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Documentation Index

Fetch the complete documentation index at: https://docs.go.gbgplc.com/llms.txt

Use this file to discover all available pages before exploring further.

This page covers the common errors you might encounter when sending requests to the APIs.

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Empty collection of tasks when sending a request to retrieve tasks

This is usually caused by the selected modules in the journey builder not having the needed credentials. In this case, you encounter a 201 status code that returns an empty collection of tasks. This happens even when you have modules in the journey builder. The response looks like this: 
{
    "status": "Completed",
    "instanceId": "Qs7Zj2p4LMWT3V8Ndu9k6BRa",
    "tasks": []
}
To confirm this, send a POST request to the /journey/state/fetch endpoint. You will receive a response showing the GET_CREDENTIALS_ERRORcode. To resolve this, contact your GBG GO account manager to update the credentials for your modules.
When you call the /journey/state/fetch endpoint and receive a “COMPLETED” status (rather than a credentials error), this means that the journey has been successfully finished. All tasks associated with this journey instance have been completed, and no further action is required.

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Immediate logout after authentication

If you are a new user who attempts to log in to GBG GO with valid credentials but is immediately logged out, this might be because your organization hasn’t been created in the system yet. The account exists, but without an associated organization the system cannot direct you to your dashboard. As a result, the system automatically logs you out. To resolve this, contact your GBG GO account manager for help troubleshooting the issue.

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Facematch task returns an error in adaptive journeys

In adaptive mode, the Facematch Verification module requires both face images to be submitted in the API payload. Submitting only one image causes the task to fail.

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Symptom

When you run a journey in adaptive mode and reach the facematch verification task, the submit task data request returns a system error. The same journey completes successfully when executed in prefill mode.

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Cause

The Facematch Verification module compares two face images against each other to produce a match decision. The module needs both images available before it can run:
  • face1Image is the selfie image captured during the journey.
  • face2Image is the anchor (reference) image that the selfie is compared against.
In prefill mode, both images are supplied up front in context.subject when the journey starts, so the platform has everything it needs for facematch verification. In adaptive mode, task data is collected progressively as the journey executes. You’re responsible for submitting both images together when the facematch verification task is presented. If only one of face1Image or face2Image is submitted, then the Facematch Verification module cannot perform the comparison and the task returns an error.

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Resolution

When the Facematch Verification task is reached, submit face1Image (selfie) and face2Image (anchor) together in the API payload:
JSON
{
  "intent": "Complete",
  "instanceId": "<instanceId>",
  "taskId": "<taskId>",
  "data": {
    "context": {
      "subject": {
        "biometrics": [
          {
            "face1Image": "<base64-encoded string>",
            "face2Image": "<base64-encoded string>"
          }
        ]
      }
    }
  }
}

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Why this differs from prefill

Prefill journeys front-load all subject data when the journey starts, so modules that depend on multiple inputs receive them before any task runs. Adaptive journeys collect data task-by-task, which means modules with multi-input dependencies, such as facematch verification must receive all required inputs in the API payload for that task. If a task errors in adaptive mode but works in prefill, check the module’s reference page for the inputs that task expects.