A. Use to load the 'location' column data into a Pandas DataFrame, call the external LLM API in your Python script to enrich the location data and then use to store the enriched data back into a Snowflake table.

B. Create a Snowflake External Function that calls the external LLM API. Pass the 'location' column data to the External Function and retrieve the structured location features. Then apply the External Function directly on the Snowpark DataFrame.

C. Create a Snowpark User-Defined Function (UDF) that calls the external LLM API. Pass the 'location' column data to the UDF and retrieve the structured location features. Then apply the UDF directly on the Snowpark DataFrame.

D. Use Snowpark's 'createOrReplaceStage' to create an external stage pointing to the LLM API endpoint. Load the 'location' data into this stage and call the LLM API directly from the Snowflake stage using SQL.

E. Use the Snowflake Connector for Python to directly query the 'location' column and call the external LLM API from the connector. Then write the updated data into a new table.