Base

Provides the most basic view into the model. This view will simply apply the model to the provided data and return the model-output along with the model-output

gordo.server.blueprints.base.delete_model_revision(gordo_name: str, revision: str, **kwargs)

Delete provided model revision from the disk.

gordo.server.blueprints.base.get(gordo_project: str)

Returns list of models for this project. Those models are expected to be built.

gordo.server.blueprints.base.get_download_model()

Download the trained model

Responds with a serialized copy of the current model being served.

Return type:

Results from gordo.serializer.dumps()

gordo.server.blueprints.base.get_metadata()

Serve model / server metadata

Get metadata about this endpoint, also serves as /healthcheck endpoint

gordo.server.blueprints.base.get_model_list(gordo_project: str)

List the current models capable of being served by the server

gordo.server.blueprints.base.get_revision_list(gordo_project: str)

List the available revisions the model can serve.

gordo.server.blueprints.base.post_prediction()

Process a POST request by using provided user data

A typical response might look like this

{
    'data': [
        {
            'end': ['2016-01-01T00:10:00+00:00'],
            'model-output': [0.0005317790200933814,
                             -0.0001525811239844188,
                             0.0008310950361192226,
                             0.0015755111817270517],
            'original-input': [0.9135588550070414,
                               0.3472517774179448,
                               0.8994921857179736,
                               0.11982773108991263],
            'start': ['2016-01-01T00:00:00+00:00'],
        },
        ...
    ],

    'tags': [
        {'asset': None, 'name': 'tag-0'},
        {'asset': None, 'name': 'tag-1'},
        {'asset': None, 'name': 'tag-2'},
        {'asset': None, 'name': 'tag-3'}
    ],
    'time-seconds': '0.1937'
}