Connect
The standard way to connect to Superduper is via the superduper
decorator:
Development mode​
In development mode, you may provide the URI/ connection details of your data deployment directly
db = superduper('<database-uri>')
For example if you are running a (not secure) MongoDB deployment locally, and you want to connect to the "documents"
database, you might write:
from superduper import superduper
db = superduper('mongodb://localhost:27017/documents')
Complete connection guide​
For a semi-exhaustive list of possible connections see here.
Fine grained configuration​
superduper
chooses default artifact_store
(file blob storage) and metadata_store
(AI metadata) values for your connection. These defaults may be overridden directly:
db = superduper(
'<database-uri>',
artifact_store='<artifact-store-uri>,
metadata_store='<metadata-store-uri>,
)
Cluster mode​
In cluster mode, the connection string needs to be provided in a configuration file or via environment variable so that all services can connect correctly:
Add these lines to your configuration:
data_backend: mongodb://localhost:27018/documents
Read more about configuration here.
After doing this, you may connect directly with the superduper
decorator:
db = superduper()
Fine grained configuration​
For more granular configuration add these lines:
data_backend: <database-uri>,
artifact_store: <artifact-store-uri>
metadata_store: <metadata-store-uri>
Next steps​
db
is now your connection to your data, models, and model meta-data.
Now that you have established this connection you are ready to build, deploy and manage AI with Superduper.