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The FAQ enrichment use case of the LWAI Prediction API uses a large language model (LLM) to ingest input text and return a JSON response that contains a list of question and answer pairs. The questions are what the LLM believes are, or could be, frequently asked questions. The answers are generated based on the content of the text. This use case can be used to generate questions and answers from each document that can be used for the following purposes:
  • Populate a Frequently Asked Questions page
  • Support a search of similar questions
  • Prepare test data for Smart Answers

Prerequisites

To use this API, you need:
  • The unique APPLICATION_ID for your Lucidworks AI application, which is provided by Lucidworks.
  • A bearer token generated with a scope value of machinelearning.predict. For more information, see Authentication API.
  • The USE_CASE and MODEL_ID fields for the use case request. The path is: /ai/prediction/USE_CASE/MODEL_ID. A list of supported models is returned in the link:/lw-platform/ai/0stpyb/use-case-api[Lucidworks AI Use Case API]. For more information about supported models, see Generative AI models.
  • Other required fields specified in each individual use case.

Common parameters and fields

Some parameters in the /ai/prediction/USE_CASE/MODEL_ID request are common to all of the generative AI (Gen-AI) use cases, such as the modelConfig parameter. Also referred to as hyperparameters, these fields set certain controls on the response. Refer to the API spec for more information.

Unique values for the FAQ enrichment use case

Some parameter values in the faq-enrichment use case are unique and may not be available in other use cases, including values for the text and useCaseConfig parameters. Refer to the API spec for more information.

Example request

This example does not include modelConfig parameters, but you can submit requests that include parameters described in Common parameters and fields.
The following is an example response: