Adds defensive guard against empty/None/missing choices in SamplingHandler.__call__
before accessing response.choices[0]. Returns proper ErrorData instead of crashing
with IndexError/TypeError on content filtering, provider errors, or rate limits.
Authored by 0xbyt4.
Co-authored-by: 0xbyt4 <0xbyt4@users.noreply.github.com>
Adds tool_choice, parallel_tool_calls, and prompt_cache_key to the
Codex Responses API request kwargs — matching what the official Codex
CLI sends.
- tool_choice: 'auto' — enables the model to proactively call tools.
Without this, the model may default to not using tools, which explains
reports of the agent claiming it lacks shell access (#747).
- parallel_tool_calls: True — allows the model to issue multiple tool
calls in a single turn for efficiency.
- prompt_cache_key: session_id — enables server-side prompt caching
across turns in the same session, reducing latency and cost.
Refs #747
Isolate Telegram forum topic sessions — each topic gets its own independent session key, history, and interrupt tracking. Progress, hygiene, and cron messages all route to the correct topic.
Four cleanups to code merged today:
1. New hermes_cli/curses_ui.py — shared curses_checklist() used by both
hermes tools and hermes skills. Eliminates ~140 lines of near-identical
curses code (scrolling, key handling, color setup, numbered fallback).
2. Fix _find_all_skills() perf — was calling load_config() per skill
(~100+ YAML parses). Now loads disabled set once via
_get_disabled_skill_names() and does a set lookup.
3. Eliminate _list_all_skills_unfiltered() duplication — _find_all_skills()
now accepts skip_disabled=True for the config UI, removing 30 lines
of copy-pasted discovery logic from skills_config.py.
4. Fix fragile label round-trip in skills_command — was building label
strings, passing to checklist, then mapping labels back to skill names
(collision-prone). Now works with indices directly, like tools_config.
Authored by teyrebaz33. Closes#643.
- /personality none/default/neutral clears system prompt overlay
- Dict format personalities with description, tone, style fields
- Works in both CLI and gateway
- 18 tests
Add /background <prompt> to the gateway, allowing users on Telegram,
Discord, Slack, etc. to fire off a prompt in a separate agent session.
The result is delivered back to the same chat when done, without
modifying the active conversation history.
Implementation:
- _handle_background_command: validates input, spawns asyncio task
- _run_background_task: creates AIAgent in executor thread, delivers
result (text, images, media files) back via the platform adapter
- Inherits model, toolsets, provider routing from gateway config
- Error handling with user-visible failure messages
Also adds /background to hermes_cli/commands.py registry so it
appears in /help and autocomplete.
Tests: 15 new tests covering usage, task creation, uniqueness,
multi-platform, error paths, and help/autocomplete integration.
Fixes#898 — Python 3.11 changed argparse to raise an exception on
duplicate subparser names (CPython #94331). The 'skills' name was
registered twice: once for Skills Hub and once for skills config.
Changes:
- Remove duplicate 'skills' subparser registration
- Add 'config' as a sub-action under the existing 'hermes skills' command
- Route 'hermes skills config' to skills_config module
- Add regression test to catch future duplicates
Migration: 'hermes skills' (config) is now 'hermes skills config'
Two-tier warning system that nudges the LLM as it approaches
max_iterations, injected into the last tool result JSON rather
than as a separate system message:
- Caution (70%): {"_budget_warning": "[BUDGET: 42/60...]"}
- Warning (90%): {"_budget_warning": "[BUDGET WARNING: 54/60...]"}
For JSON tool results, adds a _budget_warning field to the existing
dict. For plain text results, appends the warning as text.
Key properties:
- No system messages injected mid-conversation
- No changes to message structure
- Prompt cache stays valid
- Configurable thresholds (0.7 / 0.9)
- Can be disabled: _budget_pressure_enabled = False
Inspired by PR #421 (@Bartok9) and issue #414.
8 tests covering thresholds, edge cases, JSON and text injection.
Replaces head-only stdout capture with a two-buffer approach (40% head,
60% tail rolling window) so scripts that print() their final results
at the end never lose them. Adds truncation notice between sections.
Cherry-picked from PR #755, conflict resolved (test file additions).
3 new tests for short output, head+tail preservation, and notice format.
Adds configurable bot message filtering via DISCORD_ALLOW_BOTS env var:
- 'none' (default): ignore all bot messages
- 'mentions': accept bots only when they @mention us
- 'all': accept all bot messages
Includes 8 tests.
Authored by teyrebaz33. Adds config-driven quick commands that execute
shell commands without invoking the LLM — zero token usage, works from
Telegram/Discord/Slack/etc. Closes#744.
