🤖 Albus Bot

A simple AI Chatbot built with Python, powered by Neural Networks and Deep Learning using TensorFlow, TFLearn, and NLTK.

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🧠 Overview

Albus Bot is a conversational chatbot capable of understanding and responding to user input using natural language processing (NLP).
It was designed as a foundational project to explore how neural networks and intent classification can be applied to create human-like conversation systems.

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🚀 Features

• Built using TensorFlow and TFLearn for neural network training
• Utilizes NLTK for text preprocessing and tokenization
• Employs NumPy for numerical computations
• Trains on custom intents.json file for conversational context
• Capable of classifying user input into predefined intents
• Modular and easily extendable for adding new responses or intents

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🧩 Tech Stack

• Python 3.x
• TensorFlow
• TFLearn
• NLTK
• NumPy
• JSON

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⚙️ Setup & Installation

1. Clone the repository:

   git clone https://github.com/HirushaR/albus-bot.git
   cd albus-bot

2. Install dependencies:

   pip install tensorflow tflearn nltk numpy

3. Train the model:

   python train.py

4. Run the chatbot:

   python chat.py
   

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🗣️Usage

• Modify the intents.json file to define new patterns and responses.
• Run the chatbot and start chatting!
• The model will classify the user's intent and generate contextually relevant replies.

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📚 Example intents.json

{
"intents": [
  {
    "tag": "greeting",
    "patterns": ["Hi", "Hello", "Hey there"],
    "responses": ["Hello!", "Hi, how can I help you today?"]
  },
  {
    "tag": "goodbye",
    "patterns": ["Bye", "See you", "Goodnight"],
    "responses": ["Goodbye!", "Talk to you later!"]
  }
]
}