Adds role='leaf'|'orchestrator' to delegate_task. With max_spawn_depth>=2,
an orchestrator child retains the 'delegation' toolset and can spawn its
own workers; leaf children cannot delegate further (identical to today).
Default posture is flat — max_spawn_depth=1 means a depth-0 parent's
children land at the depth-1 floor and orchestrator role silently
degrades to leaf. Users opt into nested delegation by raising
max_spawn_depth to 2 or 3 in config.yaml.
Also threads acp_command/acp_args through the main agent loop's delegate
dispatch (previously silently dropped in the schema) via a new
_dispatch_delegate_task helper, and adds a DelegateEvent enum with
legacy-string back-compat for gateway/ACP/CLI progress consumers.
Config (hermes_cli/config.py defaults):
delegation.max_concurrent_children: 3 # floor-only, no upper cap
delegation.max_spawn_depth: 1 # 1=flat (default), 2-3 unlock nested
delegation.orchestrator_enabled: true # global kill switch
Salvaged from @pefontana's PR #11215. Overrides vs. the original PR:
concurrency stays at 3 (PR bumped to 5 + cap 8 — we keep the floor only,
no hard ceiling); max_spawn_depth defaults to 1 (PR defaulted to 2 which
silently enabled one level of orchestration for every user).
Co-authored-by: pefontana <fontana.pedro93@gmail.com>
Matches the default-config removal in the preceding commit.
default_toolsets was documented for users to set but was never actually
read at runtime, so showing it in the example config and the delegation
user guide was misleading.
No deprecation note is added: the key was always a no-op, so users who
copied it from the example continue to see no behavior change. Their
config.yaml still parses; the key is just silently unused, same as
before.
Part of Initiative 2 / M0.5.
Users can declare shell scripts in config.yaml under a hooks: block that
fire on plugin-hook events (pre_tool_call, post_tool_call, pre_llm_call,
subagent_stop, etc). Scripts receive JSON on stdin, can return JSON on
stdout to block tool calls or inject context pre-LLM.
Key design:
- Registers closures on existing PluginManager._hooks dict — zero changes
to invoke_hook() call sites
- subprocess.run(shell=False) via shlex.split — no shell injection
- First-use consent per (event, command) pair, persisted to allowlist JSON
- Bypass via --accept-hooks, HERMES_ACCEPT_HOOKS=1, or hooks_auto_accept
- hermes hooks list/test/revoke/doctor CLI subcommands
- Adds subagent_stop hook event fired after delegate_task children exit
- Claude Code compatible response shapes accepted
Cherry-picked from PR #13143 by @pefontana.
Smart model routing (auto-routing short/simple turns to a cheap model
across providers) was opt-in and disabled by default. This removes the
feature wholesale: the routing module, its config keys, docs, tests, and
the orchestration scaffolding it required in cli.py / gateway/run.py /
cron/scheduler.py.
The /fast (Priority Processing / Anthropic fast mode) feature kept its
hooks into _resolve_turn_agent_config — those still build a route dict
and attach request_overrides when the model supports it; the route now
just always uses the session's primary model/provider rather than
running prompts through choose_cheap_model_route() first.
Also removed:
- DEFAULT_CONFIG['smart_model_routing'] block and matching commented-out
example sections in hermes_cli/config.py and cli-config.yaml.example
- _load_smart_model_routing() / self._smart_model_routing on GatewayRunner
- self._smart_model_routing / self._active_agent_route_signature on
HermesCLI (signature kept; just no longer initialised through the
smart-routing pipeline)
- route_label parameter on HermesCLI._init_agent (only set by smart
routing; never read elsewhere)
- 'Smart Model Routing' section in website/docs/integrations/providers.md
- tip in hermes_cli/tips.py
- entries in hermes_cli/dump.py + hermes_cli/web_server.py
- row in skills/autonomous-ai-agents/hermes-agent/SKILL.md
Tests:
- Deleted tests/agent/test_smart_model_routing.py
- Rewrote tests/agent/test_credential_pool_routing.py to target the
simplified _resolve_turn_agent_config directly (preserves credential
pool propagation + 429 rotation coverage)
- Dropped 'cheap model' test from test_cli_provider_resolution.py
- Dropped resolve_turn_route patches from cli + gateway test_fast_command
— they now exercise the real method end-to-end
- Removed _smart_model_routing stub assignments from gateway/cron test
helpers
Targeted suites: 74/74 in the directly affected test files;
tests/agent + tests/cron + tests/cli pass except 5 failures that
already exist on main (cron silent-delivery + alias quick-command).
AWS Bedrock paths (bedrock_converse + AnthropicBedrock SDK) use boto3
with its own timeout config and are not wired to the per-provider knob.
Documented in cli-config.yaml.example and website configuration.md so
users don't expect it to take effect there.
Live test with timeout_seconds: 0.5 on claude-sonnet-4.6 proved the
initial wiring was insufficient: run_agent.py was overriding the
client-level timeout on every call via hardcoded per-request kwargs.
Root cause: run_agent.py had two sites that pass an explicit timeout=
kwarg into chat.completions.create() — api_kwargs['timeout'] at line
7075 (HERMES_API_TIMEOUT=1800s default) and the streaming path's
_httpx.Timeout(..., read=HERMES_STREAM_READ_TIMEOUT=120s, ...) at line
5760. Both override the per-provider config value the client was
constructed with, so a 0.5s config timeout would silently not enforce.
