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Search Functionality

Spice provides advanced search capabilities that go beyond standard SQL queries, offering both traditional SQL search patterns and vector-based search functionality.

SQL-based search requires the integration of data connectors or data accelerators. For more information on setting up data connectors and accelerators, see Data Connectors and Data Accelerators.

Spice supports basic search patterns directly through SQL, leveraging its SQL query features. For example, you can perform a text search within a table using SQL's LIKE clause:

SELECT id, text_column
FROM my_table
WHERE
    LOWER(text_column) LIKE '%search_term%'
  AND
    date_published > '2021-01-01'

Vector-based search requires configured data sources (connectors or accelerators) in addition to embeddings. These embeddings convert data to numerical representations that can be used by machine learning models, facilitating similarity comparisons for more advanced search capabilities.

Configuring embeddings is crucial for the effectiveness of vector-based search. For detailed instructions on setting up embeddings, refer to Configured Embeddings.

For performing vector-based search, see Vector-Based Search.