Build Your First LLM App with OpenAI SDK (No Framework No LangChain Needed!) | Chat API Explained

Welcome to Lab 1 of the Agentic AI Practical Series!
In this video, we’ll learn how to use the OpenAI SDK directly — no LangChain, no frameworks, just pure Python and the SDK itself.

You’ll discover how to build your first LLM-powered application using both:

🧩 Responses API (new and modern)

💬 Chat Completions API (classic and still supported)

Together, we’ll explore how parameters like temperature, max_tokens, top_p, and penalties affect model behavior — and how to structure your prompts effectively for agentic AI workflows.

🎯 What You’ll Learn:
Setting up your OpenAI SDK and API key securely
Calling GPT models with Python
Exploring creativity using temperature
Creating reusable LLM functions
Returning structured JSON outputs
Comparing Responses vs Chat Completions APIs

🧠 This is the foundation of building Agentic AI systems — the same approach used by modern frameworks, but here we do it from scratch to understand what’s happening under the hood.

📚 Resources & Code:
🔗 GitHub Repository - https://github.com/TEJAPS/agentic-dpoint


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