urlparse raises ValueError on non-integer / out-of-range ports, and
http://myhost:99999/v1 passes OpenAI-client construction (only httpx
rejects it later), so the crash was reachable from build_kwargs on
every request for such a URL. Wrap the parsed.port check in the same
try/except ValueError guard hermes_cli.models already uses around its
11434 check, and pin it with parametrized tests.
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).
Widens the salvaged #91323 fix (@vinsew): the effort vocabulary moves to
agent.reasoning_effort (OX_ALPHA_EFFORTS/OVERRIDES, the declared-policy
home every other model vocabulary lives in), and the translation is
shared between the opencode-zen profile and the keyless opencode-free
profile — Ox Alpha is reachable through both, and the free profile
previously dropped effort entirely.
Live-verified: medium clamps to low (raw medium 400s: 'This model always
engages in thinking... use low, high, or max'), xhigh rounds to max, and
full agent turns with effort=medium complete on BOTH providers.
OpenCode documents x-preview-f-free as accepting low, high, and max reasoning effort on its Zen Chat Completions endpoint. Hermes previously resolved the user's per-model override to max but the plain Zen provider profile discarded it, so successful calls silently ran at the server default.
Introduce an OpenCodeZenProfile scoped only to x-preview-f-free. It forwards the normalized top-level reasoning_effort, maps xhigh to max, preserves server defaults when unset or disabled, and leaves every other Zen model untouched.
Add profile and full transport tests that prove max reaches the outgoing request and that non-target models are unaffected. Also correct the nanoid security-pin comment to match the already-locked 3.3.18 release.
Both the wire path and the picker only consulted the catalog's
`mandatory` flag, so a route the Portal lists as accepting no reasoning
parameter at all still got sent a disable, and still offered a Thinking
toggle in the model picker.
For a route it serves, the aggregator's own catalog outranks the
models.dev inference: `supports_reasoning: false` now suppresses the
disable on the wire and drops reasoning controls from the picker
entirely, so there is no disable left to describe.
reasoning: {enabled: false} is the only shape the Portal honors, and the
profile refused to send it for every model. Sending nothing means the
upstream default instead, which on a thinking-first route like
deepseek/deepseek-v4-pro (catalog: default_effort high) is thinking ON — so
turning thinking off kept billing reasoning tokens on every turn.
The blanket omission was over-broad. The Portal only rejects a disable on
reasoning-mandatory routes ("Reasoning is mandatory for this model"), which
its catalog flags per model, so that flag now gates the omission. Models the
catalog can't speak to keep the old behavior rather than risk the 400.
extra_body.thinking, DeepSeek's own disable shape, is not forwarded upstream
by the Portal and is not an option here.
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).
Follow-up to the salvaged CommandCode signature fix: accepting base_url
but ignoring it left custom endpoints (user-configured model.base_url /
COMMANDCODE_BASE_URL proxies) fetching the public catalog instead of the
configured one. Reviewer dansigma flagged this on PR #88851.
Class-wide fix, not a CommandCode patch:
- providers/base.py: a caller base_url that DIFFERS from the profile's
default now wins over models_url. Equality with the default means "not
customised" (callers pass base_url unconditionally, defaulting to the
profile's own URL) and keeps models_url as the endpoint, preserving the
OpenRouter-style split-catalog behavior.
- commandcode: _fetch_commandcode_models() takes the endpoint override;
both profile overrides forward base_url.
- Tests: base-class precedence (custom beats models_url, default does
not), CommandCode redirect via live local HTTP server incl. claude-*
filter, and default-echo hitting the canonical endpoint. All verified
to fail against the pre-fix implementation (sabotage run).
Plugin-only providers (commandcode, tencent-tokenhub, ...) are absent from
models.dev and HERMES_OVERLAYS, so resolve_provider_full returned None and
/model switches failed with "Unknown provider ..." even though the picker
lists them (CANONICAL_PROVIDERS auto-extends from the same registry).
Fall back to providers.get_provider_profile() before giving up, mapping the
profile api_mode to the ProviderDef transport.
The model picker's generic live-fetch path (hermes_cli/models.py
provider_model_ids) calls profile.fetch_models(api_key=..., base_url=...).
