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Classifiers purpose-built for specialist tasks.

classify_uniclass 

classify_uniclass(text, filter='', title='N/A', model=None)

Classifies the input text to a matching Uniclass code. Implements the Hoppa HARDR algorithm - a multi-step approach leveraging vector similarity search and LLM steps - with Azure OpenAI.

More information on Uniclass can be found at: https://uniclass.thenbs.com/

Parameters:

Name Type Description Default
text str

input text to be classified.

required
title str

a brief title for the input text.

'N/A'
filter str

an ODATA query to filter to Uniclass table (subsystem). See examples below.

''
model str

Model deployment name within your Azure resource. If not provided will default to environment variable AZURE_OPENAI_DEPLOYMENT.

 None

Returns:

Type Description
Dict[str, Any]

JSON-formatted dictionary containing:

  1. code: selected classification code.
  2. title: title / description of the classification code
  3. certainty: confidence score, either "low", "medium" or "high".
  4. explanation: concise explanation of why this code was chosen.

Examples:

Classify to the Products table only. 

>>> classify_uniclass(text="In-situ reinforced concrete upstand beam", filter="subsystem eq Products")

beta_classify_etim 

beta_classify_etim()

Classifies the input text to a matching ETIM code.

More information on Omniclass can be found at: https://www.etim-international.com/.

beta_classify_omniclass 

beta_classify_omniclass()

Classifies the input text to a matching Omniclass code.

More information on Omniclass can be found at: https://www.csiresources.org/standards/omniclass.