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

Introduction to Python Environments for Agentic Development

• Configuring Python, virtual environments, and dependency management.
• Leveraging Git and Docker for version control and isolation.
• Establishing best practices for reproducible development environments.

Overview of Agent SDKs and Frameworks

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

Building Functional Agents in Python

• Developing 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 utilization.
• Ensuring secure API integration and managing keys effectively.
• Incorporating external data sources and custom function calls.

Agent Orchestration and Communication Patterns

• Facilitating multi-agent collaboration through AutoGen.
• Implementing task delegation and planning logic.
• Utilizing event-driven and asynchronous orchestration models.

Testing, Debugging, and Observability

• Testing agents using mock inputs within controlled environments.
• Debugging message flows and tool invocations.
• Implementing structured logging and tracking performance metrics.

Deployment and Production Considerations

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

Summary and Next Steps