Google Vertex

The vertex provider enables integration with Google's Vertex AI platform, which provides access to foundation models including Gemini, PaLM (Bison), Llama, Claude, and specialized models for text, code, and embeddings.

Available Models

Latest Gemini Models

vertex:gemini-2.0-flash-001 - Next-gen workhorse model for all daily tasks. Supports text, code, images, audio, video, video with audio, and PDF inputs.
vertex:gemini-2.0-pro-exp-02-05 - Strongest model quality, especially for code & world knowledge (2M context). Supports text, images, video, audio, and PDF inputs.
vertex:gemini-2.0-flash-lite-preview-02-05 - Cost-effective offering for high throughput. Supports text, images, video, audio, and PDF inputs.
vertex:gemini-2.0-flash-thinking-exp-01-21 - Enhanced reasoning with thinking process in responses. Supports text and images.
vertex:gemini-1.5-flash - Speed and efficiency for high-volume applications. Supports text, code, images, audio, video, video with audio, and PDF inputs.
vertex:gemini-1.5-pro - Long-context understanding and general-purpose use. Supports text, code, images, audio, video, video with audio, and PDF inputs.
vertex:gemini-1.5-pro-latest - Latest Gemini 1.5 Pro model with same capabilities as gemini-1.5-pro
vertex:gemini-1.0-pro - Best performing model for text-only tasks (deprecated)
vertex:gemini-1.0-pro-vision - Best performing image and video understanding model (deprecated)

Claude Models

Anthropic's Claude models are available with the following versions:

vertex:claude-3-haiku@20240307 - Fast Claude 3 Haiku
vertex:claude-3-sonnet@20240229 - Claude 3 Sonnet
vertex:claude-3-opus@20240229 - Claude 3 Opus (Public Preview)
vertex:claude-3-5-haiku@20241022 - Claude 3.5 Haiku
vertex:claude-3-5-sonnet-v2@20241022 - Claude 3.5 Sonnet

note

Claude models require explicit access enablement through the Vertex AI Model Garden. Navigate to the Model Garden, search for "Claude", and enable the specific models you need.

Note: Claude models support up to 200,000 tokens context length and include built-in safety features.

Llama Models (Preview)

Meta's Llama models are available through Vertex AI with the following versions:

vertex:llama-3.3-70b-instruct-maas - Latest Llama 3.3 70B model (Preview)
vertex:llama-3.2-90b-vision-instruct-maas - Vision-capable Llama 3.2 90B (Preview)
vertex:llama-3.1-405b-instruct-maas - Llama 3.1 405B (GA)
vertex:llama-3.1-70b-instruct-maas - Llama 3.1 70B (Preview)
vertex:llama-3.1-8b-instruct-maas - Llama 3.1 8B (Preview)

Note: Llama models support up to 128,000 tokens context length and include built-in safety features through Llama Guard.

Llama Configuration Example

providers:
  - id: vertex:llama-3.3-70b-instruct-maas
    config:
      region: us-central1 # Llama models are only available in this region
      temperature: 0.7
      maxOutputTokens: 1024
      llamaConfig:
        safetySettings:
          enabled: true # Llama Guard is enabled by default
          llama_guard_settings: {} # Optional custom settings

By default, Llama models use Llama Guard for content safety. You can disable it by setting enabled: false, but this is not recommended for production use.

Gemma Models (Open Models)

vertex:gemma - Lightweight text model for generation and summarization
vertex:codegemma - Code-specialized model for generation and completion
vertex:paligemma - Vision-language model for image tasks

PaLM 2 (Bison) Models

Please note the PaLM (Bison) models are scheduled for deprecation (April 2025) and it's recommended to migrate to the Gemini models.

vertex:chat-bison[@001|@002] - Chat model
vertex:chat-bison-32k[@001|@002] - Extended context chat
vertex:codechat-bison[@001|@002] - Code-specialized chat
vertex:codechat-bison-32k[@001|@002] - Extended context code chat
vertex:text-bison[@001|@002] - Text completion
vertex:text-unicorn[@001] - Specialized text model
vertex:code-bison[@001|@002] - Code completion
vertex:code-bison-32k[@001|@002] - Extended context code completion

Embedding Models

vertex:textembedding-gecko@001 - Text embeddings (3,072 tokens, 768d)
vertex:textembedding-gecko@002 - Text embeddings (2,048 tokens, 768d)
vertex:textembedding-gecko@003 - Text embeddings (2,048 tokens, 768d)
vertex:text-embedding-004 - Latest text embeddings (2,048 tokens, ≤768d)
vertex:text-embedding-005 - Latest text embeddings (2,048 tokens, ≤768d)
vertex:textembedding-gecko-multilingual@001 - Multilingual embeddings (2,048 tokens, 768d)
vertex:text-multilingual-embedding-002 - Latest multilingual embeddings (2,048 tokens, ≤768d)
vertex:multimodalembedding - Multimodal embeddings for text, image, and video

tip

If you're using Google AI Studio directly, see the google provider documentation instead.

