This is a simple type of chatbot that relies on predefined rules.

A simple rule-based chatbot built using Python. It responds to user inputs like greetings, identity questions, jokes, and more — all based on keyword matching. A beginner-friendly project to explore how basic chatbots work!

Swasthya Mitra is a health-tech web application designed to assist users with disease prediction, precautionary measures, and medical guidance based on symptoms.

Simple rule-based chatbot built with Python functions, loops, and conditionals.

A rule-based chatbot built with Python that simulates natural conversations using predefined responses, demonstrating functions, conditional logic, loops, and user interaction through a clean command-line interface.

A full-stack Rule-Based AI Chatbot Workspace built for DecodeLabs AI Engineering Internship 2026. Features an interactive chatbot, Python terminal simulator, code explanations, automated verification, and beginner-friendly AI learning modules.

ROSE 🤖 – A simple rule-based personal chatbot that greets users, opens websites, performs Google searches, checks the time, and provides weather/news updates. Built with Python. 🐍🌐

A lightweight NLP-based Python chatbot built with intents and pattern matching — capable of responding to user queries using JSON-defined intents.

🚀 Just built a Local NLP Chatbot using Python and NLTK!Unlike modern LLM wrappers, this project focuses on foundational core NLP principles. It processes text completely offline with zero API costs, cloud latency, or data privacy risks.Key implementations:✅ Text Tokenization & Punctuation Filtering✅ Stop Word Removal for optimized keyword weight

🤖 5 Internship AI Projects: Multi-Personality Chatbot, Unbeatable Minimax Tic-Tac-Toe, Transformers.js Image Captioner, content/collaborative Movie & Book Recommender, and live Webcam FaceID scanner.

RuleBot is a deterministic, rule-based AI chatbot built on the IPO (Input → Process → Output) model. No ML. No LLM. Just clean control flow and O(1) dictionary logic. Built for DecodeLabs Batch 2026 to demonstrate the foundation of AI guardrail systems before moving to probabilistic models.

A simple rule-based chatbot built using Python.

A simple rule-based chatbot built using Python that responds to user commands through conditional statements and loops.

A modern Flask-based customer service chatbot with FAQ matching, chat history, voice input, text-to-speech, and dark/light mode.

Rule-based AI Chatbot built using Python, Regex, and OOP concepts as part of the DecodeLabs AI Internship.

Description A simple Python chatbot that responds to basic user inputs such as greetings, jokes, and farewells. It remembers the user’s name, provides personalized replies, and demonstrates fundamental concepts of conditional logic and state management in Python.

Rule-Based NLP Chatbot in Python — intent matching using JSON

A simple rule-based chatbot built using Python and NLTK that demonstrates fundamental NLP techniques such as tokenization, lemmatization, cosine similarity, and response generation.

A rule-based chatbot that helps students instantly check teacher availability, messages, and room locations — built with Flask & SQLite

This project is a rule-based chatbot that responds to user inputs based on predefined patterns and responses. It follows a structured approach using pattern matching, if-else conditions, and NLP techniques to provide relevant answers.