# AI Agent Chain Workshop

## Overview

Complete interactive demonstration of building intelligent AI agent workflows using classic design patterns, mimicking LangChain and LangGraph architectures.

## Key Features

* **Chain of Responsibility Pattern**: Core agent routing mechanism
* **SubGraph Architecture**: Hierarchical agent composition (LangGraph-style)
* **Multi-Provider Support**: Works with Gemini, OpenAI, Anthropic
* **Stateful Agents**: Maintain context across interactions
* **Mock Client Testing**: Test without API calls

## Patterns Demonstrated

### Primary Patterns

* **Chain of Responsibility**: Agent routing and request processing
* **Strategy**: Dynamic provider selection
* **Abstract Factory**: Different agent type creation

### Supporting Patterns

* **Template Method**: Standardized agent workflows
* **Adapter**: API client abstraction
* **Facade**: Simplified system interfaces

## What You'll Learn

1. **Agent Architecture**: Build modular, scalable AI systems
2. **Request Routing**: Intelligent query distribution
3. **SubGraph Composition**: Hierarchical agent organization
4. **State Management**: Context-aware conversations
5. **Production Patterns**: Error handling and resilience

## Real-World Applications

* **Customer Support**: Multi-tier agent routing
* **Content Systems**: Research → Writing → Production workflows
* **Technical Support**: Issue classification and escalation
* **Multi-Modal Processing**: Text → Image → Audio pipelines

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## 🚀 Interactive Implementation

**Ready to build intelligent agent systems?**

### 📓 [**Open Interactive Notebook**](https://github.com/liyedanpdx/llm-python-patterns/blob/main/workshops/ai_agent_chain_example.ipynb) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/liyedanpdx/llm-python-patterns/blob/main/workshops/ai_agent_chain_example.ipynb)

**🎯 Workshop Highlights:**

* Live agent routing demonstrations
* SubGraph architecture implementation
* Real OpenAI/Gemini API integration
* StateFul conversation management
* Production-ready error handling

**💡 Perfect For:**

* Understanding LangChain/LangGraph architectures
* Building multi-agent AI systems
* Learning enterprise AI patterns
* Creating scalable agent workflows

_Experience enterprise-grade agent architecture with hands-on coding and real API integration._
