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*   [Get started](/v0.1/docs/get_started/)
    
    *   [Introduction](/v0.1/docs/get_started/introduction/)
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*   [LangChain Expression Language](/v0.1/docs/expression_language/)
    
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    *   [Why use LCEL?](/v0.1/docs/expression_language/why/)
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    *   [How to](/v0.1/docs/expression_language/how_to/routing/)
        
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    *   [LangChain Expression Language (LCEL)](/v0.1/docs/expression_language/)
*   [Modules](/v0.1/docs/modules/)
    
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*   SvelteKit

On this page

SvelteKit
=========

If you're looking to use LangChain in a [SvelteKit](https://kit.svelte.dev/) project, you can check out [svelte-chat-langchain](https://github.com/SimonPrammer/svelte-chat-langchain).

The app is a SvelteKit implementation of the QA Chatbot [Chat Langchain](https://github.com/langchain-ai/chat-langchain) and is best used as a reference to learn the basics of a QA chatbot over documents or as a starting point for your own custom implementation.

The example shows one possible way to implement ingestion (document loading, splitting, and embedding) as well as RAG (Retrieval Augmented Generation), LCEL, conditional chaining, and streaming.

![SvelteKit Chat Langchain screenshot](/v0.1/assets/images/sveltekit-chat-langchain-6f8b0015dfbb3b2df50669346a14dccb.png)

Links[​](#links "Direct link to Links")
---------------------------------------

*   Repository: [https://github.com/SimonPrammer/svelte-chat-langchain](https://github.com/SimonPrammer/svelte-chat-langchain)
*   Blog post: [QA Chatbot: Chatting with your Documents made simple](https://simon-prammer.vercel.app/blog/post/easiest-qa-chatbot) for a step-by-step guide!

* * *

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