Smart model routing (auto-routing short/simple turns to a cheap model
across providers) was opt-in and disabled by default. This removes the
feature wholesale: the routing module, its config keys, docs, tests, and
the orchestration scaffolding it required in cli.py / gateway/run.py /
cron/scheduler.py.
The /fast (Priority Processing / Anthropic fast mode) feature kept its
hooks into _resolve_turn_agent_config — those still build a route dict
and attach request_overrides when the model supports it; the route now
just always uses the session's primary model/provider rather than
running prompts through choose_cheap_model_route() first.
Also removed:
- DEFAULT_CONFIG['smart_model_routing'] block and matching commented-out
example sections in hermes_cli/config.py and cli-config.yaml.example
- _load_smart_model_routing() / self._smart_model_routing on GatewayRunner
- self._smart_model_routing / self._active_agent_route_signature on
HermesCLI (signature kept; just no longer initialised through the
smart-routing pipeline)
- route_label parameter on HermesCLI._init_agent (only set by smart
routing; never read elsewhere)
- 'Smart Model Routing' section in website/docs/integrations/providers.md
- tip in hermes_cli/tips.py
- entries in hermes_cli/dump.py + hermes_cli/web_server.py
- row in skills/autonomous-ai-agents/hermes-agent/SKILL.md
Tests:
- Deleted tests/agent/test_smart_model_routing.py
- Rewrote tests/agent/test_credential_pool_routing.py to target the
simplified _resolve_turn_agent_config directly (preserves credential
pool propagation + 429 rotation coverage)
- Dropped 'cheap model' test from test_cli_provider_resolution.py
- Dropped resolve_turn_route patches from cli + gateway test_fast_command
— they now exercise the real method end-to-end
- Removed _smart_model_routing stub assignments from gateway/cron test
helpers
Targeted suites: 74/74 in the directly affected test files;
tests/agent + tests/cron + tests/cli pass except 5 failures that
already exist on main (cron silent-delivery + alias quick-command).
- only use the native adapter for the canonical Gemini native endpoint
- keep custom and /openai base URLs on the OpenAI-compatible path
- preserve Hermes keepalive transport injection for native Gemini clients
- stabilize streaming tool-call replay across repeated SSE events
- add follow-up tests for base_url precedence, async streaming, and duplicate tool-call chunks
- add a native Gemini adapter over generateContent/streamGenerateContent
- switch the built-in gemini provider off the OpenAI-compatible endpoint
- preserve thought signatures and native functionResponse replay
- route auxiliary Gemini clients through the same adapter
- add focused unit coverage plus native-provider integration checks
The cherry-picked salvage (admin28980's commit) added codex headers only on the
primary chat client path, with two inaccuracies:
- originator was 'hermes-agent' — Cloudflare whitelists codex_cli_rs,
codex_vscode, codex_sdk_ts, and Codex* prefixes. 'hermes-agent' isn't on
the list, so the header had no mitigating effect on the 403 (the
account-id header alone may have been carrying the fix).
- account-id header was 'ChatGPT-Account-Id' — upstream codex-rs auth.rs
uses canonical 'ChatGPT-Account-ID' (PascalCase, trailing -ID).
Also, the auxiliary client (_try_codex + resolve_provider_client raw_codex
branch) constructs OpenAI clients against the same chatgpt.com endpoint with
no default headers at all — so compression, title generation, vision, session
search, and web_extract all still 403 from VPS IPs.
Consolidate the header set into _codex_cloudflare_headers() in
agent/auxiliary_client.py (natural home next to _read_codex_access_token and
the existing JWT decode logic) and call it from all four insertion points:
- run_agent.py: AIAgent.__init__ (initial construction)
- run_agent.py: _apply_client_headers_for_base_url (credential rotation)
- agent/auxiliary_client.py: _try_codex (aux client)
- agent/auxiliary_client.py: resolve_provider_client raw_codex branch
Net: -36/+55 lines, -25 lines of duplicated inline JWT decode replaced by a
single helper. User-Agent switched to 'codex_cli_rs/0.0.0 (Hermes Agent)' to
match the codex-rs shape while keeping product attribution.
Tests in tests/agent/test_codex_cloudflare_headers.py cover:
- originator value, User-Agent shape, canonical header casing
- account-ID extraction from a real JWT fixture
- graceful handling of malformed / non-string / claim-missing tokens
- wiring at all four insertion points (primary init, rotation, both aux paths)
- non-chatgpt base URLs (openrouter) do NOT get codex headers
- switching away from chatgpt.com drops the headers
Several correctness and cost-safety fixes to the Honcho dialectic path
after a multi-turn investigation surfaced a chain of silent failures:
- dialecticCadence default flipped 3 → 1. PR #10619 changed this from 1 to
3 for cost, but existing installs with no explicit config silently went
from per-turn dialectic to every-3-turns on upgrade. Restores pre-#10619
behavior; 3+ remains available for cost-conscious setups. Docs + wizard
+ status output updated to match.
- Session-start prewarm now consumed. Previously fired a .chat() on init
whose result landed in HonchoSessionManager._dialectic_cache and was
never read — pop_dialectic_result had zero call sites. Turn 1 paid for
a duplicate synchronous dialectic. Prewarm now writes directly to the
plugin's _prefetch_result via _prefetch_lock so turn 1 consumes it with
no extra call.
