YandexGPT API, gRPC: EmbeddingsService.Embedding

Статья создана

Обновлена 17 октября 2024 г.

RPC method to obtain embeddings for input text data.

gRPC request

{
  "embeddingType": "EmbeddingType",
  "model": "string",
  "text": "string"
}

Represents a request to obtain embeddings for text data.

Field	Description
embeddingType	enum EmbeddingType The type of embedding to be generated. `EMBEDDING_TYPE_UNSPECIFIED`: Unspecified embedding type. `EMBEDDING_TYPE_QUERY`: Embedding for a query. Use this when you have a short query or search term that you want to obtain an embedding for. Query embeddings are typically used in information retrieval and search applications. `EMBEDDING_TYPE_DOCUMENT`: Embedding for a document. Use this when you have a longer document or a piece of text that you want to obtain an embedding for. Document embeddings are often used in natural language understanding and document similarity tasks.
model	string The name or identifier of the model to be used for embedding. Possible value for now: `general:embedding`.
text	string The input text for which the embedding is requested.

{
  "embedding": [
    "double"
  ],
  "numTokens": "int64"
}

Represents a response containing embeddings for input text data.

Field

Description

embedding[]

double

A repeated list of double values representing the embedding.

numTokens

int64

The number of tokens in the input text.