Trying to wire up a Go service that hits the Genesys Cloud Agent Assist search endpoint to feed our Datadog dashboards, but the payload validation keeps throwing a 400. The target is /api/v2/agent-assist/knowledge-bases/{id}/search and the JSON gets constructed right before the http.Post call. Here’s the raw payload currently being pushed: {"query": "refund policy", "filters": {"category": "billing", "status": "published"}, "ranking": {"algorithm": "bm25", "boost_fields": ["title", "keywords"]}, "max_results": 25}. The docs mention ranking directives need to align with the search engine constraints, but bm25 might not actually be exposed through this REST layer. It’s probably that default is the only safe bet. Walking through the request lifecycle step by step to catch the exact break point. First, the schema validates against the max result limit. Then the atomic POST fires. Format verification should pass cleanly, which normally triggers an automatic cache warm-up for safe search iteration. The response comes back empty with a validation_failed error code instead. Synonym expansion checking needs to happen on the client side before the query leaves, otherwise relevance scores drift and agents get flooded with junk articles during peak Assist scaling. We’ve got a webhook handler ready to sync search events to our analytics platform, and latency plus hit rates are already shipping to dogstatsd. Audit logging is just a simple append to S3 after the POST, but the ranking directive mismatch is blocking the whole automated management flow. Filter matrices keep shifting and the relevance score verification pipeline stalls right at execution. The cache never actually warms up.
{
"query": "refund policy",
"filters": {
"category": "billing",
"status": "published"
},
"ranking": [
{
"field": "relevance",
"direction": "desc"
}
],
"maxResults": 15
}
The 400 comes from the ranking structure. Genesys expects an array of directives, not a single object with an algorithm key. That field doesn’t exist in the v2 spec. You’ll also need to swap http.Post for http.NewRequest so you can attach the Content-Type header. The endpoint rejects missing media types instantly.
kbSearchUrl := fmt.Sprintf("%s/api/v2/agent-assist/knowledge-bases/%s/search", baseURL, kbID)
payload := map[string]interface{}{
"query": "refund policy",
"filters": map[string]string{"category": "billing", "status": "published"},
"ranking": []map[string]string{{"field": "relevance", "direction": "desc"}},
"maxResults": 15,
}
body, _ := json.Marshal(payload)
req, _ := http.NewRequest("POST", kbSearchUrl, bytes.NewBuffer(body))
req.Header.Set("Content-Type", "application/json")
req.Header.Set("Authorization", "Bearer "+accessToken)
client := &http.Client{Timeout: 10 * time.Second}
resp, err := client.Do(req)
Cache warming triggers don’t belong in the request body either. They’re handled server side when you configure the knowledge base sync rules. If you’re wiring this for dashboards, just grab the raw results and let Datadog do the math. The platform validator is pretty strict about schema mismatches. You’ll hit the same wall if you forget the agent-assist:knowledge-base:read scope.
The suggestion above nailed the ranking array fix. The algorithm: bm25 key from the original payload definitely doesn’t belong in the v2.3 spec. That belongs in the index configuration, not the search request itself. You’ll want to make sure the Go struct matches it exactly before marshaling, otherwise the serializer drops fields silently.
type RankingDirective struct {
Field string `json:"field"`
Direction string `json:"direction"`
}
payload := map[string]interface{}{
"query": "refund policy",
"filters": map[string]string{"category": "billing", "status": "published"},
"ranking": []RankingDirective{{Field: "relevance", Direction: "desc"}},
"maxResults": 15,
}
Cache warming usually trips people up here too. If the knowledge base just spun up, the first few POSTs hit a cold index and return partial results. Real-time dashboards relying on those events will show dropped packets until the search index warms. Index lag is real. Don’t fight it. A quick client-side retry loop with exponential backoff keeps the event stream ordered when the backend finally pushes the full batch. WebSocket reconnection logic should handle the gap automatically. Just make sure the sequence numbers align before pushing to the chart.
Also, the Content-Type: application/json header isn’t optional. The gateway drops untagged payloads straight to the error queue. Watch out for the X-Gateway-Id header as well. It helps trace exactly which edge node processed the search request. Usually saves hours of digging through logs when latency spikes. Just keep the payload under 15kb. The WebSocket listeners on the dashboard side will choke if the search results get too heavy. Might want to cap maxResults at 10 anyway.
Problem
The ranking array fix works, but that cache warming trigger in the payload is a trap. Agent Assist search doesn’t support dynamic cache warming via the request body. It’s strictly read-only. If the Go service is pushing this through a Data Action to force a refresh, the API returns 200 but drops the warm-up instruction silently.
Code
"cacheControl": "no-store"
This gets stripped by the gateway before it hits the index.
Error
You’ll get a 200 OK response while the results sit stale for 30 minutes. The Five9 migration parity docs flagged this exact gap. The search endpoint just queries the index, it doesn’t mutate state.
Question
Does the fallback logic handle the TTL delay?