- Prewarm is now dialecticDepth-aware. A single-pass prewarm can return
weak output on cold peers; the multi-pass audit/reconcile cycle is
exactly the case dialecticDepth was built for. Prewarm now runs the
full configured depth in the background.
- Silent dialectic failure no longer burns the cadence window.
_last_dialectic_turn now advances only when the result is non-empty.
Empty result → next eligible turn retries immediately instead of
waiting the full cadence gap.
- Thread pile-up guard. queue_prefetch skips when a prior dialectic
thread is still in-flight, preventing stacked races on _prefetch_result.
- First-turn sync timeout is recoverable. Previously on timeout the
background thread's result was stored in a dead local list. Now the
thread writes into _prefetch_result under lock so the next turn
picks it up.
- Cadence gate applies uniformly. At cadence=1 the old "cadence > 1"
guard let first-turn sync + same-turn queue_prefetch both fire.
Gate now always applies.
- Restored query-length reasoning-level scaling, dropped in 9a0ab34c.
Scales dialecticReasoningLevel up on longer queries (+1 at ≥120 chars,
+2 at ≥400), clamped at reasoningLevelCap. Two new config keys:
`reasoningHeuristic` (bool, default true) and `reasoningLevelCap`
(string, default "high"; previously parsed but never enforced).
Respects dialecticDepthLevels and proportional lighter-early passes.
- Restored short-prompt skip, dropped in ef7f3156. One-word
acknowledgements ("ok", "y", "thanks") and slash commands bypass
both injection and dialectic fire.
- Purged dead code in session.py: prefetch_dialectic, _dialectic_cache,
set_dialectic_result, pop_dialectic_result — all unused after prewarm
refactor.
Tests: 542 passed across honcho_plugin/, agent/test_memory_provider.py,
and run_agent/test_run_agent.py. New coverage:
- TestTrivialPromptHeuristic (classifier + prefetch/queue skip)
- TestDialecticCadenceAdvancesOnSuccess (empty-result retry, pile-up guard)
- TestSessionStartDialecticPrewarm (prewarm consumed, sync fallback)
- TestReasoningHeuristic (length bumps, cap clamp, interaction with depth)
- TestDialecticLifecycleSmoke (end-to-end 8-turn session walk)
Pass 3 of `_prune_old_tool_results` previously shrunk long `function.arguments`
blobs by slicing the raw JSON string at byte 200 and appending the literal
text `...[truncated]`. That routinely produced payloads like::
{"path": "/foo.md", "content": "# Long markdown
...[truncated]
— an unterminated string with no closing brace. Strict providers (observed
on MiniMax) reject this as `invalid function arguments json string` with a
non-retryable 400. Because the broken call survives in the session history,
every subsequent turn re-sends the same malformed payload and gets the same
400, locking the session into a re-send loop until the call falls out of
the window.
Fix: parse the arguments first, shrink long string leaves inside the parsed
structure, and re-serialise. Non-string values (paths, ints, booleans, lists)
pass through intact. Arguments that are not valid JSON to begin with (rare,
some backends use non-JSON tool args) are returned unchanged rather than
replaced with something neither we nor the provider can parse.
Observed in the wild: a `write_file` with ~800 chars of markdown `content`
triggered this on a real session against MiniMax-M2.7; every turn after
compression got rejected until the session was manually reset.
Tests:
- 7 direct tests of `_truncate_tool_call_args_json` covering valid-JSON
output, non-JSON pass-through, nested structures, non-string leaves,
scalar JSON, and Unicode preservation
- 1 end-to-end test through `_prune_old_tool_results` Pass 3 that
reproduces the exact failure payload shape from the incident
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* fix(kimi): force fixed temperature on kimi-k2.* models (k2.5, thinking, turbo)
The prior override only matched the literal model name "kimi-for-coding",
but Moonshot's coding endpoint is hit with real model IDs such as
`kimi-k2.5`, `kimi-k2-turbo-preview`, `kimi-k2-thinking`, etc. Those
requests bypassed the override and kept the caller's temperature, so
Moonshot returns HTTP 400 "invalid temperature: only 0.6 is allowed for
this model" (or 1.0 for thinking variants).
Match the whole kimi-k2.* family:
* kimi-k2-thinking / kimi-k2-thinking-turbo -> 1.0 (thinking mode)
* all other kimi-k2.* -> 0.6 (non-thinking / instant mode)
Also accept an optional vendor prefix (e.g. `moonshotai/kimi-k2.5`) so
aggregator routings are covered.
* refactor(kimi): whitelist-match kimi coding models instead of prefix
Addresses review feedback on PR #12144.
- Replace `startswith("kimi-k2")` with explicit frozensets sourced from
Moonshot's kimi-for-coding model list. The prefix match would have also
clamped `kimi-k2-instruct` / `kimi-k2-instruct-0905`, which are the
separate non-coding K2 family with variable temperature (recommended 0.6
but not enforced — see huggingface.co/moonshotai/Kimi-K2-Instruct).
- Confirmed via platform.kimi.ai docs that all five coding models
(k2.5, k2-turbo-preview, k2-0905-preview, k2-thinking, k2-thinking-turbo)
share the fixed-temperature lock, so the preview-model mapping is no
longer an assumption.
