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 creating reproducible environments

Overview of Agent SDKs and Frameworks

• Exploring LangChain, AutoGen, and other emerging SDKs
• Understanding agent structure and lifecycle: perception, reasoning, and action
• Comparing SDK capabilities and architectural approaches

Building Functional Agents in Python

• Developing a simple agent using LangChain
• Linking agents to external tools and APIs
• Managing input/output, memory, and persistence

Tool and API Integration

• Defining and registering tools for agent utilization
• Ensuring secure API integration and key management
• Leveraging external data sources and custom function calls

Agent Orchestration and Communication Patterns

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

Testing, Debugging, and Observability

• Testing agents using mock inputs and controlled environments
• Debugging message flow and tool invocation
• 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