Vertex AI Python SDK Integration

Use Vertex AI’s Python SDK to integrate with Helicone to log your Vertex AI usage.

Proxy Integration

Python SDK

1

Create an account + Generate an API Key

Log into helicone or create an account. Once you have an account, you can generate an API key.

2

Set API keys as environment variables

export HELICONE_API_KEY=<your API key>
export PROJECT_ID=<your Google Cloud project ID>
export LOCATION=<your location>

3

Install required packages

Ensure you have the necessary packages installed in your Python environment:

pip install google-cloud-aiplatform

4

Import libraries

from vertexai.generative_models import GenerativeModel
import vertexai
import os

5

Initialize Vertex AI with Helicone

HELICONE_API_KEY = os.environ.get("HELICONE_API_KEY")
PROJECT_ID = os.environ.get("PROJECT_ID")
LOCATION = os.environ.get("LOCATION")

vertexai.init(
    project=PROJECT_ID,
    location=LOCATION,
    api_endpoint="gateway.helicone.ai",
    api_transport="rest",  # Must be 'rest' or else it will not work
    request_metadata=[
        ('helicone-target-url', f'https://{LOCATION}-aiplatform.googleapis.com'),
        ('helicone-auth', f'Bearer {HELICONE_API_KEY}')
    ]
)

6

Initialize the model and generate content

model = GenerativeModel("gemini-1.5-flash-001")
response = model.generate_content("Tell me a fun fact about space.")
print(response.text)