docs: Update readme

README.md

@@ -1,7 +1,7 @@
 <a href="https://github.com/alexandrainst/foqa"><img src="https://github.com/alexandrainst/foqa/raw/main/gfx/alexandra_logo.png" width="239" height="175" align="right" /></a>
-# foqa
+# FoQA
 
-Faroese question-answering dataset.
+Faroese question-answering dataset, generated by GPT-4.
 
 ______________________________________________________________________
 [![Code Coverage](https://img.shields.io/badge/Coverage-100%25-brightgreen.svg)](https://github.com/alexandrainst/foqa/tree/main/tests)
@@ -16,149 +16,18 @@ Developer(s):
 - Dan Saattrup Nielsen ([email protected])
 
 
-## Setup
+## Quickstart
 
-### Installation
-
-1. Run `make install`, which sets up a virtual environment and all Python dependencies therein.
+1. Run `make install`, which sets up a virtual environment and all Python dependencies
+   therein.
 2. Run `source .venv/bin/activate` to activate the virtual environment.
+3. Run `python src/scripts/create_dataset.py` to create the dataset.
 
-### Adding and Removing Packages
-
-To install new PyPI packages, run:
-```
-poetry add <package-name>
-```
-
-To remove them again, run:
-```
-poetry remove <package-name>
-```
-
-To show all installed packages, run:
-```
-poetry show
-```
-
-
-## A Word on Modules and Scripts
-In the `src` directory there are two subdirectories, `foqa`
-and `scripts`. This is a brief explanation of the differences between the two.
-
-### Modules
-All Python files in the `foqa` directory are _modules_
-internal to the project package. Examples here could be a general data loading script,
-a definition of a model, or a training function. Think of modules as all the building
-blocks of a project.
-
-When a module is importing functions/classes from other modules we use the _relative
-import_ notation - here's an example:
-
-```
-from .other_module import some_function
-```
-
-### Scripts
-Python files in the `scripts` folder are scripts, which are short code snippets that
-are _external_ to the project package, and which is meant to actually run the code. As
-such, _only_ scripts will be called from the terminal. An analogy here is that the
-internal `numpy` code are all modules, but the Python code you write where you import
-some `numpy` functions and actually run them, that a script.
-
-When importing module functions/classes when you're in a script, you do it like you
-would normally import from any other package:
-
-```
-from foqa import some_function
-```
-
-Note that this is also how we import functions/classes in tests, since each test Python
-file is also a Python script, rather than a module.
-
-
-## Features
-
-### Docker Setup
-
-A Dockerfile is included in the new repositories, which by default runs
-`src/scripts/your_script.py`. You can build the Docker image and run the Docker
-container by running `make docker`.
-
-### Automatic Documentation
-
-Run `make docs` to create the documentation in the `docs` folder, which is based on
-your docstrings in your code. You can view this by running `make view-docs`.
-
-### Automatic Test Coverage Calculation
-
-Run `make test` to test your code, which also updates the "coverage badge" in the
-README, showing you how much of your code base that is currently being tested.
-
-### Continuous Integration
-
-Github CI pipelines are included in the repo, running all the tests in the `tests`
-directory, as well as building online documentation, if Github Pages has been enabled
-for the repository (can be enabled on Github in the repository settings).
-
-### Code Spaces
+The raw dataset will be stored in `data/raw` and will be updated continuously during
+creation, and the final dataset will appear in your `data/final`.
 
-Code Spaces is a new feature on Github, that allows you to develop on a project
-completely in the cloud, without having to do any local setup at all. This repo comes
-included with a configuration file for running code spaces on Github. When hosted on
-`alexandrainst/foqa` then simply press the `<> Code` button
-and add a code space to get started, which will open a VSCode window directly in your
-browser.
 
+## Docker
 
-## Project structure
-```
-.
-├── .devcontainer
-│   └── devcontainer.json
-├── .github
-│   └── workflows
-│       ├── ci.yaml
-│       └── docs.yaml
-├── .gitignore
-├── .pre-commit-config.yaml
-├── CODE_OF_CONDUCT.md
-├── CONTRIBUTING.md
-├── Dockerfile
-├── LICENSE
-├── README.md
-├── config
-│   ├── __init__.py
-│   ├── config.yaml
-│   └── hydra
-│       └── job_logging
-│           └── custom.yaml
-├── data
-│   ├── final
-│   │   └── .gitkeep
-│   ├── processed
-│   │   └── .gitkeep
-│   └── raw
-│       └── .gitkeep
-├── docs
-│   └── .gitkeep
-├── gfx
-│   ├── .gitkeep
-│   └── alexandra_logo.png
-├── makefile
-├── models
-│   └── .gitkeep
-├── notebooks
-│   └── .gitkeep
-├── poetry.toml
-├── pyproject.toml
-├── src
-│   ├── scripts
-│   │   ├── fix_dot_env_file.py
-│   │   └── your_script.py
-│   └── foqa
-│       ├── __init__.py
-│       └── your_module.py
-└── tests
-    ├── __init__.py
-    └── test_dummy.py
-```
+You can also run the `Dockerfile` directly, which builds the dataset without having to
+set up a Python environment.