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RSK World
nlp-text-analysis-bot
RSK World
nlp-text-analysis-bot
NLP Text Analysis Bot - Python + NLP + Flask + Machine Learning + Text Analysis + AI
nlp-text-analysis-bot
  • static
  • templates
  • .gitignore393 B
  • ADVANCED_FEATURES.md5.4 KB
  • CHANGELOG.md1.3 KB
  • FINAL_CHECK.md4.6 KB
  • GITHUB_RELEASE_INSTRUCTIONS.md4.1 KB
  • LICENSE1.2 KB
  • PROJECT_INFO.md2.7 KB
  • PROJECT_STATUS.md4 KB
  • QUICKSTART.md3.1 KB
  • README.md5.8 KB
  • RELEASE_NOTES.md3.8 KB
  • advanced_keywords.py3.9 KB
  • app.py3 KB
  • config.py668 B
  • emotion_detection.py4.3 KB
  • entity_recognition.py3 KB
  • example_usage.py2.7 KB
  • install.bat853 B
  • install.sh808 B
  • language_detection.py2.7 KB
  • nlp_pipeline.py7.1 KB
  • pos_tagging.py2.9 KB
  • readability_analysis.py3.5 KB
  • requirements.txt334 B
  • semantic_understanding.py4 KB
  • sentiment_analysis.py3.9 KB
  • setup.py1.4 KB
  • test_analysis.py2.5 KB
  • text_classification.py5 KB
  • text_preprocessing.py4.2 KB
  • text_similarity.py4.1 KB
  • text_summarization.py5 KB
  • validate_project.py4.2 KB
PROJECT_INFO.mdrequirements.txtQUICKSTART.md
PROJECT_INFO.md
Raw Download

PROJECT_INFO.md

# NLP Text Analysis Bot - Project Information

**Developer: RSK World**
**Website: https://rskworld.in**
**Email: help@rskworld.in**
**Phone: +91 93305 39277**
**Year: 2026**

## Project Details

- **ID**: 4
- **Title**: NLP Text Analysis Bot
- **Category**: NLP Chatbots
- **Difficulty**: Intermediate
- **Description**: Chatbot with natural language processing capabilities for text understanding and analysis.
- **Full Description**: This chatbot project uses advanced NLP techniques for text analysis, sentiment detection, and language understanding. Features include text preprocessing, entity recognition, and semantic analysis.

## Technologies Used

- NLTK
- spaCy
- Python
- NLP
- Transformers

## Features

1. Text preprocessing
2. Sentiment analysis
3. Entity recognition
4. Semantic understanding
5. NLP pipeline

## Project Structure

```
nlp-text-analysis-bot/
├── app.py # Flask web application
├── nlp_pipeline.py # Main NLP pipeline orchestrator
├── text_preprocessing.py # Text cleaning and preprocessing
├── sentiment_analysis.py # Sentiment analysis module
├── entity_recognition.py # Named entity recognition
├── semantic_understanding.py # Semantic analysis module
├── config.py # Configuration settings
├── test_analysis.py # Test script
├── example_usage.py # Usage examples
├── templates/
│ └── index.html # Web interface
├── static/
│ ├── css/
│ │ └── style.css # Custom styles
│ └── js/
│ └── main.js # JavaScript functions
├── requirements.txt # Python dependencies
├── setup.py # Package setup
├── install.sh # Installation script (Linux/Mac)
├── install.bat # Installation script (Windows)
├── README.md # Project documentation
├── LICENSE # License file
└── .gitignore # Git ignore rules
```

## Quick Start

1. Install dependencies: `pip install -r requirements.txt`
2. Download spaCy model: `python -m spacy download en_core_web_sm`
3. Run application: `python app.py`
4. Open browser: `http://localhost:5000`

## API Endpoints

- `GET /` - Web interface
- `POST /api/analyze` - Text analysis endpoint
- `GET /api/health` - Health check

## Contact

For support and inquiries:
- **Website**: https://rskworld.in
- **Email**: help@rskworld.in
- **Phone**: +91 93305 39277

---

**Developed by RSK World - 2026**

requirements.txt
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# NLP Text Analysis Bot - Requirements
# Developer: RSK World
# Website: https://rskworld.in
# Email: help@rskworld.in
# Phone: +91 93305 39277
# Year: 2026

Flask==3.0.0
nltk==3.8.1
spacy==3.7.2
transformers==4.35.2
torch==2.1.0
numpy==1.24.3
requests==2.31.0
langdetect==1.0.9
textstat==0.7.3
scikit-learn==1.3.2

19 lines•334 B
text
QUICKSTART.md
Raw Download

QUICKSTART.md

# Quick Start Guide - NLP Text Analysis Bot

**Developer: RSK World**
**Website: https://rskworld.in**
**Email: help@rskworld.in**
**Phone: +91 93305 39277**
**Year: 2026**

## Installation Steps

### 1. Install Python Dependencies
```bash
pip install -r requirements.txt
```

### 2. Download spaCy English Model
```bash
python -m spacy download en_core_web_sm
```

### 3. Download NLTK Data (Automatic)
The project will automatically download required NLTK data on first run, or you can download manually:
```python
import nltk
nltk.download('punkt')
nltk.download('stopwords')
nltk.download('wordnet')
nltk.download('vader_lexicon')
nltk.download('averaged_perceptron_tagger')
```

### 4. Validate Installation
```bash
python validate_project.py
```

### 5. Run the Application
```bash
python app.py
```

### 6. Access the Web Interface
Open your browser and navigate to:
```
http://localhost:5000
```

## Using the API

### Analyze Text
```bash
curl -X POST http://localhost:5000/api/analyze \
-H "Content-Type: application/json" \
-d '{"text": "Your text to analyze here"}'
```

### Calculate Text Similarity
```bash
curl -X POST http://localhost:5000/api/similarity \
-H "Content-Type: application/json" \
-d '{"text1": "First text", "text2": "Second text"}'
```

### Health Check
```bash
curl http://localhost:5000/api/health
```

## Troubleshooting

### Issue: Module not found
**Solution**: Run `pip install -r requirements.txt`

### Issue: spaCy model not found
**Solution**: Run `python -m spacy download en_core_web_sm`

### Issue: NLTK data missing
**Solution**: The project will download automatically, or run the NLTK download commands above

### Issue: Port already in use
**Solution**: Change the port in `app.py` (line 79) from `5000` to another port

## Testing

### Run Test Script
```bash
python test_analysis.py
```

### Run Example Usage
```bash
python example_usage.py
```

## Project Structure

```
nlp-text-analysis-bot/
├── app.py # Flask application
├── nlp_pipeline.py # Main pipeline
├── text_preprocessing.py # Text cleaning
├── sentiment_analysis.py # Sentiment analysis
├── entity_recognition.py # NER
├── semantic_understanding.py # Semantic analysis
├── text_summarization.py # Summarization
├── language_detection.py # Language detection
├── text_classification.py # Classification
├── readability_analysis.py # Readability
├── emotion_detection.py # Emotion detection
├── advanced_keywords.py # TF-IDF keywords
├── pos_tagging.py # POS tagging
├── text_similarity.py # Similarity calculation
├── templates/
│ └── index.html # Web interface
├── static/
│ ├── css/
│ └── js/
└── requirements.txt # Dependencies
```

## Support

For issues or questions:
- **Website**: https://rskworld.in
- **Email**: help@rskworld.in
- **Phone**: +91 93305 39277

---

**Developed by RSK World - 2026**

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Founded by Molla Samser, with Designer & Tester Rima Khatun, RSK World is your one-stop destination for free programming resources, source code, and development tools.

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