Follow-up to 58dbd81 — ensures smooth transition for existing users:
- Backward compat: old session files without last_prompt_tokens
default to 0 via data.get('last_prompt_tokens', 0)
- /compress, /undo, /retry: reset last_prompt_tokens to 0 after
rewriting transcripts (stale token counts would under-report)
- Auto-compression hygiene: reset last_prompt_tokens after rewriting
- update_session: use None sentinel (not 0) as default so callers
can explicitly reset to 0 while normal calls don't clobber
- 6 new tests covering: default value, serialization roundtrip,
old-format migration, set/reset/no-change semantics
- /reset: new SessionEntry naturally gets last_prompt_tokens=0
2942 tests pass.
Adds two tests for _handle_retry_command: verifies /retry returns the
agent response (not None), and verifies graceful handling when no
previous message exists.
Cherry-picked from PR #731 by teyrebaz33. Regression coverage for
the fix merged in PR #441.
Co-authored-by: teyrebaz33 <teyrebaz33@users.noreply.github.com>
Authored by dmahan93. Adds HERMES_YOLO_MODE env var and --yolo CLI flag
to auto-approve all dangerous command prompts.
Post-merge: renamed --fuck-it-ship-it to --yolo for brevity,
resolved conflict with --checkpoints flag.
On macOS, Docker Desktop installs the CLI to /usr/local/bin/docker, but
when Hermes runs as a gateway service (launchd) or in other non-login
contexts, /usr/local/bin is often not in PATH. This causes the Docker
requirements check to fail with 'No such file or directory: docker' even
though docker works fine from the user's terminal.
Add find_docker() helper that uses shutil.which() first, then probes
common Docker Desktop install paths on macOS (/usr/local/bin,
/opt/homebrew/bin, Docker.app bundle). The resolved path is cached and
passed to mini-swe-agent via its 'executable' parameter.
- tools/environments/docker.py: add find_docker(), use it in
_storage_opt_supported() and pass to _Docker(executable=...)
- tools/terminal_tool.py: use find_docker() in requirements check
- tests/tools/test_docker_find.py: 4 tests (PATH, fallback, not found, cache)
2877 tests pass.
Shows an immediate status message and braille spinner for slow slash
commands (/skills search|browse|inspect|install, /reload-mcp). Makes
input read-only while the command runs so the CLI doesn't appear frozen.
Cherry-picked from PR #714 by vilkasdev, rebased onto current main
with conflict resolution and bug fix (get_hint_text duplicate return).
Fixes#636
Co-authored-by: vilkasdev <vilkasdev@users.noreply.github.com>
Two related bugs prevented users from reliably switching providers:
1. OPENAI_BASE_URL poisoning OpenRouter resolution: When a user with a
custom endpoint ran /model openrouter:model, _resolve_openrouter_runtime
picked up OPENAI_BASE_URL instead of the OpenRouter URL, causing model
validation to probe the wrong API and reject valid models.
Fix: skip OPENAI_BASE_URL when requested_provider is explicitly
'openrouter'.
2. Provider never saved to config: _save_model_choice() could save
config.model as a plain string. All five _model_flow_* functions then
checked isinstance(model, dict) before writing the provider — which
silently failed on strings. With no provider in config, auto-detection
would pick up stale credentials (e.g. Codex desktop app) instead of
the user's explicit choice.
Fix: _save_model_choice() now always saves as dict format. All flow
functions also normalize string->dict as a safety net before writing
provider.
Adds 4 regression tests. 2873 tests pass.
Follow-up to PR #716 (0xbyt4):
- Log the third remaining silent except-pass in scheduler (prefill
messages JSON parse failure)
- Fix test mock: run → run_conversation (matches actual agent API)
- Remove unused imports (asyncio, AsyncMock)
- Add test for prefill_messages parse failure logging
The 4 early-return paths in _spawn_training_run (API exit, trainer
exit, env not found, env exit) were doing manual process.terminate()
or returning without cleanup, leaking open log file handles. Now all
paths call _stop_training_run() which handles both process termination
and file handle closure.
Also adds 12 tests for _stop_training_run covering file handle
cleanup, process termination, status transitions, and edge cases.
Inspired by PR #715 (0xbyt4) which identified the early-return issue.
Core file handle fix was already on main via e28dc13 (memosr.eth).
Follow-up to PR #705 (merged from 0xbyt4). Addresses several issues:
1. CONSECUTIVE-ONLY TRACKING: Redesigned the read/search tracker to only
warn/block on truly consecutive identical calls. Any other tool call
in between (write, patch, terminal, etc.) resets the counter via
notify_other_tool_call(), called from handle_function_call() in
model_tools.py. This prevents false blocks in read→edit→verify flows.
2. THRESHOLD ADJUSTMENT: Warn on 3rd consecutive (was 2nd), block on
4th+ consecutive (was 3rd+). Gives the model more room before
intervening.
3. TUPLE UNPACKING BUG: Fixed get_read_files_summary() which crashed on
search keys (5-tuple) when trying to unpack as 3-tuple. Now uses a
separate read_history set that only tracks file reads.
