interface CreateMinimaxEmbeddingRequest {
    model: string;
    texts: string[];
    type: "query" | "db";
}

Properties

Properties

model: string

CreateMinimaxEmbeddingRequest

texts: string[]

Text to generate vector expectation

CreateMinimaxEmbeddingRequest

type: "query" | "db"

The target use-case after generating the vector. When using embeddings, first generate the vector of the target content through the db and store it in the vector database, and then generate the vector of the retrieval text through the query. Note: For the parameter of the algorithm, we use the algorithm scheme of query and db separation, so a text, if it is to be retrieved as a text, should use the db, if it is used as a retrieval text, should use the query.

CreateMinimaxEmbeddingRequest

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