Flask cf deployed

This is a basic sentiment analysis project built for predicting the sentiment of restaurant reviews. It uses an SVM model that is built using Python's scikit-learn and nltk libraries. The model has been saved and stored in the Models folder inroot directory. A CI/CD pipeline has been built to integrate multiple DevOps project to create an end-to-end flow of the working, deployed application.

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The following are the tools and technologies that have been used to complete this project -

• Slack Workstreams
• GitHub
• Python
• Flask
• Cloud Foundry
• BTP
• Jenkins
• PyTest
• SonarQube
• GitHub Actions
• NgRok
• GitHub WebHooks

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To run this project, make sure the public IP provided by ngrok is active. If so, trigger the Jenkins build by making a change in the repo. Once the build has completed and the app has been deployed, use this link to navigate to the application.

Initially, a Jenkins pipeline is trigerred on changes being pushed to the repo. After the successful completion of the pipeline, new changes are pushed to the repo and GitHub actions triggers the deployment. A ‘main.yml’ file is defined, where scripts have been written to perform different jobs (Check, Deploy and Notify) for deployment.

If you have a suggestion that would make this better, please fork the repo and create a pull request.

• Anagha D Ananth
• Archana
• Natasha Sheelvant
• Neha Thipse

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