From 4f94548bb79e50996dc6d34c5040a5fc50f02b71 Mon Sep 17 00:00:00 2001 From: Hyunjoon Jeong Date: Tue, 27 May 2025 04:22:35 +0900 Subject: [PATCH] docs: fix vocabs and missing redirect links in concepts (#31352) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit ### Description Fix typo errors and missing redirect links in LangChain concepts documents. ### Issue None ### Dependencies None --------- Co-authored-by: 정현준/AIX 팀 <126749237+hyunjoon1015@users.noreply.github.com> --- docs/docs/concepts/agents.mdx | 2 +- docs/docs/concepts/async.mdx | 2 +- docs/docs/concepts/callbacks.mdx | 2 +- docs/docs/concepts/text_splitters.mdx | 4 ++-- 4 files changed, 5 insertions(+), 5 deletions(-) diff --git a/docs/docs/concepts/agents.mdx b/docs/docs/concepts/agents.mdx index 960eb2a975d..3ca96125e1f 100644 --- a/docs/docs/concepts/agents.mdx +++ b/docs/docs/concepts/agents.mdx @@ -15,7 +15,7 @@ LangChain previously introduced the `AgentExecutor` as a runtime for agents. While it served as an excellent starting point, its limitations became apparent when dealing with more sophisticated and customized agents. As a result, we're gradually phasing out `AgentExecutor` in favor of more flexible solutions in LangGraph. -### Transitioning from AgentExecutor to langgraph +### Transitioning from AgentExecutor to LangGraph If you're currently using `AgentExecutor`, don't worry! We've prepared resources to help you: diff --git a/docs/docs/concepts/async.mdx b/docs/docs/concepts/async.mdx index d81c706db24..8e8a3de9a36 100644 --- a/docs/docs/concepts/async.mdx +++ b/docs/docs/concepts/async.mdx @@ -9,7 +9,7 @@ LLM based applications often involve a lot of I/O-bound operations, such as maki :::note You are expected to be familiar with asynchronous programming in Python before reading this guide. If you are not, please find appropriate resources online to learn how to program asynchronously in Python. -This guide specifically focuses on what you need to know to work with LangChain in an asynchronous context, assuming that you are already familiar with asynch +This guide specifically focuses on what you need to know to work with LangChain in an asynchronous context, assuming that you are already familiar with asynchronous programming. ::: ## Langchain asynchronous APIs diff --git a/docs/docs/concepts/callbacks.mdx b/docs/docs/concepts/callbacks.mdx index 5a6691baa5a..5899a4a98cd 100644 --- a/docs/docs/concepts/callbacks.mdx +++ b/docs/docs/concepts/callbacks.mdx @@ -6,7 +6,7 @@ LangChain provides a callback system that allows you to hook into the various stages of your LLM application. This is useful for logging, monitoring, streaming, and other tasks. -You can subscribe to these events by using the `callbacks` argument available throughout the API. This argument is list of handler objects, which are expected to implement one or more of the methods described below in more detail. +You can subscribe to these events by using the `callbacks` argument available throughout the API. This argument is a list of handler objects, which are expected to implement one or more of the methods described below in more detail. ## Callback events diff --git a/docs/docs/concepts/text_splitters.mdx b/docs/docs/concepts/text_splitters.mdx index 335b854ec50..b5875dd33b9 100644 --- a/docs/docs/concepts/text_splitters.mdx +++ b/docs/docs/concepts/text_splitters.mdx @@ -3,8 +3,8 @@ :::info[Prerequisites] -* [Documents](/docs/concepts/retrievers/#interface) -* Tokenization(/docs/concepts/tokens) +* [Documents](./retrievers.mdx) +* [Tokenization](./tokens.mdx) ::: ## Overview