Python for Autonomous Agents: Tooling, SDKs & Orchestration Training Course

Introduction to Python Environments for Agentic Development

• Configuring Python, virtual environments, and dependency management
• Utilizing Git and Docker for version control and isolation
• Best practices for ensuring reproducible environments

Overview of Agent SDKs and Frameworks

• LangChain, AutoGen, and other emerging SDKs
• Agent architecture and lifecycle: perception, reasoning, and action
• Evaluating SDK capabilities and architectural differences

Building Functional Agents in Python

• Creating a basic agent using LangChain
• Linking agents to external tools and APIs
• Managing input/output, memory, and data persistence

Tool and API Integration

• Defining and registering tools for agent usage
• Securing API integrations and managing credentials
• Incorporating external data sources and custom function calls

Agent Orchestration and Communication Patterns

• Facilitating multi-agent collaboration with AutoGen
• Implementing task delegation and planning logic
• Designing event-driven and asynchronous orchestration

Testing, Debugging, and Observability

• Testing agents using mock inputs and controlled settings
• Debugging message flow and tool invocation processes
• Establishing structured logging and performance metrics

Deployment and Production Considerations

• Packaging and containerizing Python agent services
• Integrating with CI/CD pipelines
• Scaling, monitoring, and maintaining long-running agents

Summary and Next Steps