https://github.com/sam99dave/ml-orchestration
Simple ML pipeline orchestration.
https://github.com/sam99dave/ml-orchestration
audio-classification machine-learning orchestration prefect python ruff
Last synced: 2 months ago
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Simple ML pipeline orchestration.
- Host: GitHub
- URL: https://github.com/sam99dave/ml-orchestration
- Owner: sam99dave
- License: mit
- Created: 2023-12-31T06:26:00.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2024-01-01T07:06:57.000Z (over 2 years ago)
- Last Synced: 2025-03-14T02:46:45.379Z (over 1 year ago)
- Topics: audio-classification, machine-learning, orchestration, prefect, python, ruff
- Language: Python
- Homepage:
- Size: 3.11 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# ml-orchestration
**Simple ML pipeline orchestration**
> Repo is focused primarily on orchestration rather than the ML part
Machine Learning Usecase - [Speech Emotion Recognition](https://data-flair.training/blogs/python-mini-project-speech-emotion-recognition/)
Orchestration - Prefect
## Usage
Clone the repo
`git clone https://github.com/sam99dave/ml-orchestration.git`
Install requirements ( *same directory as pyproject.toml* )
`poetry install`
Login to prefect cloud
`prefect cloud login -k `
Want to create separate env? Run `poetry shell` before installing
`poetry run python ./ml_orchestration/start_flow.py`
## Deployment
Serve is recommended for most of the deployments
> Add `pipeline.serve(name="local-serve-deployment")` to the script
>
> Normal run `poetry run python ./ml_orchestration/start_flow.py`
>
> This will create a deployment locally. To run this, either use UI or the command displayed once the deployment is created on the console
*ruff usage*
> ruff check .
>
> ruff check --fix .
>
> ruff format .