- Test that auxiliary.compression.context_length from config is forwarded
to get_model_context_length (positive case)
- Test that invalid/non-integer config values are silently ignored
- Fix _make_agent() to set config=None (cherry-picked code reads self.config)
Users who set up Nous auth without explicitly selecting a model via
`hermes model` were silently falling back to anthropic/claude-opus-4.6
(the first entry in _PROVIDER_MODELS['nous']), causing unexpected
charges on their Nous plan. Move xiaomi/mimo-v2-pro to the first
position so unconfigured users default to a free model instead.
Four fixes for the Weixin/WeChat adapter, synthesized from the best
aspects of community PRs #8407, #8521, #8360, #7695, #8308, #8525,
#7531, #8144, #8251.
1. Streaming cursor (▉) stuck permanently — WeChat doesn't support
message editing, so the cursor appended during streaming can never
be removed. Add SUPPORTS_MESSAGE_EDITING = False to WeixinAdapter
and check it in gateway/run.py to use an empty cursor for non-edit
platforms. (Fixes#8307, #8326)
2. Media upload failures — two bugs in _send_file():
a) upload_full_url path used PUT (404 on WeChat CDN); now uses POST.
b) aes_key was base64(raw_bytes) but the iLink API expects
base64(hex_string); images showed as grey boxes. (Fixes#8352, #7529)
Also: unified both upload paths into _upload_ciphertext(), preferring
upload_full_url. Added send_video/send_voice methods and voice_item
media builder for audio/.silk files. Added video_md5 field.
3. Markdown links stripped — WeChat can't render [text](url), so
format_message() now converts them to 'text (url)' plaintext.
Code blocks are preserved. (Fixes#7617)
4. Blank message prevention — three guards:
a) _split_text_for_weixin_delivery('') returns [] not ['']
b) send() filters empty/whitespace chunks before _send_text_chunk
c) _send_message() raises ValueError for empty text as safety net
Community credit: joei4cm (#8407), lyonDan (#8521), SKFDJKLDG (#8360),
tomqiaozc (#7695), joshleeeeee (#8308), luoxiao6645(#8525),
longsizhuo (#7531), Astral-Yang (#8144), QingWei-Li (#8251).
Combines detection from both PRs into _detect_openclaw_processes():
- Cross-platform process scan (pgrep/tasklist/PowerShell) from PR #8102
- systemd service check from PR #8555
- Returns list[str] with details about what's found
Fixes in cleanup warning (from PR #8555):
- print_warning -> print_error/print_info (print_warning not in import chain)
- Added isatty() guard for non-interactive sessions
- Removed duplicate _check_openclaw_running() in favor of shared function
Updated all tests to match new API.
Add a CI-built skills index served from the docs site. The index is
crawled daily by GitHub Actions, resolves all GitHub paths upfront, and
is cached locally by the client. When the index is available:
- Search uses the cached index (0 GitHub API calls, was 23+)
- Install uses resolved paths from index (6 API calls for file
downloads only, was 31-45 for discovery + downloads)
Total: 68 → 6 GitHub API calls for a typical search + install flow.
Unauthenticated users (60 req/hr) can now search and install without
hitting rate limits.
Components:
- scripts/build_skills_index.py: Crawl all sources (skills.sh, GitHub
taps, official, clawhub, lobehub), batch-resolve GitHub paths via
tree API, output JSON index
- tools/skills_hub.py: HermesIndexSource class — search/fetch/inspect
backed by the index, with lazy GitHubSource for file downloads
- parallel_search_sources() skips external API sources when index is
available (0 GitHub calls for search)
- .github/workflows/skills-index.yml: twice-daily CI build + deploy
- .github/workflows/deploy-site.yml: also builds index during docs deploy
Graceful degradation: when the index is unavailable (first run, network
down, stale), all methods return empty/None and downstream sources
handle the request via direct API as before.
Skills.sh installs hit the GitHub API 45 times per install because the
same repo tree was fetched 6 times redundantly. Combined with search
(23 API calls), this totals 68 — exceeding the unauthenticated rate
limit of 60 req/hr, causing 'Could not fetch' errors for users without
a GITHUB_TOKEN.
Changes:
- Add _get_repo_tree() cache to GitHubSource — repo info + recursive
tree fetched once per repo per source instance, eliminating 10
redundant API calls (6 tree + 4 candidate 404s)
- _download_directory_via_tree returns {} (not None) when cached tree
shows path doesn't exist, skipping unnecessary Contents API fallback
- _check_rate_limit_response() detects exhausted quota and sets
is_rate_limited flag
- do_install() shows actionable hint when rate limited: set
GITHUB_TOKEN or install gh CLI
Before: 45 API calls per install (68 total with search)
After: 31 API calls per install (54 total with search — under 60/hr)
Reported by community user from Vietnam (no GitHub auth configured).
Three fixes for the (empty) response bug affecting open reasoning models:
1. Allow retries after prefill exhaustion — models like mimo-v2-pro always
populate reasoning fields via OpenRouter, so the old 'not _has_structured'
guard on the retry path blocked retries for EVERY reasoning model after
the 2 prefill attempts. Now: 2 prefills + 3 retries = 6 total attempts
before (empty).
2. Reset prefill/retry counters on tool-call recovery — the counters
accumulated across the entire conversation, never resetting during
tool-calling turns. A model cycling empty→prefill→tools→empty burned
both prefill attempts and the third empty got zero recovery. Now
counters reset when prefill succeeds with tool calls.
3. Strip think blocks before _truly_empty check — inline <think> content
made the string non-empty, skipping both retry paths.
Reported by users on Telegram with xiaomi/mimo-v2-pro and qwen3.5 models.
Reproduced: qwen3.5-9b emits tool calls as XML in reasoning field instead
of proper function calls, causing content=None + tool_calls=None + reasoning
with embedded <tool_call> XML. Prefill recovery works but counter
accumulation caused permanent (empty) in long sessions.
Add agent.gateway_notify_interval config option (default 600s).
Set to 0 to disable periodic 'still working' notifications.
Bridged to HERMES_AGENT_NOTIFY_INTERVAL env var (same pattern as
gateway_timeout and gateway_timeout_warning).
The inactivity warning (gateway_timeout_warning) was already
configurable; this makes the wall-clock ping configurable too.
- Remove duplicate _setup_feishu() definition (old 3-line version left
behind by cherry-pick — Python picked the new one but dead code
remained)
- Remove misleading 'Disable direct messages' DM option — the Feishu
adapter has no DM policy mechanism, so 'disable' produced identical
env vars to 'pairing'. Users who chose 'disable' would still see
pairing prompts. Reduced to 3 options: pairing, allow-all, allowlist.
- Fix test_probe_returns_bot_info_on_success and
test_probe_returns_none_on_failure: patch FEISHU_AVAILABLE=True so
probe_bot() takes the SDK path when lark_oapi is not installed
Previously, all invalid API responses (choices=None) were diagnosed
as 'fast response often indicates rate limiting' regardless of actual
response time or error code. A 738s Cloudflare 524 timeout was labeled
as 'fast response' and 'possible rate limit'.
Now extracts the error code from response.error and classifies:
- 524: upstream provider timed out (Cloudflare)
- 504: upstream gateway timeout
- 429: rate limited by upstream provider
- 500/502: upstream server error
- 503/529: upstream provider overloaded
- Other codes: shown with code number
- No code + <10s: likely rate limited (timing heuristic)
- No code + >60s: likely upstream timeout
- No code + 10-60s: neutral response time
All downstream messages (retry status, final error, interrupt message)
now use the classified hint instead of generic rate-limit language.
Reported by community member Lumen Radley (MiMo provider timeouts).
auxiliary_client.py had its own regex mirroring _strip_think_blocks
but was missing the <thought> variant. Also adds test coverage for
<thought> paired and orphaned tags.
When a user closes a terminal tab, SIGHUP exits the main thread but
the non-daemon agent_thread kept the entire Python process alive —
stuck in the API call loop with no interrupt signal. Over many
conversations, these orphan processes accumulate and cause massive
swap usage (reported: 77GB on a 32GB M1 Pro).
Changes:
- Make agent_thread daemon=True so the process exits when the main
thread finishes its cleanup. Under normal operation this changes
nothing — the main thread already waits on agent_thread.is_alive().
- Interrupt the agent in the finally/exit path so the daemon thread
stops making API calls promptly rather than being killed mid-flight.
