- 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
