https://github.com/gaborvecsei/machine-learning-inference-with-github-actions
This repository demonstrated how you can use Github Actions to perform inference with your ML model
https://github.com/gaborvecsei/machine-learning-inference-with-github-actions
github-actions github-actions-docker inference iris-dataset machine-learning machine-learning-workflow sklearn
Last synced: about 2 months ago
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This repository demonstrated how you can use Github Actions to perform inference with your ML model
- Host: GitHub
- URL: https://github.com/gaborvecsei/machine-learning-inference-with-github-actions
- Owner: gaborvecsei
- Created: 2020-03-07T10:25:13.000Z (almost 6 years ago)
- Default Branch: master
- Last Pushed: 2023-07-06T21:20:43.000Z (over 2 years ago)
- Last Synced: 2025-04-07T14:51:19.370Z (8 months ago)
- Topics: github-actions, github-actions-docker, inference, iris-dataset, machine-learning, machine-learning-workflow, sklearn
- Language: Jupyter Notebook
- Homepage: https://gaborvecsei.github.io
- Size: 78.1 KB
- Stars: 6
- Watchers: 2
- Forks: 3
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Machine Learning Inference with GitHub Actions
This repository demonstrated how you can use *Github Actions* to perform inference with your ML models. In this
example scenario a [Random Forest classifier](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestClassifier.html)
is used to make predictions trained on the [Iris dataset](https://en.wikipedia.org/wiki/Iris_flower_data_set).
The GitHub Actions workflow is triggered when an issue receives a comment. If the comment contains the `/predict`
prefix, then the `main.py` python file starts to parse the comment, make a prediction and construct the reply to the
original comment with the prediction.
Example (and also valid) comment: `/predict `
(e.g. `/predict 5.6 2.9 3.6 1.3`)
## Try it out :sunglasses:
Just go to an issue at this repository and then leave a comment with the `/predict` prefic and then 4 numbers separated
by spaces. Just like the example above.
> /predict 5.6 2.9 3.6 1.3
## Files
- `action.yml`: Describes the action which build a Docker image and performs the comment parsing and inference
- `.github/workflows/main.yaml`: contains the steps which are performed when a comment is received under an issue
- `Dockerfile`: This is the image which will be built and used for the main action
- `issue_comment.sh`: With this script you can send a comment with the GitHub Rest API
- `main.py`: parses the content of the comment, loads model, makes prediction and constructs the reply message
- `random_forest_model.pkl`: Serialized trained sklearn model which will be used for inference (btw. this file should
not be here, as model artifacts should be stored in a storage, but this is just a sample so... :smile:)
## About
Gábor Vecsei
- [Website & Blog](https://gaborvecsei.com)
- [LinkedIn](https://www.linkedin.com/in/gaborvecsei)
- [Twitter](https://twitter.com/GAwesomeBE)
- [Github](https://github.com/gaborvecsei)