About Django:
Django is an open-source web framework written in Python that follows the Model-View-Controller (MVC) architectural pattern. It is designed to simplify and expedite the process of building web applications by providing a high-level and organized structure. Django includes many built-in features and utilities that handle common web development tasks, allowing developers to focus more on the application's logic rather than boilerplate code.When it comes to creating a chatbot, Django can be used as the backend framework to handle user interactions, process input, and generate responses. The frontend of the chatbot can be implemented using HTML, CSS, and JavaScript.
Introduction
This repository contains the source code and instructions for creating a chatbot using Django, a Python-based web framework. The chatbot will be a simple text-based system that responds to user inputs with predefined messages.
Prerequisites
Before getting started, make sure you have the following installed on your machine: Python (version 3.x recommended) Django (version 3.x recommended)
Setup
Clone the repository to your local machine:
git clone https://github.com/VineelaYedlapalli/django_chatbot.git cd django-chatbot
Create a virtual environment (optional but recommended):
python -m venv venv source venv/bin/activate # On Windows, use: venv\Scripts\activate
Install the required dependencies:
pip install -r requirements.txt
Usage
Run the Django development server:
python manage.py runserver Open your web browser and go to http://localhost:8000/chatbot/ to access the chatbot interface.
Start interacting with the chatbot. Type your messages in the text input, and the chatbot will respond with predefined messages.
Customizing the Chatbot
1.The current implementation of the chatbot responds with predefined messages. To customize the chatbot's behavior or add AI capabilities, follow these steps:
2.Modify the chatbot logic in the views.py file: Open chatbot/views.py and update the get_response() function to handle user inputs and generate responses based on your desired logic. You can implement rule-based systems, retrieval-based models, or integrate machine learning models.
3.Incorporate AI capabilities: To add AI capabilities, you can use popular Natural Language Processing (NLP) libraries like NLTK, SpaCy, or integrate pre-trained machine learning models using frameworks like TensorFlow or PyTorch.
4.Improve user experience: Enhance the chatbot's frontend in chatbot/templates/chatbot/index.html. You can use HTML, CSS, and JavaScript to create a more interactive and visually appealing interface.
Deployment
To deploy the chatbot to a production server, follow the standard Django deployment procedures. Ensure to configure your database settings, static files, and set the DEBUG setting to False for security reasons.
Results
In the results page we can find out the results of this projects. When we start the server you'll get an Home page where you have 2 options to get registered and to login. Once you are registered you can chat with the AI. Later we can log =out which will redirected to the login Page. In the admin page we'll have the our past chat data history. In that page admin can perform many operations such as editing the history or user data etc. These data will be saved in SQL Database in the form of Tables.
Contributing
If you'd like to contribute to this project, feel free to submit pull requests or open issues for any improvements or bug fixes.