This commit:
- Adds AIAgent._resolved_api_call_timeout() — config > HERMES_API_TIMEOUT env > 1800s default.
- Uses it for the non-streaming api_kwargs['timeout'] field.
- Uses it for the streaming path's httpx.Timeout(connect, read, write, pool)
so both connect and read respect the configured value when set.
Local-provider auto-bump (Ollama/vLLM cold-start) only applies when
no explicit config value is set.
- New test: test_resolved_api_call_timeout_priority covers all three
precedence cases (config, env, default).
Live verified: 0.5s config on claude-sonnet-4.6 now triggers
APITimeoutError at ~3s per retry, exhausts 3 retries in ~15s total
(was: 29-47s success with timeout ignored). Positive case (60s config
+ gpt-4o-mini) still succeeds at 1.3s.
Follow-up on top of mvanhorn's cherry-picked commit. Original PR only
wired request_timeout_seconds into the explicit-creds OpenAI branch at
run_agent.py init; router-based implicit auth, native Anthropic, and the
fallback chain were still hardcoded to SDK defaults.
- agent/anthropic_adapter.py: build_anthropic_client() accepts an optional
timeout kwarg (default 900s preserved when unset/invalid).
- run_agent.py: resolve per-provider/per-model timeout once at init; apply
to Anthropic native init + post-refresh rebuild + stale/interrupt
rebuilds + switch_model + _restore_primary_runtime + the OpenAI
implicit-auth path + _try_activate_fallback (with immediate client
rebuild so the first fallback request carries the configured timeout).
- tests: cover anthropic adapter kwarg honoring; widen mock signatures
to accept the new timeout kwarg.
- docs/example: clarify that the knob now applies to every transport,
the fallback chain, and rebuilds after credential rotation.
Adds optional providers.<id>.request_timeout_seconds and
providers.<id>.models.<model>.timeout_seconds config, resolved via a new
hermes_cli/timeouts.py helper and applied where client_kwargs is built
in run_agent.py. Zero default behavior change: when both keys are unset,
the openai SDK default takes over.
Mirrors the existing _get_task_timeout pattern in agent/auxiliary_client.py
for auxiliary tasks - the primary turn path just never got the equivalent
knob.
Cross-project demand: openclaw/openclaw#43946 (17 reactions) asks for
exactly this config - specifically calls out Ollama cold-start hanging
the client.
Follow-up on the native NVIDIA NIM provider salvage. The original PR wired
PROVIDER_REGISTRY + HERMES_OVERLAYS correctly but missed several touchpoints
required for full parity with other OpenAI-compatible providers (xai,
huggingface, deepseek, zai).
Gaps closed:
- hermes_cli/main.py:
- Add 'nvidia' to the _model_flow_api_key_provider dispatch tuple so
selecting 'NVIDIA NIM' in `hermes model` actually runs the api-key
provider flow (previously fell through silently).
- Add 'nvidia' to `hermes chat --provider` argparse choices so the
documented test command (`hermes chat --provider nvidia --model ...`)
parses successfully.
- hermes_cli/config.py: Register NVIDIA_API_KEY and NVIDIA_BASE_URL in
OPTIONAL_ENV_VARS so setup wizard can prompt for them and they're
auto-added to the subprocess env blocklist.
- hermes_cli/doctor.py: Add NVIDIA NIM row to `_apikey_providers` so
`hermes doctor` probes https://integrate.api.nvidia.com/v1/models.
- hermes_cli/dump.py: Add NVIDIA_API_KEY → 'nvidia' mapping for
`hermes dump` credential masking.
- tests/tools/test_local_env_blocklist.py: Extend registry_vars fixture
with NVIDIA_API_KEY to verify it's blocked from leaking into subprocesses.
- agent/model_metadata.py: Add 'nemotron' → 131072 context-length entry
so all Nemotron variants get 128K context via substring match (rather
than falling back to MINIMUM_CONTEXT_LENGTH).
- hermes_cli/models.py: Fix hallucinated model ID
'nvidia/nemotron-3-nano-8b-a4b' → 'nvidia/nemotron-3-nano-30b-a3b'
(verified against live integrate.api.nvidia.com/v1/models catalog).
Expand curated list from 5 to 9 agentic models mapping to OpenRouter
defaults per provider-guide convention: add qwen3.5-397b-a17b,
deepseek-v3.2, llama-3.3-nemotron-super-49b-v1.5, gpt-oss-120b.
- cli-config.yaml.example: Document 'nvidia' provider option.
- scripts/release.py: Map asurla@nvidia.com → anniesurla in AUTHOR_MAP
for CI attribution.
E2E verified: `hermes chat --provider nvidia ...` now reaches NVIDIA's
endpoint (returns 401 with bogus key instead of argparse error);
`hermes doctor` detects NVIDIA NIM when NVIDIA_API_KEY is set.
- 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
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.
Remove the backward-compat code paths that read compression provider/model
settings from legacy config keys and env vars, which caused silent failures
when auto-detection resolved to incompatible backends.
