課程簡介

Introduction to CrewAI and Multi-Agent Architecture

  • Overview of CrewAI concepts and architecture
  • Understanding agent roles and flows
  • Use cases and design patterns

Designing Custom Agents and Tools

  • Defining agent goals, memory, and behavior
  • Creating and integrating custom tools
  • Tool abstraction and modular design

Advanced Agent Collaboration

  • Sequencing and synchronization of tasks
  • Nested and parallel flows
  • Multi-agent decision making

API and System Integration

  • Calling external APIs from agents
  • Incorporating real-time data sources
  • Building pipelines and dynamic inputs

Event-Driven Orchestration

  • Trigger-based workflows and custom events
  • Error handling and fallback logic
  • Using webhooks and schedulers

Monitoring, Testing, and Optimization

  • Observing agent behavior and performance
  • Debugging workflows and logging
  • Scaling strategies and optimization tips

Practical Implementation and Case Studies

  • Implementing a domain-specific use case
  • Case study: enterprise automation with CrewAI
  • Lessons learned and best practices

Summary and Next Steps

最低要求

  • 具備Python編程經驗
  • 了解AI與機器學習基礎知識
  • 熟悉API整合與軟體架構概念

目標受眾

  • AI工程師
  • 研究人員
  • 軟體架構師
 14 時間:

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