Both CommandCode overrides only accepted api_key/timeout, so every picker
open raised TypeError, which was silently swallowed, leaving the provider
with zero models.
Match the base ProviderProfile.fetch_models signature (base_url kwarg) and
add a regression test asserting both profiles accept it.
K3 only recognizes low/high/max. Previously the Kimi provider only
forwarded low/medium/high verbatim and dropped every other level
(xhigh/max/ultra/minimal) to the thinking toggle, silently ignoring
the user's requested effort.
Now maps the full Hermes vocabulary onto K3's set, matching K3's own
server-side mapping:
low, minimal → low
medium, high → high
xhigh, max, ultra → max
ref: https://www.kimi.com/code/docs/en/kimi-code/models.html
The native Gemini provider profile's default_aux_model and the curated
model picker catalog were still pinned to gemini-3.5-flash, a stale
generation now superseded by gemini-3.6-flash (documented GA). Bump
both so the auxiliary-task default and the picker stay in sync with
the current model.
Contract test asserts the durable lockstep invariant only
(default_aux_model is a member of _PROVIDER_MODELS["gemini"]) rather
than pinning either side to a frozen model-name string, so it doesn't
need updating on the next model-generation bump.
Stop offering deepseek-chat/reasoner in the static catalog and point
fallback/aux defaults at the permanent v4 IDs. Keep retired aliases in
a detection-only map so /model deepseek-chat still resolves to deepseek.
The Copilot provider profile unconditionally mapped ``xhigh`` to ``high`` before
checking the model's catalog, so models that DO support ``xhigh`` (e.g. the
gpt-5.x family per the live /models catalog) were silently capped one level
down.
Honor the requested effort when the catalog lists it as supported, and only
downgrade when it does not, choosing the nearest weaker supported level
(xhigh->high, minimal->low, else medium, else the first supported level). This
matches the nearest-down clamp behavior used elsewhere for the ``max`` effort.
Adds tests/plugins/model_providers/test_copilot_profile.py covering forward,
downgrade, and fallback paths (catalog lookup stubbed).
Three follow-up fixes to the salvaged reasoning_effort support, all verified
live against ollama.com /v1/chat/completions + /api/show on deepseek-v4-pro,
gemma3, and qwen3-coder:
1. Capability-gate on /api/show 'thinking'. The original ignored the
supports_reasoning flag and emitted reasoning_effort for every model. Now
gated: only models whose native /api/show capabilities list contains
'thinking' (deepseek-v4 yes; gemma3 / qwen3-coder no) get reasoning_effort.
Mirrors the LM Studio pattern — capability resolved once per (model,
base_url) in run_agent._supports_reasoning_extra_body via a cached probe
(hermes_cli.models.ollama_model_supports_thinking), threaded into the
profile hook as supports_reasoning. No live HTTP in the per-request path.
2. Disable actually disables. Ollama Cloud defaults to thinking ON and IGNORES
the extra_body.thinking:{type:disabled} shape (verified: still returned
reasoning). The only working off switch is top-level reasoning_effort:'none'.
The salvaged code returned ({}, {}) for enabled:false / effort:none, leaving
thinking ON. Now emits {'reasoning_effort': 'none'}.
3. Omit unrecognized effort. The original forwarded any unknown string verbatim
including 'minimal' (a real Hermes effort level). Ollama Cloud rejects
unrecognized values with a hard HTTP 400 (accepted set: low/medium/high/
max/none), so forwarding 'minimal' would break the request. Now omitted.
Core touches (run_agent.py, hermes_cli/models.py) add the capability probe;
the plugin profile only consumes the resolved flag. 24/24 profile tests green;
194 provider/transport tests unaffected.
Ollama's /v1/chat/completions silently ignores extra_body.think (it only
honours it on /api/chat — ollama/ollama#14820), so agent.reasoning_effort:
none never actually disabled thinking on OpenAI-compatible Ollama routes.
Emit the top-level reasoning_effort='none' field (which Ollama respects)
alongside think=False (kept for proxies and the native /api/chat path).
The PR's second half (propagating reasoning_config to the background-review
fork) already landed on main via agent/background_review.py, so only the
provider-profile change is salvaged here, resolved onto the current
GLM/effort-aware profile.