On macOS with uv-managed Python, stdin (fd 0) can be invalid or
unregisterable with the asyncio selector, causing:
KeyError: '0 is not registered'
during prompt_toolkit's app.run() → asyncio.run() → _add_reader(0).
Three-layer fix:
1. Pre-flight fstat(0) check before app.run() — detects broken stdin
early and prints actionable guidance instead of a raw traceback.
2. Catch KeyError/OSError around app.run() as fallback for edge cases
that slip past the fstat guard.
3. Extend asyncio exception handler to suppress selector registration
KeyErrors in async callbacks.
Fixes#6393
Fresh profiles (created without --clone) now:
- Auto-seed a default SOUL.md immediately, so users have a file to
customize right away instead of discovering it only after first use
- Print a clear warning that the profile has no API keys and will
inherit from the shell environment unless configured separately
- Show the SOUL.md path for personality customization
Previously, fresh profiles started with no SOUL.md (only seeded on
first use via ensure_hermes_home), no mention of credential isolation,
and no guidance about customizing personality. Users reported confusion
about profiles using the wrong model/plan tokens and SOUL.md not
being read — both traced to operational gaps in the creation UX.
Closes#8093 (investigated: code correctly loads SOUL.md from profile
HERMES_HOME; issue was operational, not a code bug).
The _watch_update_progress() poll loop never deleted .update_prompt.json
after forwarding the prompt to the user, causing the same prompt to be
re-sent every poll cycle (2s). Two fixes:
1. Delete .update_prompt.json after forwarding — the update process only
polls for .update_response, it doesn't need the prompt file to persist.
2. Guard re-sends with _update_prompt_pending check — belt-and-suspenders
to prevent duplicates even under race conditions.
Add regression test asserting the prompt is sent exactly once.
When a user configures a provider (e.g. `hermes auth add openai-codex`)
but never selects a model via `hermes model`, the gateway and CLI would
pass an empty model string to the API, causing:
'Codex Responses request model must be a non-empty string'
Now both gateway (_resolve_session_agent_runtime) and CLI
(_ensure_runtime_credentials) detect an empty model and fill it from
the provider's first catalog entry in _PROVIDER_MODELS. This covers
all providers that have a static model list (openai-codex, anthropic,
gemini, copilot, etc.).
The fix is conservative: it only triggers when model is truly empty
and a known provider was resolved. Explicit model choices are never
overridden.
The previous wording ('If one clearly matches') set too high a threshold,
and 'If none match, proceed normally' was an easy escape hatch for lazy
models. Now:
- Lowered threshold: 'matches or is even partially relevant'
- Added MUST directive and 'err on the side of loading' guidance
- Replaced permissive closer with 'only proceed without if genuinely none
are relevant'
This should reduce cases where the agent skips loading relevant skills
unless explicitly forced.
When the gateway shuts down gracefully (hermes update, gateway restart,
/restart), it now writes a .clean_shutdown marker file. On the next
startup, if this marker exists, suspend_recently_active() is skipped
and the marker is cleaned up.
Previously, suspend_recently_active() fired on EVERY startup —
including planned restarts from hermes update or hermes gateway restart.
This caused users to lose their conversation history unexpectedly: the
session would be marked as suspended, and the next message would
trigger an auto-reset with a notification the user never asked for.
The original purpose of suspend_recently_active() is crash recovery —
preventing stuck sessions that were mid-processing when the gateway
died unexpectedly. Graceful shutdowns already drain active agents via
_drain_active_agents(), so there is no stuck-session risk. After a
crash (no marker written), suspension still fires as before.
Fixes the scenario where a user asks the agent to run hermes update,
the gateway restarts, and the user's next message gets an unwanted
'Session automatically reset' notification with their history cleared.
When /update runs via Telegram, hermes update --gateway is spawned inside
the gateway's systemd cgroup. The update process itself calls
systemctl restart hermes-gateway, which tears down the cgroup with
KillMode=mixed — SIGKILL to all remaining processes. The wrapping bash
shell is killed before it can execute the exit-code epilogue, so
.update_exit_code is never created. The new gateway's update watcher
then polls for 30 minutes and sends a spurious timeout message.
Fix: write .update_exit_code from Python inside cmd_update() immediately
after the git pull + pip install succeed ("Update complete!"), before
attempting the gateway restart. The shell epilogue still writes it too
(idempotent overwrite), but now the marker exists even when the process
is killed mid-restart.
When running inside WSL (Windows Subsystem for Linux), inject a hint into
the system prompt explaining that the Windows host filesystem is mounted
at /mnt/c/, /mnt/d/, etc. This lets the agent naturally translate Windows
paths (Desktop, Documents) to their /mnt/ equivalents without the user
needing to configure anything.
Uses the existing is_wsl() detection from hermes_constants (cached,
checks /proc/version for 'microsoft'). Adds build_environment_hints()
in prompt_builder.py — extensible for Termux, Docker, etc. later.
Closes the UX gap where WSL users had to manually explain path
translation to the agent every session.
Follow-up for cherry-picked PR #8272:
- Add MATRIX_RECOVERY_KEY to module docstring header in matrix.py
- Register in OPTIONAL_ENV_VARS (config.py) with password=True, advanced=True
- Add to _NON_SETUP_ENV_VARS set
- Document cross-signing verification in matrix.md E2EE section
- Update migration guide with recovery key step (step 3)
- Add to environment-variables.md reference
OpenAI OAuth refresh tokens are single-use and rotate on every refresh.
When Hermes refreshes a Codex token, it consumed the old refresh_token
but never wrote the new pair back to ~/.codex/auth.json. This caused
Codex CLI and VS Code to fail with 'refresh_token_reused' on their
next refresh attempt.
This mirrors the existing Anthropic write-back pattern where refreshed
tokens are written to ~/.claude/.credentials.json via
_write_claude_code_credentials().
Changes:
- Add _write_codex_cli_tokens() in hermes_cli/auth.py (parallel to
_write_claude_code_credentials in anthropic_adapter.py)
- Call it from _refresh_codex_auth_tokens() (non-pool refresh path)
- Call it from credential_pool._refresh_entry() (pool happy path + retry)
- Add tests for the new write-back behavior
- Update existing test docstring to clarify _save_codex_tokens vs
_write_codex_cli_tokens separation
Fixes refresh token conflict reported by @ec12edfae2cb221
After /model switches the model (both picker and text paths), the cached
agent's config signature becomes stale — the agent was updated in-place
via switch_model() but the cache tuple's signature was never refreshed.
The next turn *should* detect the signature mismatch and create a fresh
agent, but this relies on the new model's signature differing from the
old one in _agent_config_signature().
Evicting the cached agent explicitly after storing the session override
is more defensive — the next turn is guaranteed to create a fresh agent
from the override without depending on signature mismatch detection.
Also adds debug logging at three key decision points so we can trace
exactly what happens when /model + /retry interact:
- _resolve_session_agent_runtime: which override path is taken (fast
with api_key vs fallback), or why no override was found
- _run_agent.run_sync: final resolved model/provider before agent
creation
Reported: /model switch to xiaomi/mimo-v2-pro followed by /retry still
used the old model (glm-5.1).
The monitor_for_interrupt() and backup interrupt checks were calling
get_pending_message() which pops the message from the adapter's queue.
This created a race condition: if the agent finished naturally before
checking _interrupt_requested, the pending message was permanently lost.
Timeline of the race:
1. Agent near completion, user sends message
2. Level 1 guard stores message in adapter._pending_messages, sets event
3. monitor_for_interrupt() detects event, POPS message, calls agent.interrupt()
4. Agent's run_conversation() was already returning (interrupted=False)
5. Post-run dequeue finds nothing (monitor already consumed it)
6. result.get('interrupted') is False so interrupt_message fallback doesn't fire
7. User message permanently lost — agent finishes without processing it
Fix: change all three interrupt detection sites (primary monitor + two
backup checks) from get_pending_message() (pop) to
_pending_messages.get() (peek). The message stays in the adapter's queue
until _dequeue_pending_event() consumes it in the post-run handler,
which runs regardless of whether the agent was interrupted or finished
naturally.
Reported by @_SushantSays — intermittent message loss during long
terminal command execution, persisting after the previous fix (73f970fa)
which addressed monitor task death but not this consumption race.
Reject non-URL values (e.g. shell commands typed by mistake) in the
base URL prompt during provider setup. Previously any string was saved
as-is to .env, breaking connectivity when the garbage value was used
as the API endpoint.
