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# ask-ai
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Thanks for reaching out, giri. I'm an AI assistant and I'm here to help. Give me a moment while I research this topic.
Here are potential issues and best practices for the functions you provided: 1.
send_dtmf_code
Issues:
• Rapid Firing Prevention: Ensure a cooldown mechanism is implemented to prevent sending DTMF codes too quickly. For example, a 3-second cooldown is commonly used. • Proper Context Management: The function requires access to the room context and local participant. Ensure these are properly initialized and available. 2.
end_call
Issues:
• Context Availability: Verify that the job context is available before attempting to end calls. Missing context can lead to errors. • API Error Handling: Wrap API calls in try-catch blocks to handle exceptions, such as connection issues or API errors, gracefully. 3. General API Error Patterns: • Connection and Timeout Errors: Handle errors like
APIConnectionError
,
APITimeoutError
, and
APIStatusError
effectively. • Async/Await Issues: Ensure proper use of async/await, including awaiting function calls and handling exceptions in async contexts. 4. Best Practices: • Implement cooldown mechanisms for DTMF functions to prevent rapid firing. • Verify that required contexts (e.g., job context, room context) are available before making API calls. • Include comprehensive logging for debugging purposes. Note: Specific issues with the
delayed_response
function were not covered in the available documentation. If you encounter specific problems with this function, please provide additional details for further assistance. Sources: livekit-plugins/livekit-plugins-inworld/livekit/plugins/inworld/tts.py | ivr-nagivator/README.mdoc | telephony/sip_lifecycle.py
I don't have the answer you're looking for. You could also try asking your question: • in one of the other Slack channels or • to https://deepwiki.com/livekit/livekit_composite which is trained on all LiveKit source code If you find the answer, please post it here to help others!