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๐Ÿง  Mini Chatbot Project

This repository contains a basic rule-based chatbot developed in Python. The aim of the project is to simulate a simple, conversational interaction with the user using keyword-based response logic. It serves as an educational foundation for those learning Python and interested in conversational AI systems.


๐Ÿ“Œ Project Overview

The chatbot interacts with users by identifying keywords in user input and returning predefined responses. Although it does not use machine learning or natural language processing, it demonstrates core principles such as:

  • Conditional logic in conversations
  • Input/output handling in terminal
  • Basic state management in a dialogue flow

This chatbot was developed entirely in Turkish, making it ideal for Turkish-speaking learners or local deployments.


๐Ÿ“‚ File Structure

mini_chatbot/
โ”œโ”€โ”€ FirstMiniChatBotProject.py  # Main chatbot logic

๐Ÿงฐ Requirements

  • Python 3.6+
  • No external dependencies โ€“ uses only Pythonโ€™s built-in libraries.

๐Ÿš€ Getting Started

Follow the steps below to run the chatbot locally on your machine:

  1. Clone the Repository

    git clone https://github.com/ZeynepKlc/mini_chatbot.git
    cd mini_chatbot
  2. Run the Chatbot

    python FirstMiniChatBotProject.py
  3. Start chatting! Type in a message and the chatbot will respond. To exit, use commands like รงฤฑkฤฑลŸ or gรถrรผลŸรผrรผz.


๐ŸŽฏ Use Case & Educational Value

This chatbot serves as a beginner-friendly project for:

  • Understanding basic I/O in Python
  • Practicing conditionals (if-elif-else)
  • Exploring interaction design
  • Preparing for more complex AI-driven chatbot systems

You can extend it by:

  • Adding more keyword-response pairs
  • Improving response diversity
  • Integrating it with a GUI or web app
  • Replacing rule-based logic with NLP models (e.g., spaCy or transformers)

๐Ÿ“Œ Limitations

  • It does not understand natural language or context.
  • Keyword detection is literal; no fuzzy matching or intent recognition.
  • It is not designed for production usage or concurrent conversations.

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