Adds http:// / https:// prefix check with a clear error message.
The custom-endpoint flow already had this validation (line 1620);
this brings the generic API-key provider flow to parity.
Triggered by a user support case where 'nano ~/.hermes/.env' was
accidentally entered as GLM_BASE_URL during Z.AI setup.
The previous wording ('If one clearly matches') set too high a threshold,
and 'If none match, proceed normally' was an easy escape hatch for lazy
models. Now:
- Lowered threshold: 'matches or is even partially relevant'
- Added MUST directive and 'err on the side of loading' guidance
- Replaced permissive closer with 'only proceed without if genuinely none
are relevant'
This should reduce cases where the agent skips loading relevant skills
unless explicitly forced.
- Add openai/openai-codex -> openai mapping to PROVIDER_TO_MODELS_DEV
so context-length lookups use models.dev data instead of 128k fallback.
Fixes#8161.
- Set api_mode from custom_providers entry when switching via hermes model,
and clear stale api_mode when the entry has none. Also extract api_mode
in _named_custom_provider_map(). Fixes#8181.
- Convert OpenAI image_url content blocks to Anthropic image blocks when
the endpoint is Anthropic-compatible (MiniMax, MiniMax-CN, or any URL
containing /anthropic). Fixes#8147.
* fix: list all available toolsets in delegate_task schema description
The delegate_task tool's toolsets parameter description only mentioned
'terminal', 'file', and 'web' as examples. Models (especially smaller
ones like Gemma) would substitute 'web' for 'browser' because they
didn't know 'browser' was a valid option.
Now dynamically builds the toolset list from the TOOLSETS dict at import
time, excluding blocked, composite, and platform-specific toolsets.
Auto-updates when new toolsets are added.
Reported by jeffutter on Discord.
* chore: exclude moa and rl from delegate_task toolset list
When the agent calls process(action='wait') or process(action='poll')
and gets the exited status, the completion_queue notification is
redundant — the agent already has the output from the tool return.
Previously, the drain loops in CLI and gateway would still inject
the [SYSTEM: Background process completed] message, causing the
agent to receive the same information twice.
Fix: track session IDs in _completion_consumed set when wait/poll/log
returns an exited process. Drain loops in cli.py and gateway watcher
skip completion events for consumed sessions. Watch pattern events
are never suppressed (they have independent semantics).
Adds 4 tests covering wait/poll/log marking and running-process
negative case.
Add a 'tip of the day' feature that displays a random one-liner about
Hermes Agent features on every new session — CLI startup, /clear, /new,
and gateway /new across all messaging platforms.
- New hermes_cli/tips.py module with 210 curated tips covering slash
commands, keybindings, CLI flags, config options, tools, gateway
platforms, profiles, sessions, memory, skills, cron, voice, security,
and more
- CLI: tips display in skin-aware dim gold color after the welcome line
- Gateway: tips append to the /new and /reset response on all platforms
- Fully wrapped in try/except — tips are non-critical and never break
startup or reset
Display format (CLI):
✦ Tip: /btw <question> asks a quick side question without tools or history.
Display format (gateway):
✨ Session reset! Starting fresh.
✦ Tip: hermes -c resumes your most recent CLI session.
- Add rebrand_text() that replaces OpenClaw, Open Claw, Open-Claw,
ClawdBot, and MoltBot with Hermes (case-insensitive, word-boundary)
- Apply rebranding to memory entries (MEMORY.md, USER.md, daily memory)
- Apply rebranding to SOUL.md and workspace instructions via new
transform parameter on copy_file()
- Fix moldbot -> moltbot typo across codebase (claw.py, migration
script, docs, tests)
- Add unit tests for rebrand_text and integration tests for memory
and soul migration rebranding
Users whose credentials exist only in external files — OpenAI Codex
OAuth tokens in ~/.codex/auth.json or Anthropic Claude Code credentials
in ~/.claude/.credentials.json — would not see those providers in the
/model picker, even though hermes auth and hermes model detected them.
Root cause: list_authenticated_providers() only checked the raw Hermes
auth store and env vars. External credential file fallbacks (Codex CLI
import, Claude Code file discovery) were never triggered.
Fix (three parts):
1. _seed_from_singletons() in credential_pool.py: openai-codex now
imports from ~/.codex/auth.json when the Hermes auth store is empty,
mirroring resolve_codex_runtime_credentials().
2. list_authenticated_providers() in model_switch.py: auth store + pool
checks now run for ALL providers (not just OAuth auth_type), catching
providers like anthropic that support both API key and OAuth.
3. list_authenticated_providers(): direct check for anthropic external
credential files (Claude Code, Hermes PKCE). The credential pool
intentionally gates anthropic behind is_provider_explicitly_configured()
to prevent auxiliary tasks from silently consuming tokens. The /model
picker bypasses this gate since it is discovery-oriented.
The interrupt mechanism for regular text messages (non-commands) during
active agent runs relied on a single async polling task
(monitor_for_interrupt) with no error handling. If this task died
silently due to an unhandled exception, stale adapter reference after
reconnect, or any other failure, user messages sent during agent
execution would be queued but never trigger an actual interrupt — the
agent would continue running until it finished naturally, then process
the queued message.
Three improvements:
1. Error handling in monitor_for_interrupt(): wrap the polling body in
try/except so transient errors are logged and retried instead of
silently killing the task.
2. Fresh adapter reference on each poll iteration: re-resolve
self.adapters.get(source.platform) every 200ms instead of capturing
the adapter once at task creation time. This prevents stale
references after adapter reconnects.
3. Backup interrupt check in the inactivity poll loop: both the
unlimited and timeout-enabled paths now check for pending interrupts
every 5 seconds (the existing poll interval). Uses a shared
_interrupt_detected asyncio.Event to avoid double-firing when the
primary monitor already handled the interrupt. Logs at INFO level
with monitor task state for debugging.
The TUI transition (4970705, f83e86d) replaced stacked per-tool history
lines with a single live-updating spinner widget. While the spinner
provides a nice live timer, it removed the scrollback history that
users relied on to see what the agent did during a session.
This restores stacked tool progress lines in 'all' and 'new' modes by
printing persistent scrollback lines via _cprint() when tools complete,
in addition to the existing live spinner display.
Behavior per mode:
- off: no scrollback lines, no spinner (unchanged)
- new: scrollback line on completion, skipping consecutive same-tool repeats
- all: scrollback line on every tool completion
- verbose: no scrollback (run_agent.py handles verbose output directly)
Implementation:
- Store function_args from tool.started events in _pending_tool_info
- On tool.completed, pop stored args and format via get_cute_tool_message()
- FIFO queue per function_name handles concurrent tool execution
- 'new' mode tracks _last_scrollback_tool for dedup
- State cleared at end of agent run
Reported by community user Mr.D — the stacked history provides
transparency into what the agent is doing, which builds trust.
Addresses user report from Discord about lost tool call visibility.
Rewrite the cronjob tool's 'deliver' parameter description to strongly
guide models toward omitting the parameter (which auto-detects origin
including thread/topic). The previous description listed all platform
names equally, inviting models to construct explicit targets like
'telegram:<chat_id>' which silently drops the thread_id.
New description:
- Leads with 'Omit this parameter' as the recommended path
- Explicitly warns that platform:chat_id without :thread_id loses topics
- Removes the long flat list of platform names that invited construction
Also adds diagnostic logging at two key points:
- _origin_from_env(): logs when thread_id is captured during job creation
- _deliver_result(): warns when origin has thread_id but delivery target
lost it; logs at debug when delivering to a specific thread
Helps diagnose user-reported issue where cron responses from Telegram
topics are delivered to the main chat instead of the originating topic.
On servers with broken or unreachable IPv6, Python's socket.getaddrinfo
returns AAAA records first. urllib/httpx/requests all try IPv6 connections
first and hang for the full TCP timeout before falling back to IPv4. This
affects web_extract, web_search, the OpenAI SDK, and all HTTP tools.
Adds network.force_ipv4 config option (default: false) that monkey-patches
socket.getaddrinfo to resolve as AF_INET when the caller didn't specify a
family. Falls back to full resolution if no A record exists, so pure-IPv6
hosts still work.
Applied early at all three entry points (CLI, gateway, cron scheduler)
before any HTTP clients are created.
