What kind of AI agents can I learn to build?

You'll find examples of basic agents, RAG systems, multi-agent architectures, and Agent-to-Agent (A2A) communication protocols, primarily using LangChain and LangGraph.

AI Examples is a curated collection of practical code demonstrating core AI concepts, LLMs, and intelligent agent development across various frameworks like Keras, LangChain, and LangGraph.

What types of AI models are included?

It covers implementations of deep learning models such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Transformer architectures like Tiny GPT.

Are there examples for Large Language Models (LLMs)?

Yes, it provides examples for running local LLMs using Ollama and building sophisticated LLM applications with LangChain and LangGraph, including RAG (Retrieval Augmented Generation) and multi-agent systems.

AI Examples

Name: AI Examples
Author: sumitdotgh

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Provides a curated collection of practical AI and LLM examples using various frameworks and tools.

This repository offers a curated collection of practical AI and LLM examples built with Keras, LangChain, OpenAI, Azure OpenAI, and LangGraph. It serves as a personal learning journey, demonstrating how to construct intelligent agents, integrate custom tools, work with APIs, and run local models like Mistral using Ollama. Each project within aims to provide hands-on experience, fostering a deeper understanding of core AI building blocks, from neural networks to multi-agent systems, by writing real code and experimenting with modern AI technologies.

主要功能

01Showcases various LangChain and LangGraph agent examples, including RAG and multi-agent systems

020 GitHub stars

03Illustrates running local LLMs using Ollama

04Demonstrates CNN, RNN, and Transformer (Tiny GPT) model implementations

05Provides examples of Agent-to-Agent (A2A) communication protocols

06Includes a FastAPI-based weather API as an MCP server example

使用案例

01Learning and experimenting with AI, LLM, and agent-based development

02Understanding practical applications of Keras, LangChain, LangGraph, and Ollama

03Building and testing intelligent agents and multi-agent systems architectures