Place a sentinel in _running_agents immediately after the "already
running" guard check passes — before any await. Without this, the
numerous await points between the guard (line 1324) and agent
registration (track_agent at line 4790) create a window where a
second message for the same session can bypass the guard and start
a duplicate agent, corrupting the transcript.
The await gap includes: hook emissions, vision enrichment (external
API call), audio transcription (external API call), session hygiene
compression, and the run_in_executor call itself. For messages with
media attachments the window can be several seconds wide.
The sentinel is wrapped in try/finally so it is always cleaned up —
even if the handler raises or takes an early-return path. When the
real AIAgent is created, track_agent() overwrites the sentinel with
the actual instance (preserving interrupt support).
Also handles the edge case where a message arrives while the sentinel
is set but no real agent exists yet: the message is queued via the
adapter's pending-message mechanism instead of attempting to call
interrupt() on the sentinel object.
MiniMax's default base URL was /v1 which caused runtime_provider to
default to chat_completions mode (OpenAI-style Authorization: Bearer
header). MiniMax rejects this with a 401 because they require the
Anthropic-style x-api-key header.
Changes:
- auth.py: Change default inference_base_url for minimax and minimax-cn
from /v1 to /anthropic
- runtime_provider.py: Auto-correct stale /v1 URLs from existing .env
files to /anthropic, and always default minimax/minimax-cn providers
to anthropic_messages mode
- Update tests to reflect new defaults, add tests for stale URL
auto-correction and explicit api_mode override
Based on PR #2100 by @devorun. Fixes#2094.
Co-authored-by: Test <test@test.com>
When LM Studio has a model loaded with a custom context size (e.g.,
122K), prefer that over the model's max_context_length (e.g., 1M).
This makes the TUI status bar show the actual runtime context window.
Instead of defaulting to 2M for unknown local models, query the server
API for the real context length. Supports Ollama (/api/show), vLLM
(max_model_len), and LM Studio (/v1/models). Results are cached to
avoid repeated queries.
* fix(codex): treat reasoning-only responses as incomplete, not stop
When a Codex Responses API response contains only reasoning items
(encrypted thinking state) with no message text or tool calls, the
_normalize_codex_response method was setting finish_reason='stop'.
This sent the response into the empty-content retry loop, which
burned 3 retries and then failed — exactly the pattern Nester
reported in Discord.
Two fixes:
1. _normalize_codex_response: reasoning-only responses (reasoning_items_raw
non-empty but no final_text) now get finish_reason='incomplete', routing
them to the Codex continuation path instead of the retry loop.
2. Incomplete handling: also checks for codex_reasoning_items when deciding
whether to preserve an interim message, so encrypted reasoning state is
not silently dropped when there is no visible reasoning text.
Adds 4 regression tests covering:
- Unit: reasoning-only → incomplete, reasoning+content → stop
- E2E: reasoning-only → continuation → final answer succeeds
- E2E: encrypted reasoning items preserved in interim messages
* fix(codex): ensure reasoning items have required following item in API input
Follow-up to the reasoning-only response fix. Three additional issues
found by tracing the full replay path:
1. _chat_messages_to_responses_input: when a reasoning-only interim
message was converted to Responses API input, the reasoning items
were emitted as the last items with no following item. The Responses
API requires a following item after each reasoning item (otherwise:
'missing_following_item' error, as seen in OpenHands #11406). Now
emits an empty assistant message as the required following item when
content is empty but reasoning items were added.
2. Duplicate detection: two consecutive reasoning-only incomplete
messages with identical empty content/reasoning but different
encrypted codex_reasoning_items were incorrectly treated as
duplicates, silently dropping the second response's reasoning state.
Now includes codex_reasoning_items in the duplicate comparison.
3. Added tests for both the API input conversion path and the duplicate
detection edge case.
Research context: verified against OpenCode (uses Vercel AI SDK, no
retry loop so avoids the issue), Clawdbot (drops orphaned reasoning
blocks entirely), and OpenHands (hit the missing_following_item error).
Our approach preserves reasoning continuity while satisfying the API
constraint.
---------
Co-authored-by: Test <test@test.com>
* fix: persist ACP sessions to disk so they survive process restarts
The ACP adapter stored sessions entirely in-memory. When the editor
restarted the ACP subprocess (idle timeout, crash, system sleep/wake,
editor restart), all sessions were lost. The editor's load_session /
resume_session calls would fail to find the session, forcing a new
empty session and losing all conversation history.
Changes:
- SessionManager now persists each session as a JSON file under
~/.hermes/acp_sessions/<session_id>.json
- get_session() transparently restores from disk when not in memory
- update_cwd(), fork_session(), list_sessions() all check disk
- server.py calls save_session() after prompt completion, /reset,
/compact, and model switches
- cleanup() and remove_session() delete disk files too
- Sessions have a 7-day TTL; expired sessions are pruned on startup
- Atomic writes via tempfile + os.replace to prevent corruption
- 11 new tests covering persistence, disk restoration, and TTL expiry
* refactor: use SessionDB instead of JSON files for ACP session persistence
Replace the standalone JSON file persistence layer with SessionDB
(~/.hermes/state.db) integration. ACP sessions now:
- Share the same DB as CLI and gateway sessions
- Are searchable via session_search (FTS5)
- Get token tracking, cost tracking, and session titles for free
- Follow existing session pruning policies
Key changes:
- _get_db() lazily creates a SessionDB, resolving HERMES_HOME
dynamically (not at import time) for test compatibility
- _persist() creates session record + replaces messages in DB
- _restore() loads from DB with source='acp' filter
- cwd stored in model_config JSON field (no schema migration)
- Model values coerced to str to handle mock agents in tests
- Removed: json files, sessions_dir, ttl_days, _expire logic
- Tests updated: DB-backed persistence, FTS search, tool_call
round-tripping, source filtering
---------
Co-authored-by: Test <test@test.com>
Authored by Lovre Pešut (rovle). Migrates from deprecated find_one(labels=...)
to get(sandbox_name) with deterministic naming (hermes-{task_id}), plus legacy
fallback via list(labels=...) for pre-migration sandboxes.
When a cron job references a skill that is no longer installed,
_build_job_prompt() now logs a warning and injects a user-visible notice
into the prompt instead of raising RuntimeError. The job continues with
any remaining valid skills and the user prompt.
Adds 4 regression tests for missing skill handling.
find_one is being deprecated. Primary lookup now uses get() with a
deterministic sandbox name (hermes-{task_id}). A legacy fallback via
list(labels=...) ensures sandboxes created before this migration are
still resumable.
Authored by dusterbloom. Closes#1911.
Pre-computes SQL query strings at class definition time in insights.py,
adds identifier quoting for ALTER TABLE DDL in hermes_state.py, and adds
4 regression tests verifying query construction safety.
The merge at e7844e9c re-introduced a line in _build_child_agent() that
references _saved_tool_names — a variable only defined in _run_single_child().
This caused NameError on every delegate_task call, completely breaking
subagent delegation.
Moves the child._delegate_saved_tool_names assignment to _run_single_child()
where _saved_tool_names is actually defined, keeping the save/restore in the
same scope as the try/finally block.
Adds two regression tests from PR #2038 (YanSte).
Also fixes the same issue reported in PR #2048 (Gutslabs).
Co-authored-by: Yannick Stephan <yannick.stephan@gmail.com>
Co-authored-by: Guts <gutslabs@users.noreply.github.com>
Closes#1911
- insights.py: Pre-compute SELECT queries as class constants instead of
f-string interpolation at runtime. _SESSION_COLS is now evaluated once
at class definition time.
- hermes_state.py: Add identifier quoting and whitelist validation for
ALTER TABLE column names in schema migrations.