Setup and Authentication

1. Install Dependencies

Install Google's official auth client:

npm install google-auth-library

2. Enable API Access

Enable the Vertex AI API in your Google Cloud project
For Claude models, request access through the Vertex AI Model Garden by:
- Navigating to "Model Garden"
- Searching for "Claude"
- Clicking "Enable" on the models you want to use
Set your project in gcloud CLI:
```
gcloud config set project PROJECT_ID
```

3. Authentication Methods

Choose one of these authentication methods:

User Account (recommended for development):

# First, authenticate with Google Cloud
gcloud auth login

# Then, set up application default credentials
gcloud auth application-default login

Service Account:
- Option A: Use a machine with an authorized service account
- Option B: Use service account credentials file:
```
export GOOGLE_APPLICATION_CREDENTIALS=/path/to/credentials.json
```

Configuration

Environment Variables

VERTEX_API_KEY - GCloud API token (get via gcloud auth print-access-token)
VERTEX_PROJECT_ID - GCloud project ID
VERTEX_REGION - Region (defaults to us-central1)
VERTEX_PUBLISHER - Model publisher (defaults to google)
VERTEX_API_HOST - Override API host (e.g., for LLM proxy)
VERTEX_API_VERSION - API version (defaults to v1)

Provider Configuration

Configure model behavior using the following options:

providers:
  # For Gemini models
  - id: vertex:gemini-2.0-pro
    config:
      generationConfig:
        temperature: 0
        maxOutputTokens: 1024
        topP: 0.8
        topK: 40

  # For Llama models
  - id: vertex:llama-3.3-70b-instruct-maas
    config:
      generationConfig:
        temperature: 0.7
        maxOutputTokens: 1024
        extra_body:
          google:
            model_safety_settings:
              enabled: true
              llama_guard_settings: {}

  # For Claude models
  - id: vertex:claude-3-5-sonnet-v2@20241022
    config:
      anthropic_version: 'vertex-2023-10-16'
      max_tokens: 1024

Safety Settings

Control AI safety filters:

- id: vertex:gemini-pro
  config:
    safetySettings:
      - category: HARM_CATEGORY_HARASSMENT
        threshold: BLOCK_ONLY_HIGH
      - category: HARM_CATEGORY_VIOLENCE
        threshold: BLOCK_MEDIUM_AND_ABOVE

See Google's SafetySetting API documentation for details.

Model-Specific Features

Llama Model Features

Support for text and vision tasks (Llama 3.2)
Built-in safety with Llama Guard (enabled by default)
Available in us-central1 region
Quota limits vary by model version (30-60 QPM)
Maximum context length of 128,000 tokens
Requires specific endpoint format for API calls
Only supports unary (non-streaming) responses in promptfoo

Llama Model Considerations

Regional Availability: Llama models are available only in us-central1 region
Guard Integration: All Llama models use Llama Guard for content safety by default
Specific Endpoint: Uses a different API endpoint than other Vertex models
Model Status: Most models are in Preview state, with Llama 3.1 405B being Generally Available (GA)
Vision Support: Only Llama 3.2 90B supports image input

Claude Model Features

Support for text, code, and analysis tasks
Tool use (function calling) capabilities
Available in multiple regions (us-east5, europe-west1, asia-southeast1)
Quota limits vary by model version (20-245 QPM)

Advanced Usage

Default Grading Provider

When Google credentials are configured (and no OpenAI/Anthropic keys are present), Vertex AI becomes the default provider for:

Model grading
Suggestions
Dataset generation

Override grading providers using defaultTest:

defaultTest:
  options:
    provider:
      # For llm-rubric and factuality assertions
      text: vertex:gemini-1.5-pro-002
      # For similarity comparisons
      embedding: vertex:embedding:text-embedding-004

Configuration Reference

Option	Description	Default
`apiKey`	GCloud API token	None
`apiHost`	API host override	`{region}-aiplatform.googleapis.com`
`apiVersion`	API version	`v1`
`projectId`	GCloud project ID	None
`region`	GCloud region	`us-central1`
`publisher`	Model publisher	`google`
`context`	Model context	None
`examples`	Few-shot examples	None
`safetySettings`	Content filtering	None
`generationConfig.temperature`	Randomness control	None
`generationConfig.maxOutputTokens`	Max tokens to generate	None
`generationConfig.topP`	Nucleus sampling	None
`generationConfig.topK`	Sampling diversity	None
`generationConfig.stopSequences`	Generation stop triggers	`[]`
`toolConfig`	Tool/function calling config	None
`systemInstruction`	System prompt (supports `{{var}}`)	None

note

Not all models support all parameters. See Google's documentation for model-specific details.