What changed:
- Remove compression.summary_model, summary_provider, summary_base_url from
DEFAULT_CONFIG and cli.py defaults
- Remove backward-compat block in _resolve_task_provider_model() that read
from the legacy compression section
- Remove _get_auxiliary_provider() and _get_auxiliary_env_override() helper
functions (AUXILIARY_*/CONTEXT_* env var readers)
- Remove env var fallback chain for per-task overrides
- Update hermes config show to read from auxiliary.compression
- Add config migration (v16→17) that moves non-empty legacy values to
auxiliary.compression and strips the old keys
- Update example config and openclaw migration script
- Remove/update tests for deleted code paths
Compression model/provider is now configured exclusively via:
auxiliary.compression.provider / auxiliary.compression.model
Closes#8923
The check_interval parameter on terminal_tool sent periodic output
updates to the gateway chat, but these were display-only — the agent
couldn't see or act on them. This added schema bloat and introduced
a bug where notify_on_complete=True was silently dropped when
check_interval was also set (the not-check_interval guard skipped
fast-watcher registration, and the check_interval watcher dict
was missing the notify_on_complete key).
Removing check_interval entirely:
- Eliminates the notify_on_complete interaction bug
- Reduces tool schema size (one fewer parameter for the model)
- Simplifies the watcher registration path
- notify_on_complete (agent wake-on-completion) still works
- watch_patterns (output alerting) still works
- process(action='poll') covers manual status checking
Closes#7947 (root cause eliminated rather than patched).
Add display.interim_assistant_messages config (enabled by default) that
forwards completed assistant commentary between tool calls to the user
as separate chat messages. Models already emit useful status text like
'I'll inspect the repo first.' — this surfaces it on Telegram, Discord,
and other messaging platforms instead of swallowing it.
Independent from tool_progress and gateway streaming. Disabled for
webhooks. Uses GatewayStreamConsumer when available, falls back to
direct adapter send. Tracks response_previewed to prevent double-delivery
when interim message matches the final response.
Also fixes: cursor not stripped from fallback prefix in stream consumer
(affected continuation calculation on no-edit platforms like Signal).
Cherry-picked from PR #7885 by asheriif, default changed to enabled.
Fixes#5016
Cherry-picked from PR #7702 by kshitijk4poor.
Adds Xiaomi MiMo as a direct provider (XIAOMI_API_KEY) with models:
- mimo-v2-pro (1M context), mimo-v2-omni (256K, multimodal), mimo-v2-flash (256K, cheapest)
Standard OpenAI-compatible provider checklist: auth.py, config.py, models.py,
main.py, providers.py, doctor.py, model_normalize.py, model_metadata.py,
models_dev.py, auxiliary_client.py, .env.example, cli-config.yaml.example.
Follow-up: vision tasks use mimo-v2-omni (multimodal) instead of the user's
main model. Non-vision aux uses the user's selected model. Added
_PROVIDER_VISION_MODELS dict for provider-specific vision model overrides.
On failure, falls back to aggregators (gemini flash) via existing fallback chain.
Corrects pre-existing context lengths: mimo-v2-pro 1048576→1000000,
mimo-v2-omni 1048576→256000, adds mimo-v2-flash 256000.
36 tests covering registry, aliases, auto-detect, credentials, models.dev,
normalization, URL mapping, providers module, doctor, aux client, vision
model override, and agent init.
Legacy flat stt.model config key (from cli-config.yaml.example and older
versions) was passed as a model override to transcribe_audio() by the
gateway, bypassing provider-specific model resolution. When the provider
was 'local' (faster-whisper), this caused:
ValueError: Invalid model size 'whisper-1'
Changes:
- gateway/run.py, discord.py: stop passing model override — let
transcribe_audio() handle provider-specific model resolution internally
- get_stt_model_from_config(): now provider-aware, reads from the correct
nested section (stt.local.model, stt.openai.model, etc.); ignores
legacy flat key for local provider to prevent model name mismatch
- cli-config.yaml.example: updated STT section to show nested provider
config structure instead of legacy flat key
- config migration v13→v14: moves legacy stt.model to the correct
provider section and removes the flat key
Reported by community user on Discord.
When the API returns "max_tokens too large given prompt" (input tokens
are within the context window, but input + requested output > window),
the old code incorrectly routed through the same handler as "prompt too
long" errors, calling get_next_probe_tier() and permanently halving
context_length. This made things worse: the window was fine, only the
requested output size needed trimming for that one call.
Two distinct error classes now handled separately:
Prompt too long — input itself exceeds context window.
Fix: compress history + halve context_length (existing behaviour,
unchanged).
Output cap too large — input OK, but input + max_tokens > window.
Fix: parse available_tokens from the error message, set a one-shot
_ephemeral_max_output_tokens override for the retry, and leave
context_length completely untouched.
Changes:
- agent/model_metadata.py: add parse_available_output_tokens_from_error()
that detects Anthropic's "available_tokens: N" error format and returns
the available output budget, or None for all other error types.
- run_agent.py: call the new parser first in the is_context_length_error
block; if it fires, set _ephemeral_max_output_tokens (with a 64-token
safety margin) and break to retry without touching context_length.
_build_api_kwargs consumes the ephemeral value exactly once then clears
it so subsequent calls use self.max_tokens normally.
- agent/anthropic_adapter.py: expand build_anthropic_kwargs docstring to
clearly document the max_tokens (output cap) vs context_length (total
window) distinction, which is a persistent source of confusion due to
the OpenAI-inherited "max_tokens" name.
- cli-config.yaml.example: add inline comments explaining both keys side
by side where users are most likely to look.
- website/docs/integrations/providers.md: add a callout box at the top
of "Context Length Detection" and clarify the troubleshooting entry.
- tests/test_ctx_halving_fix.py: 24 tests across four classes covering
the parser, build_anthropic_kwargs clamping, ephemeral one-shot
consumption, and the invariant that context_length is never mutated
on output-cap errors.