- Drop the fragile `"thinking" in bare` substring test for a set lookup.
- Log a debug line on each override so operators can see when Hermes
silently rewrites temperature.
- Update class docstring. Extend the negative test to parametrize over
kimi-k2-instruct, Kimi-K2-Instruct-0905, and a hypothetical future
kimi-k2-experimental name — all must keep the caller's temperature.
Seven test files were asserting against older function signatures and
behaviors. CI has been red on main because of accumulated test debt
from other PRs; this catches the tests up.
- tests/agent/test_subagent_progress.py: _build_child_progress_callback
now takes (task_index, goal, parent_agent, task_count=1); update all
call sites and rewrite tests that assumed the old 'batch-only' relay
semantics (now relays per-tool AND flushes a summary at BATCH_SIZE).
Renamed test_thinking_not_relayed_to_gateway → test_thinking_relayed_to_gateway
since thinking IS now relayed as subagent.thinking.
- tests/tools/test_delegate.py: _build_child_agent now requires
task_count; add task_count=1 to all 8 call sites.
- tests/cli/test_reasoning_command.py: AIAgent gained _stream_callback;
stub it on the two test agent helpers that use spec=AIAgent / __new__.
- tests/hermes_cli/test_cmd_update.py: cmd_update now runs npm install
in repo root + ui-tui/ + web/ and 'npm run build' in web/; assert
all four subprocess calls in the expected order.
- tests/hermes_cli/test_model_validation.py: dissimilar unknown models
now return accepted=False (previously True with warning); update
both affected tests.
- tests/tools/test_registry.py: include feishu_doc_tool and
feishu_drive_tool in the expected builtin tool set.
- tests/gateway/test_voice_command.py: missing-voice-deps message now
suggests 'pip install PyNaCl' not 'hermes-agent[messaging]'.
411/411 pass locally across these 7 files.
Before: aggregator users (OpenRouter / Nous Portal) running 'auto'
routing for auxiliary tasks — compression, vision, web extraction,
session search, etc. — got routed to a cheap provider-side default
model (Gemini Flash). Non-aggregator users already got their main
model. Behavior was inconsistent and surprising — users picked
Claude / GPT / their preferred model, but side tasks ran on
Gemini Flash.
After: 'auto' means "use my main chat model" for every user,
regardless of provider type. Only when the main provider has no
working client does the fallback chain run (OpenRouter → Nous →
custom → Codex → API-key providers). Explicit per-task overrides
in config.yaml (auxiliary.<task>.provider / .model) still win —
they are a hard constraint, not subject to the auto policy.
Vision auto-detection follows the same policy: try main provider +
main model first (with _PROVIDER_VISION_MODELS overrides preserved
for providers like xiaomi and zai that ship a dedicated multimodal
model distinct from their chat model). Aggregator strict vision
backends are fallbacks, not the primary path.
Changes:
- agent/auxiliary_client.py: _resolve_auto() drops the
`_AGGREGATOR_PROVIDERS` guard. resolve_vision_provider_client()
auto branch unifies aggregator and exotic-provider paths —
everyone goes through resolve_provider_client() with main_model.
Dead _AGGREGATOR_PROVIDERS constant removed (was only used by
the guard we just removed).
- hermes_cli/main.py: aux config menu copy updated to reflect
the new semantics ("'auto' means 'use my main model'").
- tests/agent/test_auxiliary_main_first.py: 12 regression tests
covering OpenRouter/Nous/DeepSeek main paths, runtime-override
wins, explicit-config wins, vision override preservation for
exotic providers, and fallback-chain activation when the main
provider has no working client.
Co-authored-by: teknium1 <teknium@nousresearch.com>
Google-side 429 Code Assist errors now flow through Hermes' normal rate-limit
path (status_code on the exception, Retry-After preserved via error.response)
instead of being opaque RuntimeErrors. User sees a one-line capacity message
instead of a 500-char JSON dump.
Changes
- CodeAssistError grows status_code / response / retry_after / details attrs.
_extract_status_code in error_classifier picks up status_code and classifies
429 as FailoverReason.rate_limit, so fallback_providers triggers the same
way it does for SDK errors. run_agent.py line ~10428 already walks
error.response.headers for Retry-After — preserving the response means that
path just works.
- _gemini_http_error parses the Google error envelope (error.status +
error.details[].reason from google.rpc.ErrorInfo, retryDelay from
google.rpc.RetryInfo). MODEL_CAPACITY_EXHAUSTED / RESOURCE_EXHAUSTED / 404
model-not-found each produce a human-readable message; unknown shapes fall
back to the previous raw-body format.
- Drop gemma-4-26b-it from hermes_cli/models.py, hermes_cli/setup.py, and
agent/model_metadata.py — Google returned 404 for it today in local repro.
Kept gemma-4-31b-it (capacity-constrained but not retired).
Validation
| | Before | After |
|---------------------------|--------------------------------|-------------------------------------------|
| Error message | 'Code Assist returned HTTP 429: {500 chars JSON}' | 'Gemini capacity exhausted for gemini-2.5-pro (Google-side throttle...)' |
| status_code on error | None (opaque RuntimeError) | 429 |
| Classifier reason | unknown (string-match fallback) | FailoverReason.rate_limit |
| Retry-After honored | ignored | extracted from RetryInfo or header |
| gemma-4-26b-it picker | advertised (404s on Google) | removed |
Unit + E2E tests cover non-streaming 429, streaming 429, 404 model-not-found,
Retry-After header fallback, malformed body, and classifier integration.
