diff --git a/api/core/model_runtime/model_providers/azure_openai/text_embedding/text_embedding.py b/api/core/model_runtime/model_providers/azure_openai/text_embedding/text_embedding.py
index c45ce87ea7..69d2cfaded 100644
--- a/api/core/model_runtime/model_providers/azure_openai/text_embedding/text_embedding.py
+++ b/api/core/model_runtime/model_providers/azure_openai/text_embedding/text_embedding.py
@@ -92,7 +92,10 @@ class AzureOpenAITextEmbeddingModel(_CommonAzureOpenAI, TextEmbeddingModel):
                 average = embeddings_batch[0]
             else:
                 average = np.average(_result, axis=0, weights=num_tokens_in_batch[i])
-            embeddings[i] = (average / np.linalg.norm(average)).tolist()
+            embedding = (average / np.linalg.norm(average)).tolist()
+            if np.isnan(embedding).any():
+                raise ValueError("Normalized embedding is nan please try again")
+            embeddings[i] = embedding
 
         # calc usage
         usage = self._calc_response_usage(model=model, credentials=credentials, tokens=used_tokens)
diff --git a/api/core/model_runtime/model_providers/cohere/text_embedding/text_embedding.py b/api/core/model_runtime/model_providers/cohere/text_embedding/text_embedding.py
index 5fd4d637be..9e4df27060 100644
--- a/api/core/model_runtime/model_providers/cohere/text_embedding/text_embedding.py
+++ b/api/core/model_runtime/model_providers/cohere/text_embedding/text_embedding.py
@@ -88,7 +88,10 @@ class CohereTextEmbeddingModel(TextEmbeddingModel):
                 average = embeddings_batch[0]
             else:
                 average = np.average(_result, axis=0, weights=num_tokens_in_batch[i])
-            embeddings[i] = (average / np.linalg.norm(average)).tolist()
+            embedding = (average / np.linalg.norm(average)).tolist()
+            if np.isnan(embedding).any():
+                raise ValueError("Normalized embedding is nan please try again")
+            embeddings[i] = embedding
 
         # calc usage
         usage = self._calc_response_usage(model=model, credentials=credentials, tokens=used_tokens)
diff --git a/api/core/model_runtime/model_providers/openai/text_embedding/text_embedding.py b/api/core/model_runtime/model_providers/openai/text_embedding/text_embedding.py
index bec01fe679..9c8c8d5882 100644
--- a/api/core/model_runtime/model_providers/openai/text_embedding/text_embedding.py
+++ b/api/core/model_runtime/model_providers/openai/text_embedding/text_embedding.py
@@ -97,7 +97,10 @@ class OpenAITextEmbeddingModel(_CommonOpenAI, TextEmbeddingModel):
                 average = embeddings_batch[0]
             else:
                 average = np.average(_result, axis=0, weights=num_tokens_in_batch[i])
-            embeddings[i] = (average / np.linalg.norm(average)).tolist()
+            embedding = (average / np.linalg.norm(average)).tolist()
+            if np.isnan(embedding).any():
+                raise ValueError("Normalized embedding is nan please try again")
+            embeddings[i] = embedding
 
         # calc usage
         usage = self._calc_response_usage(model=model, credentials=credentials, tokens=used_tokens)
diff --git a/api/core/model_runtime/model_providers/upstage/text_embedding/text_embedding.py b/api/core/model_runtime/model_providers/upstage/text_embedding/text_embedding.py
index 7dd495b55e..5b340e53bb 100644
--- a/api/core/model_runtime/model_providers/upstage/text_embedding/text_embedding.py
+++ b/api/core/model_runtime/model_providers/upstage/text_embedding/text_embedding.py
@@ -100,7 +100,10 @@ class UpstageTextEmbeddingModel(_CommonUpstage, TextEmbeddingModel):
                 average = embeddings_batch[0]
             else:
                 average = np.average(_result, axis=0, weights=num_tokens_in_batch[i])
-            embeddings[i] = (average / np.linalg.norm(average)).tolist()
+            embedding = (average / np.linalg.norm(average)).tolist()
+            if np.isnan(embedding).any():
+                raise ValueError("Normalized embedding is nan please try again")
+            embeddings[i] = embedding
 
         usage = self._calc_response_usage(model=model, credentials=credentials, tokens=used_tokens)
 
diff --git a/api/core/rag/embedding/cached_embedding.py b/api/core/rag/embedding/cached_embedding.py
index 652f7e145f..8ddda7e983 100644
--- a/api/core/rag/embedding/cached_embedding.py
+++ b/api/core/rag/embedding/cached_embedding.py
@@ -116,6 +116,8 @@ class CacheEmbedding(Embeddings):
 
             embedding_results = embedding_result.embeddings[0]
             embedding_results = (embedding_results / np.linalg.norm(embedding_results)).tolist()
+            if np.isnan(embedding_results).any():
+                raise ValueError("Normalized embedding is nan please try again")
         except Exception as ex:
             if dify_config.DEBUG:
                 logging.exception(f"Failed to embed query text '{text[:10]}...({len(text)} chars)'")