (catch-all): 400,000
Sources: https://developers.openai.com/api/docs/models
Remove the two-tier (top/extended) provider picker that hid most
providers behind a 'More providers...' submenu. All providers now
appear in a single flat list.
- Remove tier field from ProviderEntry namedtuple
- Remove tier values from all CANONICAL_PROVIDERS entries
- Flatten the hermes model picker (no more 'More...' submenu)
- Move 'Custom endpoint' to the bottom of the main list
Port two improvements inspired by Kilo-Org/kilocode analysis:
1. Error classifier: add context overflow patterns for vLLM, Ollama,
and llama.cpp/llama-server. These local inference servers return
different error formats than cloud providers (e.g., 'exceeds the
max_model_len', 'context length exceeded', 'slot context'). Without
these patterns, context overflow errors from local servers are
misclassified as format errors, causing infinite retries instead
of triggering compression.
2. MCP initial connection retry: previously, if the very first
connection attempt to an MCP server failed (e.g., transient DNS
blip at startup), the server was permanently marked as failed with
no retry. Post-connect reconnection had 5 retries with exponential
backoff, but initial connection had zero. Now initial connections
retry up to 3 times with backoff before giving up, matching the
resilience of post-connect reconnection.
(Inspired by Kilo Code's MCP server disappearing fix in v1.3.3)
Tests: 6 new error classifier tests, 4 new MCP retry tests, 1
updated existing test. All 276 affected tests pass.
Adds Arcee AI as a standard direct provider (ARCEEAI_API_KEY) with
Trinity models: trinity-large-thinking, trinity-large-preview, trinity-mini.
Standard OpenAI-compatible provider checklist: auth.py, config.py,
models.py, main.py, providers.py, doctor.py, model_normalize.py,
model_metadata.py, setup.py, trajectory_compressor.py.
Based on PR #9274 by arthurbr11, simplified to a standard direct
provider without dual-endpoint OpenRouter routing.
- Nav: icons only on mobile, icon+label on sm+
- Brand: abbreviated "H A" on mobile, full "Hermes Agent" on sm+
- Content: reduced padding on mobile (px-3 vs px-6)
- StatusPage: session cards stack vertically on mobile, truncate
overflow text, strip model namespace for brevity
- ConfigPage: sidebar becomes horizontal scrollable pills on mobile
instead of fixed left column, search hidden on mobile
- SessionsPage: title + search stack vertically on mobile, search
goes full-width
- Card component: add overflow-hidden to prevent content bleed
- Body/root: add overflow-x-hidden to prevent horizontal scroll
- Footer: reduced font sizes on mobile
All changes use Tailwind responsive breakpoints (sm: prefix).
No logic changes — purely layout/CSS adjustments.
The /model picker currently renders one row per ``custom_providers``
entry. When several entries share the same provider name (e.g. four
``ollama-cloud`` entries for ``qwen3-coder``, ``glm-5.1``, ``kimi-k2``,
``minimax-m2.7``), users see four separate "Ollama Cloud" rows in the
picker, which is confusing UX — there is only one Ollama Cloud
provider, so there should be one row containing four models.
This PR groups ``custom_providers`` entries that share the same provider
name into a single picker row while keeping entries with distinct names
as separate rows. So:
* Four entries named ``Ollama Cloud`` → one "Ollama Cloud" row with
four models inside.
* One entry named ``Ollama Cloud`` and one named ``Moonshot`` → two
separate rows, one model each.
Implementation
--------------
Replaces the single-pass loop in ``list_authenticated_providers()`` with
a two-pass approach:
1. First pass: build an ``OrderedDict`` keyed by ``custom_provider_slug(name)``,
accumulating ``models`` per group while preserving discovery order.
2. Second pass: iterate the groups and append one result row per group,
skipping any slug that already appeared in an earlier provider source
(the existing ``seen_slugs`` guard).
Insertion order is preserved via ``OrderedDict``, so providers and
their models still appear in the order the user listed them in
``custom_providers``. No new dependencies.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