Targeted suites: tests/agent/test_gemini_cloudcode.py (81 tests), full
tests/hermes_cli (2203 tests) green.
Co-authored-by: teknium1 <teknium@nousresearch.com>
First pass of test-suite reduction to address flaky CI and bloat.
Removed tests that fall into these change-detector patterns:
1. Source-grep tests (tests/gateway/test_feishu.py, test_email.py): tests
that call inspect.getsource() on production modules and grep for string
literals. Break on any refactor/rename even when behavior is correct.
2. Platform enum tautologies (every gateway/test_X.py): assertions like
`Platform.X.value == 'x'` duplicated across ~9 adapter test files.
3. Toolset/PLATFORM_HINTS/setup-wizard registry-presence checks: tests that
only verify a key exists in a dict. Data-layout tests, not behavior.
4. Argparse wiring tests (test_argparse_flag_propagation, test_subparser_routing
_fallback): tests that do parser.parse_args([...]) then assert args.field.
Tests Python's argparse, not our code.
5. Pure dispatch tests (test_plugins_cmd.TestPluginsCommandDispatch): patch
cmd_X, call plugins_command with matching action, assert mock called.
Tests the if/elif chain, not behavior.
6. Kwarg-to-mock verification (test_auxiliary_client ~45 tests,
test_web_tools_config, test_gemini_cloudcode, test_retaindb_plugin): tests
that mock the external API client, call our function, and assert exact
kwargs. Break on refactor even when behavior is preserved.
7. Schedule-internal "function-was-called" tests (acp/test_server scheduling
tests): tests that patch own helper method, then assert it was called.
Kept behavioral tests throughout: error paths (pytest.raises), security
tests (path traversal, SSRF, redaction), message alternation invariants,
provider API format conversion, streaming logic, memory contract, real
config load/merge tests.
Net reduction: 169 tests removed. 38 empty classes cleaned up.
Collected before: 12,522 tests
Collected after: 12,353 tests
The cache-read, cache-write, and total estimated-cost values shown in
/insights (and the per-model Cost column) were unreliable. Hide them from
both terminal and gateway renderings.
The underlying data pipeline is untouched — sessions still store
cache_read_tokens, cache_write_tokens, and estimated_cost_usd; the web
server, /usage command, and status bar are unaffected. Only the
InsightsEngine display layer is trimmed.
Changes:
- format_terminal: drop 'Cache read / Cache write' line, drop 'Est. cost'
from the Total tokens row, drop per-model 'Cost' column, drop the
'* Cost N/A for custom/self-hosted' footnote.
- format_gateway: drop cache breakdown from Tokens line, drop 'Est. cost'
line, drop per-model cost suffix.
- Tests updated to assert these strings are now absent.
Replace the HERMES_ENABLE_NOUS_MANAGED_TOOLS env-var feature flag with
subscription-based detection. The Tool Gateway is now available to any
paid Nous subscriber without needing a hidden env var.
Core changes:
- managed_nous_tools_enabled() checks get_nous_auth_status() +
check_nous_free_tier() instead of an env var
- New use_gateway config flag per tool section (web, tts, browser,
image_gen) records explicit user opt-in and overrides direct API
keys at runtime
- New prefers_gateway(section) shared helper in tool_backend_helpers.py
used by all 4 tool runtimes (web, tts, image gen, browser)
UX flow:
- hermes model: after Nous login/model selection, shows a curses
prompt listing all gateway-eligible tools with current status.
User chooses to enable all, enable only unconfigured tools, or skip.
Defaults to Enable for new users, Skip when direct keys exist.
- hermes tools: provider selection now manages use_gateway flag —
selecting Nous Subscription sets it, selecting any other provider
clears it
- hermes status: renamed section to Nous Tool Gateway, added
free-tier upgrade nudge for logged-in free users
- curses_radiolist: new description parameter for multi-line context
that survives the screen clear
Runtime behavior:
- Each tool runtime (web_tools, tts_tool, image_generation_tool,
browser_use) checks prefers_gateway() before falling back to
direct env-var credentials
- get_nous_subscription_features() respects use_gateway flags,
suppressing direct credential detection when the user opted in
Removed:
- HERMES_ENABLE_NOUS_MANAGED_TOOLS env var and all references
- apply_nous_provider_defaults() silent TTS auto-set
- get_nous_subscription_explainer_lines() static text
- Override env var warnings (use_gateway handles this properly now)
Regression from #11161 (Claude Opus 4.7 migration, commit 0517ac3e).
The Opus 4.7 migration changed `ADAPTIVE_EFFORT_MAP["xhigh"]` from "max"
(the pre-migration alias) to "xhigh" to preserve the new 4.7 effort level
as distinct from max. This is correct for 4.7, but Opus/Sonnet 4.6 only
expose 4 levels (low/medium/high/max) — sending "xhigh" there now 400s:
BadRequestError [HTTP 400]: This model does not support effort
level 'xhigh'. Supported levels: high, low, max, medium.
