LLM Basics (Python)

This repository provides a foundational, hands-on introduction to working with Large Language Models (LLMs) from Python.

The goal is to help users understand and practice the core technical building blocks required for any LLM-based application, including:

• setting up a local Python environment,
• connecting securely to an LLM via an API,
• sending prompts and receiving responses,
• structuring code and repositories for reproducibility.

This repository focuses on infrastructure and fundamentals, not on a specific application or domain. Concrete use cases (e.g. translation, classification, embeddings, search, qualitative analysis) are introduced later as examples built on top of the same foundation.

👉 Start here: docs/session_01_setup.md

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Repository structure

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├── docs/            # Conceptual notes and session guides
├── src/             # Reusable Python code (LLM client, helpers)
├── examples/        # Minimal, runnable examples
├── data/            # Small, non-sensitive sample inputs
├── Justfile         # Common commands to simplify setup
├── pyproject.toml   # Project configuration and dependencies
└── README.md        # You are here