Convert Text String to BINARY Embedding Outside Oracle AI Database

Perform a text-to-BINARY-embedding transformation by accessing a third-party BINARY vector embedding model.

WARNING:

Certain features of the database may allow you to access services offered separately by third-parties, for example, through the use of JSON specifications that facilitate your access to REST APIs.

Your use of these features is solely at your own risk, and you are solely responsible for complying with any terms and conditions related to use of any such third-party services. Notwithstanding any other terms and conditions related to the third-party services, your use of such database features constitutes your acceptance of that risk and express exclusion of Oracle’s responsibility or liability for any damages resulting from such access.

To generate a vector embedding with “hello” as the input using Cohere ubinary embed-english-v3.0 model:

1. Connect to Oracle AI Database as a local user.

   1. Log in to SQL*Plus as the SYS user, connecting as SYSDBA:

      conn sys/password as sysdba

      CREATE TABLESPACE tbs1
      DATAFILE 'tbs5.dbf' SIZE 20G AUTOEXTEND ON
      EXTENT MANAGEMENT LOCAL
      SEGMENT SPACE MANAGEMENT AUTO;

      SET ECHO ON
      SET FEEDBACK 1
      SET NUMWIDTH 10
      SET LINESIZE 80
      SET TRIMSPOOL ON
      SET TAB OFF
      SET PAGESIZE 10000
      SET LONG 10000

   2. Create a local user (docuser) and grant necessary privileges:

      DROP USER docuser cascade;

      CREATE USER docuser identified by docuser DEFAULT TABLESPACE tbs1 quota unlimited on tbs1;

      GRANT DB_DEVELOPER_ROLE, create credential to docuser;

   3. Connect as the local user (docuser):

      CONN docuser/password

2. Set the HTTP proxy server, if configured.

   EXEC UTL_HTTP.SET_PROXY('<proxy-hostname>:<proxy-port>');

3. Grant connect privilege to allow connection to the host.

   Grant connect privilege to docuser for connecting to the host, using the DBMS_NETWORK_ACL_ADMIN procedure. This example uses * to allow any host. However, you can explicitly specify the host that you want to connect to.

   BEGIN
     DBMS_NETWORK_ACL_ADMIN.APPEND_HOST_ACE(
       host => '*',
       ace => xs$ace_type(privilege_list => xs$name_list('connect'),
                          principal_name => 'docuser',
                          principal_type => xs_acl.ptype_db));
   END;
   /

4. Set up your credentials for the REST provider (in this case, Cohere) and then call UTL_TO_EMBEDDING.

   1. Run DBMS_VECTOR.CREATE_CREDENTIAL to create and store a credential.

      Cohere requires the following authentication parameter:

      { "access_token": "<access token>" }

      Replace <access token> with your own values. You will later refer to this credential name when declaring JSON parameters for the UTL_TO_EMBEDDING call.

      EXEC DBMS_VECTOR.DROP_CREDENTIAL('COHERE_CRED');
      
      DECLARE
        jo json_object_t;
      BEGIN
        jo := json_object_t();
        jo.put('access_token', '<access token>');
        DBMS_VECTOR.CREATE_CREDENTIAL(
          credential_name   => 'COHERE_CRED',
          params            => json(jo.to_string));
      END;
      /

   2. Call DBMS_VECTOR.UTL_TO_EMBEDDING to generate the BINARY embedding.

      Note: For a list of all supported REST endpoints, see Supported Third-Party Provider Operations and Endpoints.

      var params clob;
      
      BEGIN
      :params := '
                   {
                    "provider": "cohere",
                    "credential_name": "COHERE_CRED",
                    "url": "https://api.cohere.ai/v1/embed",
                    "model": "embed-english-v3.0",
                    "input_type": "search_query",
                    "embedding_types": ["ubinary"]
                   }';
      END;
      /
      
      SELECT TO_VECTOR(FROM_VECTOR(DBMS_VECTOR.UTL_TO_EMBEDDING('hello', JSON(:params))),*,BINARY);

   The generated BINARY embedding appears as follows:

   TO_VECTOR(FROM_VECTOR(DBMS_VECTOR.UTL_TO_EMBEDDING('HELLO',JSON(:PARAMS))),*,BIN
   --------------------------------------------------------------------------------
   [137,218,245,195,211,132,169,63,43,22,12,93,112,93,85,208,145,27,76,245,99,222,1
   21,63,1,161,200,24,1,30,202,233,208,2,113,27,119,78,123,192,132,115,187,146,58,1
   36,40,63,221,52,68,241,53,88,20,99,85,248,114,177,100,248,100,158,94,53,57,97,18
   2,129,14,64,173,236,107,109,37,195,173,49,128,113,204,183,158,55,139,10,205,65,4
   0,53,243,247,134,63,125,133,55,230,129,64,165,103,102,46,251,164,213,139,227,225
   ,66,98,112,100,64,145,98,80,97,192,149,77,43,114,146,197]

Related Topics

• UTL_TO_EMBEDDING and UTL_TO_EMBEDDINGS