Implement Dobby - Personal AI Assistant with OpenAI Integration

[Copilot]

Overview

This PR implements Dobby, a friendly and helpful personal AI assistant powered by OpenAI's GPT models. Named after the loyal house-elf from Harry Potter, Dobby is always eager to help users with questions, tasks, and conversations.

What's Implemented

Core Functionality (dobby.py)

• Dobby AI Assistant Class: Full-featured implementation with:
  • Chat interface using OpenAI's GPT-3.5-turbo
  • Conversation history management
  • Easy conversation reset
  • Comprehensive error handling
• Interactive CLI Mode: User-friendly command-line interface with welcome message, commands (quit, exit, reset), and clear instructions
• Dual Usage: Works both as a standalone CLI tool and as an importable Python module

Testing (test_dobby.py)

• 7 comprehensive unit tests covering all major functionality
• Tests for initialization (with/without API key), chat operations, conversation history, and error handling
• All tests passing ✅

Documentation & Examples

• README.md: Complete documentation with:
  • Installation instructions
  • Usage examples (both interactive and programmatic)
  • Feature list and configuration guide
  • Project structure overview
• example_usage.py: Three detailed examples demonstrating programmatic usage
• .env.example: Template for secure API key configuration

Project Setup

• requirements.txt: Minimal dependencies (openai, python-dotenv)
• .gitignore: Proper exclusions for Python projects (cache, virtual environments, IDE files)

Usage

Interactive Mode

python dobby.py

As a Python Module

from dobby import Dobby

dobby = Dobby()
response = dobby.chat("Hello! Can you help me with Python?")
print(response)

Setup Required

Users need to:

1. Install dependencies: pip install -r requirements.txt
2. Get an OpenAI API key from https://platform.openai.com/api-keys
3. Create a .env file with their API key (template provided in .env.example)

Key Features

• 💬 Interactive chat interface with GPT-3.5-turbo
• 🧠 Maintains conversation context within sessions
• 🔄 Easy conversation reset functionality
• 🎯 Simple and intuitive command-line interface
• 📦 Can be used as both CLI tool and Python library
• ✅ Full test coverage with unit tests
• 📖 Comprehensive documentation and examples

The implementation is minimal, focused, and production-ready!

Original prompt

AI for me - Dobby

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