Introduce gateway_timeout_warning (default 900s) as a pre-timeout alert
layer. When inactivity reaches the warning threshold, a single
notification is sent to the user offering to wait or reset. If
inactivity continues to the gateway_timeout (default 1800s), the full
timeout fires as before.
This gives users a chance to intervene before work is lost on slow
API providers without disabling the safety timeout entirely.
Config: agent.gateway_timeout_warning in config.yaml, or
HERMES_AGENT_TIMEOUT_WARNING env var (0 = disable warning).
* refactor: remove browser_close tool — auto-cleanup handles it
The browser_close tool was called in only 9% of browser sessions (13/144
navigations across 66 sessions), always redundantly — cleanup_browser()
already runs via _cleanup_task_resources() at conversation end, and the
background inactivity reaper catches anything else.
Removing it saves one tool schema slot in every browser-enabled API call.
Also fixes a latent bug: cleanup_browser() now handles Camofox sessions
too (previously only Browserbase). Camofox sessions were never auto-cleaned
per-task because they live in a separate dict from _active_sessions.
Files changed (13):
- tools/browser_tool.py: remove function, schema, registry entry; add
camofox cleanup to cleanup_browser()
- toolsets.py, model_tools.py, prompt_builder.py, display.py,
acp_adapter/tools.py: remove browser_close from all tool lists
- tests/: remove browser_close test, update toolset assertion
- docs/skills: remove all browser_close references
* fix: repeat browser_scroll 5x per call for meaningful page movement
Most backends scroll ~100px per call — barely visible on a typical
viewport. Repeating 5x gives ~500px (~half a viewport), making each
scroll tool call actually useful.
Backend-agnostic approach: works across all 7+ browser backends without
needing to configure each one's scroll amount individually. Breaks
early on error for the agent-browser path.
* feat: auto-return compact snapshot from browser_navigate
Every browser session starts with navigate → snapshot. Now navigate
returns the compact accessibility tree snapshot inline, saving one
tool call per browser task.
The snapshot captures the full page DOM (not viewport-limited), so
scroll position doesn't affect it. browser_snapshot remains available
for refreshing after interactions or getting full=true content.
Both Browserbase and Camofox paths auto-snapshot. If the snapshot
fails for any reason, navigation still succeeds — the snapshot is
a bonus, not a requirement.
Schema descriptions updated to guide models: navigate mentions it
returns a snapshot, snapshot mentions it's for refresh/full content.
* refactor: slim cronjob tool schema — consolidate model/provider, drop unused params
Session data (151 calls across 67 sessions) showed several schema
properties were never used by models. Consolidated and cleaned up:
Removed from schema (still work via backend/CLI):
- skill (singular): use skills array instead
- reason: pause-only, unnecessary
- include_disabled: now defaults to true
- base_url: extreme edge case, zero usage
- provider (standalone): merged into model object
Consolidated:
- model + provider → single 'model' object with {model, provider} fields.
If provider is omitted, the current main provider is pinned at creation
time so the job stays stable even if the user changes their default.
Kept:
- script: useful data collection feature
- skills array: standard interface for skill loading
Schema shrinks from 14 to 10 properties. All backend functionality
preserved — the Python function signature and handler lambda still
accept every parameter.
* fix: remove mixture_of_agents from core toolsets — opt-in only via hermes tools
MoA was in _HERMES_CORE_TOOLS and composite toolsets (hermes-cli,
hermes-messaging, safe), which meant it appeared in every session
for anyone with OPENROUTER_API_KEY set. The _DEFAULT_OFF_TOOLSETS
gate only works after running 'hermes tools' explicitly.
Now MoA only appears when a user explicitly enables it via
'hermes tools'. The moa toolset definition and check_fn remain
unchanged — it just needs to be opted into.
- Add OLLAMA_API_KEY to credential resolution chain for ollama.com endpoints
- Update requested_provider/_explicit_api_key/_explicit_base_url after /model
switch so _ensure_runtime_credentials() doesn't revert the switch
- Pass base_url/api_key from fallback config to resolve_provider_client()
- Add DirectAlias system: user-configurable model_aliases in config.yaml
checked before catalog resolution, with reverse lookup by model ID
- Add /model tab completion showing aliases with provider metadata
Co-authored-by: LucidPaths <LucidPaths@users.noreply.github.com>
* feat(telegram): add webhook mode as alternative to polling
When TELEGRAM_WEBHOOK_URL is set, the adapter starts an HTTP webhook
server (via python-telegram-bot's start_webhook()) instead of long
polling. This enables cloud platforms like Fly.io and Railway to
auto-wake suspended machines on inbound HTTP traffic.
Polling remains the default — no behavior change unless the env var
is set.
Env vars:
TELEGRAM_WEBHOOK_URL Public HTTPS URL for Telegram to push to
TELEGRAM_WEBHOOK_PORT Local listen port (default 8443)
TELEGRAM_WEBHOOK_SECRET Secret token for update verification
Cherry-picked and adapted from PR #2022 by SHL0MS. Preserved all
current main enhancements (network error recovery, polling conflict
detection, DM topics setup).
Co-authored-by: SHL0MS <SHL0MS@users.noreply.github.com>
* fix: send_document call in background task delivery + vision download timeout
Two fixes salvaged from PR #2269 by amethystani:
1. gateway/run.py: adapter.send_file() → adapter.send_document()
send_file() doesn't exist on BasePlatformAdapter. Background task
media files were silently never delivered (AttributeError swallowed
by except Exception: pass).
