Vertex AI V1 API - Class Google::Cloud::AIPlatform::V1::CountTokensRequest (v0.58.0)

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Reference documentation and code samples for the Vertex AI V1 API class Google::Cloud::AIPlatform::V1::CountTokensRequest.

Request message for [PredictionService.CountTokens][].

Inherits

• Object

Extended By

• Google::Protobuf::MessageExts::ClassMethods

Includes

• Google::Protobuf::MessageExts

Methods

#contents

def contents() -> ::Array<::Google::Cloud::AIPlatform::V1::Content>

Returns

• (::Array<::Google::Cloud::AIPlatform::V1::Content>) — Optional. Input content.

#contents=

def contents=(value) -> ::Array<::Google::Cloud::AIPlatform::V1::Content>

Parameter

• value (::Array<::Google::Cloud::AIPlatform::V1::Content>) — Optional. Input content.

Returns

• (::Array<::Google::Cloud::AIPlatform::V1::Content>) — Optional. Input content.

#endpoint

def endpoint() -> ::String

Returns

• (::String) — Required. The name of the Endpoint requested to perform token counting. Format: projects/{project}/locations/{location}/endpoints/{endpoint}

#endpoint=

def endpoint=(value) -> ::String

Parameter

• value (::String) — Required. The name of the Endpoint requested to perform token counting. Format: projects/{project}/locations/{location}/endpoints/{endpoint}

Returns

• (::String) — Required. The name of the Endpoint requested to perform token counting. Format: projects/{project}/locations/{location}/endpoints/{endpoint}

#generation_config

def generation_config() -> ::Google::Cloud::AIPlatform::V1::GenerationConfig

Returns

• (::Google::Cloud::AIPlatform::V1::GenerationConfig) — Optional. Generation config that the model will use to generate the response.

#generation_config=

def generation_config=(value) -> ::Google::Cloud::AIPlatform::V1::GenerationConfig

Parameter

• value (::Google::Cloud::AIPlatform::V1::GenerationConfig) — Optional. Generation config that the model will use to generate the response.

Returns

• (::Google::Cloud::AIPlatform::V1::GenerationConfig) — Optional. Generation config that the model will use to generate the response.

#instances

def instances() -> ::Array<::Google::Protobuf::Value>

Returns

• (::Array<::Google::Protobuf::Value>) — Optional. The instances that are the input to token counting call. Schema is identical to the prediction schema of the underlying model.

#instances=

def instances=(value) -> ::Array<::Google::Protobuf::Value>

Parameter

• value (::Array<::Google::Protobuf::Value>) — Optional. The instances that are the input to token counting call. Schema is identical to the prediction schema of the underlying model.

Returns

• (::Array<::Google::Protobuf::Value>) — Optional. The instances that are the input to token counting call. Schema is identical to the prediction schema of the underlying model.

#model

def model() -> ::String

Returns

• (::String) — Optional. The name of the publisher model requested to serve the prediction. Format: projects/{project}/locations/{location}/publishers/*/models/*

#model=

def model=(value) -> ::String

Parameter

• value (::String) — Optional. The name of the publisher model requested to serve the prediction. Format: projects/{project}/locations/{location}/publishers/*/models/*

Returns

• (::String) — Optional. The name of the publisher model requested to serve the prediction. Format: projects/{project}/locations/{location}/publishers/*/models/*

#system_instruction

def system_instruction() -> ::Google::Cloud::AIPlatform::V1::Content

Returns

• (::Google::Cloud::AIPlatform::V1::Content) — Optional. The user provided system instructions for the model. Note: only text should be used in parts and content in each part will be in a separate paragraph.

#system_instruction=

def system_instruction=(value) -> ::Google::Cloud::AIPlatform::V1::Content

Parameter

• value (::Google::Cloud::AIPlatform::V1::Content) — Optional. The user provided system instructions for the model. Note: only text should be used in parts and content in each part will be in a separate paragraph.

Returns

• (::Google::Cloud::AIPlatform::V1::Content) — Optional. The user provided system instructions for the model. Note: only text should be used in parts and content in each part will be in a separate paragraph.

#tools

def tools() -> ::Array<::Google::Cloud::AIPlatform::V1::Tool>

Returns

• (::Array<::Google::Cloud::AIPlatform::V1::Tool>) — Optional. A list of Tools the model may use to generate the next response.

  A Tool is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model.

#tools=

def tools=(value) -> ::Array<::Google::Cloud::AIPlatform::V1::Tool>

Parameter

• value (::Array<::Google::Cloud::AIPlatform::V1::Tool>) — Optional. A list of Tools the model may use to generate the next response.

  A Tool is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model.

Returns

• (::Array<::Google::Cloud::AIPlatform::V1::Tool>) — Optional. A list of Tools the model may use to generate the next response.

  A Tool is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model.