The Lucidworks AI Async Prediction API is used to send asynchronous API calls that run predictions on specific models. The Lucidworks AI Async Prediction API contains two requests:
  • POST request - submits a prediction task for a specific useCase and modelId. The API responds with the following information:
  • predictionId. A unique UUID for the submitted prediction task that can be used later to retrieve the results.
  • status. The current state of the prediction task.
    • GET request - uses the predictionId you submit from a previously-submitted POST request and returns the results associated with that previous request.
The LWAI Async Prediction API supports models hosted by Lucidworks and specific third-party models. The Lucidworks AI Use Case API returns a list of all supported models. For more information about supported models, see Generative AI models. You can enter the values returned in the Lucidworks AI Use Case API for the USE_CASE and MODEL_ID fields in the /async-prediction use case POST requests. The generic path for the Async Prediction API is /ai/async-prediction/USE_CASE/MODEL_ID.
For detailed API specifications in Swagger/OpenAPI format, see Platform APIs.

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Prerequisites

To use this API, you need:
  • The unique APPLICATION_ID for your Lucidworks AI application. For more information, see credentials to use APIs.
  • A bearer token generated with a scope value of machinelearning.predict. For more information, see Authentication API.
  • Other required fields specified in each individual use case.

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Common POST request parameters and fields

Some parameters in the /ai/async-prediction/USE_CASE/MODEL_ID POST request are common to all of the generative AI (GenAI) 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.

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Async prediction use case by modelid

The /ai/async-prediction/USE_CASE/MODEL_ID request submits a prediction task for a specific useCase and modelId. Upon submission, a successful response includes a unique predictionId and a status. The predictionId can be used later in the GET request to retrieve the results.
Unique fields and values in the request are described in each use case.

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Example POST request

curl --request POST \
  --url https://APPLICATION_ID.applications.lucidworks.com/ai/async-prediction/USE_CASE/MODEL_ID \
  --header 'Accept: application/json' \
  --header 'Content-Type: application/json' \
  --header 'Authorization: Bearer ACCESS_TOKEN'
  --data '{
  "batch": [
    {
      "text": "Content for the model to analyze."
    }
  ],
  "useCaseConfig": [
    {
      "useSystemPrompt": true
    }
  ],
  "modelConfig": [
    {
      "temperature": 0.8,
      "topP": 1,
      "presencePenalty": 2,
      "frequencyPenalty": 1,
      "maxTokens": 1
    }
  ]
}'

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Example GET request

curl --request GET
--url https://APPLICATION_ID.applications.lucidworks.com/ai/async-prediction/PREDICTION_ID
--header 'Authorization: Bearer Auth '
The response varies based on the specific use case and the fields included in the request.