2. tools/vision_tools.py: configurable image download timeout via
HERMES_VISION_DOWNLOAD_TIMEOUT env var (default 30s), plus guard
against raise None when max_retries=0.
The third fix in #2269 (opencode-go auth config) was already resolved
on main.
Co-authored-by: amethystani <amethystani@users.noreply.github.com>
---------
Co-authored-by: SHL0MS <SHL0MS@users.noreply.github.com>
Co-authored-by: amethystani <amethystani@users.noreply.github.com>
Previously, when no API keys or provider credentials were found, Hermes
silently defaulted to OpenRouter + Claude Opus. This caused confusion
when users configured local servers (LM Studio, Ollama, etc.) with a
typo or unrecognized provider name — the system would silently route to
OpenRouter instead of telling them something was wrong.
Changes:
- resolve_provider() now raises AuthError when no credentials are found
instead of returning 'openrouter' as a silent fallback
- Added local server aliases: lmstudio, ollama, vllm, llamacpp → custom
- Removed hardcoded 'anthropic/claude-opus-4.6' fallback from gateway
and cron scheduler (they read from config.yaml instead)
- Updated cli-config.yaml.example with complete provider documentation
including all supported providers, aliases, and local server setup
Add skills.external_dirs config option — a list of additional directories
to scan for skills alongside ~/.hermes/skills/. External dirs are read-only:
skill creation/editing always writes to the local dir. Local skills take
precedence when names collide.
This lets users share skills across tools/agents without copying them into
Hermes's own directory (e.g. ~/.agents/skills, /shared/team-skills).
Changes:
- agent/skill_utils.py: add get_external_skills_dirs() and get_all_skills_dirs()
- agent/prompt_builder.py: scan external dirs in build_skills_system_prompt()
- tools/skills_tool.py: _find_all_skills() and skill_view() search external dirs;
security check recognizes configured external dirs as trusted
- agent/skill_commands.py: /skill slash commands discover external skills
- hermes_cli/config.py: add skills.external_dirs to DEFAULT_CONFIG
- cli-config.yaml.example: document the option
- tests/agent/test_external_skills.py: 11 tests covering discovery, precedence,
deduplication, and skill_view for external skills
Requested by community member primco.
Users intuitively write model: { model: my-model } instead of
model: { default: my-model } and it silently falls back to the
hardcoded default. Now both spellings work across all three config
consumers: runtime_provider, CLI, and gateway.
Co-authored-by: ygd58 <ygd58@users.noreply.github.com>
Two changes:
1. Fix /queue command: remove the _agent_running guard that rejected
/queue after the agent finished. The prompt was deferred in
_pending_input until the agent completed, then the handler checked
_agent_running (now False) and rejected it. /queue now always queues
regardless of timing.
2. Add display.busy_input_mode config (CLI-only):
- 'interrupt' (default): Enter while busy interrupts the current run
(preserves existing behavior)
- 'queue': Enter while busy queues the message for the next turn,
with a 'Queued for the next turn: ...' confirmation
Ctrl+C always interrupts regardless of this setting.
Salvaged from PR #3037 by StefanoChiodino. Key differences:
- Default is 'interrupt' (preserves existing behavior) not 'queue'
- No config version bump (unnecessary for new key in existing section)
- Simpler normalization (no alias map)
- /queue fix is simpler: just remove the guard instead of intercepting
commands during busy state
- threshold: 0.80 → 0.50 (compress at 50%, not 80%)
- target_ratio: 0.40 → 0.20, now relative to threshold not total context
(20% of 50% = 10% of context as tail budget)
- summary ceiling: 32K → 12K (Gemini can't output more than ~12K)
- Updated DEFAULT_CONFIG, config display, example config, and tests
The summary_target_tokens parameter was accepted in the constructor,
stored on the instance, and never used — the summary budget was always
computed from hardcoded module constants (_SUMMARY_RATIO=0.20,
_MAX_SUMMARY_TOKENS=8000). This caused two compounding problems:
1. The config value was silently ignored, giving users no control
over post-compression size.
2. Fixed budgets (20K tail, 8K summary cap) didn't scale with
context window size. Switching from a 1M-context model to a
200K model would trigger compression that nuked 350K tokens
of conversation history down to ~30K.
Changes:
- Replace summary_target_tokens with summary_target_ratio (default 0.40)
which sets the post-compression target as a fraction of context_length.
Tail token budget and summary cap now scale proportionally:
MiniMax 200K → ~80K post-compression
GPT-5 1M → ~400K post-compression
- Change threshold_percent default: 0.50 → 0.80 (don't fire until
80% of context is consumed)
- Change protect_last_n default: 4 → 20 (preserve ~10 full turns)
- Summary token cap scales to 5% of context (was fixed 8K), capped
at 32K ceiling
- Read target_ratio and protect_last_n from config.yaml compression
section (both are now configurable)
- Remove hardcoded summary_target_tokens=500 from run_agent.py
- Add 5 new tests for ratio scaling, clamping, and new defaults
Streaming provides a better UX — tokens appear as they arrive instead
of waiting for the full response. show_reasoning remains false so
thinking blocks are not streamed to the user.
The top-level 'toolsets' key in config.yaml was never read at runtime.
Tool selection uses platform_toolsets (per-platform) or the --toolsets
CLI flag. The key existed in load_cli_config() defaults and the example
config as 'toolsets: [all]', misleading users into thinking it
controlled tool availability.
