After doing sequential graph execution in LangGraph, I wanted to explore the conditional and parallel execution graph flow, so I came up with a contrived example, where I have expanded a simple RAG ...

Victor Lee is director of product management at TigerGraph. Graph databases excel at answering complex questions about relationships in large data sets. But they hit a wall—in terms of both ...

Abstract: Financial transaction systems have become the critical backbone of modern society, and the sharp increase in fraudulent transactions has become an unavoidable significant topic. Their ...

Graph embeddings are numerical representations of graph nodes that capture their structural and semantic features. Graph embeddings can be used for various downstream tasks, such as node ...

In LangGraph, nodes are the fundamental processing units that follow the single-responsibility principle. Each node has a clear, specific task - whether it's generating topics, creating summaries, or ...

We start with the serial execution of the nodes in our graph workflow. We can arrange our nodes in the following way. workflow.add_edge(START, "create_model") workflow.add_edge("create_model", ...