From 82da9867ea3cf1905fbdf04f06b4dad656fe1d02 Mon Sep 17 00:00:00 2001 From: aravind10x <167971308+aravind10x@users.noreply.github.com> Date: Sat, 26 Oct 2024 11:24:26 +0530 Subject: [PATCH] Update README.md --- README.md | 20 ++++++++++---------- 1 file changed, 10 insertions(+), 10 deletions(-) diff --git a/README.md b/README.md index 13b3140..8e3cd25 100644 --- a/README.md +++ b/README.md @@ -2,16 +2,16 @@  # - -[](https://www.python.org/) -[](https://GitHub.com/KruxAI/ragbuilder/releases/) -[](https://github.com/KruxAI/ragbuilder/blob/master/LICENSE) -[](https://GitHub.com/KruxAI/ragbuilder/commit/) -[](https://GitHub.com/KruxAI/ragbuilder/network/) -[](https://GitHub.com/KruxAI/ragbuilder/stargazers/) - - - +
+ + RagBuilder is a toolkit that helps you create optimal Production-ready Retrieval-Augmented-Generation (RAG) setup for your data automatically. By performing hyperparameter tuning on various RAG parameters (Eg: chunking strategy: semantic, character etc., chunk size: 1000, 2000 etc.), RagBuilder evaluates these configurations against a test dataset to identify the best-performing setup for your data. Additionally, RagBuilder includes several state-of-the-art, pre-defined RAG templates that have shown strong performance across diverse datasets. So just bring your data, and RagBuilder will generate a production-grade RAG setup in just minutes.