|
12 | 12 | inference, |
13 | 13 | room_io, |
14 | 14 | ) |
15 | | -from livekit.plugins import noise_cancellation, silero |
| 15 | +from livekit.plugins import ai_coustics, noise_cancellation, silero |
16 | 16 | from livekit.plugins.turn_detector.multilingual import MultilingualModel |
17 | 17 |
|
18 | 18 | logger = logging.getLogger("agent") |
@@ -72,7 +72,7 @@ async def my_agent(ctx: JobContext): |
72 | 72 | stt=inference.STT(model="deepgram/nova-3", language="multi"), |
73 | 73 | # A Large Language Model (LLM) is your agent's brain, processing user input and generating a response |
74 | 74 | # See all available models at https://docs.livekit.io/agents/models/llm/ |
75 | | - llm=inference.LLM(model="openai/gpt-4.1-mini"), |
| 75 | + llm=inference.LLM(model="openai/gpt-5.2-chat-latest"), |
76 | 76 | # Text-to-speech (TTS) is your agent's voice, turning the LLM's text into speech that the user can hear |
77 | 77 | # See all available models as well as voice selections at https://docs.livekit.io/agents/models/tts/ |
78 | 78 | tts=inference.TTS( |
@@ -115,7 +115,9 @@ async def my_agent(ctx: JobContext): |
115 | 115 | noise_cancellation.BVCTelephony() |
116 | 116 | if params.participant.kind |
117 | 117 | == rtc.ParticipantKind.PARTICIPANT_KIND_SIP |
118 | | - else noise_cancellation.BVC() |
| 118 | + else ai_coustics.audio_enhancement( |
| 119 | + model=ai_coustics.EnhancerModel.QUAIL_VF_L |
| 120 | + ) |
119 | 121 | ), |
120 | 122 | ), |
121 | 123 | ), |
|
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