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课程大纲
Introduction to Python Environments for Agentic Development
- Setting up Python, virtual environments, and dependency management
- Using Git and Docker for versioning and isolation
- Best practices for reproducible environments
Overview of Agent SDKs and Frameworks
- LangChain, AutoGen, and other emerging SDKs
- Agent structure and lifecycle: perception, reasoning, and action
- Comparing SDK capabilities and architecture styles
Building Functional Agents in Python
- Creating a simple agent with LangChain
- Connecting agents to external tools and APIs
- Handling input/output, memory, and persistence
Tool and API Integration
- Defining and registering tools for agent use
- Secure API integration and key management
- Using external data sources and custom function calls
Agent Orchestration and Communication Patterns
- Multi-agent collaboration using AutoGen
- Task delegation and planning logic
- Event-driven and asynchronous orchestration
Testing, Debugging, and Observability
- Testing agents with mock inputs and controlled environments
- Debugging message flow and tool invocation
- Implementing structured logging and 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
要求
- An understanding of Python programming and package management
- Experience with REST APIs and JSON data structures
- Basic familiarity with asynchronous I/O in Python
Audience
- Backend engineers
- Platform engineers
- ML engineers
21 小时
