Bot Training Data Import Failing with 400 Bad Request on Zendesk Export

Just noticed that the initial bulk import of our legacy Zendesk macros into the Genesys Cloud Bot training data is failing consistently. We are trying to migrate our top 500 most-used macros to serve as initial intents for the new conversational bot. The process works fine for the first 10-15 items, but then the API starts rejecting subsequent requests.

The environment is Genesys Cloud v2024.03 running in eu-west-1. The migration script is a custom Python utility using genesys-cloud-python-sdk version 1.6.0. We are mapping Zendesk macro actions directly to Bot intents, assuming a 1:1 relationship for simplicity, similar to how we mapped ticket forms to routing rules earlier this week.

The error response from the POST /api/v2/conversation/bots/trainingdata endpoint is a 400 Bad Request. The response body contains:

{
 "errors": [
 {
 "code": "invalid_argument",
 "message": "Training data item 'intent_name' contains invalid characters or exceeds length constraints."
 }
 ]
}

This is confusing because the intent names are derived directly from Zendesk macro names, which are alphanumeric with underscores. For example, password_reset_request works, but billing_dispute_escalation fails. In Zendesk, these macro names were perfectly valid identifiers. Is Genesys Cloud enforcing stricter naming conventions for training data intents than for standard routing labels?

We have verified that the JSON payload structure matches the schema exactly, including the required language field set to en-US. The issue seems to trigger specifically when the intent name length exceeds 25 characters, but the documentation does not explicitly state a hard limit for intent names in the training data API.

Has anyone encountered similar restrictions during a Zendesk-to-GC bot migration? Are we missing a normalization step for the intent names before pushing them to the training data API? We need to resolve this to proceed with the bot certification process.

Have you tried validating the JSON payload structure against the Genesys Cloud Bot API schema before sending? The 400 error often stems from subtle formatting mismatches when migrating legacy macro data, especially if special characters or newlines from Zendesk aren’t properly escaped. Ensure each intent definition strictly follows the required format, with utterances as a clean array of strings. It might also help to inspect the specific error message in the response body, which usually points to the exact field causing the parse failure.

From a scheduling perspective, we see similar issues when bulk operations hit unexpected validation rules. Try processing the import in smaller batches, perhaps 20-30 macros at a time, to isolate any problematic entries. If the script fails mid-batch, check for duplicate intent names or conflicting training phrases. Sometimes, reformatting the export file to remove hidden characters or standardizing the text encoding to UTF-8 without BOM can resolve these stubborn import errors. Keep the payload clean and minimal to start.

I’d recommend looking at at the payload size limits for bulk imports, as the initial success followed by failure suggests a threshold breach rather than a schema error.

• Split the 500 macros into batches of 20.
• Add a 2-second delay between batch submissions.

You need to implement strict rate limiting in your Python script. The Bot API enforces throttling on bulk operations, and sending 500 requests without delay triggers the 400 error after the initial burst is accepted.

Add a sleep function between batches. This mirrors the pause strategy used in JMeter load tests for API throughput. It stabilizes the connection and prevents the server from rejecting the remaining payloads.