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update agent TTS and README #3

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1 change: 0 additions & 1 deletion .env.example
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Original file line number Diff line number Diff line change
@@ -1,5 +1,4 @@
LIVEKIT_URL=wss://testproject-12345.livekit.cloud
LIVEKIT_API_KEY=livekit-api-key
LIVEKIT_API_SECRET=livekit-api-secret
ELEVEN_API_KEY=elevenlabs-api-key
GROQ_API_KEY=groq-api-key
10 changes: 4 additions & 6 deletions README.md
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# LiveKit + Groq Voice AI Assistant

[LiveKit](https://livekit.io) complements Groq's high-performance speech recognition capabilities by providing text-to-speech and real-time communication features. This integration enables you to build end-to-end AI voice applications with:
[LiveKit](https://livekit.io) complements Groq's fast AI inference with real-time communication features. This integration enables you to build end-to-end AI voice applications with:

- **Complete Voice Pipeline:** Combine Groq's fast and accurate speech-to-text (STT) with LiveKit's text-to-speech (TTS) capabilities
- **Complete Voice Pipeline:** Combine Groq's fast and accurate text, speech-to-text (STT), and text-to-speech (TTS) models with LiveKit's infrastructure
- **Real-time Communication:** Enable multi-user voice interactions with LiveKit's WebRTC infrastructure
- **Flexible TTS Options:** Access multiple text-to-speech voices and languages through LiveKit's TTS integrations
- **Scalable Architecture:** Handle thousands of concurrent users with LiveKit's distributed system
- **Web Search Enabled:** This template uses Groq's `compound-mini` model with built-in web search capabilities. Try asking questions like "What's the weather in San Francisco?" or "What are today's top headlines?" and watch it fetch real-time information from the web!

This repository is a complete starter template for building end-to-end voice AI assistants with natural voice conversations and sub-second response times using Groq's optimized models and LiveKit's real-time media platform.
This repository is a complete starter template for building end-to-end voice AI assistants with natural voice conversations and sub-second response times using models hosted on Groq and LiveKit's real-time media platform.

## Live Demo

Expand Down Expand Up @@ -39,7 +38,7 @@ You'll need a free LiveKit Cloud account to handle the real-time media infrastru
3. Get your API credentials from the project settings

**Key Features:**
- **Sub-second response times** with Groq's optimized inference
- **Sub-second response times** with Groq's inference
- **Real-time voice streaming** via LiveKit's infrastructure
- **Production-ready** noise cancellation and turn detection
- **Modern React UI** with real-time transcription display
Expand Down Expand Up @@ -159,7 +158,6 @@ LIVEKIT_API_SECRET=your-api-secret

# Groq API key (get from Groq Console)
GROQ_API_KEY=your-groq-api-key
ELEVEN_API_KEY=elevenlabs-api-key

**You also need to create a `.env.local` in the `voice-assistant-frontend/` directory:**
```bash
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2 changes: 1 addition & 1 deletion agent.py
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Expand Up @@ -41,7 +41,7 @@ async def entrypoint(ctx: agents.JobContext):
session = AgentSession(
stt=groq.STT(model="whisper-large-v3-turbo", language="en"),
llm=groq.LLM(model="groq/compound-mini"),
tts=elevenlabs.TTS(model="eleven_flash_v2_5", voice_id="Xb7hH8MSUJpSbSDYk0k2"),
tts=groq.TTS(model="playai-tts"),
vad=silero.VAD.load(),
turn_detection=MultilingualModel(),
)
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