This commit refactors the bot's architecture to dynamically load and build conversation flows from JSON files instead of hardcoding them in Python.
- Added to read flow definitions from the directory and dynamically build s.
- Refactored to use the new flow builder and load all conversation handlers at startup.
- Moved hardcoded links to environment variables for better configuration.
- Updated to support conditional branching for 'Other' options, using a field to define state transitions.
- Updated with the new link variables.
This commit introduces a three-database architecture to the application,
as specified in the `db_logic.md` file.
The changes include:
- A SQL initialization script (`db/init/init.sql`) to create the
`USERS_ALMA`, `vanity_hr`, and `vanity_attendance` databases and their
respective tables.
- SQLAlchemy models for all tables, organized into separate files
within the `models` directory.
- Refactoring of the database connection logic in `modules/database.py`
to support connections to all three databases.
- Creation of a `modules/logger.py` to handle request logging to the
`USERS_ALMA` database.
- Updates to `docker-compose.yml` to mount the initialization script and
build the bot image locally.
- Updates to `.env.example` to include the new database environment
variables.
- Restoration of the data dictionary to `db_tasks.md`.
This commit introduces Docker and Docker Compose to containerize the application and orchestrate it with a MySQL database.
Key changes include:
- Added a `Dockerfile` to create a container for the Python bot.
- Created a `docker-compose.yml` file to manage the bot and MySQL services.
- Added a `modules/database.py` module to handle database connections and logging with SQLAlchemy.
- Integrated request logging into all command handlers.
- Updated `requirements.txt` with necessary dependencies for MySQL.
- Updated `.env` and `.gitignore` to manage database credentials securely.
- Updated `Readme.md` with instructions on how to run the application using Docker Compose.