- Add 4 tests verifying no injection vectors in SQL query construction.
* fix: detect context length for custom model endpoints via fuzzy matching + config override
Custom model endpoints (non-OpenRouter, non-known-provider) were silently
falling back to 2M tokens when the model name didn't exactly match what the
endpoint's /v1/models reported. This happened because:
1. Endpoint metadata lookup used exact match only — model name mismatches
(e.g. 'qwen3.5:9b' vs 'Qwen3.5-9B-Q4_K_M.gguf') caused a miss
2. Single-model servers (common for local inference) required exact name
match even though only one model was loaded
3. No user escape hatch to manually set context length
Changes:
- Add fuzzy matching for endpoint model metadata: single-model servers
use the only available model regardless of name; multi-model servers
try substring matching in both directions
- Add model.context_length config override (highest priority) so users
can explicitly set their model's context length in config.yaml
- Log an informative message when falling back to 2M probe, telling
users about the config override option
- Thread config_context_length through ContextCompressor and AIAgent init
Tests: 6 new tests covering fuzzy match, single-model fallback, config
override (including zero/None edge cases).
* fix: auto-detect local model name and context length for local servers
Cherry-picked from PR #2043 by sudoingX.
- Auto-detect model name from local server's /v1/models when only one
model is loaded (no manual model name config needed)
- Add n_ctx_train and n_ctx to context length detection keys for llama.cpp
- Query llama.cpp /props endpoint for actual allocated context (not just
training context from GGUF metadata)
- Strip .gguf suffix from display in banner and status bar
- _auto_detect_local_model() in runtime_provider.py for CLI init
Co-authored-by: sudo <sudoingx@users.noreply.github.com>
* fix: revert accidental summary_target_tokens change + add docs for context_length config
- Revert summary_target_tokens from 2500 back to 500 (accidental change
during patching)
- Add 'Context Length Detection' section to Custom & Self-Hosted docs
explaining model.context_length config override
---------
Co-authored-by: Test <test@test.com>
Co-authored-by: sudo <sudoingx@users.noreply.github.com>
The gateway approval system previously intercepted bare 'yes'/'no' text
from the user's next message to approve/deny dangerous commands. This was
fragile and dangerous — if the agent asked a clarify question and the user
said 'yes' to answer it, the gateway would execute the pending dangerous
command instead. (Fixes#1888)
Changes:
- Remove bare text matching ('yes', 'y', 'approve', 'ok', etc.) from
_handle_message approval check
- Add /approve and /deny as gateway-only slash commands in the command
registry
- /approve supports scoping: /approve (one-time), /approve session,
/approve always (permanent)
- Add 5-minute timeout for stale approvals
- Gateway appends structured instructions to the agent response when a
dangerous command is pending, telling the user exactly how to respond
- 9 tests covering approve, deny, timeout, scoping, and verification
that bare 'yes' no longer triggers execution
Credit to @solo386 and @FlyByNight69420 for identifying and reporting
this security issue in PR #1971 and issue #1888.
Co-authored-by: Test <test@test.com>
Three bugs prevented providers like MiniMax from using their
Anthropic-compatible endpoints (e.g. api.minimax.io/anthropic):
1. _VALID_API_MODES was missing 'anthropic_messages', so explicit
api_mode config was silently rejected and defaulted to
chat_completions.
2. API-key provider resolution hardcoded api_mode to 'chat_completions'
without checking model config or detecting Anthropic-compatible URLs.
3. run_agent.py auto-detection only recognized api.anthropic.com, not
third-party endpoints using the /anthropic URL convention.
Fixes:
- Add 'anthropic_messages' to _VALID_API_MODES
- API-key providers now check model config api_mode and auto-detect
URLs ending in /anthropic
- run_agent.py and fallback logic detect /anthropic URL convention
- 5 new tests covering all scenarios
Users can now either:
- Set MINIMAX_BASE_URL=https://api.minimax.io/anthropic (auto-detected)
- Set api_mode: anthropic_messages in model config (explicit)
- Use custom_providers with api_mode: anthropic_messages
Co-authored-by: Test <test@test.com>
When provider: custom is set in config.yaml with base_url and api_key,
those values are now used instead of falling back to OPENAI_BASE_URL and
OPENAI_API_KEY env vars. Also reads the 'api' field as an alternative to
'api_key' for config compatibility.
Cherry-picked from PR #1762 by crazywriter1.
Co-authored-by: crazywriter1 <53251494+crazywriter1@users.noreply.github.com>
_align_boundary_backward only checked messages[idx-1] to decide if
the compress-end boundary splits a tool_call/result group. When an
assistant issues 3+ parallel tool calls, their results span multiple
consecutive messages. If the boundary fell in the middle of that group,
the parent assistant was summarized away and orphaned tool results were
silently deleted by _sanitize_tool_pairs.
Now walks backward through all consecutive tool results to find the
parent assistant, then pulls the boundary before the entire group.
6 regression tests added in tests/test_compression_boundary.py.
Co-authored-by: Guts <Gutslabs@users.noreply.github.com>
Add unauthorized_dm_behavior config (pair|ignore) with global default
and per-platform override. WhatsApp can silently drop unknown DMs
instead of sending pairing codes.
Adapted config bridging to work with gw_data dict (pre-construction)
rather than config object. Dropped implementation plan document.
Co-authored-by: Frederico Ribeiro <fr@tecompanytea.com>
The previous copilot_model_api_mode() checked the catalog's
supported_endpoints first and picked /chat/completions when a model
supported both endpoints. This is wrong — GPT-5+ models should use
the Responses API even when the catalog lists both.
Replicate opencode's shouldUseCopilotResponsesApi() logic:
- GPT-5+ models (gpt-5.4, gpt-5.3-codex, etc.) → Responses API
- gpt-5-mini → Chat Completions (explicit exception)
- Everything else (gpt-4o, claude, gemini, etc.) → Chat Completions
- Model ID pattern is the primary signal, catalog is secondary
The catalog fallback now only matters for non-GPT-5 models that might
exclusively support /v1/messages (e.g. Claude via Copilot).
Models are auto-detected from the live catalog at
api.githubcopilot.com/models — no hardcoded list required for
supported models, only a static fallback for when the API is
unreachable.
Builds on PR #1879's Copilot integration with critical auth improvements
modeled after opencode's implementation:
- Add hermes_cli/copilot_auth.py with:
- OAuth device code flow (copilot_device_code_login) using the same
client_id (Ov23li8tweQw6odWQebz) as opencode and Copilot CLI
- Token type validation: reject classic PATs (ghp_*) with a clear
error message explaining supported token types
- Proper env var priority: COPILOT_GITHUB_TOKEN > GH_TOKEN > GITHUB_TOKEN
(matching Copilot CLI documentation)
- copilot_request_headers() with Openai-Intent, x-initiator, and
Copilot-Vision-Request headers (matching opencode)
- Update auth.py:
- PROVIDER_REGISTRY copilot entry uses correct env var order
- _resolve_api_key_provider_secret delegates to copilot_auth for
the copilot provider with proper token validation
- Update models.py:
- copilot_default_headers() now includes Openai-Intent and x-initiator
- Update main.py:
- _model_flow_copilot offers OAuth device code login when no token
is found, with manual token entry as fallback
- Shows supported vs unsupported token types
- 22 new tests covering token validation, env var priority, header
generation, and integration with existing auth infrastructure
* Improve tool batching independence checks
* fix: address review feedback on path-aware batching
- Log malformed/non-dict tool arguments at debug level before
falling back to sequential, instead of silently swallowing
the error into an empty dict
- Guard empty paths in _paths_overlap (unreachable in practice
due to upstream filtering, but makes the invariant explicit)
- Add tests: malformed JSON args, non-dict args, _paths_overlap
unit tests including empty path edge cases
- web_crawl is not a registered tool (only web_search/web_extract
are); no addition needed to _PARALLEL_SAFE_TOOLS
---------
Co-authored-by: kshitij <82637225+kshitijk4poor@users.noreply.github.com>
- Strip '_tools' suffix from internal toolset identifiers in the banner
(e.g. 'web_tools' -> 'web', 'homeassistant_tools' -> 'homeassistant')
- Stop appending '_tools' to unavailable toolset names
- Replace 6 hardcoded hex colors (#B8860B, #FFBF00, #FFF8DC) in toolset
rows, overflow line, and MCP server rows with the skin variables
(dim, accent, text) already resolved at the top of the function
Inspired by PR #1871 by @kshitijk4poor.
