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feat: Weekly Discovery Doc update #2919

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143 changes: 143 additions & 0 deletions google/genai/tunings.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -222,6 +222,38 @@ def _CompositeReinforcementTuningRewardConfig_to_vertex(
return to_object


def _ComputerUse_to_vertex(
from_object: Union[dict[str, Any], object],
parent_object: Optional[dict[str, Any]] = None,
root_object: Optional[Union[dict[str, Any], object]] = None,
) -> dict[str, Any]:
to_object: dict[str, Any] = {}
if getv(from_object, ['environment']) is not None:
setv(to_object, ['environment'], getv(from_object, ['environment']))

if getv(from_object, ['excluded_predefined_functions']) is not None:
setv(
to_object,
['excludedPredefinedFunctions'],
getv(from_object, ['excluded_predefined_functions']),
)

if getv(from_object, ['enable_prompt_injection_detection']) is not None:
setv(
to_object,
['enablePromptInjectionDetection'],
getv(from_object, ['enable_prompt_injection_detection']),
)

if getv(from_object, ['disabled_safety_policies']) is not None:
raise ValueError(
'disabled_safety_policies parameter is only supported in Gemini'
' Developer API mode, not in Gemini Enterprise Agent Platform mode.'
)

return to_object


def _Content_to_vertex(
from_object: Union[dict[str, Any], object],
parent_object: Optional[dict[str, Any]] = None,
Expand Down Expand Up @@ -1441,6 +1473,27 @@ def _ListTuningJobsResponse_from_vertex(
return to_object


def _McpServer_to_vertex(
from_object: Union[dict[str, Any], object],
parent_object: Optional[dict[str, Any]] = None,
root_object: Optional[Union[dict[str, Any], object]] = None,
) -> dict[str, Any]:
to_object: dict[str, Any] = {}
if getv(from_object, ['name']) is not None:
raise ValueError(
'name parameter is only supported in Gemini Developer API mode, not in'
' Gemini Enterprise Agent Platform mode.'
)

if getv(from_object, ['streamable_http_transport']) is not None:
raise ValueError(
'streamable_http_transport parameter is only supported in Gemini'
' Developer API mode, not in Gemini Enterprise Agent Platform mode.'
)

return to_object


def _MultiSpeakerVoiceConfig_to_vertex(
from_object: Union[dict[str, Any], object],
parent_object: Optional[dict[str, Any]] = None,
Expand Down Expand Up @@ -1662,6 +1715,16 @@ def _ReinforcementTuningExample_to_vertex(
),
)

if getv(from_object, ['tools']) is not None:
setv(
to_object,
['tools'],
[
_Tool_to_vertex(item, to_object, root_object)
for item in getv(from_object, ['tools'])
],
)

return to_object


Expand Down Expand Up @@ -1893,6 +1956,86 @@ def _SpeechConfig_to_vertex(
return to_object


def _Tool_to_vertex(
from_object: Union[dict[str, Any], object],
parent_object: Optional[dict[str, Any]] = None,
root_object: Optional[Union[dict[str, Any], object]] = None,
) -> dict[str, Any]:
to_object: dict[str, Any] = {}
if getv(from_object, ['retrieval']) is not None:
setv(to_object, ['retrieval'], getv(from_object, ['retrieval']))

if getv(from_object, ['computer_use']) is not None:
setv(
to_object,
['computerUse'],
_ComputerUse_to_vertex(
getv(from_object, ['computer_use']), to_object, root_object
),
)

if getv(from_object, ['file_search']) is not None:
raise ValueError(
'file_search parameter is only supported in Gemini Developer API mode,'
' not in Gemini Enterprise Agent Platform mode.'
)

if getv(from_object, ['google_search']) is not None:
setv(to_object, ['googleSearch'], getv(from_object, ['google_search']))

if getv(from_object, ['google_maps']) is not None:
setv(to_object, ['googleMaps'], getv(from_object, ['google_maps']))

if getv(from_object, ['code_execution']) is not None:
setv(to_object, ['codeExecution'], getv(from_object, ['code_execution']))

if getv(from_object, ['enterprise_web_search']) is not None:
setv(
to_object,
['enterpriseWebSearch'],
getv(from_object, ['enterprise_web_search']),
)