Users who set reasoning_effort=xhigh as their default (xhigh is the
recommended default for coding/agentic on 4.7 per the Anthropic migration
guide) now 400 every request the moment they switch back to a 4.6 model
via `/model` or config. Verified live against the Anthropic API on
`anthropic==0.94.0`.
Fix: make the mapping model-aware. Add `_supports_xhigh_effort()`
predicate (matches 4-7/4.7 substrings, mirroring the existing
`_supports_adaptive_thinking` / `_forbids_sampling_params` pattern).
On pre-4.7 adaptive models, downgrade xhigh→max (the strongest effort
those models accept, restoring pre-migration behavior). On 4.7+, keep
xhigh as a distinct level.
Per Anthropic's migration guide, xhigh is 4.7-only:
https://platform.claude.com/docs/en/about-claude/models/migration-guide
> Opus 4.7 effort levels: max, xhigh (new), high, medium, low.
> Opus 4.6 effort levels: max, high, medium, low.
SDK typing confirms: `anthropic.types.OutputConfigParam.effort: Literal[
"low", "medium", "high", "max"]` (v0.94.0 not yet updated for xhigh).
## Test plan
Verified live on macOS 15.5 / anthropic==0.94.0:
claude-opus-4-6 + effort=xhigh → output_config.effort=max → 200 OK
claude-opus-4-7 + effort=xhigh → output_config.effort=xhigh → 200 OK
claude-opus-4-6 + effort=max → output_config.effort=max → 200 OK
claude-opus-4-7 + effort=max → output_config.effort=max → 200 OK
`tests/agent/test_anthropic_adapter.py` — 120 pass (replaced 1 bugged
test that asserted the broken behavior, added 1 for 4.7 preservation).
Full adapter suite: 120 passed in 1.05s.
Broader suite (agent + run_agent + cli/gateway reasoning): 2140 passed
(2 pre-existing failures on clean upstream/main, unrelated).
## Platforms
Tested on macOS 15.5. No platform-specific code paths touched.
Claude Opus 4.7 introduced several breaking API changes that the current
codebase partially handled but not completely. This patch finishes the
migration per the official migration guide at
https://platform.claude.com/docs/en/about-claude/models/migration-guideFixesNousResearch/hermes-agent#11137
Breaking-change coverage:
1. Adaptive thinking + output_config.effort — 4.7 is now recognized by
_supports_adaptive_thinking() (extends previous 4.6-only gate).
2. Sampling parameter stripping — 4.7 returns 400 for any non-default
temperature / top_p / top_k. build_anthropic_kwargs drops them as a
safety net; the OpenAI-protocol auxiliary path (_build_call_kwargs)
and AnthropicCompletionsAdapter.create() both early-exit before
setting temperature for 4.7+ models. This keeps flush_memories and
structured-JSON aux paths that hardcode temperature from 400ing
when the aux model is flipped to 4.7.
3. thinking.display = "summarized" — 4.7 defaults display to "omitted",
which silently hides reasoning text from Hermes's CLI activity feed
during long tool runs. Restoring "summarized" preserves 4.6 UX.
4. Effort level mapping — xhigh now maps to xhigh (was xhigh→max, which
silently over-efforted every coding/agentic request). max is now a
distinct ceiling per Anthropic's 5-level effort model.
5. New stop_reason values — refusal and model_context_window_exceeded
were silently collapsed to "stop" (end_turn) by the adapter's
stop_reason_map. Now mapped to "content_filter" and "length"
respectively, matching upstream finish-reason handling already in
bedrock_adapter.
6. Model catalogs — claude-opus-4-7 added to the Anthropic provider
list, anthropic/claude-opus-4.7 added at top of OpenRouter fallback
catalog (recommended), claude-opus-4-7 added to model_metadata
DEFAULT_CONTEXT_LENGTHS (1M, matching 4.6 per migration guide).
7. Prefill docstrings — run_agent.AIAgent and BatchRunner now document
that Anthropic Sonnet/Opus 4.6+ reject a trailing assistant-role
prefill (400).
8. Tests — 4 new tests in test_anthropic_adapter covering display
default, xhigh preservation, max on 4.7, refusal / context-overflow
stop_reason mapping, plus the sampling-param predicate. test_model_metadata
accepts 4.7 at 1M context.
Tested on macOS 15.5 (darwin). 119 tests pass in
tests/agent/test_anthropic_adapter.py, 1320 pass in tests/agent/.
resolve_vision_provider_client() was receiving the raw call_llm
parameters instead of the resolved provider/model/key/url from
_resolve_task_provider_model(). This caused config overrides
(auxiliary.vision.provider, etc.) to be silently discarded.
Cherry-picked from #10901 by @lrawnsley.
Salvaged from PR #10643 by kshitijk4poor, updated for current main.
