TSA in Flask

This is a web application that allows you to analyze the sentiment of a string or a corpus of tweets.

TSA in Flask is based on my Twitter Sentiment Analyzer, which uses Gensim's Word2Vec, NLTK, Keras and now Flask. And it now works in Docker. And in Vagrant too. 🐳

Table of Contents

• Recommendations
• Installation:
  • Docker
  • Vagrant
  • Pulling from Docker Hub
  • Without Docker or Vagrant
• Usage
• Troubleshooting

Recommendations

The recommended versions of Docker and Vagrant are:

• Docker version 20.10.22, build 3a2c30b
• Vagrant 2.2.6

The recommended version of VirtualBox used by Vagrant is:

• VirtualBox 6.1.38

This build has been tested on Windows 10 and Ubuntu 20.04 focal.

Installation

TSA in Flask can be installed in 4 different ways: with Docker (1), with Vagrant (2), by pulling from Docker Hub (3), or manually (3).

1) Docker

Use the following command in the project's root directory to build and run the app:

docker compose up

The app will be available at localhost:5001.

2) Vagrant

Use the following command in the project's root directory to build and run the app:

vagrant up

The app will be available at localhost:5001.

3) Pulling from Docker Hub

Use the following commands to pull the containers' images from Docker Hub and run them:

$ cd version-image
$ docker compose up

The app will be available at localhost:5001.

4) Without Docker or Vagrant

You will have to change one line (#9) in ui_container/app.py to be able to run the app manually.

Change url = 'http://algo_container:5000' to url = 'http://localhost:5000'.

Finally, use the following commands to run the app:

$ cd algo_container
$ pip3 install -r requirements.txt
$ python3 app.py
$ cd ..
$ pip3 install -r requirements.txt
$ cd ui_container 
$ python3 app.py 

The app will be available at localhost:5001.

Usage

The app has 2 main functionalities:

• Predict the sentiment of a string
• Predict the sentiment of a corpus of tweets

Predict the sentiment of a string

Predict the sentiment of a corpus of tweets

⚠️ Only .json files can be used with this function, please refer to the TSA repository for more information on how to get a valid .json file.

Only the following format is valid:

[
    {
        "text": "Finally got a #Cyberpunk2077 crash with @GoogleStadia . First after 35 hours. Still not good to see a game crash, b… https://t.co/dhf0ewKxVX"
    },
    {
        "text": "Has nobody seriously noticed the #DeadKennedys easter egg in #Cyberpunk2077 ? I cant find any mention of it anywher… https://t.co/r6fYhaj08h"
    }
]

Troubleshooting

You might encounter some issues with Vagrant, for example:

VT-x is disabled

There was an error while executing `VBoxManage`, a CLI used by Vagrant
for controlling VirtualBox. The command and stderr is shown below.

Command: ["startvm", "a5467e19-ec3d-4e50-96c3-65216be1a90a", "--type", "headless"]

Stderr: VBoxManage: error: VT-x is disabled in the BIOS for all CPU modes (VERR_VMX_MSR_ALL_VMX_DISABLED)
VBoxManage: error: Details: code NS_ERROR_FAILURE (0x80004005), component ConsoleWrap, interface IConsole

To fix this, you will have to enable virtualization (VT-x) in your BIOS. To do so, restart your computer and press the key to enter the BIOS. Then, go to the "Advanced" tab and enable virtualization (VT-x). Save and exit and you should be good to go.

Using WSL2

If you use WSL2 in Windows to run Vagrant and VirtualBox you might encounter issues. This can be due to Hyper-V on the host and tensorflow (1.14) requiring AVX and AVX2 instructions, it's therefore not recommended to use a virtual machine to run another virtual machine!