feat(providers): GLM-5.2 native reasoning_effort controls (#58884)

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
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Teknium 2026-07-05 13:48:01 -07:00 committed by GitHub
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4 changed files with 242 additions and 10 deletions

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@ -31,6 +31,12 @@ def _is_deepseek_thinking_model(model: str | None) -> bool:
return m == "deepseek-reasoner"
def _is_glm_5_2_model(model: str | None) -> bool:
"""Detect GLM-5.2 across alias spellings (glm-5.2 / glm-5-2 / glm-5p2)."""
m = _flat_model_name(model)
return any(token in m for token in ("glm-5.2", "glm-5-2", "glm-5p2"))
class OpenCodeGoProfile(ProviderProfile):
"""OpenCode Go - model-specific reasoning controls."""
@ -55,6 +61,21 @@ class OpenCodeGoProfile(ProviderProfile):
extra_body: dict[str, Any] = {}
top_level: dict[str, Any] = {}
if _is_glm_5_2_model(model):
# GLM-5.2 on OpenCode Go uses its native OpenAI-compatible
# reasoning_effort knob, which has exactly two enabled levels:
# high and max. Map Hermes' richer scale onto those; leave the
# server default alone when reasoning is disabled or unset.
if not isinstance(reasoning_config, dict):
return extra_body, top_level
if reasoning_config.get("enabled") is False:
return extra_body, top_level
effort = (reasoning_config.get("effort") or "").strip().lower()
if not effort or effort == "none":
return extra_body, top_level
top_level["reasoning_effort"] = "max" if effort in {"xhigh", "max"} else "high"
return extra_body, top_level
if _is_kimi_k2_model(model):
# Kimi K2 on OpenCode Go uses Moonshot's native wire shape:
# extra_body.thinking (binary toggle) + top-level reasoning_effort

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@ -16,6 +16,12 @@ When no reasoning preference is set (``reasoning_config is None``) the field
is omitted so the server default applies, matching prior behavior. GLM
models before 4.5 (e.g. ``glm-4-9b``) don't accept ``thinking`` and are left
untouched.
GLM-5.2 additionally exposes a native ``reasoning_effort`` knob with exactly
two enabled levels ``high`` and ``max`` on the OpenAI-compatible endpoint
(per Z.AI / BigModel docs). Hermes' richer effort scale is collapsed onto
those two so the user's effort preference actually reaches the model instead
of being silently dropped.
"""
from __future__ import annotations
@ -40,8 +46,44 @@ def _model_supports_thinking(model: str | None) -> bool:
return (major, minor) >= (4, 5)
def _is_glm_5_2(model: str | None) -> bool:
"""Detect GLM-5.2 across the alias spellings providers use.
Covers the canonical ``glm-5.2`` plus the ``glm-5-2`` / ``glm-5p2``
variants seen on relays (Fireworks ``glm-5p2``, etc.) and any
vendor-prefixed form (``z-ai/glm-5.2``, ``zai-org-glm-5-2``).
"""
m = (model or "").strip().lower()
if not m:
return False
return any(token in m for token in ("glm-5.2", "glm-5-2", "glm-5p2"))
def _glm_5_2_reasoning_effort(reasoning_config: dict | None) -> str | None:
"""Map Hermes reasoning effort onto GLM-5.2's native ``high``/``max``.
GLM-5.2 only supports two enabled effort levels. ``xhigh``/``max``
request the top tier; everything else that is enabled requests ``high``
(its minimum thinking level). When reasoning is explicitly disabled, or
no effort preference is supplied, the server default is left untouched.
"""
if not isinstance(reasoning_config, dict):
return None
if reasoning_config.get("enabled") is False:
return None
effort = (reasoning_config.get("effort") or "").strip().lower()
if not effort or effort == "none":
return None
if effort in {"xhigh", "max"}:
return "max"
# low / medium / minimal / high all clamp to GLM-5.2's minimum: high.
return "high"
class ZaiProfile(ProviderProfile):
"""Z.AI / GLM — extra_body.thinking enabled/disabled."""
"""Z.AI / GLM — extra_body.thinking on/off + GLM-5.2 reasoning_effort."""
def build_api_kwargs_extras(
self, *, reasoning_config: dict | None = None, model: str | None = None, **context
@ -49,7 +91,7 @@ class ZaiProfile(ProviderProfile):
extra_body: dict[str, Any] = {}
top_level: dict[str, Any] = {}
if not _model_supports_thinking(model):
if not _model_supports_thinking(model) and not _is_glm_5_2(model):
return extra_body, top_level
# Only emit when the user expressed a preference; omitting the field
@ -58,6 +100,11 @@ class ZaiProfile(ProviderProfile):
enabled = reasoning_config.get("enabled") is not False
extra_body["thinking"] = {"type": "enabled" if enabled else "disabled"}
if _is_glm_5_2(model):
effort = _glm_5_2_reasoning_effort(reasoning_config)
if effort is not None:
top_level["reasoning_effort"] = effort
return extra_body, top_level

