SmartDocker NLP

A Docker-integrated Python toolkit for performing various NLP tasks.

Table of Contents

• Getting Started
  • Prerequisites
  • Installation

Getting Started

These instructions will help you set up the project on your local machine for development and testing.

Prerequisites

Make sure the following are installed:

• Docker Desktop
• Python

Task Examples

Sentiment Analysis

Analyze the emotional tone of text: positive, negative, or neutral.

Named Entity Recognition

Identify entities like persons, organizations, or locations in a sentence.

Text Classification

Predict the category or class of a given text.

Text Summarization

Summarize lengthy text into concise information.

Text Translation

Translate text from one language to another.

Usage with Docker

1. Pull Docker image:

   docker pull humanxtech/basic-nlp:v1

2. Run Docker image:

   docker run -it humanxtech/basic-nlp:v1 <file-name.py>

   • Sentiment Analysis Example:

   docker run -it humanxtech/basic-nlp:v1 01_sentiment_analysis.py

   Enter your text:

   Enter the text for semantic analysis (type 'exit' to end): Docker is an amazing tool!
   Sentiment: Positive
   

Installation

1. Clone the repository:

   git clone https://github.com/humanxtech/SmartDocker-NLP.git

2. Install dependencies and create a virtual environment:

   python3 -m venv venv && pip install -r requirements.txt && source venv/bin/activate

3. Run examples:

   python 01_sentiment_analysis.py
   python 02_name_entity_recognition.py
   python 03_text_classification.py
   python 04_text_summarization.py
   python 05_language_translation.py