From 38581f31dd59fa462aaed2e71224ffc0516ec5a8 Mon Sep 17 00:00:00 2001 From: Kanav Bansal <13186335+bansalkanav@users.noreply.github.com> Date: Mon, 21 Jul 2025 18:47:54 +0530 Subject: [PATCH] docs(docs): update RAG tutorials link to point to correct path in Google Vertex AI Embeddings (#32141) --- .../integrations/text_embedding/google_vertex_ai_palm.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/docs/integrations/text_embedding/google_vertex_ai_palm.ipynb b/docs/docs/integrations/text_embedding/google_vertex_ai_palm.ipynb index ac90af8488c..4f07b8245d2 100644 --- a/docs/docs/integrations/text_embedding/google_vertex_ai_palm.ipynb +++ b/docs/docs/integrations/text_embedding/google_vertex_ai_palm.ipynb @@ -167,7 +167,7 @@ "source": [ "## Indexing and Retrieval\n", "\n", - "Embedding models are often used in retrieval-augmented generation (RAG) flows, both as part of indexing data as well as later retrieving it. For more detailed instructions, please see our [RAG tutorials](/docs/tutorials/).\n", + "Embedding models are often used in retrieval-augmented generation (RAG) flows, both as part of indexing data as well as later retrieving it. For more detailed instructions, please see our [RAG tutorials](/docs/tutorials/rag).\n", "\n", "Below, see how to index and retrieve data using the `embeddings` object we initialized above. In this example, we will index and retrieve a sample document in the `InMemoryVectorStore`." ]