Reported by user @29n — Chinese Ubuntu server with unreachable IPv6 causing
timeouts on lobste.rs and other IPv6-enabled sites while Google/GitHub
worked fine (IPv4-only resolution).
After compression, models (especially Kimi 2.5) would sometimes respond
to questions from the summary instead of the latest user message. This
happened ~30% of the time on Telegram.
Root cause: the summary's 'Next Steps' section read as active instructions,
and the SUMMARY_PREFIX didn't explicitly tell the model to ignore questions
in the summary. When the summary merged into the first tail message, there
was no clear separator between historical context and the actual user message.
Changes inspired by competitor analysis (Claude Code, OpenCode, Codex):
1. SUMMARY_PREFIX rewritten with explicit 'Do NOT answer questions from
this summary — respond ONLY to the latest user message AFTER it'
2. Summarizer preamble (shared by both prompts) adds:
- 'Do NOT respond to any questions' (from OpenCode's approach)
- 'Different assistant' framing (from Codex) to create psychological
distance between summary content and active conversation
3. New summary sections:
- '## Resolved Questions' — tracks already-answered questions with
their answers, preventing re-answering (from Claude Code's
'Pending user asks' pattern)
- '## Pending User Asks' — explicitly marks unanswered questions
- '## Remaining Work' replaces '## Next Steps' — passive framing
avoids reading as active instructions
4. merge-summary-into-tail path now inserts a clear separator:
'--- END OF CONTEXT SUMMARY — respond to the message below ---'
5. Iterative update prompt now instructs: 'Move answered questions to
Resolved Questions' to maintain the resolved/pending distinction
across multiple compactions.
Adds an optional focus topic to /compress: `/compress database schema`
guides the summariser to preserve information related to the focus topic
(60-70% of summary budget) while compressing everything else more aggressively.
Inspired by Claude Code's /compact <focus>.
Changes:
- context_compressor.py: focus_topic parameter on _generate_summary() and
compress(); appends FOCUS TOPIC guidance block to the LLM prompt
- run_agent.py: focus_topic parameter on _compress_context(), passed through
to the compressor
- cli.py: _manual_compress() extracts focus topic from command string,
preserves existing manual_compression_feedback integration (no regression)
- gateway/run.py: _handle_compress_command() extracts focus from event args
and passes through — full gateway parity
- commands.py: args_hint="[focus topic]" on /compress CommandDef
Salvaged from PR #7459 (CLI /compress focus only — /context command deferred).
15 new tests across CLI, compressor, and gateway.
* feat: add `hermes backup` and `hermes import` commands
hermes backup — creates a zip of ~/.hermes/ (config, skills, sessions,
profiles, memories, skins, cron jobs, etc.) excluding the hermes-agent
codebase, __pycache__, and runtime PID files. Defaults to
~/hermes-backup-<timestamp>.zip, customizable with -o.
hermes import <zipfile> — restores from a backup zip, validating it
looks like a hermes backup before extracting. Handles .hermes/ prefix
stripping, path traversal protection, and confirmation prompts (skip
with --force).
29 tests covering exclusion rules, backup creation, import validation,
prefix detection, path traversal blocking, confirmation flow, and a
full round-trip test.
* test: improve backup/import coverage to 97%
Add 17 additional tests covering:
- _format_size helper (bytes through terabytes)
- Nonexistent hermes home error exit
- Output path is a directory (auto-names inside it)
- Output without .zip suffix (auto-appends)
- Empty hermes home (all files excluded)
- Permission errors during backup and import
- Output zip inside hermes root (skips itself)
- Not-a-zip file rejection
- EOFError and KeyboardInterrupt during confirmation
- 500+ file progress display
- Directory-only zip prefix detection
Remove dead code branch in _detect_prefix (unreachable guard).
* feat: auto-restore profile wrapper scripts on import
After extracting backup files, hermes import now scans profiles/ for
subdirectories with config.yaml or .env and recreates the ~/.local/bin
wrapper scripts so profile aliases (e.g. 'coder chat') work immediately.
Also prints guidance for re-installing gateway services per profile.
Handles edge cases:
- Skips profile dirs without config (not real profiles)
- Skips aliases that collide with existing commands
- Gracefully degrades if hermes_cli.profiles isn't available (fresh install)
- Shows PATH hint if ~/.local/bin isn't in PATH
3 new profile restoration tests (49 total).
* feat: component-separated logging with session context and filtering
Phase 1 — Gateway log isolation:
- gateway.log now only receives records from gateway.* loggers
(platform adapters, session management, slash commands, delivery)
- agent.log remains the catch-all (all components)
- errors.log remains WARNING+ catch-all
- Moved gateway.log handler creation from gateway/run.py into
hermes_logging.setup_logging(mode='gateway') with _ComponentFilter
Phase 2 — Session ID injection:
- Added set_session_context(session_id) / clear_session_context() API
using threading.local() for per-thread session tracking
- _SessionFilter enriches every log record with session_tag attribute
- Log format: '2026-04-11 10:23:45 INFO [session_id] logger.name: msg'
- Session context set at start of run_conversation() in run_agent.py
- Thread-isolated: gateway conversations on different threads don't leak
Phase 3 — Component filtering in hermes logs:
- Added --component flag: hermes logs --component gateway|agent|tools|cli|cron
- COMPONENT_PREFIXES maps component names to logger name prefixes
- Works with all existing filters (--level, --session, --since, -f)
- Logger name extraction handles both old and new log formats
Files changed:
- hermes_logging.py: _SessionFilter, _ComponentFilter, COMPONENT_PREFIXES,
set/clear_session_context(), gateway.log creation in setup_logging()
- gateway/run.py: removed redundant gateway.log handler (now in hermes_logging)
- run_agent.py: set_session_context() at start of run_conversation()
- hermes_cli/logs.py: --component filter, logger name extraction
- hermes_cli/main.py: --component argument on logs subparser
Addresses community request for component-separated, filterable logging.
Zero changes to existing logger names — __name__ already provides hierarchy.
* fix: use LogRecord factory instead of per-handler _SessionFilter
The _SessionFilter approach required attaching a filter to every handler
we create. Any handler created outside our _add_rotating_handler (like
the gateway stderr handler, or third-party handlers) would crash with
KeyError: 'session_tag' if it used our format string.
Replace with logging.setLogRecordFactory() which injects session_tag
into every LogRecord at creation time — process-global, zero per-handler
wiring needed. The factory is installed at import time (before
setup_logging) so session_tag is available from the moment hermes_logging
is imported.
- Idempotent: marker attribute prevents double-wrapping on module reload
- Chains with existing factory: won't break third-party record factories
- Removes _SessionFilter from _add_rotating_handler and setup_verbose_logging
- Adds tests: record factory injection, idempotency, arbitrary handler compat
Add display.platforms section to config.yaml for per-platform overrides of
display settings (tool_progress, show_reasoning, streaming, tool_preview_length).
Each platform gets sensible built-in defaults based on capability tier:
- High (telegram, discord): tool_progress=all, streaming follows global
- Medium (slack, mattermost, matrix, feishu): tool_progress=new
- Low (signal, whatsapp, bluebubbles, wecom, etc.): tool_progress=off, streaming=false
- Minimal (email, sms, webhook, homeassistant): tool_progress=off, streaming=false
Example config:
display:
platforms:
telegram:
tool_progress: all
show_reasoning: true
slack:
tool_progress: off
Resolution order: platform override > global setting > built-in platform default.
Changes:
- New gateway/display_config.py: resolver module with tier-based platform defaults
- gateway/run.py: tool_progress, tool_preview_length, streaming, show_reasoning
all resolve per-platform via the new resolver
- /verbose command: now cycles tool_progress per-platform (saves to
display.platforms.<platform>.tool_progress instead of global)
- /reasoning show|hide: now saves show_reasoning per-platform
- Config version 15 -> 16: migrates tool_progress_overrides into display.platforms
- Backward compat: legacy tool_progress_overrides still read as fallback
- 27 new tests for resolver, normalization, migration, backward compat
- Updated verbose command tests for per-platform behavior
Addresses community request for per-channel verbosity control (Guillaume Meyer,
Nathan Danielsen) — high verbosity on backchannel Telegram, low on customer-facing
Slack, none on email.
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).
