docs: feedback from suggestions

explodinggradients · Dec 13, 2024 · 6afe6ce · 6afe6ce
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diff --git a/docs/getstarted/rag_evaluation.md b/docs/getstarted/rag_evaluation.md
@@ -53,7 +53,9 @@ metrics = [
 results = evaluate(dataset=eval_dataset, metrics=metrics)
 ```
 
-### Exporting and analyzing results
+### Analyzing results
+
+You can use the `to_pandas()` method to get a pandas dataframe of the results and do various analysis on it.
 
 ```python
 df = results.to_pandas()
@@ -62,12 +64,9 @@ df.head()
 
 ![evaluation-result](./raga_evaluation_output.png)
 
-### Analyzing the results with Ragas Dashboard (optional)
-
-!!! note
-    This section is optional. The dashboard provides additional visualization capabilities like being able to see the traces of evaluator LLMs but is not required for basic RAG evaluation and can be configured with other tools in the [Integrations](../howtos/integrations/index.md) section.
+Once you have evaluated, you may want to view, analyse and share results. For this you can use app.ragas.io or any other similar tools available for you in the [Integrations](../howtos/integrations/index.md) section.
 
-In order to use the dashboard, you need to have an account on [app.ragas.io](https://app.ragas.io/). If you don't have one, you can sign up for one [here](https://app.ragas.io/login). You will also need to have a [Ragas API key](https://app.ragas.io/settings/api-keys).
+In order to use the [app.ragas.io](http://app.ragas.io) dashboard, you need to have an account on [app.ragas.io](https://app.ragas.io/). If you don't have one, you can sign up for one [here](https://app.ragas.io/login). You will also need to generate a [Ragas API key](https://app.ragas.io/settings/api-keys).
 
 Once you have the API key, you can use the `upload()` method to export the results to the dashboard.
 

diff --git a/docs/getstarted/rag_testset_generation.md b/docs/getstarted/rag_testset_generation.md
@@ -43,22 +43,19 @@ generator = TestsetGenerator(llm=generator_llm, embedding_model=generator_embedd
 dataset = generator.generate_with_langchain_docs(docs, testset_size=10)
 ```
 
-### Export
+### Analyzing the testset
 
-You may now export and inspect the generated testset.
+Once you have generated a testset, you would want to view it and select the queries you see fit to include in your final testset. You can export the testset to a pandas dataframe and do various analysis on it.
 
 ```python
 dataset.to_pandas()
 ```
 
 ![testset](./testset_output.png)
 
-### View and Select your Testset with Ragas Dashboard (optional)
+You can also use other tools like [app.ragas.io](https://app.ragas.io/) or any other similar tools available for you in the [Integrations](../howtos/integrations/index.md) section.
 
-!!! note
-    This section is optional. The Dashboard makes it easier to view the testset generated and choose the queries you want to include in your testset. You can use other tools to do this as well, check out the [Integrations](../howtos/integrations/index.md) section for more information.
-
-In order to use the dashboard, you need to have an account on [app.ragas.io](https://app.ragas.io/). If you don't have one, you can sign up for one [here](https://app.ragas.io/login). You will also need to have a [Ragas API key](https://app.ragas.io/settings/api-keys).
+In order to use the [app.ragas.io](https://app.ragas.io/) dashboard, you need to have an account on [app.ragas.io](https://app.ragas.io/). If you don't have one, you can sign up for one [here](https://app.ragas.io/login). You will also need to have a [Ragas API key](https://app.ragas.io/settings/api-keys).
 
 Once you have the API key, you can use the `upload()` method to export the results to the dashboard.