Overview
GeminiLiveVertexLLMService
enables natural, real-time conversations with Google’s Gemini model through Vertex AI. It provides built-in audio transcription, voice activity detection, and context management for creating interactive AI experiences with multimodal capabilities including audio, video, and text processing.
Want to start building? Check out our Gemini Live
Guide for general concepts, then follow the
Vertex AI-specific setup below.
Gemini Live Vertex API Reference
Pipecat’s API methods for Gemini Live Vertex AI integration
Example Implementation
Complete Gemini Live Vertex AI function calling example
Vertex AI Gemini Documentation
Official Vertex AI Gemini Live API documentation
Google Cloud Vertex AI
Official Google Cloud Vertex AI platform
Installation
To use Gemini Live Vertex AI services, install the required dependencies:Prerequisites
Google Cloud Setup
Before using Gemini Live Vertex AI services, you need:- Google Cloud Project: Set up a project in the Google Cloud Console
- Vertex AI API: Enable the Vertex AI API in your project
- Service Account: Create a service account with
roles/aiplatform.user
androles/ml.developer
permissions - Authentication: Set up service account credentials or Application Default Credentials
Required Environment Variables
GOOGLE_VERTEX_TEST_CREDENTIALS
: JSON string of service account credentials (optional if using ADC)GOOGLE_CLOUD_PROJECT_ID
: Your Google Cloud project IDGOOGLE_CLOUD_LOCATION
: Vertex AI region (e.g., “us-east4”)
Key Features
- Enterprise Authentication: Secure service account-based authentication
- Multimodal Processing: Handle audio, video, and text inputs simultaneously
- Real-time Streaming: Low-latency audio and video processing
- Voice Activity Detection: Automatic speech detection and turn management
- Function Calling: Advanced tool integration and API calling capabilities
- Context Management: Intelligent conversation history and system instruction handling