The _get_budget_warning() method already returned None unconditionally —
the entire budget warning system was disabled. Remove all dead code:
- _BUDGET_WARNING_RE regex
- _strip_budget_warnings_from_history() function and its call site
- Both injection blocks (concurrent + sequential tool execution)
- _get_budget_warning() method
- 7 tests for the removed functions
The budget exhaustion grace call system (_budget_exhausted_injected,
_budget_grace_call) is a separate recovery mechanism and is preserved.
Switch estimate_tokens_rough(), estimate_messages_tokens_rough(), and
estimate_request_tokens_rough() from floor division (len // 4) to
ceiling division ((len + 3) // 4). Short texts (1-3 chars) previously
estimated as 0 tokens, causing the compressor and pre-flight checks to
systematically undercount when many short tool results are present.
Also replaced the inline duplicate formula in run_conversation()
(total_chars // 4) with a call to the shared
estimate_messages_tokens_rough() function.
Updated 4 tests that hardcoded floor-division expected values.
Related: issue #6217, PR #6629
- Fix auto list (was only gpt, actually includes codex/gemini/gemma/grok)
- Document the three guidance layers (general, OpenAI-specific, Google-specific)
- Add 'When to turn it on' section for users on non-default models
- Clarify that substring matching is case-insensitive
Three root causes of the 'agent stops mid-task' gateway bug:
1. Compression threshold floor (64K tokens minimum)
- The 50% threshold on a 100K-context model fired at 50K tokens,
causing premature compression that made models lose track of
multi-step plans. Now threshold_tokens = max(50% * context, 64K).
- Models with <64K context are rejected at startup with a clear error.
2. Budget warning removal — grace call instead
- Removed the 70%/90% iteration budget warnings entirely. These
injected '[BUDGET WARNING: Provide your final response NOW]' into
tool results, causing models to abandon complex tasks prematurely.
- Now: no warnings during normal execution. When the budget is
actually exhausted (90/90), inject a user message asking the model
to summarise, allow one grace API call, and only then fall back
to _handle_max_iterations.
3. Activity touches during long terminal execution
- _wait_for_process polls every 0.2s but never reported activity.
The gateway's inactivity timeout (default 1800s) would fire during
long-running commands that appeared 'idle.'
- Now: thread-local activity callback fires every 10s during the
poll loop, keeping the gateway's activity tracker alive.
- Agent wires _touch_activity into the callback before each tool call.
Also: docs update noting 64K minimum context requirement.
Closes#7915 (root cause was agent-loop termination, not Weixin delivery limits).
Replace the verbose_logging-gated logging.exception() with an
unconditional logger.debug(exc_info=True). The full traceback now
always lands in agent.log when debug logging is enabled, without
requiring the verbose_logging flag or spamming the console.
Previously, production errors in the 700-line response processing
block (normalization, tool dispatch, final response handling) were
logged as one-line messages with the traceback hidden behind
verbose_logging — making post-mortem debugging difficult.
Add the missing 'Adding a Platform Adapter' developer guide — a
comprehensive step-by-step checklist covering all 20+ integration
points (enum, adapter, config, runner, CLI, tools, toolsets, cron,
webhooks, tests, and docs). Includes common patterns for long-poll,
callback/webhook, and token-lock adapters with reference implementations.
Also adds full docs coverage for the WeCom Callback platform:
- New docs page: user-guide/messaging/wecom-callback.md
- Environment variables reference (9 WECOM_CALLBACK_* vars)
- Toolsets reference (hermes-wecom-callback)
- Messaging index (comparison table, architecture diagram, toolsets,
security, next-steps links)
- Integrations index listing
- Sidebar entries for both new pages
All retry counters (_invalid_tool_retries, _invalid_json_retries,
_empty_content_retries, _incomplete_scratchpad_retries,
_codex_incomplete_retries) are initialized to 0 at the top of
run_conversation() (lines 7566-7570). The hasattr guards added before
the reset block existed are now dead code — the attributes always exist.
Removed 7 redundant hasattr checks (5 original targets + 2 bonus for
_codex_incomplete_retries found during cleanup).
When _try_activate_fallback() switches to a new provider, retry_count was
reset to 0 but compression_attempts and primary_recovery_attempted were
not. This meant a fallback provider that hit context overflow would only
get the leftover compression budget from the failed primary provider,
and transport recovery was blocked because the flag was still True from
the old provider's attempt.
Reset both counters at all 5 fallback activation sites inside the retry
loop so each fallback provider gets a fresh compression budget (3 attempts)
and its own transport recovery opportunity.
Cron jobs run from whatever directory the scheduler process lives in
(typically the hermes-agent install dir), so without this flag the agent
picks up AGENTS.md, SOUL.md, or .cursorrules from that cwd — injecting
irrelevant project context into the cron job's system prompt.
batch_runner.py and gateway boot_md already pass skip_context_files=True
for the same reason. This aligns cron with the established pattern for
autonomous/headless agent runs.
* fix(tools): neutralize shell injection in _write_to_sandbox via path quoting
_write_to_sandbox interpolated storage_dir and remote_path directly into
a shell command passed to env.execute(). Paths containing shell
metacharacters (spaces, semicolons, $(), backticks) could trigger
arbitrary command execution inside the sandbox.
Fix: wrap both paths with shlex.quote(). Clean paths (alphanumeric +
slashes/hyphens/dots) are left unmodified by shlex.quote, so existing
behavior is unchanged. Paths with unsafe characters get single-quoted.
Tests added for spaces, $(command) substitution, and semicolon injection.
* fix: is_local_endpoint misses Docker/Podman DNS names
host.docker.internal, host.containers.internal, gateway.docker.internal,
and host.lima.internal are well-known DNS names that container runtimes
use to resolve the host machine. Users running Ollama on the host with
the agent in Docker/Podman hit the default 120s stream timeout instead
of the bumped 1800s because these hostnames weren't recognized as local.
Add _CONTAINER_LOCAL_SUFFIXES tuple and suffix check in
is_local_endpoint(). Tests cover all three runtime families plus a
negative case for domains that merely contain the suffix as a substring.
Wire Signal, Email, SMS (Twilio), DingTalk, Feishu/Lark, and WeCom into
the hermes setup gateway interactive wizard. These platforms all had
working adapters and _PLATFORMS entries in gateway.py but were invisible
in the setup checklist — users had to manually edit .env to configure them.
Changes:
- gateway.py: Add _setup_email/sms/dingtalk/feishu/wecom functions
delegating to _setup_standard_platform (Signal already had a custom one)
- setup.py: Add wrapper functions for all 6 new platforms
- setup.py: Add all 6 to _GATEWAY_PLATFORMS checklist registry
- setup.py: Add missing env vars to any_messaging check
- setup.py: Add all missing platforms to _get_section_config_summary
(was also missing Matrix, Mattermost, Weixin, Webhooks)
- docs: Add FEISHU_ALLOWED_USERS and WECOM_ALLOWED_USERS examples
Incorporates and extends the work from PR #7918 by bugmaker2.
- add all_profiles=False to find_gateway_pids() and
kill_gateway_processes() so hermes update and gateway stop --all
can still discover processes across all profiles
- narrow bare 'except Exception' to (OSError, subprocess.TimeoutExpired)
- update test mocks to match new signatures
Adds two tests verifying that duplicate reasoning item IDs across
multi-turn Codex Responses conversations are correctly deduplicated
in both _chat_messages_to_responses_input() and
_preflight_codex_input_items().
_write_to_sandbox interpolated storage_dir and remote_path directly into
a shell command passed to env.execute(). Paths containing shell
metacharacters (spaces, semicolons, $(), backticks) could trigger
arbitrary command execution inside the sandbox.
Fix: wrap both paths with shlex.quote(). Clean paths (alphanumeric +
slashes/hyphens/dots) are left unmodified by shlex.quote, so existing
behavior is unchanged. Paths with unsafe characters get single-quoted.
Tests added for spaces, $(command) substitution, and semicolon injection.
The cherry-picked fix from PR #7916 placed model propagation after
the credential pool early-return in _resolve_named_custom_runtime(),
making it dead code when a pool is active (which happens whenever
custom_providers has an api_key that auto-seeds the pool).
- Inject model into pool_result before returning
- Add 5 regression tests covering direct path, pool path, empty
model, and absent model scenarios
- Add 'model' to _VALID_CUSTOM_PROVIDER_FIELDS for config validation
The startup guard tests called connect() which bound a real aiohttp
server on port 8080 — flaky in any environment where the port is
in use. Mock AppRunner, TCPSite, and ClientSession instead.
