Create an Embed Job

ID of the embedding model.

Available models and corresponding embedding dimensions:

• embed-english-v3.0 : 1024
• embed-multilingual-v3.0 : 1024
• embed-english-light-v3.0 : 384
• embed-multilingual-light-v3.0 : 384

ID of a Dataset. The Dataset must be of type embed-input and must have a validation status Validated

Specifies the type of input passed to the model. Required for embedding models v3 and higher.

• "search_document": Used for embeddings stored in a vector database for search use-cases.
• "search_query": Used for embeddings of search queries run against a vector DB to find relevant documents.
• "classification": Used for embeddings passed through a text classifier.
• "clustering": Used for the embeddings run through a clustering algorithm.
• "image": Used for embeddings with image input.

The name of the embed job.

Specifies the types of embeddings you want to get back. Not required and default is None, which returns the Embed Floats response type. Can be one or more of the following types.

• "float": Use this when you want to get back the default float embeddings. Valid for all models.
• "int8": Use this when you want to get back signed int8 embeddings. Valid for only v3 models.
• "uint8": Use this when you want to get back unsigned int8 embeddings. Valid for only v3 models.
• "binary": Use this when you want to get back signed binary embeddings. Valid for only v3 models.
• "ubinary": Use this when you want to get back unsigned binary embeddings. Valid for only v3 models.

One of START|END to specify how the API will handle inputs longer than the maximum token length.

Passing START will discard the start of the input. END will discard the end of the input. In both cases, input is discarded until the remaining input is exactly the maximum input token length for the model.