- Remove from load_cli_config() hardcoded defaults
- Remove from hermes config show output
- Replace in cli-config.yaml.example with deprecation note pointing
to platform_toolsets and hermes tools
Docker terminal sessions are secret-dark by default. This adds
terminal.docker_forward_env as an explicit allowlist for env vars
that may be forwarded into Docker containers.
Values resolve from the current shell first, then fall back to
~/.hermes/.env. Only variables the user explicitly lists are
forwarded — nothing is auto-exposed.
Cherry-picked from PR #1449 by @teknium1, conflict-resolved onto
current main.
Fixes#1436
Supersedes #1439
* feat: add optional smart model routing
Add a conservative cheap-vs-strong routing option that can send very short/simple turns to a cheaper model across providers while keeping the primary model for complex work. Wire it through CLI, gateway, and cron, and document the config.yaml workflow.
* fix(gateway): remove recursive ExecStop from systemd units, extend TimeoutStopSec to 60s
* fix(gateway): avoid recursive ExecStop in user systemd unit
* fix: extend ExecStop removal and TimeoutStopSec=60 to system unit
The cherry-picked PR #1448 fix only covered the user systemd unit.
The system unit had the same TimeoutStopSec=15 and could benefit
from the same 60s timeout for clean shutdown. Also adds a regression
test for the system unit.
---------
Co-authored-by: Ninja <ninja@local>
* feat(skills): add blender-mcp optional skill for 3D modeling
Control a running Blender instance from Hermes via socket connection
to the blender-mcp addon (port 9876). Supports creating 3D objects,
materials, animations, and running arbitrary bpy code.
Placed in optional-skills/ since it requires Blender 4.3+ desktop
with a third-party addon manually started each session.
* feat(acp): support slash commands in ACP adapter (#1532)
Adds /help, /model, /tools, /context, /reset, /compact, /version
to the ACP adapter (VS Code, Zed, JetBrains). Commands are handled
directly in the server without instantiating the TUI — each command
queries agent/session state and returns plain text.
Unrecognized /commands fall through to the LLM as normal messages.
/model uses detect_provider_for_model() for auto-detection when
switching models, matching the CLI and gateway behavior.
Fixes#1402
* fix(logging): improve error logging in session search tool (#1533)
* fix(gateway): restart on retryable startup failures (#1517)
* feat(email): add skip_attachments option via config.yaml
* feat(email): add skip_attachments option via config.yaml
Adds a config.yaml-driven option to skip email attachments in the
gateway email adapter. Useful for malware protection and bandwidth
savings.
Configure in config.yaml:
platforms:
email:
skip_attachments: true
Based on PR #1521 by @an420eth, changed from env var to config.yaml
(via PlatformConfig.extra) to match the project's config-first pattern.
* docs: document skip_attachments option for email adapter
* fix(telegram): retry on transient TLS failures during connect and send
Add exponential-backoff retry (3 attempts) around initialize() to
handle transient TLS resets during gateway startup. Also catches
TimedOut and OSError in addition to NetworkError.
Add exponential-backoff retry (3 attempts) around send_message() for
NetworkError during message delivery, wrapping the existing Markdown
fallback logic.
Both imports are guarded with try/except ImportError for test
environments where telegram is mocked.
Based on PR #1527 by cmd8. Closes#1526.
* feat: permissive block_anchor thresholds and unicode normalization (#1539)
Salvaged from PR #1528 by an420eth. Closes#517.
Improves _strategy_block_anchor in fuzzy_match.py:
- Add unicode normalization (smart quotes, em/en-dashes, ellipsis,
non-breaking spaces → ASCII) so LLM-produced unicode artifacts
don't break anchor line matching
- Lower thresholds: 0.10 for unique matches (was 0.70), 0.30 for
multiple candidates — if first/last lines match exactly, the
block is almost certainly correct
- Use original (non-normalized) content for offset calculation to
preserve correct character positions
Tested: 3 new scenarios fixed (em-dash anchors, non-breaking space
anchors, very-low-similarity unique matches), zero regressions on
all 9 existing fuzzy match tests.
Co-authored-by: an420eth <an420eth@users.noreply.github.com>
* feat(cli): add file path autocomplete in the input prompt (#1545)
When typing a path-like token (./ ../ ~/ / or containing /),
the CLI now shows filesystem completions in the dropdown menu.
Directories show a trailing slash and 'dir' label; files show
their size. Completions are case-insensitive and capped at 30
entries.
Triggered by tokens like:
edit ./src/ma → shows ./src/main.py, ./src/manifest.json, ...
check ~/doc → shows ~/docs/, ~/documents/, ...
read /etc/hos → shows /etc/hosts, /etc/hostname, ...
open tools/reg → shows tools/registry.py
Slash command autocomplete (/help, /model, etc.) is unaffected —
it still triggers when the input starts with /.
Inspired by OpenCode PR #145 (file path completion menu).
