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Graduating your AI Agents Workshop 🤖

Welcome to the Graduating your AI Agents Workshop! This repository contains a comprehensive, hands-on tutorial for building AI agents that are ready for production use.

🎯 Workshop Overview

This workshop takes you from a simple toy example to a production-ready AI agent system. You'll learn the essential patterns, tools, and practices needed to build, deploy, and maintain AI agents in real-world scenarios.

🚀 What You'll Build

By the end of this workshop, you'll have built:

  • A simple coding agent (toy example)
  • A multi-agent system with specialized roles
  • An agent with state management and memory
  • A fully instrumented system with tracing and observability
  • A production-ready agent with evaluation and monitoring

📋 Prerequisites

  • Python 3.8+ installed on your system
  • OpenAI API Key (get one from OpenAI Platform)
  • Basic Python knowledge (functions, classes, async/await)
  • Git for version control
  • Terminal/Command Line familiarity

🗺️ Workshop Structure

🎬 Introduction & Motivation (30 min)

What we'll cover:

  • Setting up the development environment
  • Understanding what makes an AI agent "production-ready"
  • Analyzing existing production systems (e.g., GitHub Copilot)
  • Key challenges in agent development

Learning outcomes:

  • Understand the difference between toy examples and production systems
  • Identify the key components of a production AI agent
  • Set up your development environment

🧸 Module 1: Toy Example (30 min)

Build a simple coding agent from scratch

What you'll learn:

  • Core agent architecture patterns
  • Tool calling and integration
  • Basic error handling
  • Agent-tool interaction loops

What you'll build:

  • A coding agent that can write, execute, and test Python code
  • Integration with file system operations using Composio's FileTool app
  • A simple REPL (Read-Eval-Print Loop) tool

Key files:

  • coding_agent.py - Main agent implementation
  • examples.py - Demonstration scripts
  • requirements.txt - Dependencies

📚 Start with Module 1 →


When and how to use multiple agents

What you'll learn:

  • Multi-agent design patterns
  • Agent coordination and communication
  • Task decomposition and specialization
  • When to use multiple agents vs. a single agent

What you'll build:

  • A software development team with specialized agents
  • Agent-to-agent communication protocols
  • Task orchestration and workflow management

Key concepts:

  • Agent roles and responsibilities
  • Inter-agent communication
  • Conflict resolution
  • Performance optimization

Monitoring, debugging, and performance optimization

What you'll learn:

  • Tracing for agent systems
  • Performance monitoring and alerting
  • Debugging complex agent behaviors
  • Integration with observability platforms
  • Lifecycle hooks (pre/post execution)

What you'll build:

  • Comprehensive logging system
  • Trace correlation across agent calls
  • Error tracking and alerting
  • Lifecycle event handlers

Key concepts:

  • Structured logging
  • Performance bottleneck identification
  • Real-time monitoring
  • Hook-based instrumentation

Memory and context management

What you'll learn:

  • State persistence patterns
  • Memory management for long-running agents

What you'll build:

  • Persistent agent memory system
  • Context-aware agents

Key concepts:

  • Short-term vs. long-term memory
  • Context retrieval and relevance

Quality assurance and continuous improvement

What you'll learn:

  • Agent evaluation frameworks
  • LLM-based evaluation techniques

What you'll build:

  • Automated evaluation pipeline
  • Performance benchmarking system

Key concepts:

  • Evaluation metrics design

🚀 Quick Start

1. Clone the Repository

git clone https://github.com/yourusername/ai-agents-workshop.git
cd ai-agents-workshop

2. Set Up Environment

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies (we'll do this per module)

3. Get API Keys

You'll need an OpenAI API key for all modules:

  1. Go to OpenAI Platform
  2. Create a new API key
  3. Keep it secure - you'll add it to each module's .env file

4. Start with Module 1

cd 1-toy-example
pip install -r requirements.txt
# Follow the README instructions to set up your .env file
python coding_agent.py

📚 Learning Path

For Beginners

Start with Module 1 and work through each module sequentially. Each module builds on the previous one.

For Intermediate Developers

You can jump to specific modules based on your interests:

  • Multi-agent patterns → Module 2
  • Monitoring → Module 3
  • State management → Module 4
  • Testing → Module 5

For Advanced Users

Focus on Modules 3-5 for production-ready patterns, or use the repository as a reference implementation.

🛠️ Development Environment

Recommended Setup

  • IDE: VS Code with Python extension
  • Python: 3.8+ (3.10+ recommended)
  • Terminal: Built-in terminal or iTerm2/Windows Terminal
  • Git: Latest version

Optional Tools

  • Docker: For containerized development
  • Poetry: For dependency management
  • Pre-commit: For code quality checks

📖 Additional Resources

Documentation

Community & Support

Further Learning

🤝 Contributing

We welcome contributions! Here's how you can help:

  1. Report bugs or suggest improvements
  2. Add new examples or exercises
  3. Improve documentation
  4. Share your agent implementations

See CONTRIBUTING.md for detailed guidelines.

📄 License

This workshop is licensed under the MIT License. See LICENSE for details.

🙏 Acknowledgments

  • Thanks to the OpenAI team for the excellent APIs and tools
  • Thanks to Composio for the comprehensive tool integrations
  • Thanks to the open-source community for inspiration and tools

Ready to start building production-ready AI agents?

🚀 Begin with Module 1: Toy Example →


This workshop is designed for educational purposes. Please follow OpenAI's usage policies and best practices when building production systems.

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Repository for the hands-on workshop on building AI agents hosted by Composio and the Fifth Elephant

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