WhatsApp changed their server protocol for property queries, causing
400 bad-request errors in fetchProps/executeInitQueries on every
reconnect (Baileys issue #2477). The fix in PR #2473 changes the IQ
namespace from 'w' to 'abt' and protocol from '2' to '1'.
Pin to the fix branch until the next Baileys release includes it.
The interrupt mechanism in tools/interrupt.py used a process-global
threading.Event. In the gateway, multiple agents run concurrently in
the same process via run_in_executor. When any agent was interrupted
(user sends a follow-up message), the global flag killed ALL agents'
running tools — terminal commands, browser ops, web requests — across
all sessions.
Changes:
- tools/interrupt.py: Replace single threading.Event with a set of
interrupted thread IDs. set_interrupt() targets a specific thread;
is_interrupted() checks the current thread. Includes a backward-
compatible _ThreadAwareEventProxy for legacy _interrupt_event usage.
- run_agent.py: Store execution thread ID at start of run_conversation().
interrupt() and clear_interrupt() pass it to set_interrupt() so only
this agent's thread is affected.
- tools/code_execution_tool.py: Use is_interrupted() instead of
directly checking _interrupt_event.is_set().
- tools/process_registry.py: Same — use is_interrupted().
- tests: Update interrupt tests for per-thread semantics. Add new
TestPerThreadInterruptIsolation with two tests verifying cross-thread
isolation.
When a Python process exits uncleanly (SIGKILL, crash, gateway restart
via hermes update), in-memory _active_sessions tracking is lost but the
agent-browser node daemons and their Chromium child processes keep
running indefinitely. On a long-running system this causes unbounded
memory growth — 24 orphaned sessions consumed 7.6 GB on a production
machine over 9 days.
Add _reap_orphaned_browser_sessions() which scans the tmp directory for
agent-browser-{h_*,cdp_*} socket dirs on cleanup thread startup. For
each dir not tracked by the current process, reads the daemon PID file
and sends SIGTERM if the daemon is still alive. Handles edge cases:
dead PIDs, corrupt PID files, permission errors, foreign processes.
The reaper runs once on thread startup (not every 30s) to avoid races
with sessions being actively created by concurrent agents.
The test expected content=None to immediately trigger thinking-exhaustion,
but PR #7738 correctly gates that check on _has_think_tags. Without think
tags, the agent falls through to normal continuation retry (3 attempts).
Background process watchers (notify_on_complete, check_interval) created
synthetic SessionSource objects without user_id/user_name. While the
internal=True bypass (1d8d4f28) prevented false pairing for agent-
generated notifications, the missing identity caused:
- Garbage entries in pairing rate limiters (discord:None, telegram:None)
- 'User None' in approval messages and logs
- No user identity available for future code paths that need it
Additionally, platform messages arriving without from_user (Telegram
service messages, channel forwards, anonymous admin actions) could still
trigger false pairing because they are not internal events.
Fix:
1. Propagate user_id/user_name through the full watcher chain:
session_context.py → gateway/run.py → terminal_tool.py →
process_registry.py (including checkpoint persistence/recovery)
2. Add None user_id guard in _handle_message() — silently drop
non-internal messages with no user identity instead of triggering
the pairing flow.
Salvaged from PRs #7664 (kagura-agent, ContextVar approach),
#6540 (MestreY0d4-Uninter, tests), and #7709 (guang384, None guard).
Closes#6341, #6485, #7643
Relates to #6516, #7392
Two-phase design so the warning fires before the user's first message
on every platform:
Phase 1 (__init__):
_check_compression_model_feasibility() runs during agent construction.
Resolves the auxiliary compression model (same chain as call_llm with
task='compression'), compares its context length to the main model's
compression threshold. If too small, emits via _emit_status() (prints
for CLI) and stores the warning in _compression_warning.
Phase 2 (run_conversation, first call):
_replay_compression_warning() re-sends the stored warning through
status_callback — which the gateway wires AFTER construction. The
warning is then cleared so it only fires once.
This ensures:
- CLI users see the warning immediately at startup (right after the
context limit line)
- Gateway users (Telegram, Discord, Slack, WhatsApp, Signal, Matrix,
Mattermost, Home Assistant, DingTalk, etc.) receive it via
status_callback('lifecycle', ...) on their first message
- logger.warning() always hits agent.log regardless of platform
Also warns when no auxiliary LLM provider is configured at all.
Entire check wrapped in try/except — never blocks startup.
11 tests covering: core warning logic, boundary conditions, exception
safety, two-phase store+replay, gateway callback wiring, and
single-delivery guarantee.
The Weixin adapter was splitting responses at every top-level newline,
causing notification spam (up to 70 API calls for a single long markdown
response). This salvages the best aspects of six contributor PRs:
Compact mode (new default):
- Messages under the 4000-char limit stay as a single bubble even with
multiple lines, paragraphs, and code blocks
- Only oversized messages get split at logical markdown boundaries
- Inter-chunk delay (0.3s) between chunks prevents WeChat rate-limit drops
Legacy mode (opt-in):
- Set split_multiline_messages: true in platforms.weixin.extra config
- Or set WEIXIN_SPLIT_MULTILINE_MESSAGES=true env var
- Restores the old per-line splitting behavior
Salvaged from PRs #7797 (guantoubaozi), #7792 (luoxiao6645),
#7838 (qyx596), #7825 (weedge), #7784 (sherunlock03), #7773 (JnyRoad).
Core fix unanimous across all six; config toggle from #7838; inter-chunk
delay from #7825.
hermes claw migrate now always shows a full dry-run preview before
making any changes. The user reviews what would be imported, then
confirms to proceed. --dry-run stops after the preview. --yes skips
the confirmation prompt.
This matches the existing setup wizard flow (_offer_openclaw_migration)
which already did preview-then-confirm.
Docs updated across both docs/migration/openclaw.md and
website/docs/guides/migrate-from-openclaw.md to reflect:
- New preview-first UX flow
- workspace-main/ fallback paths
- accounts.default channel token layout
- TTS edge/microsoft rename
- openclaw.json env sub-object as API key source
- Hyphenated provider API types
- Matrix accessToken field
- SecretRef file/exec warnings
- Skills session restart note
- WhatsApp re-pairing note
- Archive cleanup step
Consolidates fixes from PRs #7869, #7860, #7861, #7862, #7864, #7868.
OpenClaw restructured several internal paths and config schemas that the
migration tool was reading from stale locations:
- workspace/ renamed to workspace-main/ (and workspace-{agentId} for
multi-agent). source_candidate() now checks fallback paths.
- Channel tokens moved from channels.*.botToken to
channels.*.accounts.default.botToken. New _get_channel_field() checks
both flat and accounts.default layout.
- TTS provider 'edge' renamed to 'microsoft'. Migration now checks both
and normalizes back to 'edge' for Hermes.
- API keys stored in openclaw.json 'env' sub-object (env.<KEY> or
env.vars.<KEY>) are now discovered as an additional key source.
- Provider apiType values now hyphenated (openai-completions,
anthropic-messages, google-generative-ai). thinkingDefault expanded
with minimal, xhigh, adaptive.
- Matrix uses accessToken field, not botToken.
- SecretRef file/exec sources now warn instead of silently skipping.
- Migration notes now mention skills requiring session restart and
WhatsApp requiring QR re-pairing.
Co-authored-by: SHL0MS <SHL0MS@users.noreply.github.com>
The auxiliary client previously checked env vars (AUXILIARY_{TASK}_PROVIDER,
AUXILIARY_{TASK}_MODEL, etc.) before config.yaml's auxiliary.{task}.* section.
This violated the project's '.env is for secrets only' policy — these are
behavioral settings, not API keys.
Flipped the resolution order in _resolve_task_provider_model():
1. Explicit args (always win)
2. config.yaml auxiliary.{task}.* (PRIMARY)
3. Env var overrides (backward-compat fallback only)
4. 'auto' (full auto-detection chain)
Env var reading code is kept for backward compatibility but config.yaml
now takes precedence. Updated module docstring and function docstring.
Also removed AUXILIARY_VISION_MODEL from _EXTRA_ENV_KEYS in config.py.
The summary model used for context compaction must have a context window
at least as large as the main agent model. If it's smaller, the
summarization API call fails and middle turns are dropped without a
summary, silently losing conversation context.
Promoted the existing note in configuration.md to a visible warning
admonition, and added a matching warning in the developer guide's
context compression page.