Troubleshooting

Authentication Errors

If you see an error like:

API call error: Error: {"error":"invalid_grant","error_description":"reauth related error (invalid_rapt)","error_uri":"https://support.google.com/a/answer/9368756","error_subtype":"invalid_rapt"}

Re-authenticate using:

gcloud auth application-default login

Claude Model Access Errors

If you encounter errors like:

API call error: Error: Project is not allowed to use Publisher Model `projects/.../publishers/anthropic/models/claude-*`

API call error: Error: Publisher Model is not servable in region us-central1

You need to:

Enable access to Claude models:
- Visit the Vertex AI Model Garden
- Search for "Claude"
- Click "Enable" on the specific Claude models you want to use
Use a supported region. Claude models are only available in:
- us-east5
- europe-west1

Example configuration with correct region:

providers:
  - id: vertex:claude-3-5-sonnet-v2@20241022
    config:
      region: us-east5 # or europe-west1
      anthropic_version: 'vertex-2023-10-16'
      max_tokens: 1024

Model Features and Capabilities

Function Calling and Tools

Gemini and Claude models support function calling and tool use. Configure tools in your provider:

providers:
  - id: vertex:gemini-2.0-pro
    config:
      toolConfig:
        functionCallingConfig:
          mode: 'AUTO' # or "ANY", "NONE"
          allowedFunctionNames: ['get_weather', 'search_places']
      tools:
        - functionDeclarations:
            - name: 'get_weather'
              description: 'Get weather information'
              parameters:
                type: 'OBJECT'
                properties:
                  location:
                    type: 'STRING'
                    description: 'City name'
                required: ['location']

Tools can also be loaded from external files:

providers:
  - id: vertex:gemini-2.0-pro
    config:
      tools: 'file://tools.json' # Supports variable substitution

System Instructions

Configure system-level instructions for the model:

providers:
  - id: vertex:gemini-2.0-pro
    config:
      systemInstruction:
        parts:
          - text: 'You are a helpful assistant that {{role}}' # Supports Nunjucks templates

Generation Configuration

Fine-tune model behavior with these parameters:

providers:
  - id: vertex:gemini-2.0-pro
    config:
      generationConfig:
        temperature: 0.7 # Controls randomness (0.0 to 1.0)
        maxOutputTokens: 1024 # Limit response length
        topP: 0.8 # Nucleus sampling
        topK: 40 # Top-k sampling
        stopSequences: ["\n"] # Stop generation at specific sequences

Context and Examples

Provide context and few-shot examples:

providers:
  - id: vertex:gemini-2.0-pro
    config:
      context: 'You are an expert in machine learning'
      examples:
        - input: 'What is regression?'
          output: 'Regression is a statistical method...'

Safety Settings

Configure content filtering with granular control:

providers:
  - id: vertex:gemini-2.0-pro
    config:
      safetySettings:
        - category: 'HARM_CATEGORY_HARASSMENT'
          threshold: 'BLOCK_ONLY_HIGH'
        - category: 'HARM_CATEGORY_HATE_SPEECH'
          threshold: 'BLOCK_MEDIUM_AND_ABOVE'
        - category: 'HARM_CATEGORY_SEXUALLY_EXPLICIT'
          threshold: 'BLOCK_LOW_AND_ABOVE'

Available Models​

Latest Gemini Models​

Claude Models​

Llama Models (Preview)​

Llama Configuration Example​

Gemma Models (Open Models)​

PaLM 2 (Bison) Models​

Embedding Models​

Setup and Authentication​

1. Install Dependencies​

2. Enable API Access​

3. Authentication Methods​

Configuration​

Environment Variables​

Provider Configuration​

Safety Settings​

Model-Specific Features​

Llama Model Features​

Llama Model Considerations​

Claude Model Features​

Advanced Usage​

Default Grading Provider​

Configuration Reference​

Troubleshooting​

Authentication Errors​

Claude Model Access Errors​

Model Features and Capabilities​

Function Calling and Tools​

System Instructions​

Generation Configuration​

Context and Examples​

Safety Settings​

Available Models

Latest Gemini Models

Claude Models

Llama Models (Preview)

Llama Configuration Example

Gemma Models (Open Models)

PaLM 2 (Bison) Models

Embedding Models

Setup and Authentication

1. Install Dependencies

2. Enable API Access

3. Authentication Methods

Configuration

Environment Variables

Provider Configuration

Safety Settings

Model-Specific Features

Llama Model Features

Llama Model Considerations

Claude Model Features

Advanced Usage

Default Grading Provider

Configuration Reference

Troubleshooting

Authentication Errors

Claude Model Access Errors

Model Features and Capabilities

Function Calling and Tools

System Instructions

Generation Configuration

Context and Examples

Safety Settings