From 440158b9694fb7e2cce8e20263fa7829eb7488a5 Mon Sep 17 00:00:00 2001 From: Eugene Yurtsev Date: Tue, 28 Jan 2025 12:57:01 -0500 Subject: [PATCH] Update functional_api.md (#3227) --- docs/docs/concepts/functional_api.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/docs/concepts/functional_api.md b/docs/docs/concepts/functional_api.md index 1b8936c4d..9d58519e5 100644 --- a/docs/docs/concepts/functional_api.md +++ b/docs/docs/concepts/functional_api.md @@ -122,7 +122,7 @@ def workflow(topic: str) -> dict: ## Functional API vs. Graph API -The **Functional API** and the [Graph APIs (StateGraph)](./low_level.md#stategraph) provide two different paradigms to create in LangGraph. Here are some key differences: +The **Functional API** and the [Graph APIs (StateGraph)](./low_level.md#stategraph) provide two different paradigms to create applications with LangGraph. Here are some key differences: - **Control flow**: The Functional API does not require thinking about graph structure. You can use standard Python constructs to define workflows. This will usually trim the amount of code you need to write. - **State management**: The **GraphAPI** requires declaring a [**State**](./low_level.md#state) and may require defining [**reducers**](./low_level.md#reducers) to manage updates to the graph state. `@entrypoint` and `@tasks` do not require explicit state management as their state is scoped to the function and is not shared across functions.