Implementation:
- hermes_cli/commands.py: _extract_path_word() detects path-like
tokens, _path_completions() yields filesystem Completions with
size labels, get_completions() routes to paths vs slash commands
- tests/hermes_cli/test_path_completion.py: 26 tests covering
path extraction, prefix filtering, directory markers, home
expansion, case-insensitivity, integration with slash commands
* feat(privacy): redact PII from LLM context when privacy.redact_pii is enabled
Add privacy.redact_pii config option (boolean, default false). When
enabled, the gateway redacts personally identifiable information from
the system prompt before sending it to the LLM provider:
- Phone numbers (user IDs on WhatsApp/Signal) → hashed to user_<sha256>
- User IDs → hashed to user_<sha256>
- Chat IDs → numeric portion hashed, platform prefix preserved
- Home channel IDs → hashed
- Names/usernames → NOT affected (user-chosen, publicly visible)
Hashes are deterministic (same user → same hash) so the model can
still distinguish users in group chats. Routing and delivery use
the original values internally — redaction only affects LLM context.
Inspired by OpenClaw PR #47959.
* fix(privacy): skip PII redaction on Discord/Slack (mentions need real IDs)
Discord uses <@user_id> for mentions and Slack uses <@U12345> — the LLM
needs the real ID to tag users. Redaction now only applies to WhatsApp,
Signal, and Telegram where IDs are pure routing metadata.
Add 4 platform-specific tests covering Discord, WhatsApp, Signal, Slack.
* feat: smart approvals + /stop command (inspired by OpenAI Codex)
* feat: smart approvals — LLM-based risk assessment for dangerous commands
Adds a 'smart' approval mode that uses the auxiliary LLM to assess
whether a flagged command is genuinely dangerous or a false positive,
auto-approving low-risk commands without prompting the user.
Inspired by OpenAI Codex's Smart Approvals guardian subagent
(openai/codex#13860).
Config (config.yaml):
approvals:
mode: manual # manual (default), smart, off
Modes:
- manual — current behavior, always prompt the user
- smart — aux LLM evaluates risk: APPROVE (auto-allow), DENY (block),
or ESCALATE (fall through to manual prompt)
- off — skip all approval prompts (equivalent to --yolo)
When smart mode auto-approves, the pattern gets session-level approval
so subsequent uses of the same pattern don't trigger another LLM call.
When it denies, the command is blocked without user prompt. When
uncertain, it escalates to the normal manual approval flow.
The LLM prompt is carefully scoped: it sees only the command text and
the flagged reason, assesses actual risk vs false positive, and returns
a single-word verdict.
* feat: make smart approval model configurable via config.yaml
Adds auxiliary.approval section to config.yaml with the same
provider/model/base_url/api_key pattern as other aux tasks (vision,
web_extract, compression, etc.).
Config:
auxiliary:
approval:
provider: auto
model: '' # fast/cheap model recommended
base_url: ''
api_key: ''
Bridged to env vars in both CLI and gateway paths so the aux client
picks them up automatically.
* feat: add /stop command to kill all background processes
Adds a /stop slash command that kills all running background processes
at once. Currently users have to process(list) then process(kill) for
each one individually.
Inspired by OpenAI Codex's separation of interrupt (Ctrl+C stops current
turn) from /stop (cleans up background processes). See openai/codex#14602.
Ctrl+C continues to only interrupt the active agent turn — background
dev servers, watchers, etc. are preserved. /stop is the explicit way
to clean them all up.
* feat: first-class plugin architecture + hide status bar cost by default (#1544)
The persistent status bar now shows context %, token counts, and
duration but NOT $ cost by default. Cost display is opt-in via:
display:
show_cost: true
in config.yaml, or: hermes config set display.show_cost true
The /usage command still shows full cost breakdown since the user
explicitly asked for it — this only affects the always-visible bar.
Status bar without cost:
⚕ claude-sonnet-4 │ 12K/200K │ 6% │ 15m
Status bar with show_cost: true:
⚕ claude-sonnet-4 │ 12K/200K │ 6% │ $0.06 │ 15m
* feat: improve memory prioritization + aggressive skill updates (inspired by OpenAI Codex)
* feat: improve memory prioritization — user preferences over procedural knowledge
Inspired by OpenAI Codex's memory prompt improvements (openai/codex#14493)
which focus memory writes on user preferences and recurring patterns
rather than procedural task details.
Key insight: 'Optimize for reducing future user steering — the most
valuable memory prevents the user from having to repeat themselves.'
Changes:
- MEMORY_GUIDANCE (prompt_builder.py): added prioritization hierarchy
and the core principle about reducing user steering
- MEMORY_SCHEMA (memory_tool.py): reordered WHEN TO SAVE list to put
corrections first, added explicit PRIORITY guidance
- Memory nudge (run_agent.py): now asks specifically about preferences,
corrections, and workflow patterns instead of generic 'anything'
- Memory flush (run_agent.py): now instructs to prioritize user
preferences and corrections over task-specific details
* feat: more aggressive skill creation and update prompting
Press harder on skill updates — the agent should proactively patch
skills when it encounters issues during use, not wait to be asked.
Changes:
- SKILLS_GUIDANCE: 'consider saving' → 'save'; added explicit instruction
to patch skills immediately when found outdated/wrong
- Skills header: added instruction to update loaded skills before finishing
if they had missing steps or wrong commands
- Skill nudge: more assertive ('save the approach' not 'consider saving'),
now also prompts for updating existing skills used in the task
- Skill nudge interval: lowered default from 15 to 10 iterations
- skill_manage schema: added 'patch it immediately' to update triggers
* feat: first-class plugin architecture (#1555)
Plugin system for extending Hermes with custom tools, hooks, and
integrations — no source code changes required.
