Looking for advice on mapping Zendesk ticket fields to Genesys Cloud Virtual Agent context variables via the Omni-Channel API. Using Python SDK v4.0.2, the POST to /api/v2/omnichannel/users/{userId}/sessions/{sessionId}/messages returns a 400 Bad Request with error code 400001 when trying to push custom attributes that match the Zendesk metadata schema. The GC documentation suggests strict JSON schema validation, unlike the flexible key-value pairs in Zendesk. Is there a specific attribute naming convention required for GC to accept these mappings during the migration phase?
Check your attribute nesting.
The Virtual Agent expects custom data within the attributes object, not at the root level of the message payload.
Flatten those Zendesk keys into a nested JSON structure before sending. This resolves the schema validation 400 error instantly.
You need to verify that the custom attributes align with the Genesys Cloud schema requirements before attempting the push. The suggestion to nest data is correct, but there is a significant risk regarding data persistence and visibility within the Virtual Agent context. If the attributes are not explicitly defined in the Virtual Agent’s context schema, they may be accepted by the API but remain inaccessible to the dialogue flow. This creates a silent failure where the data appears in the conversation log but cannot be used for routing or logic. Ensure the attribute types match exactly, particularly for integers versus strings. A mismatch often triggers the 400 error despite correct nesting. Review the official documentation for the Omni-Channel API payload structure here: https://developer.genesys.cloud/api/v2/omnichannel/docs/payload-schema. Validate the JSON against this schema locally before sending. This prevents unnecessary API calls and potential rate limiting issues during peak operational hours.
Make sure you validate the attribute schema definition within the Virtual Agent configuration before pushing data from Zendesk. The 400 error often stems from a mismatch between the incoming JSON structure and the expected context variable types. While nesting attributes is necessary, the Virtual Agent engine strictly enforces type safety for any custom data injected via the Omni-Channel API. If the Zendesk metadata includes null values or unexpected types (e.g., sending a string where an integer is expected), the API rejects the entire payload. Implement a preprocessing step in your Python SDK integration to cast values explicitly. For instance, ensure that numeric fields like ticket_id are converted to integers before serialization. This prevents silent failures where the API accepts the request but the Virtual Agent cannot parse the context during runtime.
Additionally, verify that the Omni-Channel session ID matches the active Virtual Agent interaction. The endpoint /api/v2/omnichannel/users/{userId}/sessions/{sessionId}/messages requires the session ID to correspond to the specific Virtual Agent channel session, not the general user session. If the session ID is stale or belongs to a different channel type, the API returns a 400 error because it cannot locate the target context object. Check the session state via the GET endpoint before posting. If the session is closed or invalid, retrieve a new session ID from the initial Virtual Agent greeting. This alignment ensures that the custom attributes are correctly bound to the dialogue flow, allowing the Virtual Agent to access the Zendesk metadata for conditional logic and dynamic responses.