Advanced AutoGen: Custom Agents & Dynamic Tool Use Training Course

Review of AutoGen Core Concepts for Government

• Definitions of agents and groups
• Function calling and role chaining
• Limitations of built-in agents and the need for customization

Building Custom Agents with Python for Government

• Defining agent behavior using user_proxy and AssistantAgent subclasses
• Injecting role-specific logic and decision-making capabilities
• Creating reusable agent modules and mixins for enhanced functionality

Advanced Tool Integration and Routing for Government

• Tool registration, binding, and invocation processes
• Conditionally routing inputs to specific tools based on requirements
• Managing multi-step toolchains and composite actions for complex tasks

Planning and Context Management for Government

• Designing task decomposers and intermediate planners to enhance efficiency
• Maintaining context across chained agents to ensure continuity
• Implementing scoped memory for long-running sessions to preserve state

Error Handling and Recovery Mechanisms for Government

• Detecting and managing failed or incomplete interactions to maintain reliability
• Agent-triggered retries and fallback logic to address issues proactively
• Logging, debugging, and response validation to ensure robust operation

Multi-Agent Collaboration with Custom Roles for Government

• Coordinating specialists within dynamic agent groups to optimize performance
• Orchestrating reasoning loops and cooperative workflows for complex tasks
• Evaluating role separation versus role blending in task assignments for flexibility

Real-World Deployment Strategies for Government

• Optimizing for performance and cost, including token use and caching techniques
• Embedding AutoGen workflows into web applications or data pipelines for seamless integration
• Ensuring security, observability, and user feedback integration to support operational needs

Summary and Next Steps for Government