Adds 4 tests.
* fix: banner skill count now respects disabled skills and platform filtering
The banner's get_available_skills() was doing a raw rglob scan of
~/.hermes/skills/ without checking:
- Whether skills are disabled (skills.disabled config)
- Whether skills match the current platform (platforms: frontmatter)
This caused the banner to show inflated skill counts (e.g. '100 skills'
when many are disabled) and list macOS-only skills on Linux.
Fix: delegate to _find_all_skills() from tools/skills_tool which already
handles both platform gating and disabled-skill filtering.
* fix: system prompt and slash commands now respect disabled skills
Two more places where disabled skills were still surfaced:
1. build_skills_system_prompt() in prompt_builder.py — disabled skills
appeared in the <available_skills> system prompt section, causing
the agent to suggest/load them despite being disabled.
2. scan_skill_commands() in skill_commands.py — disabled skills still
registered as /skill-name slash commands in CLI help and could be
invoked.
Both now load _get_disabled_skill_names() and filter accordingly.
* fix: skill_view blocks disabled skills
skill_view() checked platform compatibility but not disabled state,
so the agent could still load and read disabled skills directly.
Now returns a clear error when a disabled skill is requested, telling
the user to enable it via hermes skills or inspect the files manually.
---------
Co-authored-by: Test <test@test.com>
Recognize hermes_cli/main.py gateway command lines in gateway
process detection and PID validation so --replace reliably finds
existing gateway instances.
Adds a regression test covering script-style cmdline detection.
Closes#1830
Each configured MCP server now registers as its own toolset in TOOLSETS
(e.g. TOOLSETS['github'] = {tools: ['mcp_github_list_files', ...]}),
making raw server names resolvable in platform_toolsets overrides.
Previously MCP tools were only injected into hermes-* umbrella toolsets,
so gateway sessions using raw toolset names like ['terminal', 'github']
in platform_toolsets couldn't resolve MCP tools.
Skips server names that collide with built-in toolsets. Also handles
idempotent reloads (syncs toolsets even when no new servers connect).
Inspired by PR #1876 by @kshitijk4poor.
Adds 2 tests (standalone toolset creation + built-in collision guard).
* perf: cache base_url.lower() via property, consolidate triple load_config(), hoist set constant
run_agent.py:
- Add base_url property that auto-caches _base_url_lower on every
assignment, eliminating 12+ redundant .lower() calls per API cycle
across __init__, _build_api_kwargs, _supports_reasoning_extra_body,
and the main conversation loop
- Consolidate three separate load_config() disk reads in __init__
(memory, skills, compression) into a single call, reusing the
result dict for all three config sections
model_tools.py:
- Hoist _READ_SEARCH_TOOLS set to module level (was rebuilt inside
handle_function_call on every tool invocation)
* Use endpoint metadata for custom model context and pricing
---------
Co-authored-by: kshitij <82637225+kshitijk4poor@users.noreply.github.com>
Add _wait_for_gateway_exit() that polls get_running_pid() to confirm
the old gateway process has actually exited before starting a new one.
If the process doesn't exit within 5s, sends SIGKILL to the specific
PID. Uses the saved PID from gateway.pid (not launchd labels) so it
works correctly with multiple gateway instances under separate
HERMES_HOME directories.
Applied to both launchd_restart() and the manual restart path (replaces
the blind time.sleep(2)).
Inspired by PR #1881 by @AzothZephyr (race condition diagnosis).
Adds 4 tests.
When config.yaml had a non-default model (e.g. gpt-5.3-codex) and the
provider was openai-codex, _normalize_model_for_provider() would replace
it with the latest available codex model because _model_is_default only
checked the CLI argument, not the config value.
Now _model_is_default is False when config.yaml has a model that differs
from the global fallback (anthropic/claude-opus-4.6), so the user's
explicit config choice is preserved.
Fixes#1887
Co-authored-by: Test <test@test.com>
MiniMax: Add M2.7 and M2.7-highspeed as new defaults across provider
model lists, auxiliary client, metadata, setup wizard, RL training tool,
fallback tests, and docs. Retain M2.5/M2.1 as alternatives.
OpenRouter: Add grok-4.20-beta, nemotron-3-super-120b-a12b:free,
trinity-large-preview:free, glm-5-turbo, and hunter-alpha to the
model catalog.
MiniMax changes based on PR #1882 by @octo-patch (applied manually
due to stale conflicts in refactored pricing module).
When config.yaml had a non-default model (e.g. gpt-5.3-codex) and the
provider was openai-codex, _normalize_model_for_provider() would replace
it with the latest available codex model because _model_is_default only
checked the CLI argument, not the config value.
Now _model_is_default is False when config.yaml has a model that differs
from the global fallback (anthropic/claude-opus-4.6), so the user's
explicit config choice is preserved.
Fixes#1887
* fix: include ACP sessions in default search sources
* fix: remove hardcoded source allowlist from session search
The default source_filter was a hardcoded list that silently excluded
any platform not explicitly listed. Instead of maintaining an ever-growing
allowlist, remove it entirely so all sources are searched by default.
Callers can still pass source_filter explicitly to narrow results.
Follow-up to cherry-picked PR #1817.
---------
Co-authored-by: someoneexistsontheinternet <154079416+someoneexistsontheinternet@users.noreply.github.com>
Co-authored-by: Test <test@test.com>
- Update _is_anthropic_oauth in _try_refresh_anthropic_client_credentials()
when token type changes during credential refresh
- Set _is_anthropic_oauth in _try_activate_fallback() Anthropic path
- Move _turns_since_memory and _iters_since_skill init to __init__ so
nudge counters accumulate across run_conversation() calls in CLI mode
- Remove unreachable retry_count >= max_retries block after raise
Adds 7 regression tests. Salvaged from PR #1797 by @0xbyt4.
Add first-class GitHub Copilot and Copilot ACP provider support across
model selection, runtime provider resolution, CLI sessions, delegated
subagents, cron jobs, and the Telegram gateway.
This also normalizes Copilot model catalogs and API modes, introduces a
Copilot ACP OpenAI-compatible shim, and fixes service-mode auth by
resolving Homebrew-installed gh binaries under launchd.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Agent-created skills were using the same policy as community hub
installs, blocking any skill with medium/high severity findings
(e.g. docker pull, pip install, git clone). This meant the agent
couldn't create skills that reference Docker or other common tools.
Changed agent-created policy from (allow, block, block) to
(allow, allow, block) — matching the trusted policy. Caution-level
findings (medium/high severity) are now allowed through, while
dangerous findings (critical severity like exfiltration, prompt
injection, reverse shells) remain blocked.
Added 4 tests covering the agent-created policy: safe allowed,
caution allowed, dangerous blocked, force override.
Every cron job prompt now includes guidance that the agent can respond
with [SILENT] when it has nothing new or noteworthy to report. The
scheduler checks for this marker and skips delivery, while still saving
output to disk for audit. Failed jobs always deliver regardless.