Salvaged from PR #29820 by @Epoxidex.
Review findings from the 4-angle pass:
- Unknown-but-enabled effort levels now collapse to Solar's strongest
(high) instead of silently downgrading to the medium default — guards
against the next #62650-style vocabulary addition. Explicit-empty
effort keeps the medium default.
- fallback_models test now asserts the behavior contract (non-empty, no
denied families) instead of freezing the exact model tuple
(change-detector, AGENTS.md reject reason).
- Drop unused pytest import in test_upstage_provider.py.
Main added max/ultra effort levels (#62650) after this PR branched;
without the mapping 'ultra' silently fell through to the medium default.
Matches the xhigh/max collapse-to-strongest convention used by other
profiles.
Pin the Upstage default to the concrete solar-pro3 instead of the
solar-pro rolling alias:
- plugin fallback_models is now ("solar-pro3",); entry [0] is the setup default
- drop the "solar-pro" context-window fallback entry (solar-pro3 covers it)
- update the reasoning default-on docstring and profile tests accordingly
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Invert the reasoning-support check from an allow-list (solar-pro,
solar-open) to a deny-list of the known non-reasoning families
(solar-mini, syn-pro). Newly released Solar models now get
reasoning_effort by default instead of having it silently dropped.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Adds Upstage Solar as a bundled model-provider plugin. Solar exposes an
OpenAI-compatible chat-completions endpoint at https://api.upstage.ai/v1, so
the generic chat_completions transport handles request/response/streaming/tool
calls — the profile is the core integration.
Provider registration (Upstage isn't in models.dev, so each registry that does
not auto-wire from the plugin layer needs an explicit entry — same pattern as
nvidia/gmi):
- plugins/model-providers/upstage/: UpstageProfile + plugin.yaml. Picker default
and offline catalog list only the agentic Solar Pro models, led by `solar-pro`
(rolling alias for the latest Pro). default_aux_model empty so aux tasks use
the main model. `solar` alias. UPSTAGE_BASE_URL overrides the host.
- hermes_cli/providers.py: HERMES_OVERLAYS + label + `solar` alias, so
resolve_provider_full('upstage') resolves (without this, an explicit
`provider: upstage` in config was dropped and fell through to auto-detect).
- hermes_cli/auth.py: PROVIDER_REGISTRY entry + `solar` alias, so `hermes
doctor` / resolve_provider recognise upstage (the static-registry path the
lazy profile-extension doesn't reliably cover at validation time).
- hermes_cli/models.py: CANONICAL_PROVIDERS entry places Upstage Solar in the
curated picker order (above the auto-appended `custom`).
- agent/model_metadata.py: context-window fallbacks (/v1/models omits
context_length); `solar-pro` carries the 128K Pro context as the catch-all.
Reasoning: UpstageProfile.build_api_kwargs_extras wires Solar's top-level
`reasoning_effort` (low|medium|high; xhigh/max→high). Reasoning-capable families
are solar-pro* and solar-open*; solar-mini/syn-pro never receive it. Defaults ON
at medium when unset (matches the /reasoning "medium (default)" label);
`/reasoning none` disables; explicit/saved settings are honored. No
reasoning_content echo handling needed (unlike DeepSeek/Kimi).
Web dashboard:
- web/src/pages/EnvPage.tsx: add an "Upstage Solar" provider group so
UPSTAGE_API_KEY / UPSTAGE_BASE_URL appear under LLM Providers (not "Other").
Docs/tests:
- .env.example: documents UPSTAGE_API_KEY / UPSTAGE_BASE_URL.
- tests: profile wiring, reasoning_effort mapping (pro/open/mini, efforts,
disabled, default-on), provider-resolver regression (resolve_provider_full /
get_provider / solar alias / overlay), `solar-pro` default.
Testing: pytest tests/providers tests/plugins/model_providers
tests/hermes_cli/test_upstage_provider.py tests/run_agent/test_provider_parity.py
tests/hermes_cli/test_api_key_providers.py; ruff clean. Verified end-to-end:
`hermes doctor` shows "Upstage Solar", and live chat works via both
`--provider upstage` and `--provider solar`. Reasoning wire format per
https://console.upstage.ai/api/docs/for-agents/raw. Platforms tested: macOS.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Bundle Fireworks AI as a first-class BYOK provider across the CLI, web/TUI,
and desktop onboarding.