Core system (hermes_cli/plugins.py):
- Plugin discovery from ~/.hermes/plugins/, .hermes/plugins/, and
pip entry_points (hermes_agent.plugins group)
- PluginContext with register_tool() and register_hook()
- 6 lifecycle hooks: pre/post tool_call, pre/post llm_call,
on_session_start/end
- Namespace package handling for relative imports in plugins
- Graceful error isolation — broken plugins never crash the agent
Integration (model_tools.py):
- Plugin discovery runs after built-in + MCP tools
- Plugin tools bypass toolset filter via get_plugin_tool_names()
- Pre/post tool call hooks fire in handle_function_call()
CLI:
- /plugins command shows loaded plugins, tool counts, status
- Added to COMMANDS dict for autocomplete
Docs:
- Getting started guide (build-a-hermes-plugin.md) — full tutorial
building a calculator plugin step by step
- Reference page (features/plugins.md) — quick overview + tables
- Covers: file structure, schemas, handlers, hooks, data files,
bundled skills, env var gating, pip distribution, common mistakes
Tests: 16 tests covering discovery, loading, hooks, tool visibility.
* fix: hermes update causes dual gateways on macOS (launchd)
Three bugs worked together to create the dual-gateway problem:
1. cmd_update only checked systemd for gateway restart, completely
ignoring launchd on macOS. After killing the PID it would print
'Restart it with: hermes gateway run' even when launchd was about
to auto-respawn the process.
2. launchd's KeepAlive.SuccessfulExit=false respawns the gateway
after SIGTERM (non-zero exit), so the user's manual restart
created a second instance.
3. The launchd plist lacked --replace (systemd had it), so the
respawned gateway didn't kill stale instances on startup.
Fixes:
- Add --replace to launchd ProgramArguments (matches systemd)
- Add launchd detection to cmd_update's auto-restart logic
- Print 'auto-restart via launchd' instead of manual restart hint
* fix: add launchd plist auto-refresh + explicit restart in cmd_update
Two integration issues with the initial fix:
1. Existing macOS users with old plist (no --replace) would never
get the fix until manual uninstall/reinstall. Added
refresh_launchd_plist_if_needed() — mirrors the existing
refresh_systemd_unit_if_needed(). Called from launchd_start(),
launchd_restart(), and cmd_update.
2. cmd_update relied on KeepAlive respawn after SIGTERM rather than
explicit launchctl stop/start. This caused races: launchd would
respawn the old process before the PID file was cleaned up.
Now does explicit stop+start (matching how systemd gets an
explicit systemctl restart), with plist refresh first so the
new --replace flag is picked up.
---------
Co-authored-by: Ninja <ninja@local>
Co-authored-by: alireza78a <alireza78a@users.noreply.github.com>
Co-authored-by: Oktay Aydin <113846926+aydnOktay@users.noreply.github.com>
Co-authored-by: JP Lew <polydegen@protonmail.com>
Co-authored-by: an420eth <an420eth@users.noreply.github.com>
Documents the new streaming options in the example config:
- display.streaming for CLI (under display section)
- streaming.enabled + transport/interval/threshold/cursor for gateway
- Added streaming: false to load_cli_config() defaults dict
Add privacy.redact_pii config option (boolean, default false). When
enabled, the gateway redacts personally identifiable information from
the system prompt before sending it to the LLM provider:
- Phone numbers (user IDs on WhatsApp/Signal) → hashed to user_<sha256>
- User IDs → hashed to user_<sha256>
- Chat IDs → numeric portion hashed, platform prefix preserved
- Home channel IDs → hashed
- Names/usernames → NOT affected (user-chosen, publicly visible)
Hashes are deterministic (same user → same hash) so the model can
still distinguish users in group chats. Routing and delivery use
the original values internally — redaction only affects LLM context.
Inspired by OpenClaw PR #47959.
Keep Docker sandboxes isolated by default. Add an explicit terminal.docker_mount_cwd_to_workspace opt-in, thread it through terminal/file environment creation, and document the security tradeoff and config.yaml workflow clearly.
default group and channel sessions to per-user isolation, allow opting back into shared room sessions via config.yaml, and document Discord gateway routing and session behavior.
Integrate tirith as a pre-execution security scanner that detects
homograph URLs, pipe-to-interpreter patterns, terminal injection,
zero-width Unicode, and environment variable manipulation — threats
the existing 50-pattern dangerous command detector doesn't cover.
Architecture: gather-then-decide — both tirith and the dangerous
command detector run before any approval prompt, preventing gateway
force=True replay from bypassing one check when only the other was
shown to the user.
New files:
- tools/tirith_security.py: subprocess wrapper with auto-installer,
mandatory cosign provenance verification, non-blocking background
download, disk-persistent failure markers with retryable-cause
tracking (cosign_missing auto-clears when cosign appears on PATH)
- tests/tools/test_tirith_security.py: 62 tests covering exit code
mapping, fail_open, cosign verification, background install,
HERMES_HOME isolation, and failure recovery
- tests/tools/test_command_guards.py: 21 integration tests for the
combined guard orchestration
Modified files:
- tools/approval.py: add check_all_command_guards() orchestrator,
add allow_permanent parameter to prompt_dangerous_approval()
- tools/terminal_tool.py: replace _check_dangerous_command with
consolidated check_all_command_guards
- cli.py: update _approval_callback for allow_permanent kwarg,
call ensure_installed() at startup
- gateway/run.py: iterate pattern_keys list on replay approval,
call ensure_installed() at startup
- hermes_cli/config.py: add security config defaults, split
commented sections for independent fallback
- cli-config.yaml.example: document tirith security config
