The LWAI Prediction query stage is an integration between Fusion and Lucidworks AI and invokes the following APIs: The stage enriches search results using Generative AI such as OpenAI, Google Vertex, and Anthropic models. In addition, the stage can use pre-trained embedding models. Your organization needs to choose the models that best suit your goals. Configuration using the Fusion UI is detailed in the Configure the LWAI Prediction query stage topic.
The LWAI Prediction AI query stage is a Fusion pipeline query stage that enriches your search results with Generative AI predictions.For reference information, see LWAI Prediction query stage.To use this stage, non-admin Fusion users must be granted the PUT,POST,GET:/LWAI-ACCOUNT-NAME/** permission in Fusion, which is the Lucidworks AI API Account Name defined in Lucidworks AI Gateway when this stage is configured.To configure this stage:
  1. Sign in to Fusion and click Querying > Query Pipelines.
  2. Click Add+ to add a new pipeline.
  3. Enter the name in Pipeline ID.
  4. Click Add a new pipeline stage.
  5. In the AI section, click LWAI Prediction.
  6. In the Label field, enter a unique identifier for this stage.
  7. In the Condition field, enter a script that results in true or false, which determines if the stage should process.
  8. Select Asynchronous Execution Config if you want to run this stage asynchronously. If this field is enabled, complete the following fields:
    1. Select Enable Async Execution. Fusion automatically assigns an Async ID value to this stage. Change this to a more memorable string that describes the asynchronous stages you are merging, such as signals or access_control.
    2. Copy the Async ID value.
  9. In the Account Name field, select the name of the Lucidworks AI integration defined when the integration was created.
  10. In the Use Case field, select the Lucidworks AI use case to associate with this stage.
  • To generate a list of the use cases for your organization, see Use Case API.
  • The available use cases are described in Prediction API.
  1. In the Model field, select the Lucidworks AI model to associate with this stage.
If you do not see any model names and you are a non-admin Fusion user, verify with a Fusion administrator that your user account has these permissions: PUT,POST,GET:/LWAI-ACCOUNT-NAME/**Your Fusion account name must match the name of the account that you selected in the Account Name dropdown.For more information about models, see:
  1. In the Input context variable variable field, enter the name of the variable in context to be used as input. Template expressions are supported.
  2. In the Destination variable name and context output field, enter the name that will be used as both the query response header in the prediction results and the context variable that contains the prediction.
  • If a value is entered in this field:
    • {destination name}_t is the full response.
    • In the context:
      • _lw_ai_properties_ss contains the Lucidworks account, boolean setting for async, use case, input for the call, and the collection.
  • If no value is entered in this field:
    • _lw_ai_{use case}_t is the response.response object, which is the raw model output.
    • _lw_ai_{use case}_response_s is the full response.
  1. Select the Include Response Documents? check box to include the response documents in the Lucidworks AI request. This option is only available for certain use cases. If this is selected, run the Solr Query stage to ensure documents exist before running the LWAI Prediction query stage.
Response documents must be included in the RAG use case, which supports attaching a maximum of 3 response documents. To prevent errors, enter all of the entries described in the Document Field Mappings section.
  1. In the Document Field Mappings section, enter the LW AI Document field name and its corresponding Response document field name to map from input documents to the fields accepted by the Prediction API RAG use case. The fields are described in the Prediction API.
If information is not entered in this section, the default mappings are used.
  • The body and source fields are required.
    • body - description_t is the contents of the document.
    • source - link_t is the URL/ID of the document.
  • The title and date fields are optional.
    • title - title_t is the title of the document.
    • date - _lw_file_modified_tdt is the creation date of the document in epoch time format.
  1. In the Use Case Configuration section, click the + sign to enter the parameter name and value to send to Lucidworks AI.
  • The useCaseConfig parameter is only applicable to certain use cases. For more information, see the Async Prediction API and the Prediction API.
  • The memoryUuid parameter is required in the Standalone Query Rewriter use case, and is optional in the RAG use case. For more information, see Prediction API.
  1. In the Model Configuration section, click the + sign to enter the parameter name and value to send to Lucidworks AI. Several modelConfig parameters are common to generative AI use cases. For more information, see Prediction API.
  2. In the API Key field, enter the secret value specified in the external model. For:
  • OpenAI models, "apiKey" is the value in the model’s "[OPENAI_API_KEY]" field. For more information, see Authentication API keys.
  • Azure OpenAI models, "apiKey" is the value generated by Azure in either the model’s "[KEY1 or KEY2]" field. For requirements to use Azure models, see Generative AI models.
  • Google VertexAI models, "apiKey" is the value in the model’s "[BASE64_ENCODED_GOOGLE_SERVICE_ACCOUNT_KEY]" field. For more information, see Create and delete Google service account keys.
  1. Select the Fail on Error checkbox to generate an exception if an error occurs during this stage.
  2. Click Save.
You can also configure the stage using the parameters listed in this topic.
To use this stage, non-admin Fusion users must be granted the PUT,POST,GET:/LWAI-ACCOUNT-NAME/** permission in Fusion, which is the Lucidworks AI API Account Name defined in Lucidworks AI Gateway when this stage is configured.

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Query pipeline stage condition examples

Stages can be triggered conditionally when a script in the Condition field evaluates to true. Some examples are shown below. Run this stage only for mobile clients: 
params.deviceType === "mobile"
Run this stage when debugging is enabled: 
params.debug === "true"
Run this stage when the query includes a specific term: 
params.q && params.q.includes("sale")
Run this stage when multiple conditions are met: 
request.hasParam("fusion-user-name") && request.getFirstParam("fusion-user-name").equals("SuperUser");
!request.hasParam("isFusionPluginQuery")
The first condition checks that the request parameter “fusion-user-name” is present and has the value “SuperUser”. The second condition checks that the request parameter “isFusionPluginQuery” is not present.

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Configuration

When entering configuration values in the UI, use unescaped characters, such as \t for the tab character. When entering configuration values in the API, use escaped characters, such as \\t for the tab character.