From 15ddc0b17acac769c639765f9612016c0ead4391 Mon Sep 17 00:00:00 2001 From: Rahul Shah Date: Thu, 23 Jan 2025 15:29:20 +0530 Subject: [PATCH] Typo fix. "Confidnet" -> "Confident" --- deepeval/dataset/dataset.py | 2 +- docs/docs/getting-started.mdx | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/deepeval/dataset/dataset.py b/deepeval/dataset/dataset.py index eab1d7ebc..0e6bb70c9 100644 --- a/deepeval/dataset/dataset.py +++ b/deepeval/dataset/dataset.py @@ -622,7 +622,7 @@ def push( link = response.link console = Console() console.print( - "✅ Dataset successfully pushed to Confidnet AI! View at " + "✅ Dataset successfully pushed to Confident AI! View at " f"[link={link}]{link}[/link]" ) webbrowser.open(link) diff --git a/docs/docs/getting-started.mdx b/docs/docs/getting-started.mdx index 8898e73b3..232443549 100644 --- a/docs/docs/getting-started.mdx +++ b/docs/docs/getting-started.mdx @@ -193,7 +193,7 @@ Green rows mean your LLM improved on this particular test case, while red means ## Create Your First Metric :::info -If you're having trouble deciding on which metric to use, you can follow [this tutorial](/tutorials/tutorial-metrics-defining-an-evaluation-criteria) or use [Confident AI's metrics recommendation tool](https://confidnet-ai.com). +If you're having trouble deciding on which metric to use, you can follow [this tutorial](/tutorials/tutorial-metrics-defining-an-evaluation-criteria) or use [Confident AI's metrics recommendation tool](https://confident-ai.com). ::: `deepeval` provides two types of LLM evaluation metrics to evaluate LLM outputs: plug-and-use **default** metrics, and **custom** metrics for any evaluation criteria.