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Building an AI Agent with LangGraph - Step by Step Tutorial

MLOps.community via YouTube

MLOps.community

6076 कोर्स


11 minutes

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अवलोकन

पाठ्यक्रम

  • Introduction to AI Agents
  • Definition and fundamentals of AI agents
    Overview of agent frameworks
  • Introduction to LangGraph
  • What is LangGraph?
    Key features and advantages
    Setting up the environment
  • Working with Graph-Based Workflows
  • Understanding graph-based workflows
    Modeling workflows in LangGraph
  • Building an AI Agent Framework
  • Designing the agent architecture
    Defining tasks and goals
  • Practical Example: Budget Coach Agent
  • Overview of the budget coach use case
    Planning the agent's functionality
  • Integrating the Plaid API
  • Introduction to Plaid API
    Setting up and configuring the Plaid API
    Retrieving financial data from the Plaid API
  • Implementing the Agent in LangGraph
  • Developing the agent's logic in LangGraph
    Handling workflows and data integration
  • User Interface Design with Streamlit
  • Introduction to Streamlit
    Building the user interface for the budget coach agent
  • Testing and Debugging
  • Techniques for testing the agent
    Debugging common issues
  • Deployment and Maintenance
  • Deploying the AI agent
    Maintaining and updating the agent
  • Conclusion and Next Steps
  • Recap of the course content
    Suggested further learning paths in AI and LangGraph

विषय

Computer Science