Matrix gateway: fix sync loop never dispatching events (#5819)
- _sync_loop() called client.sync() but never called handle_sync()
to dispatch events to registered callbacks — _on_room_message was
registered but never fired for new messages
- Store next_batch token from initial sync and pass as since= to
subsequent incremental syncs (was doing full initial sync every time)
- 17 comments, confirmed by multiple users on matrix.org
Feishu docs: add interactive card configuration for approvals (#6893)
- Error 200340 is a Feishu Developer Console configuration issue,
not a code bug — users need to enable Interactive Card capability
and configure Card Request URL
- Added required 3-step setup instructions to feishu.md
- Added troubleshooting entry for error 200340
- 17 comments from Feishu users
Copilot provider drift: detect GPT-5.x Responses API requirement (#3388)
- GPT-5.x models are rejected on /v1/chat/completions by both OpenAI
and OpenRouter (unsupported_api_for_model error)
- Added _model_requires_responses_api() to detect models needing
Responses API regardless of provider
- Applied in __init__ (covers OpenRouter primary users) and in
_try_activate_fallback() (covers Copilot->OpenRouter drift)
- Fixed stale comment claiming gateway creates fresh agents per message
(it caches them via _agent_cache since the caching was added)
- 7 comments, reported on Copilot+Telegram gateway
The _PROVIDER_MODELS['openai-codex'] static list was a manually maintained
duplicate of DEFAULT_CODEX_MODELS in codex_models.py. They drifted — the
static list was missing gpt-5.3-codex-spark (and previously gpt-5.4).
Replace the hardcoded list with _codex_curated_models() which calls
DEFAULT_CODEX_MODELS + _add_forward_compat_models() from codex_models.py.
Now both the CLI 'hermes model' flow and the gateway /model picker derive
from the same source of truth. New models added to DEFAULT_CODEX_MODELS
or _FORWARD_COMPAT_TEMPLATE_MODELS automatically appear everywhere.
Telegram flood control during streaming caused messages to be cut off
mid-response. The old behavior permanently disabled edits after a single
flood-control failure, losing the remainder of the response.
Changes:
- Adaptive backoff: on flood-control edit failures, double the edit interval
instead of immediately disabling edits. Only permanently disable after 3
consecutive failures (_MAX_FLOOD_STRIKES).
- Cursor strip: when entering fallback mode, best-effort edit to remove the
cursor (▉) from the last visible message so it doesn't appear stuck.
- Fallback send retry: _send_fallback_final retries each chunk once on
flood-control failures (3s delay) before giving up.
- Default edit_interval increased from 0.3s to 1.0s. Telegram rate-limits
edits at ~1/s per message; 0.3s was virtually guaranteed to trigger flood
control on any non-trivial response.
- _send_or_edit returns bool so the overflow split loop knows not to
truncate accumulated text when an edit fails (prevents content loss).
Fixes: messages cutting/stopping mid-response on Telegram, especially
with streaming enabled.
* feat: add watch_patterns to background processes for output monitoring
Adds a new 'watch_patterns' parameter to terminal(background=true) that
lets the agent specify strings to watch for in process output. When a
matching line appears, a notification is queued and injected as a
synthetic message — triggering a new agent turn, similar to
notify_on_complete but mid-process.
Implementation:
- ProcessSession gets watch_patterns field + rate-limit state
- _check_watch_patterns() in ProcessRegistry scans new output chunks
from all three reader threads (local, PTY, env-poller)
- Rate limited: max 8 notifications per 10s window
- Sustained overload (45s) permanently disables watching for that process
- watch_queue alongside completion_queue, same consumption pattern
- CLI drains watch_queue in both idle loop and post-turn drain
- Gateway drains after agent runs via _inject_watch_notification()
- Checkpoint persistence + crash recovery includes watch_patterns
- Blocked in execute_code sandbox (like other bg params)
- 20 new tests covering matching, rate limiting, overload kill,
checkpoint persistence, schema, and handler passthrough
Usage:
terminal(
command='npm run dev',
background=true,
watch_patterns=['ERROR', 'WARN', 'listening on port']
)
* refactor: merge watch_queue into completion_queue
Unified queue with 'type' field distinguishing 'completion',
'watch_match', and 'watch_disabled' events. Extracted
_format_process_notification() in CLI and gateway to handle
all event types in a single drain loop. Removes duplication
across both CLI drain sites and the gateway.
The _PROVIDER_MODELS['openai-codex'] list was missing gpt-5.4 and gpt-5.4-mini,
causing them to not appear in the /model picker for ChatGPT OAuth users.
codex_models.py already had these models in DEFAULT_CODEX_MODELS, but the
curated list that feeds the Telegram/Discord /model picker was never updated.
Reported by @chongdashu
Follow-up fixes for cherry-pick conflicts:
- Removed test_context_keeps_pending_approval test that referenced
pop_pending() which doesn't exist on current main
- Added headers attribute to FakeResponse in vision test (needed
after #6949 added Content-Length check)
When the stream consumer has sent at least one message (already_sent=True),
the gateway skips sending the final response to avoid duplicates. But this
also suppressed error messages when the agent failed mid-loop — rate limit
exhaustion, context overflow, compression failure, etc.
The user would see the last streamed content and then nothing: no error
message, no explanation. The agent appeared to 'stop responding.'
Fix: check the 'failed' flag at both the producer (_run_agent marks
already_sent) and consumer (_handle_message_with_agent checks it) sites.
Error messages are always delivered regardless of streaming state.
_is_oauth_token() returned True for any key not starting with 'sk-ant-api',
which means MiniMax and Alibaba API keys were falsely treated as Anthropic
OAuth tokens. This triggered the Claude Code compatibility path:
- All tool names prefixed with mcp_ (e.g. mcp_terminal, mcp_web_search)
- System prompt injected with 'You are Claude Code' identity
- 'Hermes Agent' replaced with 'Claude Code' throughout
Fix: Make _is_oauth_token() positively identify Anthropic OAuth tokens by
their key format instead of using a broad catch-all:
- sk-ant-* (but not sk-ant-api-*) -> setup tokens, managed keys
- eyJ* -> JWTs from Anthropic OAuth flow
- Everything else -> False (MiniMax, Alibaba, etc.)
Reported by stefan171.
- Add agent.close() call to _finalize_shutdown_agents() to prevent
zombie processes (terminal sandboxes, browser daemons, httpx clients)
- Global cleanup (process_registry, environments, browsers) preserved
in _stop_impl() during conflict resolution
- Move /restart CommandDef from 'Info' to 'Session' category to match
/stop and /status
* fix: circuit breaker stops CPU-burning restart loops on persistent errors
When a gateway session hits a non-retryable error (e.g. invalid model
ID → HTTP 400), the agent fails and returns. But if the session keeps
receiving messages (or something periodically recreates agents), each
attempt spawns a new AIAgent — reinitializing MCP server connections,
burning CPU — only to hit the same 400 error again. On a 4-core server,
this pegs an entire core per stuck session and accumulates 300+ minutes
of CPU time over hours.
Fix: add a per-session consecutive failure counter in the gateway runner.
- Track consecutive non-retryable failures per session key
- After 3 consecutive failures (_MAX_CONSECUTIVE_FAILURES), block
further agent creation for that session and notify the user:
'⚠️ This session has failed N times in a row with a non-retryable
error. Use /reset to start a new session.'
- Evict the cached agent when the circuit breaker engages to prevent
stale state from accumulating
- Reset the counter on successful agent runs
- Clear the counter on /reset and /new so users can recover
- Uses getattr() pattern so bare GatewayRunner instances (common in
tests using object.__new__) don't crash
Tests:
- 8 new tests in test_circuit_breaker.py covering counter behavior,
threshold, reset, session isolation, and bare-runner safety
Addresses #7130.
* Revert "fix: circuit breaker stops CPU-burning restart loops on persistent errors"
This reverts commit d848ea7109.
* fix: don't evict cached agent on failed runs — prevents MCP restart loop
When a run fails (e.g. invalid model ID → 400) and fallback activated,
the gateway was evicting the cached agent to 'retry primary next time.'
But evicting a failed agent forces a full AIAgent recreation on the next
message — reinitializing MCP server connections, spawning stdio
processes — only to hit the same 400 again. This created a CPU-burning
loop (91%+ for hours, #7130).
The fix: add `and not _run_failed` to the fallback-eviction check.
