Building an AI Agent with LangGraph - Step by Step Tutorial

Overview

Syllabus

• 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

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Subjects

Computer Science