Demo Part 3 Step 1 Routing Queue AI Base

Import: part-3-step-1-routing-queue-ai-base.json

Goal

Assemble the first combined end-to-end workflow:

• inbound trunk callers first try an extension
• extension-originated outbound still works
• the fallback path enters the queue
• the queue offline path hands the caller to AI

Why This Works

• this example composes the stable lines from Part 1 and Part 2 rather than introducing new low-level behavior.
• input_extension and play_ext_unv now fall through into the queue path, so extension-first routing becomes the first stage of a larger scenario instead of a dead-end loop.
• the outbound side from Part 2 stays intact, which means the workflow already supports both inbound and extension-originated traffic before recording or tools are added.
• the queue side stays on the simpler offline-AI model from Part 1 / Step 2. That keeps the first combined scenario understandable.

How to Test

1. Import and activate the workflow.
2. Test inbound trunk routing to a valid extension.
3. Test inbound trunk routing to the queue path.
4. Test the queue offline branch into AI.
5. Test an extension-originated outbound call.

Expected Result

Flow	Result
extension-first inbound path	still reaches an extension if the target is available
queue fallback	still works after extension routing fails or falls through
queue offline	still hands the caller to AI
extension-originated outbound	still works unchanged

What The Next Example Adds

Part 3 / Step 2 adds recording without introducing tools yet.