applications/feedback_sentiment_analyzer/README.md
Feedback Sentiment Analyzer (FSA) is an example application that showcases AWS services and SDKs. Built with ❤️ for you to explore, download, and deploy.
Specifically, this application solves a fictitious use case of a hotel in New York City that receives guest feedback on comment cards in a variety of languages.
These comment cards are uploaded through a web client, transformed using a suite of machine learning services, and rendered through the same web client. The end result contains the original image, an English translation of the text, and an audio element.
This application has been implemented with the following AWS SDKs.
To deploy one of these implementations, follow the Deployment instructions.
This application uses a suite of AWS machine learning services to do the following:
Additionally, the application showcases the following AWS services:
This application is deployed using the AWS Cloud Development Kit (AWS CDK).
Get AWS credentials.
Set the following environment variables:
FSA_NAME - Any text less than 10 charactersFSA_EMAIL - A valid email address that you ownFSA_LANG - Any of the implemented languagesFor example:
Bash
export FSA_NAME=ana
export [email protected]
export FSA_LANG=ruby
Windows cmd
set FSA_NAME=ana
set [email protected]
set FSA_LANG=ruby
Windows Powershell
$Env:FSA_NAME = ana
$Env:FSA_EMAIL = [email protected]
$Env:FSA_LANG = ruby
Run the following commands:
cd cdk
npm install
cdk deploy
After deploying, observe the Output in your terminal session.
Copy the CloudFront distribution URL, which has websiteurl in the name.
Paste this URL into a browser to launch the application.
Sign in.FSA_EMAIL into the Username field.Password field.No data found.Upload.Select a file.Note: Feel free to choose a sample comment instead of writing your own. 4. Select a PNG or JPEG image that contains a positive comment about the hotel. Negative comments are saved, but not returned to the frontend.
Upload.Refresh button.