Failed runs keep the cached agent. The next message reuses it (no MCP
reinit), hits the same error, returns it to the user quickly. The user
can /reset or /model to fix their config.
Successful fallback runs still evict as before so the next message
retries the primary model.
Addresses #7130.
Follow-up fixes for the matrix-nio → mautrix migration:
1. Module-level mautrix.types import now wrapped in try/except with
proper stub classes. Without this, importing gateway.platforms.matrix
crashes the entire gateway when mautrix isn't installed — even for
users who don't use Matrix. The stubs mirror mautrix's real attribute
names so tests that exercise adapter methods (send, reactions, etc.)
work without the real SDK.
2. Removed _ensure_mautrix_mock() from test_matrix_mention.py — it
permanently installed MagicMock modules in sys.modules via setdefault(),
polluting later tests in the suite. No longer needed since the module
imports cleanly without mautrix.
3. Fixed thread persistence tests to use direct class reference in
monkeypatch.setattr() instead of string-based paths, which broke
when the module was reimported by other tests.
4. Moved the module-importability test to a subprocess to prevent it
from polluting sys.modules (reimporting creates a second module object
with different __dict__, breaking patch.object in subsequent tests).
- Add shared is_wsl() to hermes_constants (like is_termux)
- Update supports_systemd_services() to verify systemd is actually
running on WSL before returning True
- Add WSL-specific guidance in gateway install/start/setup/status
for both cases: WSL+systemd and WSL without systemd
- Improve help strings: 'run' now says recommended for WSL/Docker,
'start'/'install' now mention systemd/launchd explicitly
- Add WSL gateway FAQ section with tmux/nohup/Task Scheduler tips
- Update CLI commands docs with WSL tip
- Deduplicate _is_wsl() from clipboard.py to shared hermes_constants
- Fix clipboard tests to reset hermes_constants cache
- 20 new WSL-specific tests covering detection, systemd check,
supports_systemd_services integration, and command output
Motivated by user feedback: took 1 hour to figure out run vs start
on WSL, Telegram bot kept disconnecting due to flaky WSL systemd.
- Remove auto-activation: when context.engine is 'compressor' (default),
plugin-registered engines are NOT used. Users must explicitly set
context.engine to a plugin name to activate it.
- Add curses_radiolist() to curses_ui.py: single-select radio picker
with keyboard nav + text fallback, matching curses_checklist pattern.
- Rewrite cmd_toggle() as composite plugins UI:
Top section: general plugins with checkboxes (existing behavior)
Bottom section: provider plugin categories (Memory Provider, Context Engine)
with current selection shown inline. ENTER/SPACE on a category opens
a radiolist sub-screen for single-select configuration.
- Add provider discovery helpers: _discover_memory_providers(),
_discover_context_engines(), config read/save for memory.provider
and context.engine.
- Add tests: radiolist non-TTY fallback, provider config save/load,
discovery error handling, auto-activation removal verification.
Follow-up fixes for the context engine plugin slot (PR #5700):
- Enhance ContextEngine ABC: add threshold_percent, protect_first_n,
protect_last_n as class attributes; complete update_model() default
with threshold recalculation; clarify on_session_end() lifecycle docs
- Add ContextCompressor.update_model() override for model/provider/
base_url/api_key updates
- Replace all direct compressor internal access in run_agent.py with
ABC interface: switch_model(), fallback restore, context probing
all use update_model() now; _context_probed guarded with getattr/
hasattr for plugin engine compatibility
- Create plugins/context_engine/ directory with discovery module
(mirrors plugins/memory/ pattern) — discover_context_engines(),
load_context_engine()
- Add context.engine config key to DEFAULT_CONFIG (default: compressor)
- Config-driven engine selection in run_agent.__init__: checks config,
then plugins/context_engine/<name>/, then general plugin system,
falls back to built-in ContextCompressor
- Wire on_session_end() in shutdown_memory_provider() at real session
boundaries (CLI exit, /reset, gateway expiry)
When models return empty responses (no content, no tool calls, no
reasoning), Hermes previously retried 3 times silently then fell through
to '(empty)' — without ever trying the fallback provider chain. Users on
GLM-4.5-Air and similar models experienced what appeared to be a
complete hang, especially in gateway (Telegram/Discord) contexts where
the silent retries produced zero feedback.
Changes:
- After exhausting 3 empty retries, attempt _try_activate_fallback()
before giving up with '(empty)'. If fallback succeeds, reset retry
counter and continue the conversation loop with the new provider.
- Replace all _vprint() calls in recovery paths with _emit_status(),
which surfaces messages through both CLI (_vprint with force=True)
and gateway (status_callback -> adapter.send). Users now see:
* '⚠️ Empty response from model — retrying (N/3)' during retries
* '⚠️ Model returning empty responses — switching to fallback...'
* '↻ Switched to fallback: <model> (<provider>)' on success
* '❌ Model returned no content after all retries [and fallback]'
- Add logger.warning() throughout empty response paths for log file
visibility (model name, provider, retry counts).
- Upgrade _last_content_with_tools fallback from logger.debug to
logger.info + _emit_status so recovery is visible.
- Upgrade thinking-only prefill continuation to use _emit_status.
Tests:
- test_empty_response_triggers_fallback_provider: verifies fallback
activation after 3 empty retries produces content from fallback model
- test_empty_response_fallback_also_empty_returns_empty: verifies
graceful degradation when fallback also returns empty
- test_empty_response_emits_status_for_gateway: verifies _emit_status
is called during retries so gateway users see feedback
Addresses #7180.
Six platforms (matrix, mattermost, dingtalk, feishu, wecom, homeassistant)
were missing from the session-based discovery loop, causing /channels and
send_message to return empty results on those platforms.
Instead of adding them to the hardcoded tuple (which would break again when
new platforms are added), derive the list dynamically from the Platform enum.
Only infrastructure entries (local, api_server, webhook) are excluded;
Discord and Slack are skipped automatically because their direct builders
already populate the platforms dict.
Reported by sprmn24 in PR #7416.
The profile system expects these directories but they weren't
being created on container startup. Adds them to the mkdir list
alongside the existing dirs.
Co-authored-by: Tranquil-Flow <tranquil_flow@protonmail.com>
When _build_api_kwargs() throws an exception, the except handler in
the retry loop referenced api_kwargs before it was assigned. This
caused an UnboundLocalError that masked the real error, making
debugging impossible for the user.
Two _dump_api_request_debug() calls in the except block (non-retryable
client error path and max-retries-exhausted path) both accessed
api_kwargs without checking if it was assigned.
Fix: initialize api_kwargs = None before the retry loop and guard both
dump calls. Now the real error surfaces instead of the masking
UnboundLocalError.
Reported by Discord user gruman0.
HERMES_OVERLAYS keys use models.dev IDs (e.g. 'github-copilot') but
_PROVIDER_MODELS curated lists and config.yaml use Hermes provider IDs
('copilot'). list_authenticated_providers() Section 2 was using the
overlay key directly for model lookups and is_current checks, causing:
- 0 models shown for copilot, kimi, kilo, opencode, vercel
- is_current never matching the config provider
Fix: build reverse mapping from PROVIDER_TO_MODELS_DEV to translate
overlay keys to Hermes slugs before curated list lookup and result
construction. Also adds 'kimi-for-coding' alias in auth.py so the
picker's returned slug resolves correctly in resolve_provider().
Fixes#5223. Based on work by HearthCore (#6492) and linxule (#6287).
Co-authored-by: HearthCore <HearthCore@users.noreply.github.com>
Co-authored-by: linxule <linxule@users.noreply.github.com>
Isolate system tool configs (git, ssh, gh, npm) per profile by injecting
a per-profile HOME into subprocess environments only. The Python
process's own os.environ['HOME'] and Path.home() are never modified,
preserving all existing profile infrastructure.
Activation is directory-based: when {HERMES_HOME}/home/ exists on disk,
subprocesses see it as HOME. The directory is created automatically for:
- Docker: entrypoint.sh bootstraps it inside the persistent volume
- Named profiles: added to _PROFILE_DIRS in profiles.py
Injection points (all three subprocess env builders):
- tools/environments/local.py _make_run_env() — foreground terminal
- tools/environments/local.py _sanitize_subprocess_env() — background procs
- tools/code_execution_tool.py child_env — execute_code sandbox
Single source of truth: hermes_constants.get_subprocess_home()
Closes#4426
Teknium