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Configure Fusion to consume aggregated signals from Lucidworks Platform for query boosting and result reranking.

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Prerequisites

Before configuring Platform signals in Fusion, make sure you have the following:
  • A Lucidworks Platform application configured with a Signals Store
  • Signals Beacon or Platform Signals API configured
  • A Platform integration created for self-hosted Fusion
  • Platform Client ID and Secret
  • Access to modify Fusion Helm values and ConfigMaps
For Platform setup, see Platform signals documentation.

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Configuration steps

Add Platform credentials to Fusion via Helm values. These credentials allow Fusion to authenticate with Lucidworks Platform and retrieve aggregated signals.Add this to your Helm values:
lwai-gateway:
  lwai:
    credentials: |
      fusion.lwai.account[0].name: <integration_name>
      fusion.lwai.account[0].scopes: signals.push,machinelearning.predict,machinelearning.model
      fusion.lwai.account[0].clientId: <platform_client_id>
      fusion.lwai.account[0].clientSecret: <platform_client_secret>
      fusion.lwai.account[0].baseUrl: https://api.lucidworks.com/applications/<platform_app_id>
      fusion.lwai.default.authEndpoint: https://identity.lucidworks.com/oauth2/ausao8uveaPmyhv0v357/v1/token
Replace the placeholders with your actual values:
  • <integration_name> is the name of your Platform integration.
  • <platform_client_id> is the Client ID from the Platform integration.
  • <platform_client_secret> is the Client Secret from the Platform integration.
  • <platform_app_id> is the Platform application ID.
The authEndpoint URL is the shared Lucidworks Platform production authentication endpoint. Use this exact URL as shown; it is not environment-specific.
Apply the Helm values update and restart the affected pods.
Configure which Platform signals Fusion should retrieve and which collections to populate.Open the <release>-cloud-signals-config ConfigMap for editing:
kubectl edit configmap <release>-cloud-signals-config
Add your configuration to the signalsOperator section:
signalsOperator: |
  <platform_app_name>:
    <fusion_appId>_signals_aggr:
      formula1:
        CLICK: 2.0
        CART: 3.0
        PURCHASE: 4.0
The configuration includes the following elements:
  • <platform_app_name> is the name of your Platform application.
  • <fusion_appId>_signals_aggr is the name of the Fusion collection for storing aggregated signals. Replace <fusion_appId> with your Fusion app ID (for example, my_app_signals_aggr).
  • formula1 is the aggregation formula name and must match Platform configuration.
  • CLICK, CART, PURCHASE are the signal types and their respective weights.
The formula configuration defines how different signal types are weighted. The weights should match the aggregation formula configured in Lucidworks Platform.
Save the ConfigMap and restart the signal processing component:
kubectl delete pod -l app.kubernetes.io/component=signals-operator
If a Fusion app doesn’t exist, create one using these steps:
  1. Log in to Fusion Admin UI.
  2. Navigate to Apps.
  3. Click Create App.
  4. Enter the app name and configure as needed.
Fusion automatically creates the COLLECTION_NAME_signals_aggr collection when you configure signal retrieval. You don’t need to create the collection manually.
Add the Boost with Signals stage to your query pipeline using these steps:
  1. Navigate to your app’s default query pipeline.
  2. Add a Boost with Signals stage.
  3. Configure the stage parameters as shown in the table below:
ParameterValueDescription
Aggregation Typeformula1This must match the formula name in the signal retrieval configuration.
Rollup Fielddoc_idThis is the field containing the document ID in aggregated signals.
Rollup Weight Strategyweight_dThis is the field containing the calculated weight.
See Boost with Signals Stage for detailed configuration options.
After configuration, verify the integration is working:
  1. Check signal retrieval logs: 
    kubectl logs -l app.kubernetes.io/component=signals-operator --tail=100
    Look for successful run messages: 
    INFO  c.l.c.s.c.fetcher.SignalsOperator - Starting control loop
INFO  c.l.c.s.c.fetcher.SignalsOperator - Job status: SUCCEEDED
INFO  c.l.c.s.c.fetcher.IndexingRunner - Converting to SolrDoc
  2. Verify collection population:
    • Navigate to the COLLECTION_NAME_signals_aggr collection in Fusion.
    • Open Query Workbench.
    • Run a query: q=*:*.
    • Verify documents exist with expected fields.
  3. Test query boosting:
    • Execute a query through your configured pipeline.
    • Verify that results with signal data receive appropriate boosts.
If the integration is not working, see Troubleshooting Platform Signals.

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Next steps