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EmbeddingsRequest ​

Request parameters for creating embeddings. Generates vector representations of the input text(s).

Example Usage ​

typescript
import { EmbeddingsRequest } from "@meetkai/mka1/models/components";

let value: EmbeddingsRequest = {
  input: "The quick brown fox jumps over the lazy dog.",
  model: "auto",
};

Fields ​

FieldTypeRequiredDescription
inputcomponents.EmbeddingsRequestInput✔️The input text or array of texts to generate embeddings for. Can be a single string or an array of strings. Note: batch size and input length limits vary by model. See GET /embeddings/models for model-specific limits.
modelstring✔️ID of the model to use for generating embeddings. Use provider:model format. See GET /embeddings/models for available models and their limits.
dimensionsnumber➖The number of dimensions the resulting output embeddings should have. Only supported in certain models.
encodingFormatcomponents.EncodingFormat➖The format to return the embeddings in. Can be either 'float' (array of numbers) or 'base64' (base64-encoded binary).
userstring➖A unique identifier representing your end-user.