Traceback (most recent call last): File "C:\Users\HP\AiCallAgentBackend\main.py", line 185, in <module> agents.cli.run_app(agents.WorkerOptions(entrypoint_fnc=entrypoint, initialize_timeout=120)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ TypeError: WorkerOptions.__init__() got an unexpected keyword argument 'initialize_timeout' PS C:\Users\HP\AiCallAgentBackend> python main.py console

Thanks for reaching out, Mubbashir. I'm an AI assistant and I'm here to help. Give me a moment while I research this topic.

session = AgentSession( llm=openai.LLM( model="gpt-4o", temperature=0.3 ), tts = openai.TTS( model="gpt-4o-mini-tts", voice="ash", instructions="Speak in a friendly and conversational tone.", ), # Improved turn detection with longer silence threshold turn_detection=EnglishModel(), vad=silero.VAD.load( min_silence_duration=0.8, min_speech_duration=0.3 ), stt = openai.STT( model="gpt-4o-transcribe", ), ) Is that correct?

Your implementation of

AgentSession

looks mostly on the right track! Here are a few important points to double-check: • Make sure the

turn_detection

model you’re using is compatible. For instance,

EnglishModel()

should be a valid choice for turn detection. • Take a moment to verify that the

silero.VAD.load

method is set up correctly, especially with the

min_silence_duration

and

min_speech_duration

parameters. • Also, confirm that your

openai.TTS

and

openai.STT

models are properly initialized and supported in your environment. If you run into any specific challenges or have questions along the way, please don’t hesitate to reach out—I’m here to help! Sources: examples/voice_agents/basic_agent.py | Building voice agents | LiveKit Docs | Turn detection and interruptions | LiveKit Docs | examples/src/realtime_turn_detector.ts

utterance_end_ms: 1000

Thanks for reaching out! The parameter

utterance_end_ms

isn’t recognized as a valid configuration in LiveKit’s AgentSession or related components, but don’t worry—we do have some similar parameters that help control the end-of-utterance behavior: • `min_endpointing_delay`: This sets the minimum silence duration before we consider the user’s turn complete (usually around 400-500 ms). • `max_endpointing_delay`: This is the maximum time we wait before ending the user’s turn (typically 6 seconds). • There are also STT-specific parameters like

end_of_utterance_silence_trigger

or

endpointing_ms

that handle silence-based utterance detection. If you’re aiming to adjust the end-of-utterance timing, these parameters should be just what you need. Feel free to reach out if you’d like a hand setting them up—I’m here to help! Sources: Deepgram STT integration guide | LiveKit Docs | How does end-of-utterance detection work in conversations? | Improving voice AI&amp;#39;s turn detection with transformers | AI voice agents | LiveKit Docs | livekit-agents/livekit/agents/voice/agent_session.py

interrupt_speech_duration=0.5, interrupt_min_words=1, min_endpointing_delay=0.5

Thank you for sharing those parameters! They’re indeed important for managing interruption and turn detection in LiveKit: • interrupt_speech_duration: This sets the minimum length of detected speech (in seconds) needed to recognize an interruption. By default, it’s

0.5

seconds. • interrupt_min_words: This defines the minimum number of transcribed words required to count an interruption as valid. The default is

0

, meaning there’s no minimum. • min_endpointing_delay: This is the minimum silence duration (in seconds) before a turn is finalized. The default is

0.5

seconds. Usually, these work hand-in-hand with

allow_interruptions=True

to create a smooth and natural conversation flow. If you'd like, I’m here to help you fine-tune these settings to best fit your needs! Sources: VoicePipelineAgent | LiveKit Docs | Turn detection and interruptions | LiveKit Docs | livekit-agents/livekit/agents/voice/agent_activity.py | agents/src/voice/agent_activity.ts | AI voice agents | LiveKit Docs