- Introduced a new Jupyter notebook `update_blog_data.ipynb` for updating blog data and vector store with new posts.
- Created a Python script `pipeline.py` to handle the blog data update process, including command-line argument parsing and statistics saving.
- Added a shell script `build-vector-db.sh` to facilitate the execution of the pipeline script.
- Generated multiple JSON files in the `stats` directory to track blog statistics over time, including total documents, character counts, and length metrics.
- Removed the Jupyter notebook `utils_data_loading.ipynb` and migrated utility functions to `blog_utils.py`.
- Created a new configuration file `config.py` to manage environment variables and default settings.
- Implemented a script `update_blog_data.py` for updating the blog data vector store with command-line options.
- Added a JSON file `blog_stats_20250510_161540.json` to store blog statistics.
- Enhanced document processing functions for better modularity and error handling.
