Python

AI Chat Assistant

Build a conversational AI assistant using OpenAI API. Learn prompt engineering, streaming responses, and context management.

⏱️ 30min

📦 5 modules

🎯 Beginner

What You'll Build

In this lab, you'll build a fully functional conversational AI assistant that can maintain context across multiple messages, stream responses in real-time, and handle various conversation scenarios. You'll learn how to work with OpenAI's API, manage conversation history, implement robust error handling, and create a clean command-line interface for your assistant.

The final product will be a production-ready CLI tool that delivers a ChatGPT-like experience right in your terminal, complete with streaming responses and intelligent context management.

Learning Objectives

Understand the fundamentals of OpenAI API and GPT models
Implement streaming responses for better user experience
Manage conversation context and message history
Apply prompt engineering techniques for better responses
Handle API errors and rate limits gracefully
Build a production-ready CLI interface

Prerequisites

Basic Python programming knowledge
Understanding of REST APIs
Familiarity with async/await concepts
OpenAI API key (free tier available)

Course Modules

Setup & OpenAI API Basics

Set up your development environment, obtain API credentials, and make your first API call to OpenAI. Understand the request/response structure.

Building the Chat Loop

Create the main conversation loop, handle user input, and display AI responses. Implement basic error handling and graceful exit.

Context Management

Learn to maintain conversation history and manage token limits.

Topics covered:

Build a ConversationHistory class
Implement add_message() and get_messages() methods
Handle token counting with tiktoken
Create trim_history() for long conversations

Streaming Responses

Implement streaming to show responses as they're generated, creating a more responsive user experience similar to ChatGPT. You'll learn how to handle token-by-token delivery, update the display in real-time, and provide immediate feedback to users. This creates a much more engaging and professional feel compared to waiting for complete responses.

Advanced Features & Polish

Add system prompts, conversation saving/loading, custom commands, and create a polished CLI interface with Rich library.

Technologies

Python OpenAI asyncio Rich python-dotenv