AgentVerse
Universe of Agents

Learn agentic AI through hands-on Jupyter notebooks covering multi-agent workflows, LLM orchestration, and real-world applications.

View on GitHub Explore Projects
8+
Projects
5
Frameworks
3
Skill Levels

Featured Projects

Real-world AI agent applications across multiple domains

📚 Foundations

🏥 Beginner

MedTech AI Opportunity Finder

Generate healthcare/pharma AI business opportunities with pain points and solutions using GPT-4o-mini.

OpenAI Streaming
💊 Intermediate

MedGuard Debate

Multi-agent debate system for drug interaction analysis with structured argumentation.

Multi-Agent Healthcare
View Demo →
🌐 Advanced

PageBotAI

Web crawling chatbot that answers questions by extracting and processing web content.

Web Scraping PocketFlow
View Demo →
☀️ Intermediate

WeatherMate

AI agent for weather and event recommendations with personalized suggestions.

Weather API Recommendations
View Demo →

🔧 OpenAI SDK

📢 Intermediate

MedReach

Multi-Agentic AI System for Personalized HCP Outreach with automated email campaigns.

OpenAI SDK Email Automation
💼 Beginner

AskMyCV

AI agent for answering career questions using resume data with intelligent Q&A.

OpenAI SDK RAG
View Demo →

👥 CrewAI

💹 Advanced

PRISM

AI-powered swap trading monitoring system with 5 specialized agents working together to monitor positions and generate trading signals.

CrewAI Finance Multi-Agent
View Demo →

🕸️ LangGraph

📖 Intermediate

LangGraph Fundamentals

Learn the fundamentals of LangGraph with comparisons to LangChain and stateful agent workflows.

LangGraph Tutorial
🤖 Advanced

Sidekick

Personal AI assistant with evaluator feedback loop, web search, notifications, and persistent memory.

LangGraph Self-Evaluation Memory

🔷 Microsoft Agent Framework

🔷 Intermediate

Microsoft Agent Framework

Explore Microsoft's agent framework with agents, workflows, tools, and async LLM calls. Learn why it's replacing Autogen.

Microsoft Framework Async
🤖 Advanced

Sidekick (Microsoft)

Sidekick AI assistant rebuilt with Microsoft Agent Framework, featuring worker-evaluator feedback loops and quality control.

Microsoft Self-Evaluation Workflows

🔗 MCP (Model Context Protocol)

📚 Intermediate

MCP Fundamentals

Learn the Model Context Protocol (MCP) basics, architecture, transport mechanisms, and how to build MCP servers.

MCP Protocol Tutorial
📅 Intermediate

DateTime MCP Server

Practical MCP server implementation for date and time operations with complex date parsing and scheduling capabilities.

MCP Server DateTime

Learning Path

Progressive journey from beginner to advanced agentic AI

1

Foundations

Start with basic LLM workflows, prompt chaining, and simple agent patterns. Learn to build your first AI agents with OpenAI.

2

OpenAI SDK

Master the OpenAI SDK for building more sophisticated agents with function calling, streaming, and multi-step reasoning.

3

Multi-Agent Systems

Explore CrewAI for orchestrating multiple specialized agents working together on complex tasks.

4

Stateful Workflows

Learn LangGraph for building stateful, non-linear agent workflows with loops, conditionals, and memory.

5

Microsoft Agent Framework

Master Microsoft's modern agent framework with async workflows, tools, and state management. Learn why it's replacing Autogen.

6

MCP (Model Context Protocol)

Explore the Model Context Protocol for building extensible agent systems with standardized server-client communication.

What's Included

Everything you need to master agentic AI

📝

Clear Problem Statements

Each project includes real-world context and clear problem definitions

🔧

Step-by-Step Implementation

Detailed explanations and code walkthroughs for every project

📊

Workflow Schemas

Visual diagrams to understand agent architectures and data flows

🔑

Setup Instructions

Complete API key requirements and environment setup guides

Get Started

Ready to dive into the world of Agentic AI? Follow these simple steps to get started.

Quick Start 
# 1. Clone the repository
git clone https://github.com/lisekarimi/agentverse.git
cd agentverse

# 2. Setup environment
mv .env.example .env  # Add your API keys here

# 3. Install dependencies
uv sync

Requirements

  • Python 3.11.x (not 3.12+)
  • uv package manager
  • IDE with AI integration (VS Code, Cursor, or similar)

Based on Ed Donner's AI Agents Course

This project is inspired by the comprehensive agentic AI engineering course. Explore the full curriculum and resources.

Udemy Course GitHub Repository Course Page
🏆

Certification

Successfully completed Ed Donner's Complete Agentic AI Engineering Course

View Certificate

Do you like this project?

Find similar projects inspired from Ed Donner's course and explore more AI projects on my portfolio.

🧠

Lexo

LLM toolkit for RAG, fine-tuning, agents, and more. Another comprehensive collection inspired by Ed Donner.

View Lexo
💼

Portfolio

Explore more AI projects, demos, and applications on my personal portfolio website.

Visit Portfolio