Root causes fixed:
1. Telegram xdist mock pollution — new tests/gateway/conftest.py with shared
mock that runs at collection time (prevents ChatType=None caching)
2. VIRTUAL_ENV env var leak — monkeypatch.delenv in _detect_venv_dir tests
3. Copilot base_url missing — add fallback in _resolve_runtime_from_pool_entry
4. Stale vision model assertion — zai now uses glm-5v-turbo
5. Reasoning item id intentionally stripped — assert 'id' not in (store=False)
6. Context length warning unreachable — pass base_url to AIAgent in test
7. Kimi provider label updated — 'Kimi / Kimi Coding Plan' matches models.py
8. Google Workspace calendar tests — rewritten for current production code,
properly mock subprocess on api_module, removed stale +agenda assertions
9. Credential pool auto-seeding — mock _select_pool_entry / _resolve_auto /
_import_codex_cli_tokens to prevent real credentials from leaking into tests
When Nous returns a 429, the retry amplification chain burns up to 9
API requests per conversation turn (3 SDK retries × 3 Hermes retries),
each counting against RPH and deepening the rate limit. With multiple
concurrent sessions (cron + gateway + auxiliary), this creates a spiral
where retries keep the limit tapped indefinitely.
New module: agent/nous_rate_guard.py
- Shared file-based rate limit state (~/.hermes/rate_limits/nous.json)
- Parses reset time from x-ratelimit-reset-requests-1h, x-ratelimit-
reset-requests, retry-after headers, or error context
- Falls back to 5-minute default cooldown if no header data
- Atomic writes (tempfile + rename) for cross-process safety
- Auto-cleanup of expired state files
run_agent.py changes:
- Top-of-retry-loop guard: when another session already recorded Nous
as rate-limited, skip the API call entirely. Try fallback provider
first, then return a clear message with the reset time.
- On 429 from Nous: record rate limit state and skip further retries
(sets retry_count = max_retries to trigger fallback path)
- On success from Nous: clear the rate limit state so other sessions
know they can resume
auxiliary_client.py changes:
- _try_nous() checks rate guard before attempting Nous in the auxiliary
fallback chain. When rate-limited, returns (None, None) so the chain
skips to the next provider instead of piling more requests onto Nous.
This eliminates three sources of amplification:
1. Hermes-level retries (saves 6 of 9 calls per turn)
2. Cross-session retries (cron + gateway all skip Nous)
3. Auxiliary fallback to Nous (compression/session_search skip too)
Includes 24 tests covering the rate guard module, header parsing,
state lifecycle, and auxiliary client integration.
When proxy env vars (HTTP_PROXY, HTTPS_PROXY, ALL_PROXY) contain
malformed URLs — e.g. 'http://127.0.0.1:6153export' from a broken
shell config — the OpenAI/httpx client throws a cryptic 'Invalid port'
error that doesn't identify the offending variable.
Add _validate_proxy_env_urls() and _validate_base_url() in
auxiliary_client.py, called from resolve_provider_client() and
_create_openai_client() to fail fast with a clear, actionable error
message naming the broken env var or URL.
Closes#6360
Co-authored-by: MestreY0d4-Uninter <MestreY0d4-Uninter@users.noreply.github.com>
Found via trace data audit: JWT tokens (eyJ...) and Discord snowflake
mentions (<@ID>) were passing through unredacted.
JWT pattern: matches 1/2/3-part tokens starting with eyJ (base64 for '{').
Zero false-positive risk — no normal text matches eyJ + 10+ base64url chars.
Discord pattern: matches <@digits> and <@!digits> with 17-20 digit snowflake
IDs. Syntactically unique to Discord's mention format.
Both patterns follow the same structural-uniqueness standard as existing
prefix patterns (sk-, ghp_, AKIA, etc.).
Memory provider discovery (discover_memory_providers, load_memory_provider)
only scanned the bundled plugins/memory/ directory. User-installed providers
at $HERMES_HOME/plugins/<name>/ were invisible, forcing users to symlink
into the repo source tree — which broke on hermes update and created a
dual-registration path causing duplicate tool names (400 errors on strict
providers like Xiaomi MiMo).
Changes:
- Add _get_user_plugins_dir(), _is_memory_provider_dir(), _iter_provider_dirs(),
and find_provider_dir() helpers to plugins/memory/__init__.py
- discover_memory_providers() now scans both bundled and user dirs
- load_memory_provider() uses find_provider_dir() (bundled-first)
- discover_plugin_cli_commands() uses find_provider_dir()
- _install_dependencies() in memory_setup.py uses find_provider_dir()
- User plugins use _hermes_user_memory namespace to avoid sys.modules collisions
- Non-memory user plugins filtered via source text heuristic
- Bundled providers always take precedence on name collisions
Fixes#4956, #9099. Supersedes #4987, #9123, #9130, #9132, #9982.
Memory provider plugins (e.g. Mnemosyne) can register tools via two paths:
1. Plugin system (ctx.register_tool) → tool registry → get_tool_definitions()
2. Memory manager → get_all_tool_schemas() → direct append in AIAgent.__init__
Path 2 blindly appended without checking if path 1 already added the same
tool names. This created duplicate function names in the tools array sent
to the API. Most providers silently handle duplicates, but Xiaomi MiMo
(via Nous Portal) strictly rejects them with a 400 Bad Request.
Fix: build a set of existing tool names before memory manager injection
and skip any tool whose name is already present.
Confirmed via live testing against Nous Portal:
- Unique tool names → 200 OK
- Duplicate tool names → 400 'Provider returned error'
The on_memory_write bridge that notifies external memory providers
(ClawMem, retaindb, supermemory, etc.) of built-in memory writes was
only present in the concurrent tool execution path (_invoke_tool).
The sequential path (_execute_tool_calls_sequential) — which handles
all single tool calls, the common case — was missing it entirely.
