About Project
This AI-powered chatbot leverages natural language processing techniques to understand user queries and deliver contextual, meaningful responses. Built entirely in Python, it uses NLTK for tokenization, stemming, and pattern matching against a rich knowledge base stored in JSON format. The chatbot maintains conversation history to provide contextually aware replies and continuously improves its response accuracy through interaction patterns.
Key Features
Contextual Understanding
NLP-powered intent recognition with pattern matching and keyword extraction for accurate response selection.
Conversation Memory
Maintains session history to reference previous messages and deliver contextually relevant follow-up responses.
Knowledge Base
JSON-structured FAQ database with categorized topics, enabling rapid lookup and extensible content management.
Learning Mode
Adaptive response ranking based on user feedback, improving answer quality over time without manual tuning.
Multi-Topic Support
Handles queries across technology, general knowledge, weather, math, and custom configurable domains.
CLI & Web Interface
Dual interface supporting terminal-based interaction and a browser-accessible web frontend via Flask.
Tech Stack
Project Preview
The chatbot interface features a clean terminal-style design with real-time message streaming, typing indicators, and syntax-highlighted code responses. The web version includes a modern chat UI with message bubbles, timestamps, and quick-action buttons.