From 0928ff5b12824f2a4d27f8f0b8129d561bd35cbf Mon Sep 17 00:00:00 2001 From: Kush Goswami <97998375+goswamikush@users.noreply.github.com> Date: Thu, 28 Aug 2025 10:29:35 -0400 Subject: [PATCH] docs: fix typo in LangGraph section of Introduction (#32728) Change "Linkedin" to "LinkedIn" to be consistent with LinkedIn's spelling. Thank you for contributing to LangChain! Follow these steps to mark your pull request as ready for review. **If any of these steps are not completed, your PR will not be considered for review.** - [x] **Add tests and docs**: If you're adding a new integration, you must include: 1. A test for the integration, preferably unit tests that do not rely on network access, 2. An example notebook showing its use. It lives in `docs/docs/integrations` directory. - [x] **Lint and test**: Run `make format`, `make lint` and `make test` from the root of the package(s) you've modified. **We will not consider a PR unless these three are passing in CI.** See [contribution guidelines](https://python.langchain.com/docs/contributing/) for more. Additional guidelines: - Make sure optional dependencies are imported within a function. - Please do not add dependencies to `pyproject.toml` files (even optional ones) unless they are **required** for unit tests. - Most PRs should not touch more than one package. - Changes should be backwards compatible. --- docs/docs/introduction.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/docs/introduction.mdx b/docs/docs/introduction.mdx index f659cfd37fb..de01d3d4401 100644 --- a/docs/docs/introduction.mdx +++ b/docs/docs/introduction.mdx @@ -104,7 +104,7 @@ Head to the reference section for full documentation of all classes and methods Trace and evaluate your language model applications and intelligent agents to help you move from prototype to production. ### [🦜🕸️ LangGraph](https://langchain-ai.github.io/langgraph) -Build stateful, multi-actor applications with LLMs. Integrates smoothly with LangChain, but can be used without it. LangGraph powers production-grade agents, trusted by Linkedin, Uber, Klarna, GitLab, and many more. +Build stateful, multi-actor applications with LLMs. Integrates smoothly with LangChain, but can be used without it. LangGraph powers production-grade agents, trusted by LinkedIn, Uber, Klarna, GitLab, and many more. ## Additional resources