HANDS-ON IMPLEMENTATIONS

This directory contains hands-on workshop series designed to provide practical, interactive learning experiences with Python design patterns in LLM applications.

📚 Available Workshops

🔧 Python Context Manager Workshop

Status: ✅ Completed (2025-08-21) Modules: 8 comprehensive modules Focus: Enterprise-grade resource management for LLM applications

A complete workshop series covering Context Manager mastery from basic concepts to enterprise-grade implementations:

1. Basic Concepts (基础概念) | 中文

2. LLM Session Manager (大语言模型会话管理器) | 中文

3. Async Manager (异步管理器) | 中文

4. Smart Session (智能会话) | 中文

5. Nested Managers (嵌套管理器) | 中文

6. MCP Implementation (MCP 实现) | 中文

7. AsyncExitStack vs @asynccontextmanager (对比分析) | 中文

8. Local MCP Integration (本地 MCP 集成) | 中文

9. Design Patterns Analysis (设计模式分析) | 中文

Key Learnings:

• Context Manager is essential for enterprise LLM applications

• AsyncExitStack enables complex multi-resource management

• MCP protocol requires sophisticated resource orchestration

• Production-ready error handling and cleanup strategies

🤖 AI Agent Chain Workshop

Multi-agent systems using Chain of Responsibility pattern, featuring LangGraph-style SubGraph architecture.

🔄 JSON Schema Factory Workshop

Structured LLM output control using Factory pattern with Pydantic validation across multiple providers.