4. WEB_EXTRACT DOCSTRING: Reverted incorrect removal of 'title' from
web_extract return docs in code_execution_tool.py — the field IS
returned by web_tools.py.
5. TESTS: Rewrote test_read_loop_detection.py (35 tests) to cover
consecutive-only behavior, notify_other_tool_call, interleaved
read/search, and summary-unaffected-by-searches.
Three separate code paths all wrote to the same SQLite state.db with
no deduplication, inflating session transcripts by 3-4x:
1. _log_msg_to_db() — wrote each message individually after append
2. _flush_messages_to_session_db() — re-wrote ALL new messages at
every _persist_session() call (~18 exit points), with no tracking
of what was already written
3. gateway append_to_transcript() — wrote everything a third time
after the agent returned
Since load_transcript() prefers SQLite over JSONL, the inflated data
was loaded on every session resume, causing proportional token waste.
Fix:
- Remove _log_msg_to_db() and all 16 call sites (redundant with flush)
- Add _last_flushed_db_idx tracking in _flush_messages_to_session_db()
so repeated _persist_session() calls only write truly new messages
- Reset flush cursor on compression (new session ID)
- Add skip_db parameter to SessionStore.append_to_transcript() so the
gateway skips SQLite writes when the agent already persisted them
- Gateway now passes skip_db=True for agent-managed messages, still
writes to JSONL as backup
Verified: a 12-message CLI session with tool calls produces exactly
12 SQLite rows with zero duplicates (previously would be 36-48).
Tests: 9 new tests covering flush deduplication, skip_db behavior,
compression reset, and initialization. Full suite passes (2869 tests).
- Add agent/embeddings.py with Embedder protocol, FastEmbedEmbedder, OpenAIEmbedder
- Factory function get_embedder() reads provider from config.yaml embeddings section
- Lazy initialization — no startup impact, model loaded on first embed call
- cosine_similarity() and cosine_similarity_matrix() utility functions included
- Add fastembed as optional dependency in pyproject.toml
- 30 unit tests, all passing
Closes#675
Completes the fix started in 8318a51 — handle_function_call() accepted
enabled_tools but run_agent.py never passed it. Now both call sites in
_execute_tool_calls() pass self.valid_tool_names, so each agent session
uses its own tool list instead of the process-global
_last_resolved_tool_names (which subagents can overwrite).
Also simplifies the redundant ternary in code_execution_tool.py:
sandbox_tools is already computed correctly (intersection with session
tools, or full SANDBOX_ALLOWED_TOOLS as fallback), so the conditional
was dead logic.
Inspired by PR #663 (JasonOA888). Closes#662.
Tests: 2857 passed.
Add support for using Nous Portal via a direct API key, mirroring
how OpenRouter and other API-key providers work. This gives users a
simpler alternative to the OAuth device-code flow when they already
have a Nous API key.
Changes:
- Add 'nous-api' to PROVIDER_REGISTRY as an api_key provider
pointing to https://inference-api.nousresearch.com/v1
- Add NOUS_API_KEY and NOUS_BASE_URL to OPTIONAL_ENV_VARS
- Add NOUS_API_BASE_URL / NOUS_API_CHAT_URL to hermes_constants
- Add 'Nous Portal API key' as first option in setup wizard
- Add provider aliases (nous_api, nousapi, nous-portal-api)
- Add test for nous-api runtime provider resolution
Closes#644
Move all new tests (schema, env filtering, edge cases, interrupt) into
the existing test_code_execution.py instead of a separate file.
Delete the now-redundant test_code_execution_schema.py.
build_execute_code_schema(set()) produced "from hermes_tools import , ..."
in the code property description — invalid Python syntax shown to the model.
This triggers when a user enables only the code_execution toolset without
any of the sandbox-allowed tools (e.g. `hermes tools code_execution`),
because SANDBOX_ALLOWED_TOOLS & {"execute_code"} = empty set.
Also adds 29 unit tests covering build_execute_code_schema, environment
variable filtering, execute_code edge cases, and interrupt handling.
Authored by tripledoublev.
After context compression on 413/400 errors, the inner retry loop was
reusing the stale pre-compression api_messages payload. Fix breaks out
of the inner retry loop so the outer loop rebuilds api_messages from
the now-compressed messages list. Adds regression test verifying the
second request actually contains the compressed payload.
Add display.background_process_notifications config option to control
how chatty the gateway process watcher is when using
terminal(background=true, check_interval=...) from messaging platforms.
Modes:
- all: running-output updates + final message (default, current behavior)
- result: only the final completion message
- error: only the final message when exit code != 0
- off: no watcher messages at all
Also supports HERMES_BACKGROUND_NOTIFICATIONS env var override.
Includes 12 tests (5 config loading + 7 watcher behavior).
Inspired by @PeterFile's PR #593. Closes#592.