This replaces the notify parameter approach from PR #1807 with a simpler
always-on design — the model is smart enough to decide when there's
nothing worth reporting without needing a per-job flag.
* feat: OpenAI-compatible API server platform adapter
Salvaged from PR #956, updated for current main.
Adds an HTTP API server as a gateway platform adapter that exposes
hermes-agent via the OpenAI Chat Completions and Responses APIs.
Any OpenAI-compatible frontend (Open WebUI, LobeChat, LibreChat,
AnythingLLM, NextChat, ChatBox, etc.) can connect by pointing at
http://localhost:8642/v1.
Endpoints:
- POST /v1/chat/completions — stateless Chat Completions API
- POST /v1/responses — stateful Responses API with chaining
- GET /v1/responses/{id} — retrieve stored response
- DELETE /v1/responses/{id} — delete stored response
- GET /v1/models — list hermes-agent as available model
- GET /health — health check
Features:
- Real SSE streaming via stream_delta_callback (uses main's streaming)
- In-memory LRU response store for Responses API conversation chaining
- Named conversations via 'conversation' parameter
- Bearer token auth (optional, via API_SERVER_KEY)
- CORS support for browser-based frontends
- System prompt layering (frontend system messages on top of core)
- Real token usage tracking in responses
Integration points:
- Platform.API_SERVER in gateway/config.py
- _create_adapter() branch in gateway/run.py
- API_SERVER_* env vars in hermes_cli/config.py
- Env var overrides in gateway/config.py _apply_env_overrides()
Changes vs original PR #956:
- Removed streaming infrastructure (already on main via stream_consumer.py)
- Removed Telegram reply_to_mode (separate feature, not included)
- Updated _resolve_model() -> _resolve_gateway_model()
- Updated stream_callback -> stream_delta_callback
- Updated connect()/disconnect() to use _mark_connected()/_mark_disconnected()
- Adapted to current Platform enum (includes MATTERMOST, MATRIX, DINGTALK)
Tests: 72 new tests, all passing
Docs: API server guide, Open WebUI integration guide, env var reference
* feat(whatsapp): make reply prefix configurable via config.yaml
Reworked from PR #1764 (ifrederico) to use config.yaml instead of .env.
The WhatsApp bridge prepends a header to every outgoing message.
This was hardcoded to '⚕ *Hermes Agent*'. Users can now customize
or disable it via config.yaml:
whatsapp:
reply_prefix: '' # disable header
reply_prefix: '🤖 *My Bot*\n───\n' # custom prefix
How it works:
- load_gateway_config() reads whatsapp.reply_prefix from config.yaml
and stores it in PlatformConfig.extra['reply_prefix']
- WhatsAppAdapter reads it from config.extra at init
- When spawning bridge.js, the adapter passes it as
WHATSAPP_REPLY_PREFIX in the subprocess environment
- bridge.js handles undefined (default), empty (no header),
or custom values with \\n escape support
- Self-chat echo suppression uses the configured prefix
Also fixes _config_version: was 9 but ENV_VARS_BY_VERSION had a
key 10 (TAVILY_API_KEY), so existing users at v9 would never be
prompted for Tavily. Bumped to 10 to close the gap. Added a
regression test to prevent this from happening again.
Credit: ifrederico (PR #1764) for the bridge.js implementation
and the config version gap discovery.
---------
Co-authored-by: Test <test@test.com>
Save and restore the process-global _last_resolved_tool_names in
_run_single_child() so the parent's execute_code sandbox generates
correct tool imports after delegation completes.
The global was already mostly mitigated (run_agent.py passes
enabled_tools via self.valid_tool_names), but the global itself
remained corrupted — a footgun for any code that reads it directly.
Co-authored-by: shane9coy <shane9coy@users.noreply.github.com>
* fix(session): skip corrupt lines in load_transcript instead of crashing
Wrap json.loads() in load_transcript() with try/except JSONDecodeError
so that partial JSONL lines (from mid-write crashes like OOM/SIGKILL)
are skipped with a warning instead of crashing the entire transcript
load. The rest of the history loads fine.
Adds a logger.warning with the session ID and truncated corrupt line
content for debugging visibility.
Salvaged from PR #1193 by alireza78a.
Closes#1193
* fix(stt): respect explicit provider config instead of env-var fallback
Rework _get_provider() to separate explicit config from auto-detect.
When stt.provider is explicitly set in config.yaml, that choice is
authoritative — no silent cross-provider fallback based on which env
vars happen to be set. When no provider is configured, auto-detect
still tries: local > groq > openai.
This fixes the reported scenario where provider: local + a placeholder
OPENAI_API_KEY caused the system to silently select OpenAI and fail
with a 401.
Closes#1774
_sanitize_fts5_query() was stripping ALL double quotes (including
properly paired ones), breaking user-provided quoted phrases like
"exact phrase". Hyphenated terms like chat-send also silently
expanded to chat AND send, returning unexpected or zero results.
Fix:
1. Extract balanced quoted phrases into placeholders before
stripping FTS5-special characters, then restore them.
2. Wrap unquoted hyphenated terms (word-word) in double quotes so
FTS5 matches them as exact phrases instead of splitting on
the hyphen.
3. Unmatched quotes are still stripped as before.
Based on issue report by @bailob (#1770) and PR #1773 by @Jah-yee
(whose branch contained unrelated changes and couldn't be merged
directly).
Closes#1770Closes#1773
Co-authored-by: Jah-yee <Jah-yee@users.noreply.github.com>
compress() checks both the head and tail neighbors when choosing the
summary message role. When only the tail collides, the role is flipped.
When BOTH roles would create consecutive same-role messages (e.g.
head=assistant, tail=user), the summary is merged into the first tail
message instead of inserting a standalone message that breaks role
alternation and causes API 400 errors.
The previous code handled head-side collision but left the tail-side
uncovered — long conversations would crash mid-reply with no useful
error, forcing the user to /reset and lose session history.
Based on PR #1186 by @alireza78a, with improved double-collision
handling (merge into tail instead of unconditional 'user' fallback).
Co-authored-by: alireza78a <alireza78.crypto@gmail.com>
Wrap json.loads() in load_transcript() with try/except JSONDecodeError
so that partial JSONL lines (from mid-write crashes like OOM/SIGKILL)
are skipped with a warning instead of crashing the entire transcript
load. The rest of the history loads fine.
Adds a logger.warning with the session ID and truncated corrupt line
content for debugging visibility.
Salvaged from PR #1193 by alireza78a.
Closes#1193
- Add summary_base_url config option to compression block for custom
OpenAI-compatible endpoints (e.g. zai, DeepSeek, Ollama)
- Remove compression env var bridges from cli.py and gateway/run.py
(CONTEXT_COMPRESSION_* env vars no longer set from config)
- Switch run_agent.py to read compression config directly from
config.yaml instead of env vars
- Fix backwards-compat block in _resolve_task_provider_model to also
fire when auxiliary.compression.provider is 'auto' (DEFAULT_CONFIG
sets this, which was silently preventing the compression section's
summary_* keys from being read)
- Add test for summary_base_url config-to-client flow
- Update docs to show compression as config.yaml-only
Closes#1591
Based on PR #1702 by @uzaylisak
Salvage of PR #1707 by @kshitijk4poor (cherry-picked with authorship preserved).
Adds Tavily as a third web backend alongside Firecrawl and Parallel, using the Tavily REST API via httpx.
- Backend selection via hermes tools → saved as web.backend in config.yaml
- All three tools supported: search, extract, crawl
- TAVILY_API_KEY in config registry, doctor, status, setup wizard
- 15 new Tavily tests + 9 backend selection tests + 5 config tests
- Backward compatible
Closes#1707
Salvage of PR #1321 by @alireza78a (cherry-picked concept, reimplemented
against current main).
