Data Action’s throwing a 400 when the Architect flow tries to merge custom attributes into the interaction event payload. Lambda’s getting the trigger fine, but the response payload gets rejected before hitting the success path.
Error response screams schema mismatch even though the definition clearly includes the field.
{"error": "Data action input schema validation failed: unknown field 'customAttributes'"}
Config JSON’s matching the payload exactly.
genesyscloud-python serializes customAttributes as a JSON array by default when the SDK model detects a list input, which triggers the schema validation error since the Data Action backend strictly expects a key-value dictionary. The Python client doesn’t automatically flatten nested interaction event payloads during the merge step, so you’ll hit that 400 response when the post_data_actions_data_action_id_execute method passes the raw list structure to the endpoint. You need to force the attribute mapping into a dict object before handing it off to the SDK request builder. The validation layer rejects the payload because the application/json content type expects explicit field definitions, not a generic array wrapper. Switching the input to a standard Python dictionary resolves the serialization mismatch and lets the backend parse the merge correctly. Honestly just a type casting issue. The SDK’s internal model_serializer will handle the conversion automatically once the type matches the expected schema definition. Make sure the request_body parameter receives the exact structure shown below.
from genesyscloud_platform_api.models import DataActionRequest
payload = {
"customAttributes": {
"order_id": "ORD-9921",
"priority": "high",
"routing_data": {"skill": "support_tier2"}
}
}
result = client.data_actions.post_data_actions_data_action_id_execute(
data_action_id="your_action_id",
request_body=DataActionRequest.from_dict(payload)
)
The array serialization mismatch is exactly what’s breaking the merge. The SDK doesn’t flatten nested interaction event payloads during the merge step, which is why it’s throwing the 400. Switching to a flat dictionary structure gets past the validation.
payload = {
"customAttributes": {
"agent_tier": "L1",
"queue_source": "webchat",
"priority_flag": True
},
"interaction_id": interaction_id
}
Tried passing a list of dicts first, which just triggers the same rejection. Tested overriding the serializer in the client config, but that breaks the token refresh cycle and throws a 401 on the second request. The flat dict bypasses the merge step entirely since the backend reads it as a direct key-value map. Five9 handled this differently back in the day, so porting the logic over definitely requires adjusting how the payload gets structured. How’s the timeout handling looking on the Lambda side once the payload actually hits the success path? The callback returns 504s when the payload pushes past 4KB. Documentation leaves out any size caps for merged attributes, so the timeout is probably just choking on the response body. Might need to chunk the attributes manually if the limit holds.