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.

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What You’ll Need

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

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Basic Setup Requirements

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

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Implementation Steps

1

Set Up Environment Variables

Create a .env file in your project root:

.env
GALILEO_API_KEY=your_galileo_api_key
GALILEO_PROJECT=your_project_name
GALILEO_LOG_STREAM=your_log_stream

OPENAI_API_KEY=your_openai_api_key

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.

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See also