Phase 1 — Pre-call message sanitization:
_sanitize_api_messages() now runs unconditionally before every LLM call.
Previously gated on context_compressor being present, so sessions loaded
from disk or running without compression could accumulate dangling
tool_call/tool_result pairs causing API errors.
Phase 2a — Delegate task cap:
_cap_delegate_task_calls() truncates excess delegate_task calls per turn
to MAX_CONCURRENT_CHILDREN. The existing cap in delegate_tool.py only
limits the task array within a single call; this catches multiple
separate delegate_task tool_calls in one turn.
Phase 2b — Tool call deduplication:
_deduplicate_tool_calls() drops duplicate (tool_name, arguments) pairs
within a single turn when models stutter.
All three are static methods on AIAgent, independently testable.
29 tests covering happy paths and edge cases.
Adds .hermes.md / HERMES.md discovery for per-project agent configuration.
When the agent starts, it walks from cwd to the git root looking for
.hermes.md (preferred) or HERMES.md, strips any YAML frontmatter, and
injects the markdown body into the system prompt as project context.
- Nearest-first discovery (subdirectory configs shadow parent)
- Stops at git root boundary (no leaking into parent repos)
- YAML frontmatter stripped (structured config deferred to Phase 2)
- Same injection scanning and 20K truncation as other context files
- 22 comprehensive tests
Original implementation by ch3ronsa. Cherry-picked and adapted for current main.
Closes#681 (Phase 1)
After the first user→assistant exchange, Hermes now generates a short
descriptive session title via the auxiliary LLM (compression task config).
Title generation runs in a background thread so it never delays the
user-facing response.
Key behaviors:
- Fires only on the first 1-2 exchanges (checks user message count)
- Skips if a title already exists (user-set titles are never overwritten)
- Uses call_llm with compression task config (cheapest/fastest model)
- Truncates long messages to keep the title generation request small
- Cleans up LLM output: strips quotes, 'Title:' prefixes, enforces 80 char max
- Works in both CLI and gateway (Telegram/Discord/etc.)
Also updates /title (no args) to show the session ID alongside the title
in both CLI and gateway.
Implements #1426
* feat(web): add Parallel as alternative web search/extract backend
Adds Parallel (parallel.ai) as a drop-in alternative to Firecrawl for
web_search and web_extract tools using the official parallel-web SDK.
- Backend selection via WEB_SEARCH_BACKEND env var (auto/parallel/firecrawl)
- Auto mode prefers Firecrawl when both keys present; Parallel when sole backend
- web_crawl remains Firecrawl-only with clear error when unavailable
- Lazy SDK imports, interrupt support, singleton clients
- 16 new unit tests for backend selection and client config
Co-authored-by: s-jag <s-jag@users.noreply.github.com>
* fix: add PARALLEL_API_KEY to config registry and fix web_crawl policy tests
Follow-up for Parallel backend integration:
- Add PARALLEL_API_KEY to OPTIONAL_ENV_VARS (hermes doctor, env blocklist)
- Add to set_config_value api_keys list (hermes config set)
- Add to doctor keys display
- Fix 2 web_crawl policy tests that didn't set FIRECRAWL_API_KEY
(needed now that web_crawl has a Firecrawl availability guard)
* refactor: explicit backend selection via hermes tools, not auto-detect
Replace the auto-detect backend selection with explicit user choice:
- hermes tools saves WEB_SEARCH_BACKEND to .env when user picks a provider
- _get_backend() reads the explicit choice first
- Fallback only for manual/legacy config (uses whichever key is present)
- _is_provider_active() shows [active] for the selected web backend
- Updated tests, docs, and .env.example to remove 'auto' mode language
* refactor: use config.yaml for web backend, not env var
Match the TTS/browser pattern — web.backend is stored in config.yaml
(set by hermes tools), not as a WEB_SEARCH_BACKEND env var.
- _load_web_config() reads web: section from config.yaml
- _get_backend() reads web.backend from config, falls back to key detection
- _configure_provider() saves to config dict (saved to config.yaml)
- _is_provider_active() reads from config dict
- Removed WEB_SEARCH_BACKEND from .env.example, set_config_value, docs
- Updated all tests to mock _load_web_config instead of env vars
---------
Co-authored-by: s-jag <s-jag@users.noreply.github.com>
When container_persistent=false, the inner mini-swe-agent cleanup only
runs 'docker stop' in the background, leaving containers in Exited state.
Now cleanup() also runs 'docker rm -f' to fully remove the container.
Also fixes pre-existing test failures in model_metadata (gpt-4.1 1M context),
setup tests (TTS provider step), and adds MockInnerDocker.cleanup().
Original fix by crazywriter1. Cherry-picked and adapted for current main.
Fixes#1679
Salvaged from PR #1708 by @kartikkabadi. Cherry-picked with authorship preserved.
Fixes pre-existing test failures from setup TTS prompt flow changes and environment-sensitive assumptions.
Co-authored-by: Kartik <user2@RentKars-MacBook-Air.local>
* feat: interactive MCP tool configuration in hermes tools
Add the ability to selectively enable/disable individual MCP server
tools through the interactive 'hermes tools' TUI.
Changes:
- tools/mcp_tool.py: Add probe_mcp_server_tools() — lightweight function
that temporarily connects to configured MCP servers, discovers their
tools (names + descriptions), and disconnects. No registry side effects.
- hermes_cli/tools_config.py: Add 'Configure MCP tools' option to the
interactive menu. When selected:
1. Probes all enabled MCP servers for their available tools
2. Shows a per-server curses checklist with tool descriptions
3. Pre-selects tools based on existing include/exclude config
4. Writes changes back as tools.exclude entries in config.yaml
5. Reports which servers failed to connect
The existing CLI commands (hermes tools enable/disable server:tool)
continue to work unchanged. This adds the interactive TUI counterpart
so users can browse and toggle MCP tools visually.
Tests: 22 new tests covering probe function edge cases and interactive
flow (pre-selection, exclude/include modes, description truncation,
multi-server handling, error paths).
* feat(telegram): auto-detect HTML tags and use parse_mode=HTML in send_message
When _send_telegram detects HTML tags in the message body, it now sends
with parse_mode='HTML' instead of converting to MarkdownV2. This allows
cron jobs and agents to send rich HTML-formatted Telegram messages with
bold, italic, code blocks, etc. that render correctly.
Detection uses the same regex from PR #1568 by @ashaney:
re.search(r'<[a-zA-Z/][^>]*>', message)
Plain-text and markdown messages continue through the existing
MarkdownV2 pipeline. The HTML fallback path also catches HTML parse
errors and falls back to plain text, matching the existing MarkdownV2
error handling.
Inspired by: github.com/ashaney — PR #1568
Salvaged from PR #1573 by @eren-karakus0. Cherry-picked with authorship preserved.
Fixes#1143 — background process notifications resume after gateway restart.
Co-authored-by: Muhammet Eren Karakuş <erenkar950@gmail.com>
Add the ability to selectively enable/disable individual MCP server
tools through the interactive 'hermes tools' TUI.
Changes:
- tools/mcp_tool.py: Add probe_mcp_server_tools() — lightweight function
that temporarily connects to configured MCP servers, discovers their
tools (names + descriptions), and disconnects. No registry side effects.
- hermes_cli/tools_config.py: Add 'Configure MCP tools' option to the
interactive menu. When selected:
1. Probes all enabled MCP servers for their available tools
2. Shows a per-server curses checklist with tool descriptions
3. Pre-selects tools based on existing include/exclude config
4. Writes changes back as tools.exclude entries in config.yaml
5. Reports which servers failed to connect
The existing CLI commands (hermes tools enable/disable server:tool)
continue to work unchanged. This adds the interactive TUI counterpart
so users can browse and toggle MCP tools visually.
