openai-responses

Log OpenAI Responses API calls with tool use

This is an example project demonstrating how to use Galileo to log OpenAI Responses API calls, including multi-turn tool calling. The example uses Galileo's wrapped OpenAI client to automatically instrument and log all API interactions.

The example defines two simulated tools (get_weather and get_stock_price), sends a user query that triggers both tool calls, executes the functions locally, and feeds the results back to the model for a final response.

Getting Started

To get started with this project, you'll need to have Python 3.12 or later installed. You can then install the required dependencies in a virtual environment:

pip install -r requirements.txt 

Or, if you're using uv:

uv sync

You will also need an OpenAI API key.

Configure environment variables

You will need to configure the following 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"

Usage

Once the dependencies are installed, you can run the example application:

python main.py

The application will send a query asking about the weather in San Francisco and the stock price of Apple. It will:

1. Call the OpenAI Responses API with the defined tools.
2. Parse the function calls returned by the model.
3. Execute the simulated get_weather and get_stock_price functions.
4. Send the tool results back to the model for a final natural language response.

All API calls are automatically logged to Galileo via the wrapped OpenAI client (from galileo import openai).

Project Structure

The project structure is as follows:

openai-responses/
├── main.py            # The main application file
├── pyproject.toml     # Python project configuration and dependencies
├── .python-version    # Python version specification
└── README.md          # Project documentation