Automatic filesystem snapshots before destructive file operations,
with user-facing rollback. Inspired by PR #559 (by @alireza78a).
Architecture:
- Shadow git repos at ~/.hermes/checkpoints/{hash}/ via GIT_DIR
- CheckpointManager: take/list/restore, turn-scoped dedup, pruning
- Transparent — the LLM never sees it, no tool schema, no tokens
- Once per turn — only first write_file/patch triggers a snapshot
Integration:
- Config: checkpoints.enabled + checkpoints.max_snapshots
- CLI flag: hermes --checkpoints
- Trigger: run_agent.py _execute_tool_calls() before write_file/patch
- /rollback slash command in CLI + gateway (list, restore by number)
- Pre-rollback snapshot auto-created on restore (undo the undo)
Safety:
- Never blocks file operations — all errors silently logged
- Skips root dir, home dir, dirs >50K files
- Disables gracefully when git not installed
- Shadow repo completely isolated from project git
Tests: 35 new tests, all passing (2798 total suite)
Docs: feature page, config reference, CLI commands reference
Authored by unmodeled-tyler. Adds openclaw-migration skill to optional-skills/
with migration script, SKILL.md, and 7 tests. Also improves clarify/approval
panel rendering with dynamic width calculation.
Authored by 0xbyt4. Fixes #N/A (no linked issue).
- Sanitize user input before FTS5 MATCH to prevent OperationalError on
special characters (C++, unbalanced quotes, dangling operators, etc.)
- Close SessionDB connection in mirror._append_to_sqlite() via finally block
- Added tests for both fixes
Platform.SIGNAL was missing from default_toolset_map and platform_config_key
in gateway/run.py, causing Signal to silently fall back to hermes-telegram
toolset (same bug as HomeAssistant, fixed in PR #538).
Also updates:
- tests/test_toolsets.py: include hermes-signal and hermes-homeassistant in
the platform core-tools consistency check
- cli-config.yaml.example: document signal and homeassistant platform keys
When a user runs `hermes -w -c Pokemon Agent Dev` without quoting the
session name, argparse would fail with:
error: argument command: invalid choice: 'Agent'
This is because argparse parses `-c Pokemon` (consuming one token via
nargs='?'), then sees 'Agent' and tries to match it as a subcommand.
Fix: add _coalesce_session_name_args() that pre-processes sys.argv before
argparse, joining consecutive non-flag, non-subcommand tokens after -c or
-r into a single argument. This makes both quoted and unquoted multi-word
session names work transparently.
Includes 17 tests covering all edge cases: multi-word names, single-word,
bare flags, flag ordering, subcommand boundaries, and passthrough.
Complements PR #453 by 0xbyt4. Adds isinstance(dict) guard in
run_agent.py to catch cases where json.loads returns non-dict
(e.g. null, list, string) before they reach downstream code.
Also adds 15 tests for build_tool_preview covering None args,
empty dicts, known/unknown tools, fallback keys, truncation,
and all special-cased tools (process, todo, memory, session_search).
Validate that the username portion of ~username paths contains only
valid characters (alphanumeric, dot, hyphen, underscore) before passing
to shell echo for expansion. Previously, paths like '~; rm -rf /'
would be passed unquoted to self._exec(f'echo {path}'), allowing
arbitrary command execution.
The approach validates the username rather than using shlex.quote(),
which would prevent tilde expansion from working at all since
echo '~user' outputs the literal string instead of expanding it.
Added tests for injection blocking and valid ~username/path expansion.
Credit to @alireza78a for reporting (PR #442, issue #442).
SamplingHandler.__call__ accessed response.choices[0] without checking
if the list was non-empty. LLM APIs can return empty choices on content
filtering, provider errors, or rate limits, causing an unhandled
IndexError that propagates to the MCP SDK and may crash the connection.
Add a defensive guard that returns a proper ErrorData when choices is
empty, None, or missing. Includes three test cases covering all
variants.
Vision auto-mode previously only tried OpenRouter, Nous, and Codex
for multimodal — deliberately skipping custom endpoints with the
assumption they 'may not handle vision input.' This caused silent
failures for users running local multimodal models (Qwen-VL, LLaVA,
Pixtral, etc.) without any cloud API keys.
Now custom endpoints are tried as a last resort in auto mode. If the
model doesn't support vision, the API call fails gracefully — but
users with local vision models no longer need to manually set
auxiliary.vision.provider: main in config.yaml.
Reported by @Spadav and @kotyKD.
Skills can now declare fallback_for_toolsets, fallback_for_tools,
requires_toolsets, and requires_tools in their SKILL.md frontmatter.
The system prompt builder filters skills automatically based on which
tools are available in the current session.
