This simple streamlit app is used to deplonstrate the Azure restaurant recommender webservice.

• aimple_app.py contains the streamlit app
• create_recommender_tables1.ipynb is used to generate the artificial training data
• Procfile and setup.sh are used for launching streamlit on Heroku
• requirements.txt is used to create the conda environment used by this project.

git clone https://github.com/professorkazarinoff/simple-streamlit-app.git
cd simple-streamlit-app
conda create --name simple-streamlit-app python=3.9.7​
pip install -r requirements.txt ​
conda activate simple-streamlit-app​
streamlit run simple_app.py

Create a Heroku account and install the Heroku CLI.

You may need to save all the code in this repo to your own repo. Make sure to git add . , git commit -m "commit message", git push origin master up to GitHub.com

cd simple-streamlit-app
git init​
git add .​
git commit -m "Initial commit" ​
git remote add origin https://github.com/<your-account>/simple-streamlit-app.git​
git push origin main​```