Cortex Embed

Editions

Production use of this feature is available for specific editions only. Contact our sales team for more information.

Cortex Embed is a transformation component that allows you to convert English-language text into a Cortex vector embedding. The component takes text from a single input column and uses it to create a vector embedding of either 768 or 1024 dimensions. The output of this component is a column containing the vector embedding string. This column will be named embedding_result_<input-column-name>.

To learn more about Cortex vector embeddings, read Vector Embeddings.

To learn more about Snowflake Cortex, such as availability, usage quotas, managing costs, and more, read Large Language Model (LLM) Functions (Snowflake Cortex).

To use this component, you must use a Snowflake role that has been granted the SNOWFLAKE.CORTEX_USER database role. Read Required Privileges to learn more about granting this privilege.

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Properties

Name = string

A human-readable name for the component.

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Column to Embed = drop-down

Select the input column that will be used to create embeddings.

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Model = drop-down

The vector embedding model to be used to generate the embedding.

For a vector embedding of 768 dimensions, choose one of:

• snowflake-arctic-embed-m
• e5-base-v2

For a vector embedding of 1024 dimensions, choose:

• nv-embed-qa-4

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Include Input Columns = boolean

• Yes: Outputs both your source input columns and the new embedding_result_ column. This will also include those input columns not selected in Column to Embed.
• No: Only outputs the new embedding_result_ column.

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Snowflake	Databricks	Amazon Redshift
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