A. Use the 'functools.lru_cache' decorator to cache the results of the 'get_customer details' function within the UDF's scope. This will automatically cache the most recently used API responses.

B. Create a global dictionary within the UDF to store the API responses, using the customer ID as the key. Before calling the API, check if the customer ID exists in the dictionary; if it does, return the cached response. This approach will keep cached values during the session.

C. Utilize Snowflake's built-in caching mechanisms (result caching) by ensuring the UDF is deterministic and only depends on its input parameters. Snowflake will automatically cache the results of the UDF for subsequent calls with the same input.

D. Persist the API responses in a temporary table within Snowflake. The UDF will first query the temporary table for the customer ID; if found, return the cached data. Otherwise, call the API and store the response in the temporary table for future use.

E. Leverage external caching services like Redis by making API calls to Redis from the UDF to store and retrieve cached API responses. This would require configuring Snowflake to connect with external systems.