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Google Gemini (Independent Publisher) (Preview)

  • Reference

Custom connector for Google Gemini, providing advanced AI multi modal content generation functionalities.Gemini is a family of multimodal large language models developed by Google DeepMind, serving as the successor to LaMDA and PaLM 2. Comprising Gemini Ultra, Gemini Pro, and Gemini Nano, it was announced on December 6, 2023

This connector is available in the following products and regions:

Service Class Regions
Logic Apps Standard All Logic Apps regions except the following:
     -   Azure Government regions
     -   Azure China regions
     -   US Department of Defense (DoD)
Power Automate Premium All Power Automate regions except the following:
     -   US Government (GCC)
     -   US Government (GCC High)
     -   China Cloud operated by 21Vianet
     -   US Department of Defense (DoD)
Power Apps Premium All Power Apps regions except the following:
     -   US Government (GCC)
     -   US Government (GCC High)
     -   China Cloud operated by 21Vianet
     -   US Department of Defense (DoD)
Contact
Name Priyaranjan KS , Vidya Sagar Alti [Tata Consultancy Services]
URL https://www.tcs.com
Email priyaranjan.sathyavrathan@tcs.com
Connector Metadata
Publisher Priyaranjan KS , Vidya Sagar Alti [Tata Consultancy Services]
Website https://ai.google.dev/
Privacy policy https://policies.google.com/privacy
Categories AI

Creating a connection

The connector supports the following authentication types:
Default Parameters for creating connection. All regions Not shareable

Default

Applicable: All regions

Parameters for creating connection.

This is not shareable connection. If the power app is shared with another user, another user will be prompted to create new connection explicitly.

Name Type Description Required
API Key securestring The API Key for this api True

Throttling Limits

Name Calls Renewal Period
API calls per connection 100 60 seconds

Actions

Count tokens

Counts the number of tokens in a given text using the Generative Language Model.
Generate batch embeddings

Generates embedding vectors for a batch of text contents.
Generate embedding

This endpoint is designed to generate an embedding vector for the provided text content, which can be used for various natural language processing tasks such as text similarity, classification, and clustering.
Generate multi modal content

Generates a response from the model given an input message and an image or video.
Generate stream content

By default, the model returns a response after completing the entire generation process. You can achieve faster interactions by not waiting for the entire result, and instead use streaming to handle partial results.
Generate text content

Generates a text response from the model given an input message.
Get all models

Retrieves a list of all available models with their details.
Get model details

Retrieves details of a specific model based on the provided model name.

Count tokens

Operation ID:
countTokens

Counts the number of tokens in a given text using the Generative Language Model.

Parameters

Name Key Required Type Description
API Version
 apiVersion True string

API version to use for the vision endpoint.Eg- 'v1beta'
Model Name
 modelName True string

Model name, Eg- 'gemini-pro'.
Text
 text string

Required. Text content for which the token count is to be determined.

Returns

Name Path Type Description
totalTokens
 totalTokens integer

The total number of tokens in the provided text.

Generate batch embeddings

Operation ID:
batchEmbedContents

Generates embedding vectors for a batch of text contents.

Parameters

Name Key Required Type Description
API Version
 apiVersion True string

API version, Eg- 'v1beta'.
Model Name
 modelName True string

Model name, Eg- 'embedding-001'.
Model
 model True string

Identifier of the model used for embedding generation.This should match the format 'models/{modelName}'.
Text
 text string

Required.The text content for which the embedding is generated.

Returns

Name Path Type Description
embeddings
 embeddings array of object
values
 embeddings.values array of number

An array of numerical values representing the generated embedding.

Generate embedding

Operation ID:
generateEmbedding

This endpoint is designed to generate an embedding vector for the provided text content, which can be used for various natural language processing tasks such as text similarity, classification, and clustering.

Parameters

Name Key Required Type Description
API Version
 apiVersion True string

The version of the API to be used. This parameter defines the versioning scheme of the API endpoint. Eg- 'v1beta'
Model Name
 modelName True string

The name of the model to be used for generating the embedding. The model name should correspond to one of the models available in the API. Eg- 'embedding-001'
Model Resource Name
 model True string

Identifier of the model used for embedding generation. This should match the format 'models/{modelName}'.
Text
 text string

Required.The text content for which the embedding is generated.
Task Type
 taskType string

Optional.The type of task for which the embedding is intended. This parameter helps the model to understand the context in which the embedding is generated.
Title
 title string

Optional.An optional title for the content. This is applicable for certain task types like RETRIEVAL_DOCUMENT.

Returns

Name Path Type Description
values
 embedding.values array of number

An array of numerical values representing the generated embedding.

Generate multi modal content

Operation ID:
GenerateMultiModalContent

Generates a response from the model given an input message and an image or video.

Parameters

Name Key Required Type Description
API Version
 apiVersion True string

API version to use for the vision endpoint.Eg- v1beta
Base Model Name
 modelName True string

Name of the base model.Eg- Enter gemini-pro and corresponding vision model (gemini-pro-vision) will be used
Role
 role string

Optional. The producer of the content. Must be either 'user' or 'model'
Parts
 Parts object
Category
 category string

Optional.The category of content to be filtered.
Threshold
 threshold string

Optional.The threshold for filtering content in the specified category.
Max Output Tokens
 maxOutputTokens integer

Optional.The maximum number of tokens to include in a vision candidate.
Temperature
 temperature number

Optional.Controls the randomness of the vision output.
Top P
 topP number

Optional.The maximum cumulative probability of tokens to consider when sampling.
Top K
 topK integer

Optional.The maximum number of tokens to consider when sampling.
Stop Sequences
 stopSequences array of string

Optional.The set of character sequences that will stop text output generation.

Returns

Name Path Type Description
candidates
 candidates array of object
parts
 candidates.content.parts array of object
items
 candidates.content.parts object
finishReason
 candidates.finishReason string
index
 candidates.index integer
safetyRatings
 candidates.safetyRatings array of object
category
 candidates.safetyRatings.category string
probability
 candidates.safetyRatings.probability string
safetyRatings
 promptFeedback.safetyRatings array of object
category
 promptFeedback.safetyRatings.category string
probability
 promptFeedback.safetyRatings.probability string

Generate stream content

Operation ID:
generateStreamContent

By default, the model returns a response after completing the entire generation process. You can achieve faster interactions by not waiting for the entire result, and instead use streaming to handle partial results.

Parameters

Name Key Required Type Description
API Version
 apiVersion True string

API version, Eg- 'v1beta'.
Model Name
 modelName True string

Model name, Eg- 'gemini-pro'.
Role
 role string

The producer of the content. Must be either 'user' or 'model'
Text
 text string

Required. Text content to be processed.
Category
 category string

Optional. Category of content to be filtered.
Threshold
 threshold string

Optional. Threshold level for content filtering.
Temperature
 temperature number

Optional. Controls randomness in the response. Higher values lead to more varied responses.
Max Output Tokens
 maxOutputTokens integer

Optional. Maximum number of tokens in the generated content.
Top P
 topP number

Optional. Controls diversity of the response. Higher values lead to more diverse responses.
Top K
 topK integer

Optional. Limits the number of high-probability tokens considered at each step.
Candidate Count
 candidateCount integer

Optional. Number of candidate responses to generate.
Stop Sequences
 stopSequences array of string

Optional.The set of character sequences that will stop text output generation.

Returns

Name Path Type Description
array of object
candidates
 candidates array of object
parts
 candidates.content.parts array of object
text
 candidates.content.parts.text string
role
 candidates.content.role string
finishReason
 candidates.finishReason string
index
 candidates.index integer
safetyRatings
 candidates.safetyRatings array of object
category
 candidates.safetyRatings.category string
probability
 candidates.safetyRatings.probability string
safetyRatings
 promptFeedback.safetyRatings array of object
category
 promptFeedback.safetyRatings.category string
probability
 promptFeedback.safetyRatings.probability string

Generate text content

Operation ID:
GenerateTextContent

Generates a text response from the model given an input message.

Parameters

Name Key Required Type Description
API Version
 apiVersion True string

API version to use for the endpoint. Eg- v1beta
Model Name
 modelName True string

Name of the model to be used for text generation. Eg - gemini-pro
Role
 role string

Optional. The producer of the content. Must be either 'user' or 'model'
Text
 text True string

Required.Text for generating the response.
Category
 category string

Optional.The category of content to be filtered.
Threshold
 threshold string

Optional.The threshold for filtering content in the specified category.
Max Output Tokens
 maxOutputTokens integer

Optional.The maximum number of tokens to include in a text candidate.
Temperature
 temperature number

Optional.Controls the randomness of the text output.
Top P
 topP number

Optional.The maximum cumulative probability of tokens to consider when sampling.
Top K
 topK integer

Optional.The maximum number of tokens to consider when sampling.
Candidate Count
 candidateCount integer

Optional. Number of candidate responses to generate.
Stop Sequences
 stopSequences array of string

Optional.The set of character sequences that will stop text output generation.

Returns

Name Path Type Description
candidates
 candidates array of object
parts
 candidates.content.parts array of object
text
 candidates.content.parts.text string
finishReason
 candidates.finishReason string
index
 candidates.index integer
safetyRatings
 candidates.safetyRatings array of object
category
 candidates.safetyRatings.category string
probability
 candidates.safetyRatings.probability string
safetyRatings
 promptFeedback.safetyRatings array of object
category
 promptFeedback.safetyRatings.category string
probability
 promptFeedback.safetyRatings.probability string

Get all models

Operation ID:
getAllModels

Retrieves a list of all available models with their details.

Parameters

Name Key Required Type Description
API Version
 apiVersion True string

API version, Eg- 'v1beta'.

Returns

Name Path Type Description
models
 models array of object
name
 models.name string

Unique identifier of the model.
version
 models.version string

Version of the model.
displayName
 models.displayName string

Display name of the model.
description
 models.description string

Description of the model.
inputTokenLimit
 models.inputTokenLimit integer

The maximum number of input tokens the model can handle.
outputTokenLimit
 models.outputTokenLimit integer

The maximum number of output tokens the model can generate.
supportedGenerationMethods
 models.supportedGenerationMethods array of string

List of supported generation methods by the model.
temperature
 models.temperature number

Default temperature setting for the model. Not present for all models.
topP
 models.topP number

Default topP setting for the model. Not present for all models.
topK
 models.topK number

Default topK setting for the model. Not present for all models.

Get model details

Operation ID:
getModelDetails

Retrieves details of a specific model based on the provided model name.

Parameters

Name Key Required Type Description
API Version
 apiVersion True string

API version, Eg- 'v1beta'.
Model Name
 modelName True string

Model name, Eg- 'gemini-pro'.

Returns

Name Path Type Description
name
 name string

Unique identifier of the model.
version
 version string

Version of the model.
displayName
 displayName string

Display name of the model.
description
 description string

Description of the model.
inputTokenLimit
 inputTokenLimit integer

The maximum number of input tokens the model can handle.
outputTokenLimit
 outputTokenLimit integer

The maximum number of output tokens the model can generate.
supportedGenerationMethods
 supportedGenerationMethods array of string

List of supported generation methods by the model.
temperature
 temperature number

Default temperature setting for the model.
topP
 topP number

Default topP setting for the model.
topK
 topK number

Default topK setting for the model.