Intents-Based Chatbot with Streamlit and NLP

The goal of this project is to create a chatbot that can understand and respond to user input based on intents. Built using Natural Language Processing (NLP) and Logistic Regression, the chatbot extracts intents and entities from user input to provide meaningful responses. The chatbot is deployed via Streamlit, a Python library for building interactive web applications.

Project Overview

This project is divided into two main parts:

1. NLP Techniques and Logistic Regression: The chatbot is trained on a dataset containing labeled intents and entities. NLP techniques such as TF-IDF Vectorization are used to process user input, and Logistic Regression is employed for intent classification.
2. Chatbot Interface with Streamlit: The interface is built using Streamlit, which provides a simple web framework for creating the chatbot interface. Users can input text and receive responses from the chatbot in an interactive manner.

Getting Started

To get started with this project, follow these simple steps:

1. Clone the Repository

Clone the repository to your local machine:

git clone https://github.com/salmasyed19/chatbot-project.git