From b00a233174d48edbb3abb4a198c7424ddb681dc4 Mon Sep 17 00:00:00 2001 From: Nuno Campos Date: Tue, 7 May 2024 13:10:22 -0700 Subject: [PATCH] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 0233bc5bc..2513dd476 100644 --- a/README.md +++ b/README.md @@ -12,7 +12,7 @@ [LangGraph](https://langchain-ai.github.io/langgraph/) is a library for building stateful, multi-actor applications with LLMs. Inspired by [Pregel](https://research.google/pubs/pub37252/) and [Apache Beam](https://beam.apache.org/), LangGraph lets you coordinate and checkpoint multiple chains (or actors) across cyclic computational steps using regular python functions (or [JS](https://github.com/langchain-ai/langgraphjs)). The public interface draws inspiration from [NetworkX](https://networkx.org/documentation/latest/). -The main use is for adding **cycles** and **persistance** to your LLM application. If you only need quick Directed Acyclic Graphs (DAGs), you can already accomplish this using [LangChain Expression Language](https://python.langchain.com/docs/expression_language/). +The main use is for adding **cycles** and **persistence** to your LLM application. If you only need quick Directed Acyclic Graphs (DAGs), you can already accomplish this using [LangChain Expression Language](https://python.langchain.com/docs/expression_language/). Cycles are important for agentic behaviors, where you call an LLM in a loop, asking it what action to take next.