From 384e4423023282a121974b5d9f65dcfad0582d4b Mon Sep 17 00:00:00 2001
From: Jeffrey Ip <143328635+penguine-ip@users.noreply.github.com>
Date: Mon, 26 Feb 2024 23:58:44 +0800
Subject: [PATCH] Update deepeval.md (#195)

* Update deepeval.md

* Update deepeval.md
---
 integrations/deepeval.md | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/integrations/deepeval.md b/integrations/deepeval.md
index 203cdcd6..665de432 100644
--- a/integrations/deepeval.md
+++ b/integrations/deepeval.md
@@ -26,7 +26,7 @@ toc: true
 
 ## Overview
 
-[DeepEval](https://docs.confident-ai.com/) is an open source framework for model-based evaluation to evaluate your LLM applications by quantifying their performance on aspects such as faithfulness, answer relevancy, contextual recall etc. More information can be found on the [documentation page](https://docs.haystack.deepset.ai/v2.0/docs/deepevalevaluator).
+[DeepEval](https://github.com/confident-ai/deepeval) (by [Confident AI](https://www.confident-ai.com/)) is an open source framework for model-based evaluation to evaluate your LLM applications by quantifying their performance on aspects such as faithfulness, answer relevancy, contextual recall etc. More information can be found on the [documentation page](https://docs.haystack.deepset.ai/v2.0/docs/deepevalevaluator).
 
 ## Installation
 
@@ -44,6 +44,8 @@ Once installed, you will have access to a [DeepEvalEvaluator](https://docs.hayst
 - Contextual Recall
 - Contextual Relevance
 
+In addition to evaluation scores, DeepEval's evaluators offer additional reasoning for each evaluation.
+
 ### DeepEvalEvaluator
 
 To use this integration for calculating model-based evaluation metrics, initialize a `DeepEvalEvaluator` with the metric name and metric input parameters: