Method: models.embedContent

Full name: projects.locations.publishers.models.embedContent

Embed content with multimodal inputs.

Endpoint

post https://aiplatform.googleapis.com/v1/{model}:embedContent

Path parameters

model string

Required. The name of the publisher model requested to serve the prediction. Format: projects/{project}/locations/{location}/publishers/*/models/*

Request body

The request body contains data with the following structure:

Fields
content object (Content)

Required. Input content to be embedded. Required.

title string

Optional. An optional title for the text.

taskType enum (EmbeddingTaskType)

Optional. The task type of the embedding.

outputDimensionality integer

Optional. Optional reduced dimension for the output embedding. If set, excessive values in the output embedding are truncated from the end.

autoTruncate boolean

Optional. Whether to silently truncate the input content if it's longer than the maximum sequence length.

Response body

Response message for PredictionService.EmbedContent.

If successful, the response body contains data with the following structure:

Fields
embedding object (Embedding)

The embedding generated from the input content.

usageMetadata object (UsageMetadata)

metadata about the response(s).

truncated boolean

Whether the input content was truncated before generating the embedding.

JSON representation 
{
  "embedding": {
    object (Embedding)
  },
  "usageMetadata": {
    object (UsageMetadata)
  },
  "truncated": boolean
}

EmbeddingTaskType

Represents a downstream task the embeddings will be used for.

Enums
UNSPECIFIED Unset value, which will default to one of the other enum values.
RETRIEVAL_QUERY Specifies the given text is a query in a search/retrieval setting.
RETRIEVAL_DOCUMENT Specifies the given text is a document from the corpus being searched.
SEMANTIC_SIMILARITY Specifies the given text will be used for STS.
CLASSIFICATION Specifies that the given text will be classified.
CLUSTERING Specifies that the embeddings will be used for clustering.
QUESTION_ANSWERING Specifies that the embeddings will be used for question answering.
FACT_VERIFICATION Specifies that the embeddings will be used for fact verification.
CODE_RETRIEVAL_QUERY Specifies that the embeddings will be used for code retrieval.

Embedding

A list of floats representing an embedding.

Fields
values[] number

Embedding vector values.

JSON representation 
{
  "values": [
    number
  ]
}

UsageMetadata

Usage metadata about the content generation request and response. This message provides a detailed breakdown of token usage and other relevant metrics.

Fields
promptTokenCount integer

The total number of tokens in the prompt. This includes any text, images, or other media provided in the request. When cachedContent is set, this also includes the number of tokens in the cached content.

candidatesTokenCount integer

The total number of tokens in the generated candidates.

totalTokenCount integer

The total number of tokens for the entire request. This is the sum of promptTokenCount, candidatesTokenCount, toolUsePromptTokenCount, and thoughtsTokenCount.

toolUsePromptTokenCount integer

Output only. The number of tokens in the results from tool executions, which are provided back to the model as input, if applicable.

thoughtsTokenCount integer

Output only. The number of tokens that were part of the model's generated "thoughts" output, if applicable.

cachedContentTokenCount integer

Output only. The number of tokens in the cached content that was used for this request.

promptTokensDetails[] object (ModalityTokenCount)

Output only. A detailed breakdown of the token count for each modality in the prompt.

cacheTokensDetails[] object (ModalityTokenCount)

Output only. A detailed breakdown of the token count for each modality in the cached content.

candidatesTokensDetails[] object (ModalityTokenCount)

Output only. A detailed breakdown of the token count for each modality in the generated candidates.

toolUsePromptTokensDetails[] object (ModalityTokenCount)

Output only. A detailed breakdown by modality of the token counts from the results of tool executions, which are provided back to the model as input.

trafficType enum (TrafficType)

Output only. The traffic type for this request.

JSON representation 
{
  "promptTokenCount": integer,
  "candidatesTokenCount": integer,
  "totalTokenCount": integer,
  "toolUsePromptTokenCount": integer,
  "thoughtsTokenCount": integer,
  "cachedContentTokenCount": integer,
  "promptTokensDetails": [
    {
      object (ModalityTokenCount)
    }
  ],
  "cacheTokensDetails": [
    {
      object (ModalityTokenCount)
    }
  ],
  "candidatesTokensDetails": [
    {
      object (ModalityTokenCount)
    }
  ],
  "toolUsePromptTokensDetails": [
    {
      object (ModalityTokenCount)
    }
  ],
  "trafficType": enum (TrafficType)
}

TrafficType

The type of traffic that this request was processed with, indicating which quota gets consumed.

Enums
TRAFFIC_TYPE_UNSPECIFIED Unspecified request traffic type.
ON_DEMAND type for Pay-As-You-Go traffic.
PROVISIONED_THROUGHPUT type for Provisioned Throughput traffic.