Does anyone know why updating participant attributes on an active voice leg via PUT /api/v2/interactions/participants fails with a 400 Bad Request?
I am trying to sync Slack user metadata to the Genesys Cloud participant record in real-time using the Bolt framework. The request body matches the schema exactly, yet the API rejects it with error_code: "invalid_request_body" and message: "Invalid input". This works fine for messaging interactions but fails consistently for voice. Is there a specific restriction on mutable fields during an established voice channel?
Make sure you validate the attributes payload structure before sending. The 400 error on voice legs usually stems from sending nested objects or non-serializable types that the voice infrastructure rejects.
import json
from platform_client import InteractionsApi
def update_participant(client, participant_id, custom_data):
# Ensure all values are JSON-serializable primitives
safe_attributes = json.loads(json.dumps(custom_data))
body = {
"attributes": safe_attributes
}
try:
return client.interactions_api.put_interactions_participant(
participant_id,
body=body
)
except Exception as e:
print(f"API Error: {e.status} - {e.reason}")
I see this often when pulling raw objects from external systems. The voice interaction API is stricter than messaging. Flatten your metadata. Check if you are passing lists of objects instead of simple key-value pairs. The transcript extraction pipeline I use requires clean JSON. If the API rejects it, your model training data will be dirty. Verify the payload locally first.
The way I solve this is by ensuring the attributes payload is strictly flat key-value pairs, as voice legs reject nested objects. Use json.dumps(custom_data, default=str) to sanitize non-serializable types before sending to /api/v2/interactions/participants.
The simplest way to resolve this is to ensure your gRPC service flattens all nested metadata before mapping it to the participant attributes, as the voice infrastructure strictly rejects complex objects during active legs.
I encountered this exact bottleneck while building a high-throughput event processing microservice in Singapore. The core issue is not just JSON serialization, but the schema validation on the voice channel which enforces flat key-value pairs. When syncing from Slack or other external systems, you often receive nested JSON structures. You must transform these into a flat map where keys use dot-notation or unique prefixes.
Here is the Go transformation logic I use in my service mesh before calling the API:
func flattenMap(m map[string]interface{}, prefix string) map[string]string {
flat := make(map[string]string)
for k, v := range m {
key := k
if prefix != "" {
key = prefix + "." + k
}
switch val := v.(type) {
case map[string]interface{}:
nested := flattenMap(val, key)
for nk, nv := range nested {
flat[nk] = nv
}
case []interface{}:
flat[key] = fmt.Sprintf("%v", val)
default:
flat[key] = fmt.Sprintf("%v", val)
}
}
return flat
}
Apply this transformation to your Bolt framework payload before invoking PUT /api/v2/interactions/participants. This prevents the invalid_request_body error by ensuring the attributes field contains only serializable string values. My microservice processes thousands of events per second using this pattern, and it maintains stability during peak load. Verify your OAuth token has interaction:write scope as well.