When working with OpenAI’s API, it’s important to set up your environment and client correctly to ensure secure and efficient API calls. This guide shows you how to create a basic integration using Galileo’s OpenAI client wrapper.
The Galileo OpenAI wrapper currently only supports the synchronous chat completions API.

​
What you’ll need

  • OpenAI API key
  • Galileo API key
  • Python or TypeScript environment
  • Required packages installed

​
Basic setup requirements

  • Environment Variables: Secure storage of API keys
  • Required Packages: Galileo and OpenAI clients
  • Python Environment: 3.9 or higher recommended

​
Implementation steps

1

Set Up Environment Variables

Create a .env file in your project root:
# Galileo Environment Variables

# Your Galileo API key
GALILEO_API_KEY=your-galileo-api-key

# Your Galileo project name
GALILEO_PROJECT="your-galileo-project-name"

# The name of the log stream you want to use for logging
GALILEO_LOG_STREAM="your-galileo-log-stream"

# Provide the console url below if you are using a
# custom deployment, and not using the free tier, or app.galileo.ai.
# This will look something like “console.galileo.yourcompany.com”.
# GALILEO_CONSOLE_URL="your-galileo-console-url"

# OpenAI properties
OPENAI_API_KEY="your-openai-api-key"

# Optional. The base URL of your OpenAI deployment. 
# Leave this commented out if you are using the default OpenAI API.
# OPENAI_BASE_URL="your-openai-base-url-here"

# Optional. Your OpenAI organization.
# OPENAI_ORGANIZATION="your-openai-organization-here"
This assumes you are using a free Galileo account. If you are using a custom deployment, then you will also need to add the URL of your Galileo Console:
.env
GALILEO_CONSOLE_URL=your-Galileo-console-URL
2

Install Required Dependencies

Install the required dependencies for your app. If you are using Python, create a virtual environment using your preferred method, then install dependencies inside that environment:
pip install "galileo[openai]" python-dotenv
3

Initialize the Client

  • Import required packages
  • Load environment variables
  • Create OpenAI client instance with Galileo wrapper
4

Create a Chat Completion

  • Structure your prompt
  • Call the API using the client
  • Process and use the response
import os
from galileo.openai import openai
from dotenv import load_dotenv

load_dotenv()

client = openai.OpenAI(
    api_key=os.environ.get("OPENAI_API_KEY"),
    organization=os.environ.get("OPENAI_ORGANIZATION")
)

prompt = "Explain the following topic succinctly: Newton's First Law"
response = client.chat.completions.create(
    model="gpt-4",
    messages=[{"role": "user", "content": prompt}],
)

print(response.choices[0].message.content.strip())
Your logging is now set up! You are ready to configure metrics for your project.

​
See also