Pipelines - Retrievers - Usage
Creating a new retriever configuration
There are two types of retrievers: table and volume. Given the different nature of the data sources, and the options required for each we have different functions to create them.
Retriever for a table data source
The aidb.create_retriever_for_table function is used to create a retriever for a table data source. This is the function signature, you can see many of those are optional and have defaults.
create_retriever_for_table(
-------------------------------------------------------------------------------
name TEXT,
model_name, TEXT,
source_table_name regclass,
source_data_column TEXT,
source_data_type aidb.RetrieverSourceDataFormat,
source_key_column TEXT DEFAULT 'id',
vector_table TEXT DEFAULT NULL,
vector_data_column TEXT DEFAULT 'embeddings',
vector_key_column TEXT DEFAULT 'id',
topk INTEGER DEFAULT 1,
distance_operator aidb.distanceoperator DEFAULT 'L2',
options JSONB DEFAULT '{}'::JSONB
)Example: Creating a retriever
SELECT aidb.create_retriever_for_table( name => 'test_retriever', model_name => 'simple_model', source_table_name => 'test_source_table', source_data_column => 'content', source_data_type => 'Text' );
In this example, we use all the defaults.
If you are only using Postgres tables, skip to the next section.
If you are using external data sources, you need to create a volume and create a retriever for it, which is explained in the next section.
Retriever for a volume data source
Creating a new volume
Before we can create a retriever for a volume, we need to create a volume. The aidb.create_volume function is used to create a volume. This is the function signature, you can see many of those are optional and have defaults.
aidb.create_volume(
-------------------------------------------------------------------------------
name TEXT,
server_name TEXT,
path TEXT,
mime_type TEXT
)Note that mime_type actually takes only Text or Image as values.
Example: Creating a volume
SELECT aidb.create_volume( name => 'test_volume', server_name => 'test_server', path => 'test_path', mime_type => 'Text' );
The server_name comes from calling PGFS functions to create a storage location; pgfs.create_storage_location. The path is the path to the data in the storage location.
Creating a retriever for a volume
The aidb.create_retriever_for_volume function is used to create a retriever for a volume data source. This is the function signature, you can see many of those are optional and have defaults.
aidb.create_retriever_for_volume(
-------------------------------------------------------------------------------
name TEXT,
model_name, TEXT,
source_volume_name TEXT,
vector_table TEXT DEFAULT NULL,
vector_data_column TEXT DEFAULT 'embeddings',
vector_key_column TEXT DEFAULT 'id',
topk INTEGER DEFAULT 1,
distance_operator aidb.distanceoperator DEFAULT 'L2',
options JSONB DEFAULT '{}'::JSONB
)Example: Creating a retriever for a volume
SELECT aidb.create_retriever_for_volume( name => 'test_retriever_volume', model_name => 'simple_model', source_volume_name => 'test_volume' );
In this example, we use all the defaults.
Creating the Embeddings
You can use bulk embedding if there is existing data in the source table:
SELECT aidb.bulk_embedding('test_retriever');
Enable auto-embedding for any future changes:
SELECT aidb.enable_auto_embedding_for_table('test_retriever');
You can disable auto-embedding as well:
SELECT aidb.disable_auto_embedding_for_table('test_retriever');
Retrieving
A basic key retriever, aidb.retrieve_key is available that does not look up the source data, but just returns the ID/key of the matching embeddings:
Retrieving the key
aidb.retrieve_key(<retriever name>, <query string>, <optional number of results>);
Example: Retrieving the key
SELECT * FROM aidb.retrieve_key('test_retriever', 'shoes', 2);
key | distance -------+-------------------- 43941 | 0.2938963414490189 19337 | 0.3023805122617119 (2 rows)
This can be used if you want to do a join/lookup yourself based on the key. For retrievers with external (volume) data sources, this is especially useful. Usually the application itself wants to do the retrieval from the external data source. Or you might want to push-down the actual retrieval to a client application.
The retrieve_text function joins the embeddings with the source data and directly returns the results:
Retrieving the text
The retrieve_text function joins the embeddings with the source data and directly returns the results:
aidb.retrieve_text(<retriever name>, <query string>, <optional number of results>);
Example
SELECT * FROM aidb.retrieve_text('test_retriever', 'jacket', 2);
key | value | distance -------+----------------------------------------------------+-------------------- 19337 | United Colors of Benetton Men Stripes Black Jacket | 0.2994317672742334 55018 | Lakme 3 in 1 Orchid Aqua Shine Lip Color | 0.3804609668507203 (2 rows)
Listing the retrievers
A view is available that lists all the retrievers. aidb.retrievers also includes some of the retrievers configuration:
SELECT * FROM aidb.retrievers;
id | name | vector_table_name | vector_table_key_column | vector_table_vector_column | model_name | topk | distance_operator | options | source_table_name | source_table_data_column | source_table_data_column_type | source_table_key_column | source_volume_name
----+---------------------+----------------------------+-------------------------+----------------------------+--------------+------+-------------------+---------+-------------------+--------------------------+-------------------------------+-------------------------+--------------------
2 | test_retriever | test_retriever_vector | id | embeddings | simple_model | 5 | InnerProduct | {} | test_source_table | content | Text | id |
5 | test_retriever_cosa | test_retriever_cosa_vector | id | embeddings | simple_model | 1 | L2 | {} | test_source_table | content | Text | id |
3 | test_retriever_cos | test_retriever_cos_vector | id | embeddings | simple_model | 5 | Cosine | {} | test_source_table | content | Text | id |
(3 rows)It is recommended that you just select the columns you are interested in:
SELECT name, source_table_name FROM aidb.retrievers;
name | source_table_name ---------------------+------------------- test_retriever | test_source_table test_retriever_cos | test_source_table test_retriever_cosa | test_source_table (3 rows)
Deleting a retriever
This will not delete the vector table or anything else, just the configuration:
SELECT aidb.delete_retriever(<name>);
End to end example
You can find an end-to-end example for a table/text retriever at on the Retrievers example page.
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