Python_Chatbot

Tools used in this project

• hydra: Manage configuration files - article
• pre-commit plugins: Automate code reviewing formatting - article
• DVC: Data version control - article
• pdoc: Automatically create an API documentation for your project

Set up the environment

To set up the environment run:

make activate
make setup

Start the application

To start the application run:

make run_app

Run a python script from the environment

To run a python script from the virtual environment run:

make run_python script="<name_of_script>"

Install new packages

To install new PyPI packages, run:

pip install <package-name>

Run the entire pipeline

To run the entire pipeline, type:

dvc repo

Version your data

Read this article on how to use DVC to version your data.

Basically, you start with setting up a remote storage. The remote storage is where your data is stored. You can store your data on DagsHub, Google Drive, Amazon S3, Azure Blob Storage, Google Cloud Storage, Aliyun OSS, SSH, HDFS, and HTTP.

dvc remote add -d remote <REMOTE-URL>

Commit the config file:

git commit .dvc/config -m "Configure remote storage"

Push the data to remote storage:

dvc push 

Add and push all changes to Git:

git add .
git commit -m 'commit-message'
git push origin <branch>

Auto-generate API documentation

To auto-generate API document for your project, run:

make docs