github-issue-similarity

Overview

This is a Kedro project, which was generated using kedro 0.19.2.

Take a look at the Kedro documentation to get started.

The file in conf/base/catalog.yml contains configuration that can be adjusted. One can change the github owner/repo to scrap a data from different repos. Relevant data folders will be populated.

After gathering the data, model embeddings will be computed using a pretrained model. After that, FAISS( Facebook AI Similarity Search ) index created to find the similar issues given a query.

Embeddings computation takes some time so feel free to execute this in Colab with GPU environment. Notebook for this and how to execute it is shown in notebooks/Compute Embeddings.ipynb.

One can execute kedro run to run everything end to end, or via kedro run --from-nodes=... to run certain functions. The workflow itself is defined in the src/github_issue_similarity/pipelines/pipeline.py

Rules and guidelines

In order to get the best out of the template:

• Don't remove any lines from the .gitignore file we provide
• Make sure your results can be reproduced by following a data engineering convention
• Don't commit data to your repository
• Don't commit any credentials or your local configuration to your repository. Keep all your credentials and local configuration in conf/local/

How to install dependencies

Conda

You can install environment.yml file to replicate the same environment. Additionally, an environment_full.yml is also provided which pins all the versions in the environment

Pip

You can install dependencies in the environment.yml file by passing them into pip.

How to run a Kedro pipeline

You can run the project with:

kedro run

How to test your Kedro project

Have a look at the file src/tests/test_run.py for instructions on how to write your tests. You can run your tests as follows:

pytest

You can configure the coverage threshold in your project's pyproject.toml file under the [tool.coverage.report] section.

How to work with Kedro and notebooks

Note: Using kedro jupyter or kedro ipython to run your notebook provides these variables in scope: context, 'session', catalog, and pipelines.

Jupyter, JupyterLab, and IPython are already included in the project requirements by default, so once you have run pip install -r requirements.txt you will not need to take any extra steps before you use them.

Jupyter

To use Jupyter notebooks in your Kedro project, you need to install Jupyter:

pip install jupyter

After installing Jupyter, you can start a local notebook server:

kedro jupyter notebook

JupyterLab

To use JupyterLab, you need to install it:

pip install jupyterlab

You can also start JupyterLab:

kedro jupyter lab

IPython

And if you want to run an IPython session:

kedro ipython

How to ignore notebook output cells in git

To automatically strip out all output cell contents before committing to git, you can use tools like nbstripout. For example, you can add a hook in .git/config with nbstripout --install. This will run nbstripout before anything is committed to git.

Note: Your output cells will be retained locally.

Package your Kedro project

Further information about building project documentation and packaging your project