Tests: 22 new tests covering probe function edge cases and interactive
flow (pre-selection, exclude/include modes, description truncation,
multi-server handling, error paths).
- Default enabled: false (zero overhead when not configured)
- Fast path: cached disabled state skips all work immediately
- TTL cache (30s) for parsed policy — avoids re-reading config.yaml
on every URL check
- Missing shared files warn + skip instead of crashing all web tools
- Lazy yaml import — missing PyYAML doesn't break browser toolset
- Guarded browser_tool import — fail-open lambda fallback
- check_website_access never raises for default path (fail-open with
warning log); only raises with explicit config_path (test mode)
- Simplified enforcement code in web_tools/browser_tool — no more
try/except wrappers since errors are handled internally
Add DingTalk as a messaging platform using the dingtalk-stream SDK
for real-time message reception via Stream Mode (no webhook needed).
Replies are sent via session webhook using markdown format.
Features:
- Stream Mode connection (long-lived WebSocket, no public URL needed)
- Text and rich text message support
- DM and group chat support
- Message deduplication with 5-minute window
- Auto-reconnection with exponential backoff
- Session webhook caching for reply routing
Configuration:
export DINGTALK_CLIENT_ID=your-app-key
export DINGTALK_CLIENT_SECRET=your-app-secret
# or in config.yaml:
platforms:
dingtalk:
enabled: true
extra:
client_id: your-app-key
client_secret: your-app-secret
Files:
- gateway/platforms/dingtalk.py (340 lines) — adapter implementation
- gateway/config.py — add DINGTALK to Platform enum
- gateway/run.py — add DingTalk to _create_adapter
- hermes_cli/config.py — add env vars to _EXTRA_ENV_KEYS
- hermes_cli/tools_config.py — add dingtalk to PLATFORMS
- tests/gateway/test_dingtalk.py — 21 tests
Add inference.sh CLI (infsh) as a tool integration, giving agents
access to 150+ AI apps through a single CLI — image gen (FLUX, Reve,
Seedream), video (Veo, Wan, Seedance), LLMs, search (Tavily, Exa),
3D, avatar/lipsync, and more. One API key manages all services.
Tools:
- infsh: run any infsh CLI command (app list, app run, etc.)
- infsh_install: install the CLI if not present
Registered as an 'inference' toolset (opt-in, not in core tools).
Includes comprehensive skill docs with examples for all app categories.
Changes from original PR:
- NOT added to _HERMES_CORE_TOOLS (available via --toolsets inference)
- Added 12 tests covering tool registration, command execution,
error handling, timeout, JSON parsing, and install flow
Inspired by PR #1021 by @okaris.
Co-authored-by: okaris <okaris@users.noreply.github.com>
* fix: thread safety for concurrent subagent delegation
Four thread-safety fixes that prevent crashes and data races when
running multiple subagents concurrently via delegate_task:
1. Remove redirect_stdout/stderr from delegate_tool — mutating global
sys.stdout races with the spinner thread when multiple children start
concurrently, causing segfaults. Children already run with
quiet_mode=True so the redirect was redundant.
2. Split _run_single_child into _build_child_agent (main thread) +
_run_single_child (worker thread). AIAgent construction creates
httpx/SSL clients which are not thread-safe to initialize
concurrently.
3. Add threading.Lock to SessionDB — subagents share the parent's
SessionDB and call create_session/append_message from worker threads
with no synchronization.
4. Add _active_children_lock to AIAgent — interrupt() iterates
_active_children while worker threads append/remove children.
5. Add _client_cache_lock to auxiliary_client — multiple subagent
threads may resolve clients concurrently via call_llm().
Based on PR #1471 by peteromallet.
* feat: Honcho base_url override via config.yaml + quick command alias type
Two features salvaged from PR #1576:
1. Honcho base_url override: allows pointing Hermes at a remote
self-hosted Honcho deployment via config.yaml:
honcho:
base_url: "http://192.168.x.x:8000"
When set, this overrides the Honcho SDK's environment mapping
(production/local), enabling LAN/VPN Honcho deployments without
requiring the server to live on localhost. Uses config.yaml instead
of env var (HONCHO_URL) per project convention.
2. Quick command alias type: adds a new 'alias' quick command type
that rewrites to another slash command before normal dispatch:
quick_commands:
sc:
type: alias
target: /context
Supports both CLI and gateway. Arguments are forwarded to the
target command.
Based on PR #1576 by redhelix.
---------
Co-authored-by: peteromallet <peteromallet@users.noreply.github.com>
Co-authored-by: redhelix <redhelix@users.noreply.github.com>
Add display.theme_mode setting (auto/light/dark) that makes the CLI
readable on light terminal backgrounds.
- Auto-detect terminal background via COLORFGBG, OSC 11, and macOS
appearance (fallback chain in hermes_cli/colors.py)
- Add colors_light overrides to all 7 built-in skins with dark/readable
colors for light backgrounds
- SkinConfig.get_color() now returns light overrides when theme is light
- get_prompt_toolkit_style_overrides() uses light bg colors for
completion menus in light mode
- init_skin_from_config() reads display.theme_mode from config
- 7 new tests covering theme mode resolution, detection fallbacks,
and light-mode skin overrides
Salvaged from PR #1187 by @peteromallet. Core design preserved;
adapted to current main (kept all existing helpers, tool_emojis,
convenience functions that were added after the PR branched).
Co-authored-by: Peter O'Mallet <peteromallet@users.noreply.github.com>
When a user sends a long message, Telegram clients split it into
multiple updates that arrive within milliseconds of each other.
Previously each chunk was dispatched independently — the first would
start the agent, and subsequent chunks would interrupt or queue as
separate turns, causing the agent to only see part of the message.
Add text message batching to TelegramAdapter following the same pattern
as the existing photo burst batching:
- _enqueue_text_event() buffers text by session key, concatenating
chunks that arrive in rapid succession
- _flush_text_batch() dispatches the combined message after a 0.6s
quiet period (configurable via HERMES_TELEGRAM_TEXT_BATCH_DELAY_SECONDS)
- Timer resets on each new chunk, so all parts of a split arrive
before the batch is dispatched
Reported by NulledVector on Discord.
Add Kilo Gateway (kilo.ai) as an API-key provider with OpenAI-compatible
endpoint at https://api.kilo.ai/api/gateway. Supports 500+ models from
Anthropic, OpenAI, Google, xAI, Mistral, MiniMax via a single API key.
- Register kilocode in PROVIDER_REGISTRY with aliases (kilo, kilo-code,
kilo-gateway) and KILOCODE_API_KEY / KILOCODE_BASE_URL env vars
- Add to model catalog, CLI provider menu, setup wizard, doctor checks
- Add google/gemini-3-flash-preview as default aux model
- 12 new tests covering registration, aliases, credential resolution,
runtime config
- Documentation updates (env vars, config, fallback providers)
- Fix setup test index shift from provider insertion
Inspired by PR #1473 by @amanning3390.
Co-authored-by: amanning3390 <amanning3390@users.noreply.github.com>
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
_bot_participated_threads was an in-memory set — lost on every restart.
After restart, the bot forgot which threads it was active in, requiring
fresh @mentions and potentially creating duplicate threads instead of
continuing existing conversations.