- New model-provider plugin with attribution headers (HTTP-Referer / X-Title)
so Fireworks can attribute Hermes traffic; PAYG-safe default aux + fallback
models (accounts/fireworks/models/...), IDs tracking fw-ai/fireconnect.
- Registered in CANONICAL_PROVIDERS so it appears in the CLI/web/TUI pickers.
- Alias wiring (fireworks-ai, fw) into both CLI resolvers.
- First-class wiring: OPTIONAL_ENV_VARS, HERMES_OVERLAYS (FIREWORKS_BASE_URL
override), doctor env hints. Live catalog + model_metadata are auto-derived.
- doctor: treat Fireworks' native slash-form IDs (accounts/fireworks/...) as
valid, not aggregator vendor prefixes, so it no longer tells Fireworks users
to switch to openrouter or drop the prefix.
- picker: plugin providers with no static curated list now lead with their
profile fallback_models, so the default is an agentic chat model instead of
whatever the live catalog returns first (Fireworks listed an image model,
flux-*, ahead of its chat models).
- Desktop onboarding: Fireworks as a RECOMMENDED hero card with the official
Fireworks logomark and a brand-purple badge, routing to the BYOK key form;
i18n in en/ja/zh/zh-hant.
- Tests: profile contract, first-class wiring (both resolvers, overlay, config,
doctor incl. the slash-form regression, aux headers, credentials), discovery
spot-check, and a live smoke test driven through the Hermes runtime.
Fire Pass (fpk_) support is coming soon; the future wiring is kept as a
commented-out scaffold in the plugin.
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
PR #57601's original branch added a top-level reasoning_effort emit to the
LEGACY build_kwargs path (agent/transports/chat_completions.py), but
provider=custom resolves to CustomProfile (plugins/model-providers/custom/),
so chat_completion_helpers takes the profile path and returns early — the
added branch was unreachable dead code for every custom endpoint.
Move the fix to its real site, CustomProfile.build_api_kwargs_extras(), and
follow the DeepSeek/Zai profile precedent:
- disabled -> extra_body.think = False (unchanged)
- enabled + effort -> TOP-LEVEL reasoning_effort (the OpenAI-compatible
format GLM-5.2/ARK expect), passed through verbatim
incl. max/xhigh
- enabled + no effort -> omit, so the endpoint's server default applies
(avoids silently forcing 'medium' as the original
branch did)
Deliberately does NOT force think=True on enable — that flag is Ollama-only
and risks a 400 on GLM/vLLM endpoints that don't recognize it; thinking is
already server-default-on for these backends.
Verified end-to-end through the real profile dispatch (temp HERMES_HOME):
custom+high -> reasoning_effort=high; custom+max -> reasoning_effort=max;
custom+none -> think=False; custom+unset -> nothing; num_ctx composes.
Adds tests/plugins/model_providers/test_custom_profile.py (13 cases).
Addresses the custom-provider half of #55276.
Co-authored-by: huanshan5195 <huanshan5195@users.noreply.github.com>
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.
Map Hermes xhigh→max to unlock DeepSeek V4's 'Max thinking' tier
through Ollama Cloud's OpenAI-compatible /v1/chat/completions endpoint.
low/medium/high pass through unchanged; disabled/none suppress
reasoning entirely.
Empirically confirmed: reasoning_effort:max produces ~2.5× more
thinking tokens than high on deepseek-v4-pro:cloud (1576 vs 642).
Follow up PR #46609's api.minimax.io reasoning report by moving the behavior out of the broad run_agent host gate and into the MiniMax provider profile. Only MiniMax-M3 on the documented OpenAI-compatible /v1 route gets reasoning_split/thinking/reasoning_effort; Anthropic-format MiniMax and non-M3 models keep their existing wire shapes.
Co-authored-by: goku94123 <gooku94123@gmail.com>
The standalone Kimi/Moonshot profile (api.moonshot.ai/v1) sent both
extra_body.thinking AND a top-level reasoning_effort. With no reasoning
config it even defaulted to thinking:enabled + reasoning_effort:medium,
pairing them on every default call. Moonshot treats these as mutually
exclusive (cannot specify both 'thinking' and 'reasoning_effort').
