Flask Chatbot using NLP Libraries

This project is a simple chatbot web app built using Python, Flask, and various NLP libraries such as NLTK, SpaCy, and transformers. The chatbot uses the Huggingface transformers library with the microsoft/DialoGPT-medium model to generate responses to user inputs. It also uses NLTK and SpaCy for additional text processing.

Table of Contents

• Installation
• Usage
• How It Works
• Examples
• License

Installation

1. Install the required dependencies:

   pip install flask nltk spacy transformers
   python -m spacy download en_core_web_sm
   

2. Download NLTK data:

   python -c "import nltk; nltk.download('punkt')"
   

Usage

1. Run the Flask application:

   py app.py
   

2. Open your web browser and navigate to:

   http://127.0.0.1:5000/
   

3. Interact with the chatbot by typing messages and clicking 'Send'.

How It Works

1. Flask Server: The Flask web server renders the HTML template and handles incoming POST requests to generate chatbot responses.

2. NLP Processing:

   • NLTK: Used for tokenizing the input message.
   • SpaCy: Used for named entity recognition (NER) and part-of-speech (POS) tagging.
   • Transformers: The chatbot uses the Huggingface transformers library with the microsoft/DialoGPT-medium model to generate responses to user inputs.

3. Frontend: The web interface uses HTML and jQuery to handle user interactions and display the conversation.

Examples

Here are some example messages you can try with the chatbot:

• "Hello!"
• "What is your name?"
• "Can you tell me a joke?"
• "I like cats."
• "What's the meaning of life?"

License

This project is licensed under the MIT License.