- Add _read_skill_conditions() to parse conditional frontmatter fields
- Add _skill_should_show() to evaluate conditions against available tools
- Update build_skills_system_prompt() to accept and apply tool availability
- Pass valid_tool_names and available toolsets from run_agent.py
- Backward compatible: skills without conditions always show; calling
build_skills_system_prompt() with no args preserves existing behavior
Closes#539
Implement send_document() and send_video() overrides in TelegramAdapter
so the agent can deliver files (PDFs, CSVs, docs, etc.) and videos as
native Telegram attachments instead of just printing the file path as
text.
The base adapter already routes MEDIA:<path> tags by extension — audio
goes to send_voice(), images to send_image_file(), and everything else
falls through to send_document(). But TelegramAdapter didn't override
send_document() or send_video(), so those fell back to plain text.
Now when the agent includes MEDIA:/path/to/report.pdf in its response,
users get a proper downloadable file attachment in Telegram.
Features:
- send_document: sends files via bot.send_document with display name,
caption (truncated to 1024), and reply_to support
- send_video: sends videos via bot.send_video with inline playback
- Both fall back to base class text if the Telegram API call fails
- 10 new tests covering success, custom filename, file-not-found,
not-connected, caption truncation, API error fallback, and reply_to
Requested by @TigerHixTang on Twitter.
- Register no-op app_mention event handler to suppress Bolt 404 errors.
The 'message' handler already processes @mentions in channels, so
app_mention is acknowledged without duplicate processing.
- Add send_document() for native file attachments (PDFs, CSVs, etc.)
via files_upload_v2, matching the pattern from Telegram PR #779.
- Add send_video() for native video uploads via files_upload_v2.
- Handle incoming document attachments from users: download, cache,
and inject text content for .txt/.md files (capped at 100KB),
following the same pattern as the Telegram adapter.
- Add _download_slack_file_bytes() helper for raw byte downloads.
- Add 24 new tests covering all new functionality.
Fixes the unhandled app_mention events reported in gateway logs.
Closes#643
Changes:
- /personality none|default|neutral — clears system prompt overlay
- Custom personalities in config.yaml support dict format with:
name, description, system_prompt, tone, style directives
- Backwards compatible — existing string format still works
- CLI + gateway both updated
- 18 tests covering none/default/neutral, dict format, string format,
list display, save to config
Add MCP sampling/createMessage capability via SamplingHandler class.
Text-only sampling + tool use in sampling with governance (rate limits,
model whitelist, token caps, tool loop limits). Per-server audit metrics.
Based on concept from PR #366 by eren-karakus0. Restructured as class-based
design with bug fixes and tests using real MCP SDK types.
50 new tests, 2600 total passing.
_FakeReadResult and _FakeSearchResult now expose the attributes
that read_file_tool/search_tool access after the redact_sensitive_text
integration from main.
Combine read/search loop detection with main's redact_sensitive_text
and truncation hint features. Add tracker reset to TestSearchHints
to prevent cross-test state leakage.
Add configurable bot message filtering via DISCORD_ALLOW_BOTS env var:
- 'none' (default): Ignore all other bot messages — matches previous
behavior where only our own bot was filtered, but now ALL bots are
filtered by default for cleaner channels
- 'mentions': Accept bot messages only when they @mention our bot —
useful for bot-to-bot workflows triggered by mentions
- 'all': Accept all bot messages — for setups where bots need to
interact freely
Previously, we only ignored our own bot's messages, allowing all other
bots through. This could cause noisy loops in channels with multiple bots.
8 new tests covering all filter modes and edge cases.
Inspired by openclaw v2026.3.7 Discord allowBots: 'mentions' config.
Enforce owner-only permissions on files and directories that contain
secrets or sensitive data:
- cron/jobs.py: jobs.json (0600), cron dirs (0700), job output files (0600)
- hermes_cli/config.py: config.yaml (0600), .env (0600), ~/.hermes/* dirs (0700)
- cli.py: config.yaml via save_config_value (0600)
All chmod calls use try/except for Windows compatibility.
Includes _secure_file() and _secure_dir() helpers with graceful fallback.
8 new tests verify permissions on all file types.
Inspired by openclaw v2026.3.7 file permission enforcement.
Two changes to prevent unnecessary Anthropic prompt cache misses in the
gateway, where a fresh AIAgent is created per user message:
1. Reuse stored system prompt for continuing sessions:
When conversation_history is non-empty, load the system prompt from
the session DB instead of rebuilding from disk. The model already has
updated memory in its conversation history (it wrote it!), so
re-reading memory from disk produces a different system prompt that
breaks the cache prefix.
2. Stabilize Honcho context per session:
- Only prefetch Honcho context on the first turn (empty history)
- Bake Honcho context into the cached system prompt and store to DB
- Remove the per-turn Honcho injection from the API call loop
This ensures the system message is identical across all turns in a
session. Previously, re-fetching Honcho could return different context
on each turn, changing the system message and invalidating the cache.