Align with the kimi-k2 handling already shipped for the opencode-go relay:
send effort when a recognized low|medium|high is requested, otherwise fall
back to the extra_body.thinking toggle. Disabled sends thinking:disabled
only. Never both.
Reported by Cars29 (NOUS Discord). DeepSeek was deliberately left untouched:
its native endpoint accepts both (verified by the live guardrail in
test_deepseek_v4_thinking_live.py), so the report's DeepSeek claim does not
hold there.
Tests: tests/plugins/model_providers/test_kimi_profile.py pins the xor
contract across all config shapes.
Three Copilot inline review comments on #37664, two worth landing
in a polish pass before merge:
1. auxiliary_client.py:270 — Copilot suggested keeping the
minimax-* entries in _API_KEY_PROVIDER_AUX_MODELS_FALLBACK as
a safety net for environments where the profile-based
resolution can't import or run plugin discovery. **Declined.**
The deepseek precedent (commit 773a0faca) explicitly removed
deepseek from the same dict for the same reason — the profile
layer is the source of truth and the dict is a legacy
pre-profiles-system fallback. We do not want to fragment the
codebase by provider: either the profile layer is authoritative
or the dict is. The minimax PR picks profile (matching deepseek)
and the dict stays cleaned up. The risk Copilot raises is
real but theoretical — plugin discovery runs at import time of
the providers module, which is the first thing any modern
Hermes entrypoint imports.
2. tests/agent/test_minimax_provider.py:162 — Copilot flagged
that the test class relies on _get_aux_model_for_provider()
resolving via provider profiles but doesn't explicitly trigger
plugin discovery. **Fixed.** Added 'import model_tools # noqa:
F401' at the top of both test_minimax_aux_is_standard and
test_minimax_aux_not_highspeed. The fixtures in the parallel
test_minimax_profile.py already did this; the legacy test in
test_minimax_provider.py was order-dependent and would silently
break if anyone reorganised the test ordering. Pinned the
dependency explicitly so the test is order-independent.
3. tests/plugins/model_providers/test_minimax_profile.py:46 —
Copilot flagged that the docstring referenced a hard-coded
line number 'hermes_cli/models.py:298' that would go stale.
**Fixed.** Replaced with the symbol reference
'hermes_cli.models._PROVIDER_MODELS[\'minimax\']' which is
stable under file edits and grep-friendly. The new docstring
also reads more naturally — readers don't have to look up
'what's at line 298' to follow the reasoning.
All 221 minimax-related tests still pass.
The minimax / minimax-cn / minimax-oauth profiles still advertised
M2.7 (and M2.7-highspeed for OAuth) as their default_aux_model,
predating the M3 release (2026-06-01). The user-facing
_PROVIDER_MODELS['minimax'] catalog top entry is M3, and the
recommended config for a Token-Plan install now sets
model.default: MiniMax-M3, so the aux default was the only
remaining drift.
Updates:
* minimax default_aux_model: M2.7 -> M3
* minimax-cn default_aux_model: M2.7 -> M3
* minimax-oauth default_aux_model: M2.7-highspeed -> M2.7
(M3 is not on the OAuth / Coding Plan tier per
platform docs as of this PR; the highspeed
variant was the 2x-cost regression from #4082
that PR #6082 collapsed to plain M2.7 for
minimax / minimax-cn but missed OAuth)
* agent/auxiliary_client.py: drop the three legacy
_API_KEY_PROVIDER_AUX_MODELS_FALLBACK entries for the minimax
family. _get_aux_model_for_provider() reads from
ProviderProfile.default_aux_model first (line 250) and only
falls back to the dict when the profile has no aux model or
the profile import fails. With the profile now set, the dict
entries are dead code and a drift hazard. Mirrors the deepseek
cleanup in 773a0faca.
* tests/agent/test_minimax_provider.py: update the existing
TestMinimaxAuxModel assertions from MiniMax-M2.7 to MiniMax-M3
(the intent — 'standard, not highspeed' — is unchanged; the
pin value is).
