Release Notes

Django Polly follows semantic versioning. This document outlines the changes in each version.

0.0.5

Date: August 12th, 2024

  • Adding images to the documentation

  • Update README.rst

  • Update version

0.0.4

Date: August 12th, 2024

  • Publishing workflow to PyPi

  • Update topics in setup.py

  • Update README.rst

  • Update version

0.0.3

Date: August 12th, 2024

  • Publishing workflow to PyPi

  • Update topics in setup.py

0.0.2

Date: August 12th, 2024

  • Publishing workflow to PyPi

0.0.1

Date: August 12th, 2024

We are excited to announce the initial release of Django Polly!

This version introduces the core functionality for integrating Language Learning Models (LLMs) into Django projects.

Features

  • LLM Integration:
    • Support for creating and managing LLM instances (Parrots)

    • Integration with various LLM backends

    • Configurable AI model path

  • SmartConversations:
    • Framework for AI-powered conversations

    • Support for both synchronous and asynchronous communication styles

  • WebSocket Support:
    • Real-time communication capabilities using Django Channels

    • Custom consumers for handling WebSocket connections

  • Admin Interface:
    • Django admin integration for managing Parrots and SmartConversations

    • Custom admin actions for LLM management

  • Management Commands:
    • download_model command for easy LLM model acquisition

  • Extensibility:
    • Flexible architecture allowing for custom LLM backends

    • Easy integration with existing Django projects

Compatibility

  • Python 3.8+

  • Django 4.2 and 5.0

  • Channels 3.0+

Installation

You can install Django Polly 0.0.1 using pip:

pip install django-polly==0.0.1

Be sure to follow the installation guide for complete setup instructions.

Upgrade Instructions

As this is the initial release, there are no upgrade instructions. For new installations, please refer to the installation guide.

Bug Fixes

As this is the initial release, there are no bug fixes to report.

Known Issues

  • Performance with very large LLM models may be suboptimal. We recommend using smaller, more efficient models for best results.

  • WebSocket connections may require additional configuration in certain deployment environments.

Please report any issues you encounter on our GitHub issue tracker.

What’s Next

We are actively working on improving Django Polly. Future releases will focus on:

  • Performance optimizations for LLM interactions

  • Expanded LLM backend support

  • Enhanced documentation and tutorials

  • Improved error handling and debugging tools

Thank you for using Django Polly! We look forward to your feedback and contributions.