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Issue: During a call, content_complete never retur...
# ❓・ai-evy-support
m
@AI Evy Issue: During a call, content_complete never returns true for any LLM response after the initial greeting (response_id 0). Because of this, when the caller gave a short affirmation ("okay"/"yes") right after the agent finished a long response, Retell's turn-taking never resolved to user_turn for that first utterance — it just sat as update_only with no turntaking field, and no response_required was ever sent to our backend for it. The caller had to repeat the confirmation ~12 seconds later before turn-taking kicked in and response_required finally fired (response_id 2). Call ID: call_0c20a368b8740f5ca1cf048776b
a
Thanks for tagging me @mannankhan. I'll look through relevant sources and get back to you shortly.
### Answer The issue you're describing involves Retell's turn-taking model and how
content_complete
affects when
response_required
events are triggered in the LLM WebSocket connection [(1) ]() . Based on the LLM WebSocket documentation, Retell sends
update_only
events for transcript updates and turn-taking changes, and
response_required
events when it determines it's appropriate to ask for a response from your server . The turn-taking model combines VAD (Voice Activity Detection) and predictive cues to determine when to listen or speak . When
content_complete
doesn't return
true
after agent responses (beyond response_id 0) , Retell may not recognize that the agent has fully finished speaking, which can delay turn-taking resolution to
user_turn
. This could explain why short affirmations like "okay" or "yes" weren't triggering
response_required
immediately—the system might still be waiting for the agent's content to be marked complete before confidently switching turns . Potential troubleshooting steps: 1. Verify your response events - Ensure you're setting
content_complete
to
true
in your response events when the agent finishes speaking . The response event structure requires a
content_complete
field that signals when the response is fully delivered . 2. Check responsiveness settings - If using Retell LLM, review the
responsiveness
parameter (ranging from 0-1) , which controls how responsive the agent is—lower values mean the agent waits more before responding [(2) ]() [(3) ]() [(4) ]() . 3. Review interruption sensitivity - The
interruption_sensitivity
parameter (0-1) controls how easily users c
an interrupt the agent . Lower values require more words/time for interruption, which might contribute to delayed turn-taking . For the specific call (call_0c20a368b8740f5ca1cf048776b) , I recommend checking your server logs to confirm whether
content_complete: true
was sent in response events after response_id 0, and consider adjusting responsiveness/interruption sensitivity settings if using Retell LLM .
Feel free to tag @AI Evy with additional questions. I also appreciate feedback, it helps me improve.