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Overview

GoogleVertexLLMService provides access to Google’s language models through Vertex AI. It extends GoogleLLMService with Vertex AI authentication, connecting to Google’s enterprise AI services with enhanced security and compliance.

Vertex AI LLM API Reference

Pipecat’s API methods for Google Vertex AI integration

Example Implementation

Browse examples using Vertex AI models

Vertex AI Documentation

Official Google Vertex AI documentation

Google Cloud Console

Access Vertex AI and manage credentials

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Installation

To use Google Vertex AI services, install the required dependencies: 
uv add "pipecat-ai[google]"

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Prerequisites

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Google Cloud Setup

Before using Google Vertex AI LLM services, you need:
  1. Google Cloud Account: Sign up at Google Cloud Console
  2. Project Setup: Create a project and enable the Vertex AI API
  3. Service Account: Create a service account with Vertex AI permissions
  4. Authentication: Set up credentials via service account key or Application Default Credentials

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Required Environment Variables

  • GOOGLE_APPLICATION_CREDENTIALS: Path to your service account key file (recommended)
  • Or use Application Default Credentials for cloud deployments

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Configuration

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credentials
str
default:"None"
JSON string of Google service account credentials for authentication.
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credentials_path
str
default:"None"
Path to the service account JSON key file. Alternative to providing credentials as a string.
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project_id
str
required
Google Cloud project ID.
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location
str
default:"us-east4"
GCP region for the Vertex AI endpoint (e.g., "us-east4", "us-central1").
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model
str
default:"None"
deprecated
Deprecated in v0.0.105. Use settings=GoogleVertexLLMService.Settings(model=...) instead.
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params
GoogleLLMService.InputParams
default:"None"
deprecated
Deprecated in v0.0.105. Use settings=GoogleVertexLLMService.Settings(...) instead.
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settings
GoogleVertexLLMService.Settings
default:"None"
Runtime-configurable settings. See Google Gemini Settings for the full parameter reference.
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system_instruction
str
default:"None"
deprecated
Deprecated in v0.0.105. Use settings=GoogleVertexLLMService.Settings(system_instruction=...) instead.
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tools
list
default:"None"
List of available tools/functions for the model.
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tool_config
dict
default:"None"
Configuration for tool usage behavior.
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http_options
HttpOptions
default:"None"
HTTP options for the Google AI client.

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Usage

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Basic Setup

import os
from pipecat.services.google import GoogleVertexLLMService

llm = GoogleVertexLLMService(
    credentials_path=os.getenv("GOOGLE_APPLICATION_CREDENTIALS"),
    project_id="my-gcp-project",
    location="us-east4",
    model="gemini-2.5-flash",
)

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With Credentials JSON String

from pipecat.services.google import GoogleVertexLLMService

llm = GoogleVertexLLMService(
    credentials=os.getenv("GOOGLE_CREDENTIALS_JSON"),
    project_id="my-gcp-project",
    location="us-central1",
    settings=GoogleVertexLLMService.Settings(
        model="gemini-2.5-flash",
        temperature=0.7,
        top_p=0.9,
    ),
)

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With Application Default Credentials

from pipecat.services.google import GoogleVertexLLMService

# Uses ADC when neither credentials nor credentials_path is provided
llm = GoogleVertexLLMService(
    project_id="my-gcp-project",
    location="us-east4",
    model="gemini-2.5-flash",
)

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Notes

  • This service does not accept an api_key parameter. Use credentials, credentials_path, or Application Default Credentials instead.
  • GoogleVertexLLMService extends GoogleLLMService and uses the Google AI Python SDK with Vertex AI authentication.
  • Authentication supports three methods: direct JSON credentials string, path to a service account key file, or Application Default Credentials (ADC).
  • The project_id parameter is required. If location is not provided, it defaults to "us-east4".
The InputParams / params= pattern is deprecated as of v0.0.105. Use Settings / settings= instead. See the Service Settings guide for migration details.