Troubleshooting & FAQ#

Something is not working properly. How can I debug it?

You can add debug step before or after the step, which is problematic.

{
    "step": "debugger",
    "type": "log_fields",
    "fields": ["body"],
    "log_level": "warning"
}

As a result you will see something similar to:

2022-06-21 10:22:37,087 : squirro.lib.nlp.steps.debuggers.fields_debugger : WARNING : ++++++++++++++++++++++++++++++++++++++++++++++++++++
2022-06-21 10:22:37,087 : squirro.lib.nlp.steps.debuggers.fields_debugger : WARNING : Logging fields for Document '0' (skipped=False)
2022-06-21 10:22:37,087 : squirro.lib.nlp.steps.debuggers.fields_debugger : WARNING : 'body' (truncated) ----> '<html><body><p>This is a fake Squirro Item. It is composed of a couple fake sentences.</p></body></h'

Note that the list of fields needs to be adjusted based on the steps before and after.

How can I test my ML Worklflow before uploading to the Squirro Platform?

  • Download the libNLP here and install it using pip

  • Create a python script as described in the runner documentation and execute it

How can I uploading ML Worklflow to the Squirro Platform?
client = SquirroClient(None, None, cluster=CLUSTER)
client.authenticate(refresh_token=TOKEN)
client.new_machinelearning_workflow(
    project_id=PROJECT_ID,
    name = NAME_OF_THE_WORKFLOW,
    config=CONFIG,
    ml_models=PATH # this only needs to be set if trained models or custom steps are existing
)
How can I use a ML Workflow in the enrich pipeline?
I have developed my own machine learning approach and would like to use it for data enrichment in Squirro