Create Your Own AI Agents from Scratch: Step-by-Step Python Tutorial

🚀 Ready to build your own AI agents from scratch? In this hands-on Python tutorial, I show you how to: wire up OpenAI’s API, enforce JSON schemas with Pydantic, chain custom tools (weather lookups, DB queries, RAG retrievals), and create an LLM-powered assistant that thinks and acts like a pro. 📌 What You’ll Learn: ✔️ API Basics – Set up your OpenAI client, manage API keys, and send your first chat completion ✔️ Structured Output with Pydantic – Enforce JSON schemas for reliable machine-readable responses ✔️ Tool Integration – Register custom Python functions like weather lookups and database queries ✔️ Retrieval & Memory – Implement RAG-style retrieval from a knowledge base for real-world Q&A ✔️ Tool Chaining – Chain multiple tools and see your agent dynamically plan and execute steps ✔️ Debugging & Best Practices – Avoid common errors and deploy agents in real-world scenarios ⏱️ Time-stamped Chapters: 0:00 Intro & Why AI Agents Aren’t Magic 2:00 OpenAI API Setup & Basic Requests 4:06 Using Pydantic for Structured JSON Responses 6:34 Defining & Registering Your First Tool 14:00 Building a Retrieval Agent with a Knowledge Base 18:40 Advanced Tool Chaining Example 24:30 Debugging & Best Practices 27:00 Wrap-Up & Next Steps 💡 Whether you’re a Python developer, AI enthusiast, or data scientist, this tutorial will help you master AI agent creation from scratch and level up your AI skills. 👉 Like 👍, Comment 💬, and Subscribe 🔔 for weekly videos on: • AI & Machine Learning Tutorials 🤖 • Python Programming 🐍 • LLMs & OpenAI Projects 🚀 💻 Code & Resources Get the full code on GitHub → https://github.com/pythonlessons/ai-agents/tree/main/tutorials/bulding_blocks Read the recommended Entropic blog post on AI agents → https://www.anthropic.com/engineering/building-effective-agents #AIAgents #PythonTutorial #OpenAIAPI #LLMProjects #AIProgramming #MachineLearning #AIassistant #Pydantic #RAGretrieval #PythonCoding #AIdevelopment #AItools