Changes:
- Persist thread IDs to ~/.hermes/discord_threads.json
- Load on adapter init, save on every new thread participation
- _track_thread() replaces direct .add() calls for atomic persist
- Cap at 500 tracked threads to prevent unbounded growth
- /thread slash command also tracks participation
- 7 new tests covering persistence, restart survival, corruption
recovery, cap enforcement
* fix(security): harden terminal safety and sandbox file writes
Two security improvements:
1. Dangerous command detection: expand shell -c pattern to catch
combined flags (bash -lc, bash -ic, ksh -c) that were previously
undetected. Pattern changed from matching only 'bash -c' to
matching any shell invocation with -c anywhere in the flags.
2. File write sandboxing: add HERMES_WRITE_SAFE_ROOT env var that
constrains all write_file/patch operations to a configured directory
tree. Opt-in — when unset, behavior is unchanged. Useful for
gateway/messaging deployments that should only touch a workspace.
Based on PR #1085 by ismoilh.
* fix: correct "POSIDEON" typo to "POSEIDON" in banner ASCII art
The poseidon skin's banner_logo had the E and I letters swapped,
spelling "POSIDEON-AGENT" instead of "POSEIDON-AGENT".
---------
Co-authored-by: ismoilh <ismoilh@users.noreply.github.com>
Co-authored-by: unmodeled-tyler <unmodeled.tyler@proton.me>
* fix: prevent infinite 400 failure loop on context overflow (#1630)
When a gateway session exceeds the model's context window, Anthropic may
return a generic 400 invalid_request_error with just 'Error' as the
message. This bypassed the phrase-based context-length detection,
causing the agent to treat it as a non-retryable client error. Worse,
the failed user message was still persisted to the transcript, making
the session even larger on each attempt — creating an infinite loop.
Three-layer fix:
1. run_agent.py — Fallback heuristic: when a 400 error has a very short
generic message AND the session is large (>40% of context or >80
messages), treat it as a probable context overflow and trigger
compression instead of aborting.
2. run_agent.py + gateway/run.py — Don't persist failed messages:
when the agent returns failed=True before generating any response,
skip writing the user's message to the transcript/DB. This prevents
the session from growing on each failure.
3. gateway/run.py — Smarter error messages: detect context-overflow
failures and suggest /compact or /reset specifically, instead of a
generic 'try again' that will fail identically.
* fix(skills): detect prompt injection patterns and block cache file reads
Adds two security layers to prevent prompt injection via skills hub
cache files (#1558):
1. read_file: blocks direct reads of ~/.hermes/skills/.hub/ directory
(index-cache, catalog files). The 3.5MB clawhub_catalog_v1.json
was the original injection vector — untrusted skill descriptions
in the catalog contained adversarial text that the model executed.
2. skill_view: warns when skills are loaded from outside the trusted
~/.hermes/skills/ directory, and detects common injection patterns
in skill content ("ignore previous instructions", "<system>", etc.).
Cherry-picked from PR #1562 by ygd58.
* fix(tools): chunk long messages in send_message_tool before dispatch (#1552)
Long messages sent via send_message tool or cron delivery silently
failed when exceeding platform limits. Gateway adapters handle this
via truncate_message(), but the standalone senders in send_message_tool
bypassed that entirely.
- Apply truncate_message() chunking in _send_to_platform() before
dispatching to individual platform senders
- Remove naive message[i:i+2000] character split in _send_discord()
in favor of centralized smart splitting
- Attach media files to last chunk only for Telegram
- Add regression tests for chunking and media placement
Cherry-picked from PR #1557 by llbn.
* fix(approval): show full command in dangerous command approval (#1553)
Previously the command was truncated to 80 chars in CLI (with a
[v]iew full option), 500 chars in Discord embeds, and missing entirely
in Telegram/Slack approval messages. Now the full command is always
displayed everywhere:
- CLI: removed 80-char truncation and [v]iew full menu option
- Gateway (TG/Slack): approval_required message includes full command
in a code block
- Discord: embed shows full command up to 4096-char limit
- Windows: skip SIGALRM-based test timeout (Unix-only)
- Updated tests: replaced view-flow tests with direct approval tests
Cherry-picked from PR #1566 by crazywriter1.
* fix(cli): flush stdout during agent loop to prevent macOS display freeze (#1624)
The interrupt polling loop in chat() waited on the queue without
invalidating the prompt_toolkit renderer. On macOS, the StdoutProxy
buffer only flushed on input events, causing the CLI to appear frozen
during tool execution until the user typed a key.
Fix: call _invalidate() on each queue timeout (every ~100ms, throttled
to 150ms) to force the renderer to flush buffered agent output.
* fix(claw): warn when API keys are skipped during OpenClaw migration (#1580)
When --migrate-secrets is not passed (the default), API keys like
OPENROUTER_API_KEY are silently skipped with no warning. Users don't
realize their keys weren't migrated until the agent fails to connect.
Add a post-migration warning with actionable instructions: either
re-run with --migrate-secrets or add the key manually via
hermes config set.
Cherry-picked from PR #1593 by ygd58.
* fix(security): block sandbox backend creds from subprocess env (#1264)
Add Modal and Daytona sandbox credentials to the subprocess env
blocklist so they're not leaked to agent terminal sessions via
printenv/env.
Cherry-picked from PR #1571 by ygd58.
---------
Co-authored-by: buray <ygd58@users.noreply.github.com>
Co-authored-by: lbn <llbn@users.noreply.github.com>
Co-authored-by: crazywriter1 <53251494+crazywriter1@users.noreply.github.com>
* feat(skills): add bundled neutts optional skill
Add NeuTTS optional skill with CLI scaffold, bootstrap helper, and
sample voice profile. Also fixes skills_hub.py to handle binary
assets (WAV files) during skill installation.
Changes:
- optional-skills/mlops/models/neutts/ — skill + CLI scaffold
- tools/skills_hub.py — binary asset support (read_bytes, write_bytes)
- tests/tools/test_skills_hub.py — regression tests for binary assets
* feat(tts): add NeuTTS as local TTS provider backend
Add NeuTTS as a fourth TTS provider option alongside Edge, ElevenLabs,
and OpenAI. NeuTTS runs fully on-device via neutts_cli — no API key
needed.
Provider behavior:
- Explicit: set tts.provider to 'neutts' in config.yaml
- Fallback: when Edge TTS is unavailable and neutts_cli is installed,
automatically falls back to NeuTTS instead of failing
- check_tts_requirements() now includes NeuTTS in availability checks
NeuTTS outputs WAV natively. For Telegram voice bubbles, ffmpeg
converts to Opus (same pattern as Edge TTS).
Changes:
- tools/tts_tool.py — _generate_neutts(), _check_neutts_available(),
provider dispatch, fallback logic, Opus conversion
- hermes_cli/config.py — tts.neutts config defaults
---------
Co-authored-by: unmodeled-tyler <unmodeled.tyler@proton.me>
Remove HERMES_API_MODE env var. api_mode is now configured where the
endpoint is defined:
- model.api_mode in config.yaml (for the active model config)
- custom_providers[].api_mode (for named custom providers)
Replace _get_configured_api_mode() with _parse_api_mode() which just
validates a value against the whitelist without reading env vars.
Both paths (model config and named custom providers) now read api_mode
from their respective config entries rather than a global override.
Add in-session tool management via /tools disable/enable/list, plus
hermes tools list/disable/enable CLI subcommands. Supports both
built-in toolsets (web, memory) and MCP tools (github:create_issue).
To preserve prompt caching, /tools disable/enable in a chat session
saves the change to config and resets the session cleanly — the user
is asked to confirm before the reset happens.
Also improves prefix matching: /qui now dispatches to /quit instead
of showing ambiguous when longer skill commands like /quint-pipeline
are installed.
Based on PR #1520 by @YanSte.
Co-authored-by: Yannick Stephan <YanSte@users.noreply.github.com>
Add HERMES_API_MODE env var and model.api_mode config field to let
custom OpenAI-compatible endpoints opt into codex_responses mode
without requiring the OpenAI Codex OAuth provider path.
