From d17355cd683403aa91f3d0d918c548e57a9b42f8 Mon Sep 17 00:00:00 2001 From: resitaydin Date: Tue, 13 May 2025 11:47:36 +0300 Subject: [PATCH] update compare_embeddings doc links --- docs/howtos/applications/compare_embeddings.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/howtos/applications/compare_embeddings.md b/docs/howtos/applications/compare_embeddings.md index 22387153c..4ddb8341f 100644 --- a/docs/howtos/applications/compare_embeddings.md +++ b/docs/howtos/applications/compare_embeddings.md @@ -18,12 +18,12 @@ This tutorial notebook provides a step-by-step guide on how to compare and choos !!! tip - Ragas can also work with your dataset. Refer to [data preparation](./data_preparation.md) to see how you can use your dataset with ragas. + Ragas can also work with your dataset. Refer to [data preparation](../customizations/testgenerator/index.md) to see how you can use your dataset with ragas. Ragas offers a unique test generation paradigm that enables the creation of evaluation datasets specifically tailored to your retrieval and generation tasks. Unlike traditional QA generators, Ragas can generate a wide variety of challenging test cases from your document corpus. !!! tip - Refer to [testset generation](../../concepts/testset_generation.md) to know more on how it works. + Refer to [testset generation](../../getstarted/rag_testset_generation.md) to know more on how it works. For this tutorial notebook, I am using papers from Semantic Scholar that is related to large language models to build RAG.