LLM Tutorials

Set up Ollama in Docker to run local LLMs like Llama and Mistral. Keep your data private, eliminate API costs, and build AI apps that work offline.

Learn how Anthropic's Imagine with Claude introduces a new paradigm for AI-assisted software development, generating functionality on the fly.

Learn how the Claude Agent SDK works by building three projects, from one-shot to custom-tool agents.

Learn how to run Qwen3-Next locally, serve it with transformers serve, and interact using cURL and the OpenAI SDK, making it ready for your app integrations.

Learn how Self-RAG improves traditional RAG by incorporating iterative reasoning and self-evaluation, and how to implement it step-by-step using LangGraph.

Compare LangChain, LangGraph, LangSmith, and LangFlow. Learn their roles, strengths, and when to use each for building production-ready AI applications.

Learn what LiteLLM is and how to use it for unified API calls to various LLM providers, covering basic API usage, error handling, fallbacks, streaming, structured outputs, and cost tracking.

Learn how to build a Streamlit app for side-by-side comparison of Qwen3-Next-80B-A3B and other Qwen models, focusing on real-world performance metrics.

Learn how to install and use Roo Code, an open-source AI coding assistant, and compare its features and functionalities with Cline.

Learn how to build an AI image editor using Tabnine and Google's Nano Banana model.

Learn to set up and use LangExtract for extracting structured data and relationships from unstructured text, comparing its approach to traditional NLP libraries.

Learn what GitHub Models are and how they enhance productivity by integrating AI capabilities into development workflows.