This meant external memory providers silently missed every single-call
memory write, which is the vast majority of memory operations.
Fix: add the identical bridge block to the sequential path, right
after the memory_tool call returns.
Closes#10174
OV transparently handles message history across /new and /compress: old
messages stay in the same session and extraction is idempotent, so there's
no need to rebind providers to a new session_id. The only thing the
session boundary actually needs is to trigger extraction.
- MemoryProvider / MemoryManager: remove on_session_reset hook
- OpenViking: remove on_session_reset override (nothing to do)
- AIAgent: replace rotate_memory_session with commit_memory_session
(just calls on_session_end, no rebind)
- cli.py / run_agent.py: single commit_memory_session call at the
session boundary before session_id rotates
- tests: replace on_session_reset coverage with routing tests for
MemoryManager.on_session_end
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Replace hasattr-forked OpenViking-specific paths with a proper base-class
hook. Collapse the two agent wrappers into a single rotate_memory_session
so callers don't orchestrate commit + rebind themselves.
- MemoryProvider: add on_session_reset(new_session_id) as a default no-op
- MemoryManager: on_session_reset fans out unconditionally (no hasattr,
no builtin skip — base no-op covers it)
- OpenViking: rename reset_session -> on_session_reset; drop the explicit
POST /api/v1/sessions (OV auto-creates on first message) and the two
debug raise_for_status wrappers
- AIAgent: collapse commit_memory_session + reinitialize_memory_session
into rotate_memory_session(new_sid, messages)
- cli.py / run_agent.py: replace hasattr blocks and the split calls with
a single unconditional rotate_memory_session call; compression path
now passes the real messages list instead of []
- tests: align with on_session_reset, assert reset does NOT POST /sessions
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The OpenViking memory provider extracts memories when its session is
committed (POST /api/v1/sessions/{id}/commit). Before this fix, the
CLI had two code paths that changed the active session_id without ever
committing the outgoing OpenViking session:
1. /new (new_session() in cli.py) — called flush_memories() to write
MEMORY.md, then immediately discarded the old session_id. The
accumulated OpenViking session was never committed, so all context
from that session was lost before extraction could run.
2. /compress and auto-compress (_compress_context() in run_agent.py) —
split the SQLite session (new session_id) but left the OpenViking
provider pointing at the old session_id with no commit, meaning all
messages synced to OpenViking were silently orphaned.
The gateway already handles session commit on /new and /reset via
shutdown_memory_provider() on the cached agent; the CLI path did not.
Fix: introduce a lightweight session-transition lifecycle alongside
the existing full shutdown path:
- OpenVikingMemoryProvider.reset_session(new_session_id): waits for
in-flight background threads, resets per-session counters, and
creates the new OV session via POST /api/v1/sessions — without
tearing down the HTTP client (avoids connection overhead on /new).
- MemoryManager.restart_session(new_session_id): calls reset_session()
on providers that implement it; falls back to initialize() for
providers that do not. Skips the builtin provider (no per-session
state).
- AIAgent.commit_memory_session(messages): wraps
memory_manager.on_session_end() without shutdown — commits OV session
for extraction but leaves the provider alive for the next session.
- AIAgent.reinitialize_memory_session(new_session_id): wraps
memory_manager.restart_session() — transitions all external providers
to the new session after session_id has been assigned.
Call sites:
- cli.py new_session(): commit BEFORE session_id changes, reinitialize
AFTER — ensuring OV extraction runs on the correct session and the
new session is immediately ready for the next turn.
- run_agent._compress_context(): same pattern, inside the
if self._session_db: block where the session_id split happens.
/compress and auto-compress are functionally identical at this layer:
both call _compress_context(), so both are fixed by the same change.
Tests added to tests/agent/test_memory_provider.py:
- TestMemoryManagerRestartSession: reset_session() routing, builtin
skip, initialize() fallback, failure tolerance, empty-manager noop.
- TestOpenVikingResetSession: session_id update, per-session state
clear, POST /api/v1/sessions call, API failure tolerance, no-client
noop.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Seed qwen-oauth credentials from resolve_qwen_runtime_credentials() in
_seed_from_singletons(). Users who authenticate via 'qwen auth qwen-oauth'
store tokens in ~/.qwen/oauth_creds.json which the runtime resolver reads
but the credential pool couldn't detect — same gap pattern as copilot.
Uses refresh_if_expiring=False to avoid network calls during discovery.
Seed copilot credentials from resolve_copilot_token() in the credential
pool's _seed_from_singletons(), alongside the existing anthropic and
openai-codex seeding logic. This makes copilot appear in the /model
provider picker when the user authenticates solely through gh auth token.
Cherry-picked from PR #9767 by Marvae.
