Wagtail Vector Index provides a way to turn Django models, Wagtail pages, and anything else in to embeddings which are stored in a one of multiple vector database backends.
This provides the backbone for features including:
- Natural language search
- Similarity search
- Content recommendations
- Wagtail 5.2
- Django 4.2
- Python 3.11, 3.12
To make changes to this project, first clone this repository:
git clone https://github.com/wagtail/wagtail-vector-index.git
cd wagtail-vector-index
With your preferred virtualenv activated, install testing dependencies:
python -m pip install --upgrade pip>=21.3
python -m pip install -e .'[testing,llm,numpy,pgvector,qdrant,weaviate]' -U
python -m pip install flit
python -m flit install -s
Note that this project uses pre-commit. It is included in the project testing requirements. To set up locally:
# go to the project directory
$ cd wagtail-vector-index
# initialize pre-commit
$ pre-commit install
# Optional, run all checks once for this, then the checks will run only on the changed files
$ git ls-files --others --cached --exclude-standard | xargs pre-commit run --files
Now you can run tests as shown below:
tox
or, you can run them for a specific environment tox -e py3.11-django4.2-wagtail5.2
or specific test
tox -e py3.11-django4.2-wagtail5.2 -- tests.test_file.TestClass.test_method
Sometimes tox contains cached dependencies, so if you want to run tests with the latest dependencies, you can use tox -r
or run rm -rf .tox
to delete the whole tox environment.
To run the test app interactively, use tox -e interactive
, visit http://127.0.0.1:8020/admin/
and log in with admin
/changeme
.