Introduction

In real-world AI systems, models alone are not enough. They need memory, structured outputs, and backend logic to work effectively.

To understand this, I built a simple end-to-end AI pipeline using a local model (llama.cpp) and MongoDB.

In this session, I focused on:

• Running a local AI model …

Introduction

In Generative AI systems, models do not work in isolation. They rely on APIs to receive input, process data, and return responses.

To understand how backend systems work in AI applications, I built my first API using FastAPI.

In this session, I focused on:

• Creating API endpoints
• Handling data …

Introduction

In Generative AI (GenAI), building models is only one part of the process. The real foundation lies in how we handle and structure data before it reaches the model.

To get started, I focused on three essential Python concepts:

• Variables
• Lists
• Dictionaries

These form the backbone of how data …