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Toolkit for fast and flexible integration with Azure OpenAI

Project description

PyPI version License: MIT

rsazure-openai-toolkit

A lightweight, independent toolkit to simplify and accelerate integration with Azure OpenAI.


Installation

From PyPI:

pip install rsazure-openai-toolkit

From GitHub:

pip install git+https://github.com/renan-siqueira/rsazure-openai-toolkit

Usage

from rsazure_openai_toolkit import call_azure_openai_handler

response = call_azure_openai_handler(
    api_key="your-api-key",
    azure_endpoint="https://your-resource.openai.azure.com/",
    api_version="2023-12-01-preview",
    deployment_name="gpt-35-turbo",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Summarize what artificial intelligence is."}
    ]
)

print(response)

Environment Configuration

To simplify local development and testing, this toolkit supports loading environment variables from a .env file.

Create a .env file in your project root (or copy the provided .env.example) and add your Azure OpenAI credentials:

AZURE_OPENAI_API_KEY=your-api-key
AZURE_OPENAI_ENDPOINT=https://your-resource.openai.azure.com/
AZURE_OPENAI_API_VERSION=2023-12-01-preview
AZURE_DEPLOYMENT_NAME=your-deployment-name

In your script, load the environment variables before calling the handler:

from dotenv import load_dotenv
import os

load_dotenv()  # defaults to loading from .env in the current directory

from rsazure_openai_toolkit import call_azure_openai_handler

response = call_azure_openai_handler(
    api_key=os.getenv("AZURE_OPENAI_API_KEY"),
    azure_endpoint=os.getenv("AZURE_OPENAI_ENDPOINT"),
    api_version=os.getenv("AZURE_OPENAI_API_VERSION"),
    deployment_name=os.getenv("AZURE_DEPLOYMENT_NAME"),
    messages=[...]
)

Features

  • Modular and easy to extend
  • Retry mechanism with exponential backoff
  • Accepts OpenAI-compatible parameters
  • Ready for production use

Requirements

  • Python 3.9+
  • Azure OpenAI resource and deployment

License

This project is open-sourced and available to everyone under the MIT License.


🚨 Possible Issues

  • Invalid API Key or Endpoint
    Ensure your AZURE_OPENAI_API_KEY and AZURE_OPENAI_ENDPOINT are correctly set in your .env file.

  • Deployment Not Found
    Check that your deployment_name matches exactly the name defined in your Azure OpenAI resource.

  • Timeouts or 5xx Errors
    The toolkit includes automatic retries with exponential backoff via tenacity. If errors persist, verify network access or Azure service status.

  • Missing Environment Variables
    Always ensure load_dotenv() is called before accessing os.getenv(...), especially when testing locally.


📬 Contact

This project is maintained by Renan Siqueira Antonio.

Feel free to reach out via:

Contributions, suggestions, and bug reports are welcome!


👨‍💻 About the Author

Hi, I'm Renan Siqueira Antonio — a technical leader in Artificial Intelligence with hands-on experience in delivering real-world AI solutions across different industries.

Over the years, I've had the opportunity to collaborate with incredible teams and contribute to initiatives recognized by companies.

This project was born from a personal need: to create a clean, reusable, and production-ready way to interact with Azure OpenAI. I'm sharing it with the hope that it helps others move faster and build better.

🔗 LinkedIn

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