diff --git a/src/ragas/metrics/_answer_relevance.py b/src/ragas/metrics/_answer_relevance.py
index f4cc2b10e..03b6ea4f9 100644
--- a/src/ragas/metrics/_answer_relevance.py
+++ b/src/ragas/metrics/_answer_relevance.py
@@ -95,7 +95,9 @@ class ResponseRelevancy(MetricWithLLM, MetricWithEmbeddings, SingleTurnMetric):
     strictness: int = 3
 
     def calculate_similarity(self, question: str, generated_questions: list[str]):
-        assert self.embeddings is not None
+        assert (
+            self.embeddings is not None
+        ), f"Error: '{self.name}' requires embeddings to be set."
         question_vec = np.asarray(self.embeddings.embed_query(question)).reshape(1, -1)
         gen_question_vec = np.asarray(
             self.embeddings.embed_documents(generated_questions)
diff --git a/src/ragas/metrics/_answer_similarity.py b/src/ragas/metrics/_answer_similarity.py
index 67bd2c546..061c221ec 100644
--- a/src/ragas/metrics/_answer_similarity.py
+++ b/src/ragas/metrics/_answer_similarity.py
@@ -65,7 +65,9 @@ async def _single_turn_ascore(
         return await self._ascore(row, callbacks)
 
     async def _ascore(self, row: t.Dict, callbacks: Callbacks) -> float:
-        assert self.embeddings is not None, "embeddings must be set"
+        assert (
+            self.embeddings is not None
+        ), f"Error: '{self.name}' requires embeddings to be set."
 
         ground_truth = t.cast(str, row["reference"])
         answer = t.cast(str, row["response"])