GLM-5.3 accepts a graded low/medium/high/max reasoning_effort scale
(verified live in #91789: monotonic reasoning-token scaling, no 400s),
but the effort mapper reused GLM-5.2's two-level vocabulary, silently
rewriting low/medium to high. Adds GLM53_EFFORTS/GLM53_OVERRIDES and a
per-model vocabulary pick in the zai plugin; 5.2 keeps its high/max
clamp. Closes#91789. Also covers the gap noted when closing #86947
(credit @santhanakrishnan-d and @terje1965 for the graded-scale finding).
GLM-5.3 is live on api.z.ai (coding plan endpoint) but had no entries in
Hermes, so it silently fell back to the generic 202K GLM context —
triggering premature context compression on a 1M-window model.
- model_metadata: 'glm-5.3': 1_048_576 (same base model as 5.2; 1M
context / 128K max output per docs.z.ai/guides/llm/glm-5.3, verified
2026-08-14)
- auth: add glm-5.3 to coding-plan probe lists (global + CN)
- models: add glm-5.3 to picker/model lists (6 sites)
- zai provider: reasoning_effort mapping covers glm-5.3 (accepted live
by the endpoint, HTTP 200)
The #89503/#70058/#74295/#87279 bug class kept regenerating because every
transport and provider profile hand-rolled its own effort translation map
(9 sites, 4 distinct policies). New agent/reasoning_effort.py is the single
source of truth:
- EFFORT_LADDER: canonical low->high ordering (superset check against
VALID_REASONING_EFFORTS pinned by test)
- clamp_effort(): one policy — supported passes verbatim, otherwise nearest
WEAKER supported level (never escalate, never invert the ladder), floor
when nothing weaker, 'none' never a degradation target, declared
vendor-documented overrides win, bespoke names pass through
- declared wire vocabularies as data: OpenAI-compat, Codex Responses,
xAI (4.6/legacy), Actual relays, Kimi K3/K2, TokenHub, GLM-5.2,
DeepSeek V4, Ollama Cloud, Meta, Solar
Converted sites (all behavior-preserving except noted):
- chat_completions chokepoint, Kimi + TokenHub paths
- codex transport (backend branches now pick a declared set)
- auxiliary_client Responses path
- hermes_cli.models clamp_reasoning_effort_to_supported -> thin wrapper
- plugins: kimi-coding, zai, opencode-zen, deepseek, ollama-cloud,
meta-ai, upstage, custom (copilot already routes via the wrapper)
Behavior fixes the shared policy surfaces:
- ollama-cloud/opencode-go 'minimal' now degrades to 'low' instead of
being dropped (drop left the server default = MORE thinking than asked)
New tests: ladder contract (every configurable level is clamped by every
declared wire set; monotonicity across the full ladder for every set).
Port from Kilo-Org/kilocode#11555: GLM-5.2 exposes a native
reasoning_effort knob with two enabled levels (high / max) on its
OpenAI-compatible endpoints. Previously the zai profile (direct Z.AI
/api/paas/v4) used the base ProviderProfile and emitted nothing, and the
OpenCode Go profile only handled Kimi K2 / DeepSeek — so a user's effort
preference for GLM-5.2 was silently dropped on both routes.
- zai: ZaiProfile maps effort onto high/max (xhigh/max -> max, lower -> high)
- opencode-go: same mapping for GLM-5.2, alongside existing Kimi/DeepSeek
- alias spellings recognized (glm-5.2 / glm-5-2 / glm-5p2, vendor-prefixed)
- disabled / no effort leaves the server default untouched
A Z.ai desktop user reported thinking reverting to medium after one turn,
burning ~200% of a week's credits in 4 days despite reasoning_effort: false
in config.yaml. Four compounding bugs:
- _session_info reported reasoning_effort "" for disabled reasoning,
indistinguishable from unset — the desktop adopted it after the first
turn, wiping its sticky "thinking off" pick so every later chat
reverted to the default effort.