Production fixes:
- Add clear_session_context() to hermes_logging.py (fixes 48 teardown errors)
- Add clear_session() to tools/approval.py (fixes 9 setup errors)
- Add SyncError M_UNKNOWN_TOKEN check to Matrix _sync_loop (bug fix)
- Fall back to inline api_key in named custom providers when key_env
is absent (runtime_provider.py)
Test fixes:
- test_memory_user_id: use builtin+external provider pair, fix honcho
peer_name override test to match production behavior
- test_display_config: remove TestHelpers for non-existent functions
- test_auxiliary_client: fix OAuth tokens to match _is_oauth_token
patterns, replace get_vision_auxiliary_client with resolve_vision_provider_client
- test_cli_interrupt_subagent: add missing _execution_thread_id attr
- test_compress_focus: add model/provider/api_key/base_url/api_mode
to mock compressor
- test_auth_provider_gate: add autouse fixture to clean Anthropic env
vars that leak from CI secrets
- test_opencode_go_in_model_list: accept both 'built-in' and 'hermes'
source (models.dev API unavailable in CI)
- test_email: verify email Platform enum membership instead of source
inspection (build_channel_directory now uses dynamic enum loop)
- test_feishu: add bot_added/bot_deleted handler mocks to _Builder
- test_ws_auth_retry: add AsyncMock for sync_store.get_next_batch,
add _pending_megolm and _joined_rooms to Matrix adapter mocks
- test_restart_drain: monkeypatch-delete INVOCATION_ID (systemd sets
this in CI, changing the restart call signature)
- test_session_hygiene: add user_id to SessionSource
- test_session_env: use relative baseline for contextvar clear check
(pytest-xdist workers share context)
Port two improvements inspired by Kilo-Org/kilocode analysis:
1. Error classifier: add context overflow patterns for vLLM, Ollama,
and llama.cpp/llama-server. These local inference servers return
different error formats than cloud providers (e.g., 'exceeds the
max_model_len', 'context length exceeded', 'slot context'). Without
these patterns, context overflow errors from local servers are
misclassified as format errors, causing infinite retries instead
of triggering compression.
2. MCP initial connection retry: previously, if the very first
connection attempt to an MCP server failed (e.g., transient DNS
blip at startup), the server was permanently marked as failed with
no retry. Post-connect reconnection had 5 retries with exponential
backoff, but initial connection had zero. Now initial connections
retry up to 3 times with backoff before giving up, matching the
resilience of post-connect reconnection.
(Inspired by Kilo Code's MCP server disappearing fix in v1.3.3)
Tests: 6 new error classifier tests, 4 new MCP retry tests, 1
updated existing test. All 276 affected tests pass.
resolve_vision_provider_client() computed resolved_api_mode from config
but never passed it to downstream resolve_provider_client() or
_get_cached_client() calls, causing custom providers with
api_mode: anthropic_messages to crash when used for vision tasks.
Also remove the for_vision special case in _normalize_aux_provider()
that incorrectly discarded named custom provider identifiers.
Fixes#8857
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Remove the backward-compat code paths that read compression provider/model
settings from legacy config keys and env vars, which caused silent failures
when auto-detection resolved to incompatible backends.
What changed:
- Remove compression.summary_model, summary_provider, summary_base_url from
DEFAULT_CONFIG and cli.py defaults
- Remove backward-compat block in _resolve_task_provider_model() that read
from the legacy compression section
- Remove _get_auxiliary_provider() and _get_auxiliary_env_override() helper
functions (AUXILIARY_*/CONTEXT_* env var readers)
- Remove env var fallback chain for per-task overrides
- Update hermes config show to read from auxiliary.compression
- Add config migration (v16→17) that moves non-empty legacy values to
auxiliary.compression and strips the old keys
- Update example config and openclaw migration script
- Remove/update tests for deleted code paths
Compression model/provider is now configured exclusively via:
auxiliary.compression.provider / auxiliary.compression.model
Closes#8923
_query_local_context_length was checking model_info.context_length
(the GGUF training max) before num_ctx (the Modelfile runtime override),
inverse to query_ollama_num_ctx. The two helpers therefore disagreed on
the same model:
hermes-brain:qwen3-14b-ctx32k # Modelfile: num_ctx 32768
underlying qwen3:14b GGUF # qwen3.context_length: 40960
query_ollama_num_ctx correctly returned 32768 (the value Ollama will
actually allocate KV cache for). _query_local_context_length returned
40960, which let ContextCompressor grow conversations past 32768 before
triggering compression — at which point Ollama silently truncated the
prefix, corrupting context.
Swap the order so num_ctx is checked first, matching query_ollama_num_ctx.
Adds a parametrized test that seeds both values and asserts num_ctx wins.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
OpenCode Zen was in _DOT_TO_HYPHEN_PROVIDERS, causing all dotted model
names (minimax-m2.5-free, gpt-5.4, glm-5.1) to be mangled. The fix:
Layer 1 (model_normalize.py): Remove opencode-zen from the blanket
dot-to-hyphen set. Add an explicit block that preserves dots for
non-Claude models while keeping Claude hyphenated (Zen's Claude
endpoint uses anthropic_messages mode which expects hyphens).
Layer 2 (run_agent.py _anthropic_preserve_dots): Add opencode-zen and
zai to the provider allowlist. Broaden URL check from opencode.ai/zen/go
to opencode.ai/zen/ to cover both Go and Zen endpoints. Add bigmodel.cn
for ZAI URL detection.
Also adds glm-5.1 to ZAI model lists in models.py and setup.py.
Closes#7710
Salvaged from contributions by:
- konsisumer (PR #7739, #7719)
- DomGrieco (PR #8708)
- Esashiero (PR #7296)
- sharziki (PR #7497)
- XiaoYingGee (PR #8750)
- APTX4869-maker (PR #8752)
- kagura-agent (PR #7157)
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.
- 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.
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.
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
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).
* 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.
