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

Introduction to Python Environments for Agentic Development

• Setting up Python, virtual environments, and managing dependencies.
• Utilizing Git and Docker for version control and environment isolation.
• Adopting 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 styles.

Building Functional Agents in Python

• Creating a simple agent using LangChain.
• Connecting agents to external tools and APIs.
• Managing input/output, memory, and persistence mechanisms.

Tool and API Integration

• Defining and registering tools for agent usage.
• Implementing secure API integration and key management.
• Utilizing external data sources and custom function calls.

Agent Orchestration and Communication Patterns

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

Testing, Debugging, and Observability

• Testing agents using mock inputs and controlled environments.
• Debugging message flows and tool invocation processes.
• Implementing structured logging and tracking 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