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@ -122,13 +122,68 @@ class TestOpenCodeGoDeepSeekThinking:
assert top_level == {"reasoning_effort": "max"}
class TestOpenCodeGoGLM52Reasoning:
"""GLM-5.2 uses its native high/max reasoning_effort knob on OpenCode Go."""
def test_high_maps_to_high(self, opencode_go_profile):
extra_body, top_level = opencode_go_profile.build_api_kwargs_extras(
reasoning_config={"enabled": True, "effort": "high"},
model="glm-5.2",
)
assert extra_body == {}
assert top_level == {"reasoning_effort": "high"}
def test_low_and_medium_clamp_up_to_high(self, opencode_go_profile):
for effort in ("low", "medium", "minimal"):
extra_body, top_level = opencode_go_profile.build_api_kwargs_extras(
reasoning_config={"enabled": True, "effort": effort},
model="glm-5.2",
)
assert extra_body == {}
assert top_level == {"reasoning_effort": "high"}
def test_xhigh_and_max_map_to_max(self, opencode_go_profile):
for effort in ("xhigh", "max"):
extra_body, top_level = opencode_go_profile.build_api_kwargs_extras(
reasoning_config={"enabled": True, "effort": effort},
model="z-ai/glm-5.2",
)
assert extra_body == {}
assert top_level == {"reasoning_effort": "max"}
def test_disabled_leaves_server_default(self, opencode_go_profile):
extra_body, top_level = opencode_go_profile.build_api_kwargs_extras(
reasoning_config={"enabled": False, "effort": "high"},
model="glm-5.2",
)
assert extra_body == {}
assert top_level == {}
def test_no_config_leaves_server_default(self, opencode_go_profile):
extra_body, top_level = opencode_go_profile.build_api_kwargs_extras(
reasoning_config=None,
model="glm-5.2",
)
assert extra_body == {}
assert top_level == {}
@pytest.mark.parametrize("model", ["glm-5-2", "glm-5p2"])
def test_alias_spellings_recognized(self, opencode_go_profile, model):
extra_body, top_level = opencode_go_profile.build_api_kwargs_extras(
reasoning_config={"enabled": True, "effort": "max"},
model=model,
)
assert top_level == {"reasoning_effort": "max"}
class TestOpenCodeGoModelGating:
"""Other OpenCode Go models must not receive Kimi/DeepSeek controls."""
"""Other OpenCode Go models must not receive Kimi/DeepSeek/GLM controls."""
@pytest.mark.parametrize(
"model",
[
"glm-5.1",
"glm-5",
"qwen3.6-plus",
"minimax-m2.7",
"deepseek-v3.1",