Both changes preserve the existing behavior for compression (which
invalidates the prompt and rebuilds from scratch) and for the CLI
(where the same AIAgent persists and the cached prompt is already
stable across turns).
Tests: 2556 passed (6 new)
Terminal output was already redacted via redact_sensitive_text() but
read_file and search_files returned raw content. Now both tools
redact secrets before returning results to the LLM.
Based on PR #372 by @teyrebaz33 (closes#363) — applied manually
due to branch conflicts with the current codebase.
The summary message was always injected as 'user' role, which causes
consecutive user messages when the last preserved head message is also
'user'. Some APIs reject this (400 error), and it produces malformed
training data.
Fix: check the role of the last head message and pick the opposite role
for the summary — 'user' after assistant/tool, 'assistant' after user.
Based on PR #328 by johnh4098. Closes#328.
Split fallback provider handling into two clean registries:
_FALLBACK_API_KEY_PROVIDERS — env-var-based (openrouter, zai, kimi, minimax)
_FALLBACK_OAUTH_PROVIDERS — OAuth-based (openai-codex, nous)
New _resolve_fallback_credentials() method handles all three cases
(OAuth, API key, custom endpoint) and returns a uniform (key, url, mode)
tuple. _try_activate_fallback() is now just validation + client build.
Adds Nous Portal as a fallback provider — uses the same OAuth flow
as the primary provider (hermes login), returns chat_completions mode.
OAuth providers get credential refresh for free: the existing 401
retry handlers (_try_refresh_codex/nous_client_credentials) check
self.provider, which is set correctly after fallback activation.
4 new tests (nous activation, nous no-login, codex retained).
27 total fallback tests passing, 2548 full suite.
Codex OAuth uses a different auth flow (OAuth tokens, not env vars)
and a different API mode (codex_responses, not chat_completions).
The fallback now handles this specially:
- Resolves credentials via resolve_codex_runtime_credentials()
- Sets api_mode to codex_responses
- Fails gracefully if no Codex OAuth session exists
Also added to the commented-out config.yaml example.
2 new tests (codex activation + graceful failure).
The gateway had a SEPARATE compression system ('session hygiene')
with hardcoded thresholds (100k tokens / 200 messages) that were
completely disconnected from the model's context length and the
user's compression config in config.yaml. This caused premature
auto-compression on Telegram/Discord — triggering at ~60k tokens
(from the 200-message threshold) or inconsistent token counts.
Changes:
- Gateway hygiene now reads model name from config.yaml and uses
get_model_context_length() to derive the actual context limit
- Compression threshold comes from compression.threshold in
config.yaml (default 0.85), same as the agent's ContextCompressor
- Removed the message-count-based trigger (was redundant and caused
false positives in tool-heavy sessions)
- Removed the undocumented session_hygiene config section — the
standard compression.* config now controls everything
- Env var overrides (CONTEXT_COMPRESSION_THRESHOLD,
CONTEXT_COMPRESSION_ENABLED) are respected
- Warn threshold is now 95% of model context (was hardcoded 200k)
- Updated tests to verify model-aware thresholds, scaling across
models, and that message count alone no longer triggers compression
For claude-opus-4.6 (200k context) at 85% threshold: gateway
hygiene now triggers at 170k tokens instead of the old 100k.
New browser capabilities and a built-in skill for agent-driven web QA.
## New tool: browser_console
Returns console messages (log/warn/error/info) AND uncaught JavaScript
exceptions in a single call. Uses agent-browser's 'console' and 'errors'
commands through the existing session plumbing. Supports --clear to reset
buffers. Verified working in both local and Browserbase cloud modes.
## Enhanced tool: browser_vision(annotate=True)
New boolean parameter on browser_vision. When true, agent-browser overlays
numbered [N] labels on interactive elements — each [N] maps to ref @eN.
Annotation data (element name, role, bounding box) returned alongside the
vision analysis. Useful for QA reports and spatial reasoning.
## Config: browser.record_sessions
Auto-record browser sessions as WebM video files when enabled:
- Starts recording on first browser_navigate
- Stops and saves on browser_close
- Saves to ~/.hermes/browser_recordings/
- Works in both local and cloud modes (verified)
- Disabled by default
## Built-in skill: dogfood
Systematic exploratory QA testing for web applications. Teaches the agent
a 5-phase workflow:
1. Plan — accept URL, create output dirs, set scope
2. Explore — systematic crawl with annotated screenshots
3. Collect Evidence — screenshots, console errors, JS exceptions
4. Categorize — severity (Critical/High/Medium/Low) and category
(Functional/Visual/Accessibility/Console/UX/Content)
5. Report — structured markdown with per-issue evidence
Includes:
- skills/dogfood/SKILL.md — full workflow instructions
- skills/dogfood/references/issue-taxonomy.md — severity/category defs
- skills/dogfood/templates/dogfood-report-template.md — report template
## Tests
21 new tests covering:
- browser_console message/error parsing, clear flag, empty/failed states
- browser_console schema registration
- browser_vision annotate schema and flag passing
- record_sessions config defaults and recording lifecycle
- Dogfood skill file existence and content validation
Addresses #315.
