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 environment isolation.
• Adopting best practices for ensuring 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.
• Comparing the capabilities and architectural styles of different SDKs.

Building Functional Agents in Python

• Creating a simple agent utilizing 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.
• Implementing secure API integration and robust key management.
• Incorporating external data sources and custom function calls.

Agent Orchestration and Communication Patterns

• Facilitating multi-agent collaboration using AutoGen.
• Structuring task delegation and planning logic.
• Implementing event-driven and asynchronous orchestration.

Testing, Debugging, and Observability

• Testing agents with 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 agent services with CI/CD pipelines.
• Scaling, monitoring, and maintaining long-running agents.

Summary and Next Steps