if getv(from_object, ['function_declarations']) is not None:
setv(
to_object,
['functionDeclarations'],
[item for item in getv(from_object, ['function_declarations'])],
)

if getv(from_object, ['google_search_retrieval']) is not None:
setv(
to_object,
['googleSearchRetrieval'],
getv(from_object, ['google_search_retrieval']),
)

if getv(from_object, ['parallel_ai_search']) is not None:
setv(
to_object,
['parallelAiSearch'],
getv(from_object, ['parallel_ai_search']),
)

if getv(from_object, ['url_context']) is not None:
setv(to_object, ['urlContext'], getv(from_object, ['url_context']))

if getv(from_object, ['mcp_servers']) is not None:
setv(
to_object,
['mcpServers'],
[
_McpServer_to_vertex(item, to_object, root_object)
for item in getv(from_object, ['mcp_servers'])
],
)

if getv(from_object, ['exa_ai_search']) is not None:
setv(to_object, ['exaAiSearch'], getv(from_object, ['exa_ai_search']))

return to_object


def _TunedModel_from_mldev(
from_object: Union[dict[str, Any], object],
parent_object: Optional[dict[str, Any]] = None,
Expand Down
81 changes: 59 additions & 22 deletions google/genai/types.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -173,6 +173,17 @@ def __getattr__(name: str) -> Any:
MetricSubclass = typing.TypeVar('MetricSubclass', bound='Metric')


class MediaProcessing(_common.CaseInSensitiveEnum):
"""How the model processes input media for understanding."""

MEDIA_PROCESSING_UNSPECIFIED = 'MEDIA_PROCESSING_UNSPECIFIED'
"""Default. Uses model-specific processing"""
STATIC = 'STATIC'
"""Fixed-rate frame extraction. All frames placed in context."""
AGENTIC = 'AGENTIC'
"""Model-driven dynamic navigation. Recommended for most use cases."""


class Outcome(_common.CaseInSensitiveEnum):
"""Outcome of the code execution."""

Expand Down Expand Up @@ -485,6 +496,17 @@ class FunctionCallingConfigMode(_common.CaseInSensitiveEnum):
"""Model is constrained to predict either function calls or natural language response. If "allowed_function_names" are set, the predicted function calls will be limited to any one of "allowed_function_names", else the predicted function calls will be any one of the provided "function_declarations"."""


class AudioTranscriptionConfigMode(_common.CaseInSensitiveEnum):
"""Transcription mode."""

MODE_UNSPECIFIED = 'MODE_UNSPECIFIED'
"""Unspecified transcription mode."""
VERBATIM = 'VERBATIM'
"""Verbatim transcription mode."""
SMART = 'SMART'
"""Smart transcription mode."""


class FinishReason(_common.CaseInSensitiveEnum):
"""Output only. The reason why the model stopped generating tokens.

Expand Down Expand Up @@ -613,6 +635,8 @@ class TrafficType(_common.CaseInSensitiveEnum):
"""Type for Priority Pay-As-You-Go traffic."""
ON_DEMAND_FLEX = 'ON_DEMAND_FLEX'
"""Type for Flex traffic."""
ON_DEMAND_OFFPEAK = 'ON_DEMAND_OFFPEAK'
"""Type for Off-Peak Pay-As-You-Go traffic."""
PROVISIONED_THROUGHPUT = 'PROVISIONED_THROUGHPUT'
"""Type for Provisioned Throughput traffic."""

Expand Down Expand Up @@ -1013,17 +1037,6 @@ class ComputationBasedMetricType(_common.CaseInSensitiveEnum):
"""ROUGE metric."""


class MediaProcessing(_common.CaseInSensitiveEnum):
"""How the model processes input media for understanding."""

MEDIA_PROCESSING_UNSPECIFIED = 'MEDIA_PROCESSING_UNSPECIFIED'
"""Default. Uses model-specific processing"""
STATIC = 'STATIC'
"""Fixed-rate frame extraction. All frames placed in context."""
AGENTIC = 'AGENTIC'
"""Model-driven dynamic navigation. Recommended for most use cases."""


class PartMediaResolutionLevel(_common.CaseInSensitiveEnum):
"""The tokenization quality used for given media."""

