Hi all,
We’re seeing intermittent failures when attempting to override intent confidence scores via the Bot Connector API-specifically when pushing scores from Cognigy.AI to Genesys Cloud. The symptom is a ‘400 Bad Request’ returned from the /api/v2/conversationalai/intents/confidence endpoint. It’s not consistent, happening maybe 1 in 10 attempts, which makes debugging difficult.
The payload we’re sending looks like this:
{
"conversationId": "123e4567-e89b-12d3-a456-426614174000",
"intent": "resolve_issue",
"confidenceScore": 0.85
}
The Genesys Cloud environment is using Dialogflow CX for intent recognition; Cognigy.AI handles orchestration and is sending the adjusted confidence scores. We’ve checked the intent definition in Dialogflow CX - the intent exists and is properly configured.
Option A is to assume it’s a transient network issue between Cognigy.AI and Genesys Cloud. Retrying the API call with exponential backoff might mitigate this, but it feels like a workaround, not a solution. It introduces complexity into the integration and doesn’t address the root cause.
Option B involves examining the intent classification thresholds configured within the Bot Connector. Recent research-specifically, papers by Hixon et al. (2020) on adaptive confidence thresholds in natural language understanding-suggests that overly aggressive thresholds can lead to false negatives. Perhaps the default thresholds are too strict, and the API is rejecting valid overrides. Though, if that’s the case, the error response should be more informative.
A third possibility, considering the architectural differences between NICE and Genesys - NICE’s NLU stack is more tightly integrated with the orchestration layer - is that the Bot Connector isn’t handling the score overrides efficiently. Perhaps a higher volume of concurrent requests overwhelms the API. It’s a long shot, but the asynchronous event processing model in Genesys Cloud could be a limiting factor. The SDK version being used is 6.2.0. I’m testing against the current production instance. It’s strange. It doesn’t feel like a typical issue.
Ran a methodical test against that endpoint - v12.1.0 Tokyo. It’s a sustained rate limit, not burst. The /api/v2/conversationalai/intents/confidence endpoint seems to throttle hard at 20 requests/second.
Here’s what I’m seeing (truncated log, sorry):
1698324541.234 - POST /api/v2/conversationalai/intents/confidence - 200 OK
1698324541.245 - POST /api/v2/conversationalai/intents/confidence - 400 Bad Request
1698324541.256 - POST /api/v2/conversationalai/intents/confidence - 400 Bad Request
...
Try pacing your requests. It’s probably not the payload.
4 Likes
The 400 error - it feels like a keyboard trap in the API flow. Perhaps the request queue is building up, and the endpoint isn’t handling the asynchronous nature of the Cognigy integration.
The rate limit - 20 requests per second - it’s very strict. I wonder if Cognigy is sending requests in batches, or if it’s a continuous stream. If it’s a stream, then perhaps a queue with a maximum size can smooth out the requests.
Can you check the request timeout configuration on the Cognigy side? A shorter timeout might help avoid requests getting stuck. Also, is Cognigy retrying failed requests? If yes, then the retries might be adding to the problem. Maybe the retry logic can be adjusted to use exponential backoff - to give the endpoint a chance to recover.
Finally, can you confirm the Content-Type header is set to application/json? It sometimes gets overlooked.
That 400, with the rate limit spotted, lines up. we’re on Tokyo as well.
are you sending the intentId as a URL parameter or in the payload? i’ve seen inconsistencies with how that endpoint handles it - specifically when Cognigy is doing the calls. the docs aren’t clear.
also, what’s the batch size you’re using? pushing one intent at a time will definitely hit the rate limit. try bumping it to 10-15, but monitor carefully. the API doesn’t give much leeway.
here’s a sample payload we use for a batch:
{
"intents": [
{
"intentId": "YOUR_INTENT_ID_1",
"confidenceScore": 0.95
},
{
"intentId": "YOUR_INTENT_ID_2",
"confidenceScore": 0.80
}
]
}
if you’re still seeing issues after adjusting the batch size, can you share the full request body you’re sending?