- config.set key=reasoning always wrote agent.reasoning_effort to global
config.yaml, so every desktop model-menu selection (preset.effort ??
'medium') clobbered the user's configured value. Now session-scoped
like the messaging gateway's /reasoning, landing on
create_reasoning_override so lazily-built sessions keep it too.
- YAML `reasoning_effort: false`/`off`/`no` (boolean False) was coerced
to "" by every loader's `str(x or "")`, silently re-enabling thinking.
parse_reasoning_effort now treats False/"false"/"disabled" as
{"enabled": False}; loaders (tui gateway, gateway, cli, cron,
delegate) pass the raw value through. The desktop config reader also
crashed on the boolean (false.trim()), aborting voice/STT settings.
- The zai provider profile never sent thinking on the wire, and GLM-4.5+
defaults to thinking ON server-side — so disabling reasoning was a
silent no-op on direct Z.ai, the actual token burner. The profile now
emits extra_body.thinking {"type": "enabled"|"disabled"} for
thinking-capable GLM models, mirroring the DeepSeek profile.
Also: /new (session reset) now carries reasoning_config across the
rebuild like model_override; config.get reasoning prefers the session's
live value and maps a config False to "none"; Settings shows "Off"
instead of a blank select for hand-written false.
GLM-5.2 ships with a 1M (1,048,576) token context window. Without this
entry, Hermes falls through to the generic 'glm' key (202,752 tokens),
under-reporting the context bar and prematurely compressing conversations.
The 1M limit was verified empirically via needle-in-a-haystack retrieval
at 789,240 prompt tokens on api.z.ai/api/coding/paas/v4 — zero errors,
zero truncation, correct retrieval at every tested size (25K through 789K).
Changes:
- agent/model_metadata.py: add 'glm-5.2': 1_048_576 before 'glm' fallback
- hermes_cli/models.py: add glm-5.2 to zai curated models
- hermes_cli/setup.py: add glm-5.2 to setup wizard zai list
- hermes_cli/auth.py: add glm-5.2 to coding plan endpoint probes
- plugins/model-providers/zai/__init__.py: add glm-5.2 to fallback_models
- tests/agent/test_model_metadata.py: context resolution + vendor-prefix tests
Every provider profile is now a self-contained plugin under
plugins/model-providers/<name>/, mirroring the plugins/platforms/
pattern established for IRC and Teams. The ProviderProfile ABC
stays in providers/; the per-provider profile data moves out.
- plugins/model-providers/<name>/__init__.py calls register_provider()
- plugins/model-providers/<name>/plugin.yaml declares kind: model-provider
- providers/__init__.py._discover_providers() lazily scans bundled plugins
then $HERMES_HOME/plugins/model-providers/<name>/ (user override path)
- User plugins with the same name override bundled ones (last-writer-wins
in register_provider)
- Legacy providers/<name>.py layout still supported for back-compat with
out-of-tree editable installs
- Hermes PluginManager: new kind=model-provider; skipped like memory
plugins (providers/ discovery owns them); standalone plugins with
register_provider+ProviderProfile in their __init__.py auto-coerce to
this kind (same heuristic as memory providers)
- skip_names extended to include 'model-providers' so the general
PluginManager doesn't double-scan the category
- 4 new tests in tests/providers/test_plugin_discovery.py covering
bundled discovery, user override, and general-loader isolation
- Docs updated: website/docs/developer-guide/adding-providers.md,
provider-runtime.md, providers/README.md, plugins/model-providers/README.md
No API break: auth.py / config.py / doctor.py / models.py / runtime_provider.py /
model_metadata.py / auxiliary_client.py / chat_completions.py / run_agent.py
all still consume providers via get_provider_profile() / list_providers() —
they just now see plugin-discovered entries instead of pkgutil-iterated ones.
Third parties can now drop a single directory into
~/.hermes/plugins/model-providers/<name>/ to add or override an inference
provider without touching the repo.
Teknium