diff --git a/README.md b/README.md index 01e9562..acffaa9 100644 --- a/README.md +++ b/README.md @@ -9,7 +9,7 @@ A complete starter project for building voice AI apps with [LiveKit Agents for P The starter project includes: - A simple voice AI assistant, ready for extension and customization -- A voice AI pipeline with [models](https://docs.livekit.io/agents/models) from OpenAI, Cartesia, and AssemblyAI served through LiveKit Cloud +- A voice AI pipeline with [models](https://docs.livekit.io/agents/models) from OpenAI, Cartesia, and Deepgram served through LiveKit Cloud - Easily integrate your preferred [LLM](https://docs.livekit.io/agents/models/llm/), [STT](https://docs.livekit.io/agents/models/stt/), and [TTS](https://docs.livekit.io/agents/models/tts/) instead, or swap to a realtime model like the [OpenAI Realtime API](https://docs.livekit.io/agents/models/realtime/openai) - Eval suite based on the LiveKit Agents [testing & evaluation framework](https://docs.livekit.io/agents/build/testing/) - [LiveKit Turn Detector](https://docs.livekit.io/agents/build/turns/turn-detector/) for contextually-aware speaker detection, with multilingual support diff --git a/src/agent.py b/src/agent.py index aab4ded..4554073 100644 --- a/src/agent.py +++ b/src/agent.py @@ -65,11 +65,11 @@ async def my_agent(ctx: JobContext): "room": ctx.room.name, } - # Set up a voice AI pipeline using OpenAI, Cartesia, AssemblyAI, and the LiveKit turn detector + # Set up a voice AI pipeline using OpenAI, Cartesia, Deepgram, and the LiveKit turn detector session = AgentSession( # Speech-to-text (STT) is your agent's ears, turning the user's speech into text that the LLM can understand # See all available models at https://docs.livekit.io/agents/models/stt/ - stt=inference.STT(model="assemblyai/universal-streaming", language="en"), + stt=inference.STT(model="deepgram/nova-3", language="multi"), # A Large Language Model (LLM) is your agent's brain, processing user input and generating a response # See all available models at https://docs.livekit.io/agents/models/llm/ llm=inference.LLM(model="openai/gpt-4.1-mini"), @@ -111,9 +111,12 @@ async def my_agent(ctx: JobContext): room=ctx.room, room_options=room_io.RoomOptions( audio_input=room_io.AudioInputOptions( - noise_cancellation=lambda params: noise_cancellation.BVCTelephony() - if params.participant.kind == rtc.ParticipantKind.PARTICIPANT_KIND_SIP - else noise_cancellation.BVC(), + noise_cancellation=lambda params: ( + noise_cancellation.BVCTelephony() + if params.participant.kind + == rtc.ParticipantKind.PARTICIPANT_KIND_SIP + else noise_cancellation.BVC() + ), ), ), )