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

Introduction to Python Environments for Agentic Development

• Setting up Python, virtual environments, and managing dependencies
• Leveraging Git and Docker for version control and isolation
• Best practices for ensuring reproducible environments

Overview 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

Building Functional Agents in Python

• Creating a basic 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
• Securing API integrations and managing keys
• Utilizing external data sources and custom function calls

Agent Orchestration and Communication Patterns

• Facilitating multi-agent collaboration using AutoGen
• Implementing task delegation and planning logic
• Event-driven and asynchronous orchestration strategies

Testing, Debugging, and Observability

• Testing agents using mock inputs and controlled settings
• Debugging message flows and tool invocations
• Implementing structured logging and performance monitoring

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