trellixvulnteam / snack-recommendation-system_xxwn

Snack-Recommendation-System

Team Information

Name	NEU ID
Shubham Mahajan	001314273
Gauri Verma	001306996
Anurag Rachcha	001375637

Getting Started

To setup on your local machine:

1. Install Anaconda with Python >= 3.6. Miniconda is a quick way to get started.

2. Clone the repository

git clone https://github.com/shubham414/Snack-Recommendation-System.git

3. Run the generate conda file script to create a conda environment: (This is for a basic python environment)

cd Snack-Recommendation-System
python tools/generate_conda_file.py
conda env create -f reco_base.yaml  

4. Activate the conda environment and register it with Jupyter:

conda activate reco_base
python -m ipykernel install --user --name reco_base --display-name "Python (reco)"

5. Start the Jupyter notebook server

jupyter notebook

6. Run the Fastai Snack Recommendation and xDeepFM Snack Recommendation notebook under the 00_quick_start folder. Make sure to change the kernel to "Python (reco)".

To run the Fast API :

1.Execute following command on terminal and run :

pip install fastapi

Go to path - 00_quick_start from git repository and run :

uvicorn FastAIfastapi:app --reload

Note - FastAIfastapi is the .py file for FastAI algorithm's FastAPI. To run FastAPI for xDeepFM put xdeepfmfastapi befor :app in above command and run

The API will be running on localhost port mentioned on the terminal.

To run the Streamlit app :

1.Execute following command on terminal and run :

pip install streamlit

Go to path - 00_quick_start from git repository and run :

streamlit run Streamlitapp.py

The app will be running on localhost port mentioned on the terminal.

Streamlit app

Jmeter integration in Streamlit