This talk was given as a workshop at the AI Engineering World's Fair on June, 24 2024. LLM-powered agents hold tremendous promise for autonomously performing tasks, but reliability is often a barrier for deployment and productionisation. Here, we'll show how to design and build reliable agents using LangGraph. We’ll cover ways to test agents using LangSmith, examining both agent's final response as well as agent tool use trajectory. We'll compare a custom LangGraph agent to a ReAct agent for RAG to showcase the reliability benefit associated with building custom agents using LangGraph.
Slides:
https://docs.google.com/presentation/d/1QWkXi4DYjfw94eHcy9RMLqpQdJtS2C_kx_u7wAUvlZE/edit?usp=sharing
CoLab:
https://drive.google.com/file/d/1KUCIBFtDytL2gFgyFC46t_Yjp3jDjdUF/view?usp=sharing
Notebook:
https://github.com/langchain-ai/langgraph/blob/main/examples/tutorials/rag-agent-testing.ipynb
LangGraph:
https://blog.langchain.dev/langgraph-cloud/
