scriptoriumadmin/litellm
1
0
Fork 0
mirror of https://github.com/BerriAI/litellm.git synced 2026-08-28 05:25:59 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions 36

test(tencent): drive thinking tests off the real cost map instead of patched internals

Browse source
This commit is contained in:
mateo-berri 2026-08-26 11:34:06 -07:00
parent 8307be68c9
commit 9c38f6f125
1 changed files with 43 additions and 82 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

125
tests/test_litellm/llms/tencent/chat/test_tencent_chat_transformation.py
View file

@ -135,22 +135,18 @@ def test_map_openai_params_overwrites_existing_extra_body():
assert result["extra_body"] == {"thinking": {"type": "enabled"}}
def test_get_optional_params_merges_thinking_with_user_extra_body():
def test_get_optional_params_merges_thinking_with_user_extra_body(local_model_cost_map):
"""End-to-end at the get_optional_params layer: a user-supplied extra_body
and the mapped thinking payload must coexist in the final extra_body."""
from litellm.utils import get_optional_params
with patch(
"litellm.llms.tencent.chat.transformation.supports_reasoning",
return_value=True,
):
result = get_optional_params(
model="tencent/deepseek-v4-pro",
custom_llm_provider="tencent",
messages=[{"role": "user", "content": "hi"}],
thinking={"type": "enabled"},
extra_body={"custom_flag": True},
)
result = get_optional_params(
model="tencent/deepseek-v4-pro",
custom_llm_provider="tencent",
messages=[{"role": "user", "content": "hi"}],
thinking={"type": "enabled"},
extra_body={"custom_flag": True},
)
assert result["extra_body"]["thinking"] == {"type": "enabled"}
assert result["extra_body"]["custom_flag"] is True
@ -190,93 +186,58 @@ class TestAdaptiveThinkingCoercion:
Ref: https://www.tencentcloud.com/document/product/1300/82345
"""
def test_reasoning_effort_maps_to_adaptive_for_adaptive_only_model(self):
def test_reasoning_effort_maps_to_adaptive_for_adaptive_only_model(self, local_model_cost_map):
config = TencentChatConfig()
with (
patch(
"litellm.llms.tencent.chat.transformation.supports_reasoning",
return_value=True,
),
patch.object(TencentChatConfig, "_is_adaptive_thinking_model", return_value=True),
):
result = config.map_openai_params(
non_default_params={"reasoning_effort": "medium"},
optional_params={},
model="tencent/minimax-m3",
drop_params=False,
)
result = config.map_openai_params(
non_default_params={"reasoning_effort": "medium"},
optional_params={},
model="tencent/minimax-m3",
drop_params=False,
)
assert result["extra_body"]["thinking"] == {"type": "adaptive"}
def test_explicit_enabled_thinking_coerced_to_adaptive(self):
def test_explicit_enabled_thinking_coerced_to_adaptive(self, local_model_cost_map):
config = TencentChatConfig()
with (
patch(
"litellm.llms.tencent.chat.transformation.supports_reasoning",
return_value=True,
),
patch.object(TencentChatConfig, "_is_adaptive_thinking_model", return_value=True),
):
result = config.map_openai_params(
non_default_params={"thinking": {"type": "enabled", "budget_tokens": 4096}},
optional_params={},
model="tencent/minimax-m3",
drop_params=False,
)
result = config.map_openai_params(
non_default_params={"thinking": {"type": "enabled", "budget_tokens": 4096}},
optional_params={},
model="tencent/minimax-m3",
drop_params=False,
)
assert result["extra_body"]["thinking"] == {"type": "adaptive", "budget_tokens": 4096}
def test_disabled_thinking_kept_for_adaptive_only_model(self):
def test_disabled_thinking_kept_for_adaptive_only_model(self, local_model_cost_map):
config = TencentChatConfig()
with (
patch(
"litellm.llms.tencent.chat.transformation.supports_reasoning",
return_value=True,
),
patch.object(TencentChatConfig, "_is_adaptive_thinking_model", return_value=True),
):
result = config.map_openai_params(
non_default_params={"thinking": {"type": "disabled"}},
optional_params={},
model="tencent/minimax-m3",
drop_params=False,
)
result = config.map_openai_params(
non_default_params={"thinking": {"type": "disabled"}},
optional_params={},
model="tencent/minimax-m3",
drop_params=False,
)
assert result["extra_body"]["thinking"] == {"type": "disabled"}
def test_none_reasoning_effort_disables_thinking_for_adaptive_only_model(self):
def test_none_reasoning_effort_disables_thinking_for_adaptive_only_model(self, local_model_cost_map):
config = TencentChatConfig()
with (
patch(
"litellm.llms.tencent.chat.transformation.supports_reasoning",
return_value=True,
),
patch.object(TencentChatConfig, "_is_adaptive_thinking_model", return_value=True),
):
result = config.map_openai_params(
non_default_params={"reasoning_effort": "none"},
optional_params={},
model="tencent/minimax-m3",
drop_params=False,
)
result = config.map_openai_params(
non_default_params={"reasoning_effort": "none"},
optional_params={},
model="tencent/minimax-m3",
drop_params=False,
)
assert result["extra_body"]["thinking"] == {"type": "disabled"}
def test_non_adaptive_model_keeps_enabled(self):
def test_non_adaptive_model_keeps_enabled(self, local_model_cost_map):
config = TencentChatConfig()
with (
patch(
"litellm.llms.tencent.chat.transformation.supports_reasoning",
return_value=True,
),
patch.object(TencentChatConfig, "_is_adaptive_thinking_model", return_value=False),
):
result = config.map_openai_params(
non_default_params={"reasoning_effort": "high"},
optional_params={},
model="tencent/kimi-k3",
drop_params=False,
)
result = config.map_openai_params(
non_default_params={"reasoning_effort": "high"},
optional_params={},
model="tencent/deepseek-v4-pro",
drop_params=False,
)
assert result["extra_body"]["thinking"] == {"type": "enabled"}