urfuMagDS2022SFgroup/urfu_ml_backend

sf_data_science_python

Welcome to our small repository(20 group)

Setup

Prerequisites

• We use python 3.10 please install it

Using poetry and Linux and Windows 10+:

1. pip install poetry (1.2+)

Install dependencies

1. poetry install --with backend,torch

Using pip and Windows or Mac:

• for Mac, Linux and CPU
  • use env_setup.sh
• for Windows and CPU
  • read this first
  • use evn_setup.ps1

Manually all OS

1. Install virtualenv
   • python3 -m pip install --user virtualenv
2. Create venv
   • python3 -m venv ./venv
3. Activate venv
   • On Linux and Mac
     • source ./venv/bin/activate
   • On Windows 7+
     • venv/bin/Activate.ps1
4. Install requirements
   • pip3 install -r requirments.txt

Run the demo app

Demo application try to understand entered sentence sentiment

Practice 2: Web app text sentiment recognition using Streamlit

• Streamlit lives here and should be run with this backend

Practice 3

1. Run uvicorn backend:app to use web API
2. Use HTTP request to know sentence sentiment as result of your sentence processing

Using Docker

1. Install docker on your system
2. From the project dir run docker build -t api . where api - tag for image and . is where project Dockerfile is
3. After build the project run docker run -d --name ml_urfu -p 80:80 api where -d detached launch --name name for the app -p 80:80 mapping outside:inside ports api built image

Server will be available on your_ip_address:80 e.g. 192.168.1.1:80 or 127.0.0.1:80

You can check the server availability using http://your_ip_here:80/info Answer should be like:

{
  "root": "/",
  "get_info": "/info",
  "create_prediction": "/predict",
  "docs": "/docs"
}

Practice 4

1. Install project using Poetry poetry install --with backend,torch,tests
2. Run tests poetry run pytest (you must be in the project folder)