Overview: This project features an intelligent chatbot that uses Natural Language Processing (NLP) to understand user inputs and respond meaningfully. Designed with a simple and clean Streamlit interface, the chatbot delivers an engaging and interactive experience. It is highly customizable and ideal for applications like FAQs, customer support, and educational tools.

Features: Intent Recognition: Identifies the user’s intent using Logistic Regression trained on labeled patterns. Web-Based Interface: User-friendly chatbot interface built with Streamlit. Conversation Logs: Automatically saves all conversations, including timestamps, for tracking or analysis. Predefined Responses: Responds based on a structured intents.json file for accuracy and clarity. Easy Expansion: New intents and responses can be added effortlessly to enhance functionality.

Technologies Used:

NLP Tools: nltk for tokenization and preprocessing user inputs. TF-IDF Vectorizer for transforming text into numerical features. Machine Learning: Logistic Regression for intent classification. Frontend: Streamlit for creating a seamless and interactive web application. Data Format: JSON file for defining intents and response patterns.