mirror of
https://github.com/BerriAI/litellm.git
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Merge 178e6e59a3 into cbe361d970
This commit is contained in:
Zach Chrystall
GitHub
commit
b44c64a331
2 changed files with 226 additions and 28 deletions
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@ -694,14 +694,24 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig):
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# Fallback: delegate to parent for unknown types
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return super().get_json_schema_from_pydantic_object(response_format)
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@staticmethod
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def _strip_regional_prefix(model: str) -> str:
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return re.sub(
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r"(^|/)(?:[a-z0-9_-]+\.)+(?=gem(?:ini|ma)-)",
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r"\1",
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model,
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flags=re.IGNORECASE,
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)
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@staticmethod
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def _is_gemini_3_or_newer(model: str) -> bool:
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"""
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Check if the model is Gemini 3 or newer.
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"""
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model_name: Final = model.split("/")[-1].lower()
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normalized_model: Final = VertexGeminiConfig._strip_regional_prefix(model).lower()
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model_name: Final = normalized_model.split("/")[-1]
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is_vertex_fine_tuned_model: Final = model_name.isdigit() or (
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model.startswith("gemini/") and not model_name.startswith("gemini-")
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normalized_model.startswith("gemini/") and not model_name.startswith("gemini-")
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)
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if not model_name or is_vertex_fine_tuned_model or model_name.startswith("gemma-"):
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return False
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@ -809,7 +819,7 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig):
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if self._supports_penalty_parameters(model):
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supported_params.extend(["frequency_penalty", "presence_penalty"])
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if supports_reasoning(model) or self._is_gemini_3_or_newer(model):
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if supports_reasoning(self._strip_regional_prefix(model)) or self._is_gemini_3_or_newer(model):
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supported_params.append("reasoning_effort")
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supported_params.append("thinking")
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@ -1400,10 +1410,13 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig):
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@staticmethod
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def _supports_minimal_thinking_level(model: str) -> bool:
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lowered: Final = model.lower()
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is_gemini3_or_newer_flash: Final = VertexGeminiConfig._is_gemini_3_or_newer(model) and "flash" in lowered
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normalized_model: Final = VertexGeminiConfig._strip_regional_prefix(model)
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lowered: Final = normalized_model.lower()
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is_gemini3_or_newer_flash: Final = (
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VertexGeminiConfig._is_gemini_3_or_newer(normalized_model) and "flash" in lowered
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)
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return is_gemini3_or_newer_flash and not is_explicitly_disabled_factory(
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model=model, custom_llm_provider=None, key="supports_minimal_reasoning_effort"
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model=normalized_model, custom_llm_provider=None, key="supports_minimal_reasoning_effort"
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)
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@staticmethod
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@ -1505,26 +1518,24 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig):
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# For Gemini 3+ models, use thinkingLevel instead of thinkingBudget
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if model and VertexGeminiConfig._is_gemini_3_or_newer(model):
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if thinking_enabled:
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if thinking_budget == 0:
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params["includeThoughts"] = False
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else:
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params["includeThoughts"] = sends_thoughts
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if thinking_budget is not None:
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warn_dropped_reasoning(
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"thinking.budget_tokens",
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thinking_budget,
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model,
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_LEVEL_ONLY_BUDGET_REASON,
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drop_params_gated=False,
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)
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# Follow provider defaults unless explicitly opted into legacy behavior.
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if litellm.enable_gemini_default_thinking_level_low is True:
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params["thinkingLevel"] = (
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"minimal" if VertexGeminiConfig._supports_minimal_thinking_level(model) else "low"
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)
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default_low_thinking_level: Final = (
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"minimal" if VertexGeminiConfig._supports_minimal_thinking_level(model) else "low"
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)
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if thinking_enabled and thinking_budget != 0:
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params["includeThoughts"] = sends_thoughts
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if thinking_budget is not None:
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warn_dropped_reasoning(
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"thinking.budget_tokens",
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thinking_budget,
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model,
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_LEVEL_ONLY_BUDGET_REASON,
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drop_params_gated=False,
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)
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# Follow provider defaults unless explicitly opted into legacy behavior.