View file

@ -1,4 +1,4 @@
"""Unit tests for the Z.AI / GLM provider profile's thinking-mode wiring.
"""Unit tests for the Z.AI / GLM provider profile's reasoning wiring.
Z.AI's GLM-4.5-and-later chat models default to thinking-mode ON when the
request omits ``thinking``. Before the profile emitted the parameter,
@ -6,6 +6,10 @@ request omits ``thinking``. Before the profile emitted the parameter,
Z.AI route users who turned thinking off kept burning thinking tokens on
every turn (the desktop "thinking reverts to medium" report).
GLM-5.2 additionally exposes a native ``reasoning_effort`` knob with two
enabled levels (high / max) on the OpenAI-compatible ``/api/paas/v4``
endpoint; the Hermes effort scale is collapsed onto those.
These tests pin the profile's wire-shape contract so Z.AI requests stay
correctly shaped without going live.
"""
@ -61,12 +65,102 @@ class TestZaiThinkingWireShape:
assert top_level == {}
def test_no_effort_levels_leak_to_top_level(self, zai_profile):
"""GLM has no effort knob — never emit ``reasoning_effort``."""
"""Non-5.2 GLM models have no effort knob — never emit
``reasoning_effort`` for them (GLM-5.2 is the exception, below)."""
for effort in ("minimal", "low", "medium", "high", "xhigh"):
_, top_level = zai_profile.build_api_kwargs_extras(
reasoning_config={"enabled": True, "effort": effort}, model="glm-5.2"
)
assert top_level == {}
for model in ("glm-5", "glm-5.1", "glm-4.6"):
_, top_level = zai_profile.build_api_kwargs_extras(
reasoning_config={"enabled": True, "effort": effort}, model=model
)
assert top_level == {}
class TestZaiGLM52ReasoningEffort:
"""GLM-5.2's native ``reasoning_effort`` knob (two enabled levels)."""
def test_high_maps_to_high(self, zai_profile):
extra_body, top_level = zai_profile.build_api_kwargs_extras(
reasoning_config={"enabled": True, "effort": "high"},
model="glm-5.2",
)
assert extra_body == {"thinking": {"type": "enabled"}}
assert top_level == {"reasoning_effort": "high"}
@pytest.mark.parametrize("effort", ["low", "medium", "minimal"])
def test_lower_efforts_clamp_up_to_high(self, zai_profile, effort):
"""GLM-5.2's minimum thinking level is high — lower Hermes levels
clamp onto it."""
extra_body, top_level = zai_profile.build_api_kwargs_extras(
reasoning_config={"enabled": True, "effort": effort},
model="glm-5.2",
)
assert extra_body == {"thinking": {"type": "enabled"}}
assert top_level == {"reasoning_effort": "high"}
@pytest.mark.parametrize("effort", ["xhigh", "max"])
def test_strong_efforts_map_to_max(self, zai_profile, effort):
extra_body, top_level = zai_profile.build_api_kwargs_extras(
reasoning_config={"enabled": True, "effort": effort},
model="glm-5.2",
)
assert extra_body == {"thinking": {"type": "enabled"}}
assert top_level == {"reasoning_effort": "max"}
def test_disabled_sends_no_effort(self, zai_profile):
"""Disabled reasoning still sends the thinking-off marker but never
an effort level."""
extra_body, top_level = zai_profile.build_api_kwargs_extras(
reasoning_config={"enabled": False, "effort": "high"},
model="glm-5.2",
)
assert extra_body == {"thinking": {"type": "disabled"}}
assert top_level == {}
def test_no_config_leaves_server_default(self, zai_profile):
extra_body, top_level = zai_profile.build_api_kwargs_extras(
reasoning_config=None,
model="glm-5.2",
)
assert extra_body == {}
assert top_level == {}
def test_no_effort_sends_no_effort_level(self, zai_profile):
"""Enabled but no effort preference → thinking marker only; the
server picks its default effort."""
extra_body, top_level = zai_profile.build_api_kwargs_extras(
reasoning_config={"enabled": True},
model="glm-5.2",
)
assert extra_body == {"thinking": {"type": "enabled"}}
assert top_level == {}
@pytest.mark.parametrize(
"model",
[
"z-ai/glm-5.2",
"glm-5-2",
"glm-5p2",
"accounts/fireworks/models/glm-5p2",
"zai-org-glm-5-2",
],
)
def test_alias_spellings_recognized(self, zai_profile, model):
_, top_level = zai_profile.build_api_kwargs_extras(
reasoning_config={"enabled": True, "effort": "max"},
model=model,
)
assert top_level == {"reasoning_effort": "max"}
@pytest.mark.parametrize(
"model",
["glm-5.1", "glm-5", "glm-4.7", "glm-4-9b", "", None],
)
def test_non_glm_5_2_models_get_no_effort(self, zai_profile, model):
_, top_level = zai_profile.build_api_kwargs_extras(
reasoning_config={"enabled": True, "effort": "high"},
model=model,
)
assert top_level == {}
class TestZaiModelGating:
@ -110,7 +204,7 @@ class TestZaiModelGating:
class TestZaiFullKwargsIntegration:
"""End-to-end: the transport's full kwargs carry the thinking marker."""
"""End-to-end: the transport's full kwargs carry the reasoning wiring."""
def test_disabled_reaches_the_wire(self, zai_profile):
from agent.transports.chat_completions import ChatCompletionsTransport
@ -139,3 +233,18 @@ class TestZaiFullKwargsIntegration:
provider_name="zai",
)
assert "thinking" not in kwargs.get("extra_body", {})
def test_glm_5_2_effort_reaches_top_level(self, zai_profile):
from agent.transports.chat_completions import ChatCompletionsTransport
kwargs = ChatCompletionsTransport().build_kwargs(
model="glm-5.2",
messages=[{"role": "user", "content": "ping"}],
tools=None,
provider_profile=zai_profile,
reasoning_config={"enabled": True, "effort": "max"},
base_url="https://api.z.ai/api/paas/v4",
provider_name="zai",
)
assert kwargs["reasoning_effort"] == "max"
assert kwargs["extra_body"]["thinking"] == {"type": "enabled"}