Expand Down Expand Up @@ -1373,17 +1386,6 @@ class VoiceActivityType(_common.CaseInSensitiveEnum):
"""End of sentence signal."""


class AudioTranscriptionConfigMode(_common.CaseInSensitiveEnum):
"""Transcription mode."""

MODE_UNSPECIFIED = 'MODE_UNSPECIFIED'
"""Unspecified transcription mode."""
VERBATIM = 'VERBATIM'
"""Verbatim transcription mode."""
SMART = 'SMART'
"""Smart transcription mode."""


class StartSensitivity(_common.CaseInSensitiveEnum):
"""Start of speech sensitivity."""

Expand Down Expand Up @@ -11324,6 +11326,10 @@ class VideoResponseFormat(_common.BaseModel):
default=None,
description="""Optional. The Google Cloud Storage URI to store the video output. Required for Vertex if delivery is URI.""",
)
resolution: Optional[str] = Field(
default=None,
description="""Optional. The video output resolution. Supported values: "360p", "720p", "1080p", "4k".""",
)


class VideoResponseFormatDict(TypedDict, total=False):
Expand All @@ -11344,6 +11350,9 @@ class VideoResponseFormatDict(TypedDict, total=False):
gcs_uri: Optional[str]
"""Optional. The Google Cloud Storage URI to store the video output. Required for Vertex if delivery is URI."""

resolution: Optional[str]
"""Optional. The video output resolution. Supported values: "360p", "720p", "1080p", "4k"."""


VideoResponseFormatOrDict = Union[VideoResponseFormat, VideoResponseFormatDict]

Expand Down Expand Up @@ -14062,6 +14071,10 @@ class ReinforcementTuningExample(_common.BaseModel):
default=None,
description="""Corresponds to system_instruction in user-facing GenerateContentRequest.""",
)
tools: Optional[list[Tool]] = Field(
default=None,
description="""Optional. Corresponds to tools in user-facing GenerateContentRequest.""",
)


class ReinforcementTuningExampleDict(TypedDict, total=False):
Expand All @@ -14076,6 +14089,9 @@ class ReinforcementTuningExampleDict(TypedDict, total=False):
system_instruction: Optional[ContentDict]
"""Corresponds to system_instruction in user-facing GenerateContentRequest."""

tools: Optional[list[ToolDict]]
"""Optional. Corresponds to tools in user-facing GenerateContentRequest."""


ReinforcementTuningExampleOrDict = Union[
ReinforcementTuningExample, ReinforcementTuningExampleDict
Expand Down Expand Up @@ -16364,6 +16380,10 @@ class ReinforcementTuningRewardInfo(_common.BaseModel):
default=None,
description="""Output only. The user-requested auxiliary info for the reward function. This field is set only if the Cloud Run reward function configured by user returns a "user_requested_aux_info". Refer to ReinforcementTuningCloudRunRewardScorer for more details.""",
)
error_status: Optional[GoogleRpcStatus] = Field(
default=None,
description="""Output only. In case of an error for this reward, this field will be populated with a detailed error status.""",
)


class ReinforcementTuningRewardInfoDict(TypedDict, total=False):
Expand All @@ -16375,6 +16395,9 @@ class ReinforcementTuningRewardInfoDict(TypedDict, total=False):
user_requested_aux_info: Optional[str]
"""Output only. The user-requested auxiliary info for the reward function. This field is set only if the Cloud Run reward function configured by user returns a "user_requested_aux_info". Refer to ReinforcementTuningCloudRunRewardScorer for more details."""

error_status: Optional[GoogleRpcStatusDict]
"""Output only. In case of an error for this reward, this field will be populated with a detailed error status."""


