diff --git a/scrapegraphai/graphs/abstract_graph.py b/scrapegraphai/graphs/abstract_graph.py
index eb4fee7f..2ae47c41 100644
--- a/scrapegraphai/graphs/abstract_graph.py
+++ b/scrapegraphai/graphs/abstract_graph.py
@@ -47,8 +47,8 @@ class AbstractGraph(ABC):
         self.source = source
         self.config = config
         self.llm_model = self._create_llm(config["llm"], chat=True)
-        self.embedder_model = self._create_default_embedder(
-        ) if "embeddings" not in config else self._create_embedder(
+        self.embedder_model = self._create_default_embedder(    
+            ) if "embeddings" not in config else self._create_embedder(
             config["embeddings"])
 
         # Set common configuration parameters
@@ -61,6 +61,7 @@ class AbstractGraph(ABC):
         self.final_state = None
         self.execution_info = None
 
+
     def _set_model_token(self, llm):
 
         if 'Azure' in str(type(llm)):
@@ -68,7 +69,7 @@ class AbstractGraph(ABC):
                 self.model_token = models_tokens["azure"][llm.model_name]
             except KeyError:
                 raise KeyError("Model not supported")
-
+            
         elif 'HuggingFaceEndpoint' in str(type(llm)):
             if 'mistral' in llm.repo_id:
                 try:
@@ -76,6 +77,7 @@ class AbstractGraph(ABC):
                 except KeyError:
                     raise KeyError("Model not supported")
 
+
     def _create_llm(self, llm_config: dict, chat=False) -> object:
         """
         Create a large language model instance based on the configuration provided.
@@ -101,7 +103,7 @@ class AbstractGraph(ABC):
             if chat:
                 self._set_model_token(llm_params['model_instance'])
             return llm_params['model_instance']
-
+        
         # Instantiate the language model based on the model name
         if "gpt-" in llm_params["model"]:
             try:
@@ -178,7 +180,7 @@ class AbstractGraph(ABC):
         else:
             raise ValueError(
                 "Model provided by the configuration not supported")
-
+    
     def _create_default_embedder(self) -> object:
         """
         Create an embedding model instance based on the chosen llm model.
@@ -209,7 +211,7 @@ class AbstractGraph(ABC):
             return BedrockEmbeddings(client=None, model_id=self.llm_model.model_id)
         else:
             raise ValueError("Embedding Model missing or not supported")
-
+        
     def _create_embedder(self, embedder_config: dict) -> object:
         """
         Create an embedding model instance based on the configuration provided.
@@ -226,7 +228,7 @@ class AbstractGraph(ABC):
 
         if 'model_instance' in embedder_config:
             return embedder_config['model_instance']
-
+        
         # Instantiate the embedding model based on the model name
         if "openai" in embedder_config["model"]:
             return OpenAIEmbeddings(api_key=embedder_config["api_key"])
@@ -241,14 +243,14 @@ class AbstractGraph(ABC):
             except KeyError:
                 raise KeyError("Model not supported")
             return OllamaEmbeddings(**embedder_config)
-
+        
         elif "hugging_face" in embedder_config["model"]:
             try:
                 models_tokens["hugging_face"][embedder_config["model"]]
             except KeyError:
                 raise KeyError("Model not supported")
             return HuggingFaceHubEmbeddings(model=embedder_config["model"])
-
+        
         elif "bedrock" in embedder_config["model"]:
             embedder_config["model"] = embedder_config["model"].split("/")[-1]
             try:
@@ -258,7 +260,7 @@ class AbstractGraph(ABC):
             return BedrockEmbeddings(client=None, model_id=embedder_config["model"])
         else:
             raise ValueError(
-                "Model provided by the configuration not supported")
+                "Model provided by the configuration not supported") 
 
     def get_state(self, key=None) -> dict:
         """""
@@ -282,7 +284,7 @@ class AbstractGraph(ABC):
         Returns:
             dict: The execution information of the graph.
         """
-
+        
         return self.execution_info
 
     @abstractmethod
@@ -298,3 +300,4 @@ class AbstractGraph(ABC):
         Abstract method to execute the graph and return the result.
         """
         pass
+