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

Foundations of Python Environments for Agentic Development

• Configuring Python, virtual environments, and dependency management.
• Utilizing Git and Docker for effective versioning and isolation.
• Adopting best practices for creating reproducible environments.

Survey of Agent SDKs and Frameworks

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

Developing Functional Agents in Python

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

Tool and API Integration Strategies

• Defining and registering tools for agent utilization.
• Implementing secure API integrations and key management.
• Incorporating external data sources and custom function calls.

Agent Orchestration and Communication Models

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

Testing, Debugging, and Observability

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

Deployment and Production-Ready Considerations

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

Summary and Future Directions