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if litellm.enable_gemini_default_thinking_level_low is True:
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params["thinkingLevel"] = default_low_thinking_level
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else:
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# Thinking disabled
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params["thinkingLevel"] = default_low_thinking_level
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params["includeThoughts"] = False
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else:
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# For older Gemini models, use thinkingBudget
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@ -33,8 +33,9 @@ from litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import (
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normalize_gemini_speech_config,
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reject_unknown_gemini_tts_voice_keys,
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)
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from litellm.types.llms.anthropic import AnthropicThinkingParam
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from litellm.types.llms.base import CachedTokensDetails
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from litellm.types.llms.vertex_ai import GeminiFinishReason, RequestBody, UsageMetadata
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from litellm.types.llms.vertex_ai import GeminiFinishReason, GeminiThinkingConfig, RequestBody, UsageMetadata
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from litellm.types.utils import ChoiceLogprobs, ModelInfo, ModelResponseStream, Usage
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from litellm.utils import _invalidate_model_cost_lowercase_map, CustomStreamWrapper
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from litellm.litellm_core_utils.logging_worker import GLOBAL_LOGGING_WORKER
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@ -8891,7 +8892,7 @@ def test_anthropic_thinking_param_to_gemini_3_provider_defaults():
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)
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assert result_disabled.get("includeThoughts") is False
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assert "thinkingLevel" not in result_disabled or result_disabled.get("thinkingLevel") is None
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assert result_disabled.get("thinkingLevel") == "low"
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thinking_param_zero: AnthropicThinkingParam = {
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"type": "enabled",
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@ -8904,7 +8905,7 @@ def test_anthropic_thinking_param_to_gemini_3_provider_defaults():
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)
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assert result_zero["includeThoughts"] is False
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assert "thinkingLevel" not in result_zero or result_zero.get("thinkingLevel") is None
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assert result_zero["thinkingLevel"] == "minimal"
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result_gemini3flashpreview = VertexGeminiConfig._map_thinking_param(
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thinking_param=thinking_param,
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@ -11031,3 +11032,189 @@ def test_grounding_support_preserves_every_web_source(chunk_indices: list[int])
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}
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for index, start, end in expected_sources
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]
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@pytest.mark.parametrize(
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("model", "expected_is_gemini_3", "expected_supports_minimal"),
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[
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("gemini-3-flash", True, True),
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("gemini-3-flash-preview", True, True),
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("gemini-3.1-flash", True, True),
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("gemini-3.1-flash-lite-preview", True, True),
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("gemini-3.5-flash", True, True),
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("gemini-3.5-flash-preview", True, True),
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("gemini-3.5-flash-lite", True, True),
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("au.gemini-3.5-flash", True, True),
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("eu.gemini-3.5-flash", True, True),
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("us.gemini-3.5-flash", True, True),
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("ca.gemini-3.5-flash", True, True),
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("jp.gemini-3.5-flash", True, True),
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("uk.gemini-3.5-flash", True, True),
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("in.gemini-3.5-flash", True, True),
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("sg.gemini-3.5-flash", True, True),
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("kr.gemini-3.5-flash", True, True),
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("global.gemini-3.5-flash", True, True),
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("apac.gemini-3.5-flash", True, True),
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("us-central1.gemini-3.5-flash", True, True),
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("europe-west4.gemini-3.5-flash", True, True),
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("australia-southeast1.gemini-3.5-flash", True, True),
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("asia-northeast1.gemini-3.5-flash", True, True),
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("southamerica-east1.gemini-3.5-flash", True, True),
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("me-central1.gemini-3.5-flash", True, True),
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("vertex_ai/au.gemini-3.5-flash", True, True),
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("vertex_ai/eu.gemini-3.5-flash", True, True),
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("vertex_ai/us-central1.gemini-3.5-flash", True, True),
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("gemini/au.gemini-3.5-flash", True, True),
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("gemini/gemini-3.5-flash-preview", True, True),
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("gemini-3-pro", True, False),
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("gemini-3-pro-preview", True, False),
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("gemini-3.1-pro", True, False),
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("gemini-3.1-pro-preview", True, False),
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("gemini-3.5-pro", True, False),
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("au.gemini-3.1-pro", True, False),
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("eu.gemini-3.5-pro", True, False),
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("us-central1.gemini-3.5-pro", True, False),
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("vertex_ai/au.gemini-3.5-pro", True, False),
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("gemini-2.5-flash", False, False),
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("au.gemini-2.5-flash", False, False),
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("eu.gemini-2.5-pro", False, False),
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("us.gemini-2.5-flash", False, False),
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("us-central1.gemini-2.0-flash", False, False),
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("vertex_ai/au.gemini-2.5-flash", False, False),
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("gemini/eu.gemini-2.5-flash", False, False),
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("eu.gemma-3-27b-it", False, False),
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],
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)
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def test_gemini_3_helpers_with_regional_prefixes(
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local_model_cost_map: None,
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model: str,
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expected_is_gemini_3: bool,
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expected_supports_minimal: bool,
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) -> None:
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assert VertexGeminiConfig._is_gemini_3_or_newer(model) is expected_is_gemini_3
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assert VertexGeminiConfig._supports_minimal_thinking_level(model) is expected_supports_minimal
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@pytest.mark.parametrize(
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"model",
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[
