diff --git a/docs/concepts/prompt_adaptation.md b/docs/concepts/prompt_adaptation.md
index 056668977..790f54104 100644
--- a/docs/concepts/prompt_adaptation.md
+++ b/docs/concepts/prompt_adaptation.md
@@ -39,7 +39,7 @@ Create a sample prompt using `Prompt` class.
 ```{code-block} python
 
 from langchain.chat_models import ChatOpenAI
-from ragas.llms import LangchainLLM
+from ragas.llms import LangchainLLMWrapper
 from ragas.llms.prompt import Prompt
 
 noun_extractor = Prompt(
@@ -55,7 +55,7 @@ examples=[{
 )
 
 openai_model = ChatOpenAI(model_name="gpt-4")
-openai_model = LangchainLLM(llm=openai_model)
+openai_model = LangchainLLMWrapper(llm=openai_model)
 ```
 
 Prompt adaption is done using the `.adapt` method: 
diff --git a/docs/howtos/applications/use_prompt_adaptation.md b/docs/howtos/applications/use_prompt_adaptation.md
index 5e2eb408e..e087a9fa9 100644
--- a/docs/howtos/applications/use_prompt_adaptation.md
+++ b/docs/howtos/applications/use_prompt_adaptation.md
@@ -46,6 +46,11 @@ The prompts belonging to respective metrics will be now automatically adapted to
 
 Let’s inspect the adapted prompt belonging to the answer correctness metric
 
+```{note}
+When adapting prompts, it is recommended to review them manually prior to evaluation, as language models may introduce errors during translation
+````
+
+
 ```{code-block} python
 print(answer_correctness.correctness_prompt.to_string())
 ```