diff --git a/pages/techniques/rag.en.mdx b/pages/techniques/rag.en.mdx
index 4694ca54d..34816bc15 100644
--- a/pages/techniques/rag.en.mdx
+++ b/pages/techniques/rag.en.mdx
@@ -22,4 +22,4 @@ This shows the potential of RAG as a viable option for enhancing outputs of lang
 
 More recently, these retriever-based approaches have become more popular and are combined with popular LLMs like ChatGPT to improve capabilities and factual consistency.
 
-You can find a [simple example of how to use retrievers and LLMs for question answering with sources](https://python.langchain.com/en/latest/modules/chains/index_examples/vector_db_qa_with_sources.html) from the LangChain documentation.
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+You can find a [simple example of how to use retrievers and LLMs for question answering with sources](https://python.langchain.com/docs/modules/chains/popular/vector_db_qa) from the LangChain documentation.