"Python Chatbot Tutorial 2026: Build AI from Scratch"

In this masterclass, we solve the biggest problem beginner developers face: "How do I make the AI remember the conversation?" By default, Large Language Models (LLMs) are stateless. In this video, we build a professional "State Management System" from scratch using Python and the OpenAI API.

We move beyond basic scripts to build a robust, secure, and intelligent chatbot that runs locally on your machine. We also cover essential security practices, including how to hide your API keys using Environment Variables (.env) to prevent hacking.

🚀 What You Will Learn in This Tutorial:

Architecture: Understanding Stateless vs. Stateful LLM architecture.

Security: How to use python-dotenv to secure your API Keys.

Logic: Implementing a dynamic List structure for conversation history.

Error Handling: Using try/except blocks to prevent crashes.

API Mastery: Optimizing temperature and model parameters (GPT-4o / GPT-3.5).

📂 Project Resources:

Library Installation: pip install openai python-dotenv


Get API Key: https://platform.openai.com

Timestamps:
0:00 | Introduction: Stateless vs. Stateful Architecture
0:58 | Getting OpenAI API Keys & Billing Setup
2:07 | Project Setup: Securing Keys with Python-Dotenv
3:32 | The Common Mistake: Why Chatbots "Forget"
5:23 | Implementing Conversation History (List Logic)
6:47 | API Parameters: Model & Temperature Explained
8:19 | Completing the Loop & Error Handling (Try/Except)
9:30 | Final Test: Multi-Turn Conversation Demo

Next Episode Teaser: In the next video, we will upgrade this bot to save conversations to a JSON file (Long-term Memory). Make sure to Subscribe so you don't miss it.

#Python #OpenAI #Chatbot #Coding #ArtificialIntelligence #PythonTutorial #ITSolutionsPro #Automation #LLM

Hey everyone! In this new IT Solutions Pro tutorial, we're going step-by-step on understanding the core of large language models (llm). This guide explains the stateless architecture of the OpenAI API, where each interaction is treated independently, lacking api context.

We then dive into how to build a chatbot that remembers user interactions by implementing proper session management, addressing how to overcome this default stateless behavior and improving overall system architecture.