## Version 0.5.0

This release includes several improvements and new features for the LlamaBot project.

### New Features

- Added a new Jupyter notebook example demonstrating how to build a bot for checking if docstrings match the function source code (3f87427) (Eric Ma)
- Enhanced the StructuredBot initialization process by including default language model configuration (7a352ca) (Eric Ma)
- Introduced a new Jupyter notebook example showcasing the usage of LlamaBot with the Groq API (2dc21be) (Eric Ma)
- Renamed and enhanced the PydanticBot example notebook to better reflect its purpose of extracting structured data from unstructured text (bf27391) (Eric Ma)
- Added unit tests for StructuredBot functionality to ensure it properly returns a Pydantic model when given a specific input (912a76c) (Eric Ma)
- Restructured bot imports and added StructuredBot to the top-level API (320869d) (Eric Ma)

### Bug Fixes

- Corrected the conditional check in the GitHub Actions workflow for building the devcontainer to use `github.repository_owner` instead of `github.owner`, ensuring the build is triggered by the correct repository owner context (a79b4c4) (Eric Ma)
- Changed the quote style around `github.owner` condition to maintain consistency across the project (86b1732) (Eric Ma)
- Fixed the title in the `structuredbot.ipynb` example to reflect the correct bot name (1f2e2b7) (Eric Ma)

### Deprecations

- The import paths for ChatBot, QueryBot, SimpleBot, and ImageBot have changed due to the restructuring of bot imports. Users will need to update their import statements to reflect the new structure (320869d) (Eric Ma)

Please note that this release also includes various improvements to the GitHub Actions workflow, such as adding a push event trigger for the main branch, streamlining conditions for the build-container job, and enabling cache for Docker layers to improve build speed.
