codeflash-agent/.tessl/tiles/tessl/pypi-anthropic/docs/platforms/vertex.md

Google Vertex AI Integration

Access Claude models on Google Cloud Platform with Vertex AI integration.

Installation

pip install anthropic[vertex]

Client Initialization

class AnthropicVertex:
    """Synchronous client for Claude on Google Vertex AI."""

    def __init__(
        self,
        *,
        project_id: str | None = None,
        region: str | None = None,
        timeout: float | httpx.Timeout = DEFAULT_TIMEOUT,
        max_retries: int = DEFAULT_MAX_RETRIES,
        default_headers: dict[str, str] | None = None,
        http_client: httpx.Client | None = None,
    ):
        """
        Initialize Vertex AI client.

        Parameters:
            project_id: GCP project ID (or CLOUD_ML_PROJECT_ID/GOOGLE_CLOUD_PROJECT env var)
            region: GCP region (or CLOUD_ML_REGION env var, default: us-east5)
            timeout: Request timeout
            max_retries: Maximum retry attempts
            default_headers: Custom headers
            http_client: Custom httpx.Client
        """
        ...

class AsyncAnthropicVertex:
    """Asynchronous client for Claude on Google Vertex AI."""
    # Same parameters as AnthropicVertex
    ...

Vertex Model Identifiers

# Claude models on Vertex AI
"claude-3-5-sonnet-v2@20241022"
"claude-3-5-sonnet@20240620"
"claude-3-5-haiku@20241022"
"claude-3-opus@20240229"
"claude-3-sonnet@20240229"
"claude-3-haiku@20240307"

Quick Examples

Basic Usage

from anthropic import AnthropicVertex

client = AnthropicVertex(
    project_id="my-gcp-project",
    region="us-east5"
)

message = client.messages.create(
    model="claude-3-5-sonnet-v2@20241022",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Hello!"}]
)

Using Environment Variables

# Set: CLOUD_ML_PROJECT_ID=my-gcp-project
# Set: CLOUD_ML_REGION=us-east5

client = AnthropicVertex()  # Automatically uses env vars

Using Application Default Credentials

# First authenticate: gcloud auth application-default login

client = AnthropicVertex(
    project_id="my-gcp-project",
    region="us-east5"
)

Streaming

with client.messages.stream(
    model="claude-3-5-sonnet-v2@20241022",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Write a story"}]
) as stream:
    for text in stream.text_stream:
        print(text, end="", flush=True)

Multi-Region Deployment

regions = ["us-east5", "europe-west1", "asia-southeast1"]

for region in regions:
    client = AnthropicVertex(
        project_id="my-gcp-project",
        region=region
    )
    message = client.messages.create(...)
    client.close()

Async Client

import asyncio
from anthropic import AsyncAnthropicVertex

async def main():
    client = AsyncAnthropicVertex(
        project_id="my-gcp-project",
        region="us-east5"
    )
    message = await client.messages.create(...)
    await client.close()

asyncio.run(main())

Environment Variables

• CLOUD_ML_PROJECT_ID or GOOGLE_CLOUD_PROJECT - GCP project ID
• CLOUD_ML_REGION - GCP region (default: us-east5)
• GOOGLE_APPLICATION_CREDENTIALS - Path to service account key JSON

Available Regions

• us-east5
• us-central1
• europe-west1
• europe-west4
• asia-southeast1

See Also

• Messages API - Core message creation
• Streaming API - Streaming responses