ReinforcementTuningRewardInfoOrDict = Union[
ReinforcementTuningRewardInfo, ReinforcementTuningRewardInfoDict
Expand Down Expand Up @@ -23094,6 +23117,10 @@ class EvaluationParserConfigCustomCodeParserConfig(_common.BaseModel):
default=None,
description="""Required. Python function for parsing results. The function should be defined within this string. The function takes a list of strings (LLM responses) and should return either a list of dictionaries (for rubrics) or a single dictionary (for a metric result). Example function signature: def parse(responses: list[str]) -> list[dict[str, Any]] | dict[str, Any]: When parsing rubrics, return a list of dictionaries, where each dictionary represents a Rubric. Example for rubrics: [ { "content": {"property": {"description": "The response is factual."}}, "type": "FACTUALITY", "importance": "HIGH" }, { "content": {"property": {"description": "The response is fluent."}}, "type": "FLUENCY", "importance": "MEDIUM" } ] When parsing critique results, return a dictionary representing a MetricResult. Example for a metric result: { "score": 0.8, "explanation": "The model followed most instructions.", "rubric_verdicts": [...] } ... code for result extraction and aggregation""",
)
code_execution_region: Optional[str] = Field(
default=None,
description="""Optional. The region to use for code execution. If set, the Code Execution Sandbox will be invoked in the specified region regardless of the request's originating region. Must be a region where the Code Execution Sandbox is available. Supported regions: us-central1, us-east1, us-east4, us-west1, us-west4, southamerica-east1, europe-west2, europe-west3, asia-east1, asia-south1, asia-southeast1. If unset, the request's originating region is used.""",
)


class EvaluationParserConfigCustomCodeParserConfigDict(TypedDict, total=False):
Expand All @@ -23105,6 +23132,9 @@ class EvaluationParserConfigCustomCodeParserConfigDict(TypedDict, total=False):
parsing_function: Optional[str]
"""Required. Python function for parsing results. The function should be defined within this string. The function takes a list of strings (LLM responses) and should return either a list of dictionaries (for rubrics) or a single dictionary (for a metric result). Example function signature: def parse(responses: list[str]) -> list[dict[str, Any]] | dict[str, Any]: When parsing rubrics, return a list of dictionaries, where each dictionary represents a Rubric. Example for rubrics: [ { "content": {"property": {"description": "The response is factual."}}, "type": "FACTUALITY", "importance": "HIGH" }, { "content": {"property": {"description": "The response is fluent."}}, "type": "FLUENCY", "importance": "MEDIUM" } ] When parsing critique results, return a dictionary representing a MetricResult. Example for a metric result: { "score": 0.8, "explanation": "The model followed most instructions.", "rubric_verdicts": [...] } ... code for result extraction and aggregation"""

code_execution_region: Optional[str]
"""Optional. The region to use for code execution. If set, the Code Execution Sandbox will be invoked in the specified region regardless of the request's originating region. Must be a region where the Code Execution Sandbox is available. Supported regions: us-central1, us-east1, us-east4, us-west1, us-west4, southamerica-east1, europe-west2, europe-west3, asia-east1, asia-south1, asia-southeast1. If unset, the request's originating region is used."""


EvaluationParserConfigCustomCodeParserConfigOrDict = Union[
EvaluationParserConfigCustomCodeParserConfig,
Expand Down Expand Up @@ -23228,6 +23258,10 @@ def evaluate(instance: dict[str, Any]) -> float:
Instance is the evaluation instance, any fields populated in the instance
are available to the function as instance[field_name].""",
)
code_execution_region: Optional[str] = Field(
default=None,
description="""Optional. The region to use for code execution. If set, the Code Execution Sandbox will be invoked in the specified region regardless of the request's originating region. Must be a region where the Code Execution Sandbox is available. Supported regions: us-central1, us-east1, us-east4, us-west1, us-west4, southamerica-east1, europe-west2, europe-west3, asia-east1, asia-south1, asia-southeast1. If unset, the request's originating region is used; requests from regions where the sandbox is unavailable will fail with UNIMPLEMENTED.""",
)


class CustomCodeExecutionSpecDict(TypedDict, total=False):
Expand All @@ -23241,6 +23275,9 @@ def evaluate(instance: dict[str, Any]) -> float:
Instance is the evaluation instance, any fields populated in the instance
are available to the function as instance[field_name]."""

code_execution_region: Optional[str]
"""Optional. The region to use for code execution. If set, the Code Execution Sandbox will be invoked in the specified region regardless of the request's originating region. Must be a region where the Code Execution Sandbox is available. Supported regions: us-central1, us-east1, us-east4, us-west1, us-west4, southamerica-east1, europe-west2, europe-west3, asia-east1, asia-south1, asia-southeast1. If unset, the request's originating region is used; requests from regions where the sandbox is unavailable will fail with UNIMPLEMENTED."""


CustomCodeExecutionSpecOrDict = Union[
CustomCodeExecutionSpec, CustomCodeExecutionSpecDict
Expand Down
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