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We have researched and tested the studied solution. After testing, we built an api that quickly deploys the application on other environments.
We use anaconda to create python environment:
conda create --name ood_api python=3.8
Activate enviroment
conda activate ood_api
Install all required libraries:
pip install -r requirements.txt
python application.py
For open source projects, say how it is licensed.
FAQs
domain classification
We found that nlp-ood demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
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