Metadata-Version: 2.4
Name: rsazure-openai-toolkit
Version: 0.1.0
Summary: Toolkit for fast and flexible integration with Azure OpenAI
Author-email: Renan Siqueira Antonio <renan.siqu@gmail.com>
License: MIT
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: openai>=1.0.0
Requires-Dist: tenacity>=8.2.0
Requires-Dist: python-dotenv>=1.0.0
Dynamic: license-file

![PyPI - Python Version](https://img.shields.io/pypi/pyversions/rsazure-openai-toolkit)
![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)

# rsazure-openai-toolkit

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

### From PyPI:
```bash
pip install rsazure-openai-toolkit
```
### From GitHub:
```bash
pip install git+https://github.com/renan-siqueira/rsazure-openai-toolkit
```
___
## Usage

```python
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:

```env
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:

```python
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](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:

- GitHub: [github.com/renan-siqueira](https://github.com/renan-siqueira)
- Email: [renan.siqu@gmail.com](mailto:renan.siqu@gmail.com)

Contributions, suggestions, and bug reports are welcome!