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"gemini-3.5-flash",
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"au.gemini-3.5-flash",
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"eu.gemini-3.5-flash",
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"us.gemini-3.5-flash",
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"global.gemini-3.5-flash",
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"us-central1.gemini-3.5-flash",
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"europe-west4.gemini-3.5-flash",
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"australia-southeast1.gemini-3.5-flash",
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"vertex_ai/au.gemini-3.5-flash",
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"gemini/au.gemini-3.5-flash",
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"gemini-3.5-flash-preview",
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"gemini-3.1-flash",
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"gemini-3-flash",
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],
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)
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@pytest.mark.parametrize(
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("reasoning_effort", "expected"),
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[
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("none", {"thinkingLevel": "minimal", "includeThoughts": False}),
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("disable", {"thinkingLevel": "minimal", "includeThoughts": False}),
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("minimal", {"thinkingLevel": "minimal", "includeThoughts": True}),
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("low", {"thinkingLevel": "low", "includeThoughts": True}),
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("medium", {"thinkingLevel": "medium", "includeThoughts": True}),
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("high", {"thinkingLevel": "high", "includeThoughts": True}),
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],
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)
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def test_gemini_3_flash_reasoning_effort_mapping_all_regions(
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local_model_cost_map: None,
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model: str,
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reasoning_effort: str,
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expected: GeminiThinkingConfig,
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) -> None:
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result: Final = VertexGeminiConfig._map_reasoning_effort_to_thinking_level(
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reasoning_effort=reasoning_effort,
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model=model,
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)
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assert result == expected
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@pytest.mark.parametrize(
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"model",
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[
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"gemini-3.1-pro",
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"gemini-3.1-pro-preview",
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"gemini-3.5-pro",
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"au.gemini-3.1-pro",
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"eu.gemini-3.5-pro",
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"us-central1.gemini-3.5-pro",
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"vertex_ai/au.gemini-3.7-flash",
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"us-central1.gemini-3.8-flash",
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],
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)
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@pytest.mark.parametrize(
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("reasoning_effort", "expected"),
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[
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("none", {"thinkingLevel": "low", "includeThoughts": False}),
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("disable", {"thinkingLevel": "low", "includeThoughts": False}),
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("minimal", {"thinkingLevel": "low", "includeThoughts": True}),
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("low", {"thinkingLevel": "low", "includeThoughts": True}),
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("medium", {"thinkingLevel": "medium", "includeThoughts": True}),
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("high", {"thinkingLevel": "high", "includeThoughts": True}),
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],
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)
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def test_gemini_3_pro_and_37_38_flash_reasoning_effort_mapping_all_regions(
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local_model_cost_map: None,
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model: str,
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reasoning_effort: str,
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expected: GeminiThinkingConfig,
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) -> None:
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result: Final = VertexGeminiConfig._map_reasoning_effort_to_thinking_level(
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reasoning_effort=reasoning_effort,
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model=model,
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)
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assert result == expected
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@pytest.mark.parametrize(
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("model", "expected_level"),
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[
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("gemini-3.5-flash", "minimal"),
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("au.gemini-3.5-flash", "minimal"),
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("eu.gemini-3.5-flash", "minimal"),
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("us.gemini-3.5-flash", "minimal"),
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("us-central1.gemini-3.5-flash", "minimal"),
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("europe-west4.gemini-3.5-flash", "minimal"),
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("australia-southeast1.gemini-3.5-flash", "minimal"),
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("vertex_ai/au.gemini-3.5-flash", "minimal"),
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("gemini/eu.gemini-3.5-flash", "minimal"),
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("gemini-3.5-flash-preview", "minimal"),
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("gemini-3.1-flash", "minimal"),
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("gemini-3-flash", "minimal"),
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("gemini-3.1-pro", "low"),
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("gemini-3.1-pro-preview", "low"),
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("gemini-3.5-pro", "low"),
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("au.gemini-3.5-pro", "low"),
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("gemini-3.8-flash", "low"),
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("au.gemini-3.8-flash", "low"),
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],
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)
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@pytest.mark.parametrize(
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"thinking_param",
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[
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{"type": "disabled"},
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{"type": "enabled", "budget_tokens": 0},
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],
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)
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def test_map_thinking_param_disabled_or_zero_budget_gemini_3(
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local_model_cost_map: None,
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model: str,
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expected_level: str,
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thinking_param: AnthropicThinkingParam,
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) -> None:
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result: Final = VertexGeminiConfig._map_thinking_param(
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thinking_param=thinking_param,
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model=model,
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)
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assert result == {
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"thinkingLevel": expected_level,
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"includeThoughts": False,
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}
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