Remove hallucinated providers (openai, deepseek, together, groq,
fireworks, mistral, gemini, nous) from the fallback provider map.
These don't exist in hermes-agent's provider system.
The real supported providers for fallback are:
openrouter (OPENROUTER_API_KEY)
zai (ZAI_API_KEY)
kimi-coding (KIMI_API_KEY)
minimax (MINIMAX_API_KEY)
minimax-cn (MINIMAX_CN_API_KEY)
For any other OpenAI-compatible endpoint, users can use the
base_url + api_key_env overrides in the config.
Also adds Kimi User-Agent header for kimi fallback (matching
the main provider system).
When the primary model/provider fails after retries (rate limit, overload,
auth errors, connection failures), Hermes automatically switches to a
configured fallback model for the remainder of the session.
Config (in ~/.hermes/config.yaml):
fallback_model:
provider: openrouter
model: anthropic/claude-sonnet-4
Supports all major providers: OpenRouter, OpenAI, Nous, DeepSeek, Together,
Groq, Fireworks, Mistral, Gemini — plus custom endpoints via base_url and
api_key_env overrides.
Design principles:
- Dead simple: one fallback model, not a chain
- One-shot: switches once, doesn't ping-pong back
- Zero new dependencies: uses existing OpenAI client
- Minimal code: ~100 lines in run_agent.py, ~5 lines in cli.py/gateway
- Three trigger points: max retries exhausted, non-retryable client errors,
and invalid response exhaustion
Does NOT trigger on context overflow or payload-too-large errors (those
are handled by the existing compression system).
Addresses #737.
25 new tests, 2492 total passing.
Complete Signal adapter using signal-cli daemon HTTP API.
Based on PR #268 by ibhagwan, rebuilt on current main with bug fixes.
Architecture:
- SSE streaming for inbound messages with exponential backoff (2s→60s)
- JSON-RPC 2.0 for outbound (send, typing, attachments, contacts)
- Health monitor detects stale SSE connections (120s threshold)
- Phone number redaction in all logs and global redact.py
Features:
- DM and group message support with separate access policies
- DM policies: pairing (default), allowlist, open
- Group policies: disabled (default), allowlist, open
- Attachment download with magic-byte type detection
- Typing indicators (8s refresh interval)
- 100MB attachment size limit, 8000 char message limit
- E.164 phone + UUID allowlist support
Integration:
- Platform.SIGNAL enum in gateway/config.py
- Signal in _is_user_authorized() allowlist maps (gateway/run.py)
- Adapter factory in _create_adapter() (gateway/run.py)
- user_id_alt/chat_id_alt fields in SessionSource for UUIDs
- send_message tool support via httpx JSON-RPC (not aiohttp)
- Interactive setup wizard in 'hermes gateway setup'
- Connectivity testing during setup (pings /api/v1/check)
- signal-cli detection and install guidance
Bug fixes from PR #268:
- Timestamp reads from envelope_data (not outer wrapper)
- Uses httpx consistently (not aiohttp in send_message tool)
- SIGNAL_DEBUG scoped to signal logger (not root)
- extract_images regex NOT modified (preserves group numbering)
- pairing.py NOT modified (no cross-platform side effects)
- No dual authorization (adapter defers to run.py for user auth)
- Wildcard uses set membership ('*' in set, not list equality)
- .zip default for PK magic bytes (not .docx)
No new Python dependencies — uses httpx (already core).
External requirement: signal-cli daemon (user-installed).
Tests: 30 new tests covering config, init, helpers, session source,
phone redaction, authorization, and send_message integration.
Co-authored-by: ibhagwan <ibhagwan@users.noreply.github.com>
The gateway had a SEPARATE compression system ('session hygiene')
with hardcoded thresholds (100k tokens / 200 messages) that were
completely disconnected from the model's context length and the
user's compression config in config.yaml. This caused premature
auto-compression on Telegram/Discord — triggering at ~60k tokens
(from the 200-message threshold) or inconsistent token counts.
Changes:
- Gateway hygiene now reads model name from config.yaml and uses
get_model_context_length() to derive the actual context limit
- Compression threshold comes from compression.threshold in
config.yaml (default 0.85), same as the agent's ContextCompressor
- Removed the message-count-based trigger (was redundant and caused
false positives in tool-heavy sessions)
- Removed the undocumented session_hygiene config section — the
standard compression.* config now controls everything
- Env var overrides (CONTEXT_COMPRESSION_THRESHOLD,
CONTEXT_COMPRESSION_ENABLED) are respected
- Warn threshold is now 95% of model context (was hardcoded 200k)
- Updated tests to verify model-aware thresholds, scaling across
models, and that message count alone no longer triggers compression
For claude-opus-4.6 (200k context) at 85% threshold: gateway
hygiene now triggers at 170k tokens instead of the old 100k.