* tests/plugins/model_providers/test_minimax_profile.py: new
file mirroring tests/plugins/model_providers/test_deepseek_profile.py.
Pins each of the three profiles' default_aux_model and
asserts _get_aux_model_for_provider() returns it. A second
class guards against the highspeed regression coming back.
Refs:
- Closes#36196 in spirit (M3 support — the catalog half of
that issue is #36212; this PR covers the profile half)
- Related: #4082 (M2.7-highspeed 2x-cost), #6082 (previous
M2.7-highspeed -> M2.7 fix that missed OAuth + the
auxiliary_client.py fallback dict)
- Pattern: 773a0faca (same profile-layer fix for deepseek)
The Kimi K2 branch added in the prior commit only emitted extra_body.thinking
and dropped reasoning_effort entirely. KimiProfile (api.moonshot.ai/v1) sends
both fields, and OpenCode Go proxies to the same Moonshot backend. Mirror that
shape on the Go path so /reasoning effort actually reaches Kimi.
- low/medium/high pass through verbatim
- xhigh/max clamp to high (Moonshot's max supported value)
- minimal / unknown effort → omit reasoning_effort, keep thinking on
- disabled / no config → unchanged
- DeepSeek branch unchanged
Closes#26924 (and supersedes #26926) in spirit.
DeepSeek was missing `default_aux_model` on its `ProviderProfile`, so
`_get_aux_model_for_provider("deepseek")` returned an empty string and
the compression / vision / session-search paths emitted
"No auxiliary LLM provider configured -- context compression will
drop middle turns without a summary."
on every DeepSeek session, even when the user had perfectly working
DeepSeek credentials.
Fix lands at the profile layer rather than the legacy
`_API_KEY_PROVIDER_AUX_MODELS_FALLBACK` dict the original PR targeted.
Every modern provider (gemini, zai, minimax, anthropic, kimi-coding,
stepfun, ollama-cloud, gmi, novita, kilocode, ai-gateway, opencode-zen)
sets `default_aux_model` on its `ProviderProfile`; the fallback dict
only exists for providers that predate the profiles system.
Tests added under `tests/plugins/model_providers/test_deepseek_profile.py`:
- `test_profile_advertises_deepseek_chat` -- pins the profile attribute
- `test_consumer_api_returns_deepseek_chat` -- pins the consumer API behavior
- `test_consumer_api_returns_non_empty` -- regression guard for the
symptom in the issue
Original diagnosis and aux-model choice from @kriscolab in PR #26926;
moved one layer up.
Co-authored-by: kriscolab <71590782+kriscolab@users.noreply.github.com>
The cherry-picked PR #15251 from @tw2818 correctly identified the
DeepSeek 400 root cause but placed the fix in the legacy fallback path
of `build_kwargs`, which DeepSeek never reaches — DeepSeek has a
registered ProviderProfile and goes through `_build_kwargs_from_profile`
instead. The legacy-path block was therefore dead code.
This commit pivots the fix to where it actually fires:
- New `DeepSeekProfile` in `plugins/model-providers/deepseek/__init__.py`
overrides `build_api_kwargs_extras` to emit DeepSeek's expected wire
format (mirrors `KimiProfile`):
{"reasoning_effort": "<low|medium|high|max>",
"extra_body": {"thinking": {"type": "enabled" | "disabled"}}}
- Model gating: only `deepseek-v4-*` and `deepseek-reasoner` emit
thinking control. `deepseek-chat` (V3) is untouched — current behavior.
- Effort mapping: low/medium/high passthrough, xhigh/max → max, unset →
omitted (DeepSeek server applies its own default).
- Revert the legacy-path additions from PR #15251 — they were dead code,
and the `_copy_reasoning_content_for_api` strip block specifically
would have nullified the existing reasoning_content padding machinery
(`_needs_deepseek_tool_reasoning` → space-pad on replay) that the
active provider already relies on for replay correctness.
- Unit tests pin the wire-shape contract and the model gating rules
(26 tests, all passing). Existing transport + provider profile suites
(321 tests) continue to pass.
- AUTHOR_MAP: map twebefy@gmail.com → tw2818 for release notes credit.
Closes#15700, #17212, #17825.
Co-authored-by: tw2818 <twebefy@gmail.com>
kshitijk4poor