Sending canned responses via Conversations API returns 400 Bad Request

NICE CXone API & Integrations
1

Anyone know why the Python SDK throws a validation error when attempting to send a canned response during an active chat interaction? I am building a CLI tool using Typer that automates agent workflows, and I need to programmatically inject pre-defined text snippets into the conversation stream. I have successfully retrieved the canned response object using the Knowledge API and have the correct interaction ID and media type set to ‘webchat’. However, when I pass the canned response ID directly to the send_text method or attempt to use the POST /api/v2/conversations/webchat/interactions/{interactionId}/messages endpoint with the canned response payload structure, the API responds with a 400 Bad Request. The error message indicates that the cannedResponseId field is not recognized in the request body, which contradicts the documentation that suggests this field should be supported for enriched message types.

I have tried constructing the payload manually to ensure all required fields are present, including the from address, text body, and the cannedResponseId. I am also ensuring that the OAuth token used has the webchat:interaction:send scope. Here is the minimal JSON payload I am sending in the request body:
{
“from”: {
“id”: “agent-id-123”
},
“to”: [
{
“id”: “customer-id-456”
}
],
“text”: {
“content”: “This is a test canned response.”
},
“cannedResponseId”: “canned-id-789”
}
The API consistently rejects this, stating that the schema does not match the expected structure for a text message. I suspect there might be a specific wrapper object or a different endpoint required for sending canned responses that is not explicitly documented in the standard WebChat interaction methods.

I am working from my development environment in Lagos, so I am using the standard Genesys Cloud Python SDK version 1.5.0. I have also tried using the genesyscloud_conversations module directly to see if the SDK handles the serialization differently, but the result is identical. Is there a specific flag or a different API path I should be using to associate a canned response ID with a message send operation? I need this to work for my CLI automation script to ensure agents can quickly deploy standardized responses without manual typing. Any insight into the correct payload structure or SDK method would be greatly appreciated.

2

The documentation actually says you cannot directly inject a canned response ID into the conversation message payload. The API expects raw text content, not a reference to a Knowledge object. This is a common integration pitfall when building automation tools.

  1. First, retrieve the CannedResponse object using the Knowledge API.
  2. Extract the content field from that object.
  3. Use the Conversations API to send that raw string as the message body.

Here is the Python SDK logic:

from platformclientv2 import ConversationApi, KnowledgeApi

# 1. Get canned response content
knowledge_api = KnowledgeApi()
canned_resp = knowledge_api.get_knowledge_cannedresponse(canned_response_id)
text_content = canned_resp.content

# 2. Send as a standard message
conv_api = ConversationApi()
msg = {
 "text": text_content,
 "to": [{"id": interaction_id, "type": "webchat"}]
}
conv_api.post_conversations_conversation_messages(interaction_id, body=msg)

Always validate the content field exists before posting. This avoids the 400 error and ensures the text renders correctly in the agent desktop.

3

Make sure you extract the content field from the retrieved CannedResponse object before injecting it into the conversation payload. The Conversations API does not accept Knowledge object IDs directly in the message body. It requires the raw text string.

Here is how to handle it in Python using the SDK:

from genesyscloud import knowledge_api

# 1. Fetch the canned response
knowledge_client = knowledge_api.KnowledgeApi(platform_client)
canned_resp = knowledge_client.get_knowledge_document_cannedresponse(canned_response_id)

# 2. Extract the actual text content
message_body = canned_resp.content

# 3. Send via Conversations API
conversations_client = conversations_api.ConversationsApi(platform_client)
message = Message(
 text=message_body,
 from_={'name': 'Automated Tool'}
)
conversations_client.post_conversations_webchat_messages(
 conversation_id=interaction_id,
 body=message
)

Note: Ensure your OAuth token includes the webchat:messages:send scope, or the request will fail with a 403, not a 400.

4

I’d recommend looking at at the raw JSON structure of the content field before passing it to the conversations API.

# Ensure you are sending the string, not a dict or list
payload_text = str(canned_response.content)

The validation error usually stems from sending a nested object instead of a plain string.

5

As far as I remember, the 400 error often stems from how the Python SDK serializes the content field when it contains rich text or embedded entities. Even if the field looks like a string in the debugger, the underlying JSON structure might retain metadata tags that the Conversations API rejects. I recently hit this while syncing Teams messages to GC webchat sessions. The solution is to strip the HTML or markdown before sending. Here is the minimal repro code I use to sanitize the payload. It ensures only plain text reaches the endpoint. This avoids the validation error completely. I also cache the sanitized version to avoid repeated API calls to Knowledge if the same canned response is used multiple times in a session. It works reliably for my bot integration logic.