The 'openai' provider was redundant — using OPENAI_BASE_URL +
OPENAI_API_KEY with provider: 'main' already covers direct OpenAI API.
Provider options are now: auto, openrouter, nous, codex, main.
- Removed _try_openai(), _OPENAI_AUX_MODEL, _OPENAI_BASE_URL
- Replaced openai tests with codex provider tests
- Updated all docs to remove 'openai' option and clarify 'main'
- 'main' description now explicitly mentions it works with OpenAI API,
local models, and any OpenAI-compatible endpoint
Tests: 2467 passed.
The Codex Responses API (chatgpt.com/backend-api/codex) supports
vision via gpt-5.3-codex. This was verified with real API calls
using image analysis.
Changes to _CodexCompletionsAdapter:
- Added _convert_content_for_responses() to translate chat.completions
multimodal format to Responses API format:
- {type: 'text'} → {type: 'input_text'}
- {type: 'image_url', image_url: {url: '...'}} → {type: 'input_image', image_url: '...'}
- Fixed: removed 'stream' from resp_kwargs (responses.stream() handles it)
- Fixed: removed max_output_tokens and temperature (Codex endpoint rejects them)
Provider changes:
- Added 'codex' as explicit auxiliary provider option
- Vision auto-fallback now includes Codex (OpenRouter → Nous → Codex)
since gpt-5.3-codex supports multimodal input
- Updated docs with Codex OAuth examples
Tested with real Codex OAuth token + ~/.hermes/image2.png — confirmed
working end-to-end through the full adapter pipeline.
Tests: 2459 passed.
The Codex model normalization was rejecting any model without 'codex'
in its name, forcing a fallback to gpt-5.3-codex. This blocked models
like gpt-5.4 that the Codex API actually supports.
The fix simplifies _normalize_model_for_provider() to two operations:
1. Strip provider prefixes (API needs bare slugs)
2. Replace the *untouched default* model with a Codex-compatible one
If the user explicitly chose a model — any model — we trust them and
let the API be the judge. No allowlists, no slug checks.
Also removes the 'codex not in slug' filter from _read_cache_models()
so the local cache preserves all API-available models.
Inspired by OpenClaw's approach which explicitly lists non-codex models
(gpt-5.4, gpt-5.2) as valid Codex models.
Users can now set provider: "openai" for auxiliary tasks (vision, web
extract, compression) to use OpenAI's API directly with their
OPENAI_API_KEY. This hits api.openai.com/v1 with gpt-4o-mini as the
default model — supports vision since GPT-4o handles image input.
Provider options are now: auto, openrouter, nous, openai, main.
Changes:
- agent/auxiliary_client.py: added _try_openai(), "openai" case in
_resolve_forced_provider(), updated auxiliary_max_tokens_param()
to use max_completion_tokens for OpenAI
- Updated docs: cli-config.yaml.example, AGENTS.md, and user-facing
configuration.md with Common Setups section showing OpenAI,
OpenRouter, and local model examples
- 3 new tests for OpenAI provider resolution
Tests: 2459 passed (was 2429).
Improvements on top of PR #606 (auxiliary model configuration):
1. Gateway bridge: Added auxiliary.* and compression.summary_provider
config bridging to gateway/run.py so config.yaml settings work from
messaging platforms (not just CLI). Matches the pattern in cli.py.
2. Vision auto-fallback safety: In auto mode, vision now only tries
OpenRouter + Nous Portal (known multimodal-capable providers).
Custom endpoints, Codex, and API-key providers are skipped to avoid
confusing errors from providers that don't support vision input.
Explicit provider override (AUXILIARY_VISION_PROVIDER=main) still
allows using any provider.
3. Comprehensive tests (46 new):
- _get_auxiliary_provider env var resolution (8 tests)
- _resolve_forced_provider with all provider types (8 tests)
- Per-task provider routing integration (4 tests)
- Vision auto-fallback safety (7 tests)
- Config bridging logic (11 tests)
- Gateway/CLI bridge parity (2 tests)
- Vision model override via env var (2 tests)
- DEFAULT_CONFIG shape validation (4 tests)
4. Docs: Added auxiliary_client.py to AGENTS.md project structure.
Updated module docstring with separate text/vision resolution chains.
Tests: 2429 passed (was 2383).
- Added support for auxiliary model overrides in the configuration, allowing users to specify providers and models for vision and web extraction tasks.
- Updated the CLI configuration example to include new auxiliary model settings.
- Enhanced the environment variable mapping in the CLI to accommodate auxiliary model configurations.
- Improved the resolution logic for auxiliary clients to support task-specific provider overrides.
- Updated relevant documentation and comments for clarity on the new features and their usage.
