๐ง Resources for Learning about GenAI & LLM
This post lists all the GenAI & LLM releated tutorials for learning purposes. Most of them are held and updated in my GitHub, including the Intro to AI repository. All these tutorials are beginner-friendly.
Platform for LLM Systems
Ollama
Ollama is a free, open-source tool that allows users to run large language models (LLMs) locally on their computers. Details can be found on their GitHub Page.
- ollama-python, the Python library for Ollama.
- Or use Command Line program. Ex., Command Prompt for WindowsOS and Terminal for macOS.
- Please be aware of the security issues of ollama: read the article vulnerabilities in ollama.
Ollama Tutorial 1: get started with Ollama: The tutorial explains how to install Ollama, download and run open-source AI models (e.g., DeepSeek-R1) via command line, and manage them with key CLI and in-model commands. It also covers using Ollama in Python, customizing models with
Modelfiles, and optional GUI tools like Chatbox and LMStudio.Ollama Tutorial 2: build your custom LLM with Ollama: The tutorial shows how to create a custom Python Instructor AI using Ollama by writing a
Modelfilebased on an open-source model likecodellama:7b, adjusting parameters, and adding a system prompt to define its teaching style. It also explains deploying the model in the Chatbox AI interface for easier interaction, with guidance on security when connecting to remote Ollama services.
Context Engineering
With the rising popularity of Agentic AI and multi-agent GenAI systems, managing and optimizing the context window for AI agents has evolved into an art. A leading strategy for context engineering introduces a four-step approach: write, select, compress, and isolate.
I also highly recommend reading the manual for Anthropic Claude Code to understand how this cutting-edge Agentic AI tool structures and optimizes its processes involved with context window.
Additional References
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