- _get_configured_api_mode() reads HERMES_API_MODE env (precedence)
then model.api_mode from config.yaml; validates against whitelist
- Applied in both _resolve_openrouter_runtime() and
_resolve_named_custom_runtime() (original PR only covered openrouter)
- Fix _dump_api_request_debug() to show /responses URL when in
codex_responses mode instead of always showing /chat/completions
- Tests for config override, env override, invalid values, named
custom providers, and debug dump URL for both API modes
Inspired by PR #1041 by @mxyhi.
Co-authored-by: mxyhi <mxyhi@users.noreply.github.com>
browser_console was registered in the tool registry but missing from
all toolset definitions (TOOLSETS, _HERMES_CORE_TOOLS, _LEGACY_TOOLSET_MAP),
so the agent could never discover or use it.
Added to all 4 locations + 4 wiring tests.
Cherry-picked from PR #1084 by @0xbyt4 (authorship preserved in tests).
The primary injection vector in #1558 was search_files discovering
catalog cache files in .hub/index-cache/ via find or grep, which
don't skip hidden directories like ripgrep does by default.
Three-layer fix:
1. _search_files (find): add -not -path '*/.*' to exclude hidden
directories, matching ripgrep's default behavior.
2. _search_with_grep: add --exclude-dir='.*' to skip hidden
directories in the grep fallback path.
3. _write_index_cache: write a .ignore file to .hub/ so ripgrep
also skips it even when invoked with --hidden (belt-and-suspenders).
This makes all three search backends (rg, grep, find) consistently
exclude hidden directories, preventing the agent from discovering
and reading unvetted community content in hub cache files.
* fix: prevent infinite 400 failure loop on context overflow (#1630)
When a gateway session exceeds the model's context window, Anthropic may
return a generic 400 invalid_request_error with just 'Error' as the
message. This bypassed the phrase-based context-length detection,
causing the agent to treat it as a non-retryable client error. Worse,
the failed user message was still persisted to the transcript, making
the session even larger on each attempt — creating an infinite loop.
Three-layer fix:
1. run_agent.py — Fallback heuristic: when a 400 error has a very short
generic message AND the session is large (>40% of context or >80
messages), treat it as a probable context overflow and trigger
compression instead of aborting.
2. run_agent.py + gateway/run.py — Don't persist failed messages:
when the agent returns failed=True before generating any response,
skip writing the user's message to the transcript/DB. This prevents
the session from growing on each failure.
3. gateway/run.py — Smarter error messages: detect context-overflow
failures and suggest /compact or /reset specifically, instead of a
generic 'try again' that will fail identically.
* fix(skills): detect prompt injection patterns and block cache file reads
Adds two security layers to prevent prompt injection via skills hub
cache files (#1558):
1. read_file: blocks direct reads of ~/.hermes/skills/.hub/ directory
(index-cache, catalog files). The 3.5MB clawhub_catalog_v1.json
was the original injection vector — untrusted skill descriptions
in the catalog contained adversarial text that the model executed.
2. skill_view: warns when skills are loaded from outside the trusted
~/.hermes/skills/ directory, and detects common injection patterns
in skill content ("ignore previous instructions", "<system>", etc.).
Cherry-picked from PR #1562 by ygd58.
* fix(tools): chunk long messages in send_message_tool before dispatch (#1552)
Long messages sent via send_message tool or cron delivery silently
failed when exceeding platform limits. Gateway adapters handle this
via truncate_message(), but the standalone senders in send_message_tool
bypassed that entirely.
- Apply truncate_message() chunking in _send_to_platform() before
dispatching to individual platform senders
- Remove naive message[i:i+2000] character split in _send_discord()
in favor of centralized smart splitting
- Attach media files to last chunk only for Telegram
- Add regression tests for chunking and media placement
Cherry-picked from PR #1557 by llbn.
* fix(approval): show full command in dangerous command approval (#1553)
Previously the command was truncated to 80 chars in CLI (with a
[v]iew full option), 500 chars in Discord embeds, and missing entirely
in Telegram/Slack approval messages. Now the full command is always
displayed everywhere:
- CLI: removed 80-char truncation and [v]iew full menu option
- Gateway (TG/Slack): approval_required message includes full command
in a code block
- Discord: embed shows full command up to 4096-char limit
- Windows: skip SIGALRM-based test timeout (Unix-only)
- Updated tests: replaced view-flow tests with direct approval tests
Cherry-picked from PR #1566 by crazywriter1.
---------
Co-authored-by: buray <ygd58@users.noreply.github.com>
Co-authored-by: lbn <llbn@users.noreply.github.com>
Co-authored-by: crazywriter1 <53251494+crazywriter1@users.noreply.github.com>
Fixes hanging when using /skills install or /skills uninstall from the
TUI — bare input() calls hang inside prompt_toolkit's event loop.
Changes:
- Add skip_confirm parameter to do_install() and do_uninstall()
- Separate --yes/-y (confirmation bypass) from --force (scan override)
in both argparse and slash command handlers
- Update usage hint for /skills uninstall to show [--yes]
The original PR (#1595) accidentally deleted the install_from_quarantine()
call, which would have broken all installs. That bug is not present here.
Based on PR #1595 by 333Alden333.
Co-authored-by: 333Alden333 <333Alden333@users.noreply.github.com>
* fix: prevent infinite 400 failure loop on context overflow (#1630)
When a gateway session exceeds the model's context window, Anthropic may
return a generic 400 invalid_request_error with just 'Error' as the
message. This bypassed the phrase-based context-length detection,
causing the agent to treat it as a non-retryable client error. Worse,
the failed user message was still persisted to the transcript, making
the session even larger on each attempt — creating an infinite loop.
Three-layer fix:
1. run_agent.py — Fallback heuristic: when a 400 error has a very short
generic message AND the session is large (>40% of context or >80
messages), treat it as a probable context overflow and trigger
compression instead of aborting.
2. run_agent.py + gateway/run.py — Don't persist failed messages:
when the agent returns failed=True before generating any response,
skip writing the user's message to the transcript/DB. This prevents
the session from growing on each failure.
3. gateway/run.py — Smarter error messages: detect context-overflow
failures and suggest /compact or /reset specifically, instead of a
generic 'try again' that will fail identically.
* fix(skills): detect prompt injection patterns and block cache file reads
Adds two security layers to prevent prompt injection via skills hub
cache files (#1558):
1. read_file: blocks direct reads of ~/.hermes/skills/.hub/ directory
(index-cache, catalog files). The 3.5MB clawhub_catalog_v1.json
was the original injection vector — untrusted skill descriptions
in the catalog contained adversarial text that the model executed.
2. skill_view: warns when skills are loaded from outside the trusted
~/.hermes/skills/ directory, and detects common injection patterns
in skill content ("ignore previous instructions", "<system>", etc.).
Cherry-picked from PR #1562 by ygd58.
* fix(tools): chunk long messages in send_message_tool before dispatch (#1552)
Long messages sent via send_message tool or cron delivery silently
failed when exceeding platform limits. Gateway adapters handle this
via truncate_message(), but the standalone senders in send_message_tool
bypassed that entirely.
- Apply truncate_message() chunking in _send_to_platform() before
dispatching to individual platform senders
- Remove naive message[i:i+2000] character split in _send_discord()
in favor of centralized smart splitting
- Attach media files to last chunk only for Telegram
- Add regression tests for chunking and media placement
Cherry-picked from PR #1557 by llbn.
---------
Co-authored-by: buray <ygd58@users.noreply.github.com>
Co-authored-by: lbn <llbn@users.noreply.github.com>
