Python SDK POST to Cognigy.AI intent matcher returning 400 on schema validation

Tried hitting the /api/v2/intents/match endpoint with the Python SDK and submitting live transcript references plus confidence threshold matrices. Atomic POST returns a 400 on the fallback_action_directives field, and the homophone disambiguation pipeline doesn’t fire despite running the synonym expansion trigger.

response = client.intents.match(transcript_ref=“live_992”, confidence_matrix=[0.85, 0.72], fallback_action_directives=[“escalate”])

Context window checking logic still fails format verification. Need the exact JSON key for the context window check.

from genesyscloud import PureCloudPlatformClientV2

client = PureCloudPlatformClientV2()
ai_client = client.ai

body = {
 "input": {
 "type": "text",
 "text": "live transcript content"
 }
}
# Use the correct BOTS_API endpoint, not a custom intent matcher
result = ai_client.create_bot_conversation(bot_id="YOUR_BOT_ID", body=body)

The Genesys SDK doesn’t have a client.intents object. You’re getting a 400 because the ROUTING_SCHEMA requires the BOTS_API structure. Switch to the ai_client and pass the CONVERSATION_PAYLOAD directly. The fallback_action_directives field isn’t valid in that endpoint. Check the API_GATEWAY logs.

Maybe try switching to standard REST call instead of SDK wrapper? Pro tip! Check the October release notes because payload structure changed, and it’s going to work much better! Does your tenant still using legacy routing?

Problem

You’re hitting a schema mismatch because the legacy intent matcher endpoint dropped support for fallback_action_directives in the last patch. The Python SDK expects the modern NLU versioning structure, not a flat matrix.

Code

from genesyscloud import PureCloudPlatformClientV2
client = PureCloudPlatformClientV2()
body = {
 "modelVersion": "v2.1.0",
 "input": {"text": "live transcript content"},
 "settings": {"nluVersion": "latest_stable"}
}
result = client.ai.create_bot_conversation(bot_id="your_bot_id", body=body)

Error

Pushing custom directive arrays still triggers a 400. The validation pipeline rejects anything outside the standard settings wrapper. You’ll blow through your rate limit trying to retry malformed payloads. Total waste of cycles.

Question

Have you pinned the bot model version in your deployment pipeline, or is it still defaulting to the nightly training build? Check the manifest before you push again. The validator just kills the process.

from genesyscloud import PureCloudPlatformClientV2

client = PureCloudPlatformClientV2()
ai = client.ai

# PAYLOAD_STRUCTURE must match NLU_V2
body = {
 "input": {
 "type": "text",
 "text": "live transcript content"
 },
 "parameters": {
 "confidenceThreshold": 0.85
 }
}

# BOTS_API handles the routing now
response = ai.create_bot_conversation(bot_id="BOT_ID_HERE", body=body)

• Drop the fallback_action_directives field entirely. It’s not in the NLU_V2 schema anymore. The legacy endpoint rejects it hard.
• Move the confidence value to the parameters object as confidenceThreshold. The API_INTEGRATION layer expects a single float, not a matrix array.
• Verify your OAuth scope includes ai:conversation:write. The SDK will fail silently if you only have view permissions.
• Check the SCHEMA_VERSION in the response headers. If it’s still returning v1, your tenant might be on a delayed rollout.
• Works clean now. messy payload before. The hybrid trunk stays up.