diff --git a/cognitive_architecture/modules/cognify/llm/classify_content.py b/cognitive_architecture/modules/cognify/llm/classify_content.py
index 7561eabfe..8b9a30eb1 100644
--- a/cognitive_architecture/modules/cognify/llm/classify_content.py
+++ b/cognitive_architecture/modules/cognify/llm/classify_content.py
@@ -13,3 +13,8 @@ async def content_to_cog_layers(text_input: str,system_prompt_path:str, response
     return await llm_client.acreate_structured_output(text_input,system_prompt_path, response_model)
 
 
+if __name__ == "__main__":
+
+    content_to_cog_layers("test", "test", ContentPrediction)
+
+
diff --git a/cognitive_architecture/modules/cognify/llm/content_to_cog_layers.py b/cognitive_architecture/modules/cognify/llm/content_to_cog_layers.py
index 6ceada36e..5aa1ce5e6 100644
--- a/cognitive_architecture/modules/cognify/llm/content_to_cog_layers.py
+++ b/cognitive_architecture/modules/cognify/llm/content_to_cog_layers.py
@@ -1,7 +1,7 @@
 from typing import Type
 from pydantic import BaseModel
 from cognitive_architecture.infrastructure.llm.get_llm_client import get_llm_client
-
+from cognitive_architecture.shared.data_models import CognitiveLayer
 
 async def content_to_cog_layers(text_input: str,system_prompt_path:str, response_model: Type[BaseModel]):
     llm_client = get_llm_client()
@@ -12,6 +12,10 @@ async def content_to_cog_layers(text_input: str,system_prompt_path:str, response
 
     return await llm_client.acreate_structured_output(text_input,system_prompt_path, response_model)
 
+if __name__ == "__main__":
+
+    content_to_cog_layers("test", "test", response_model=CognitiveLayer)
+
 
 
 
diff --git a/cognitive_architecture/modules/cognify/llm/content_to_propositions.py b/cognitive_architecture/modules/cognify/llm/content_to_propositions.py
index b91a1ed71..6e3c36a4f 100644
--- a/cognitive_architecture/modules/cognify/llm/content_to_propositions.py
+++ b/cognitive_architecture/modules/cognify/llm/content_to_propositions.py
@@ -2,10 +2,15 @@
 from typing import Type
 from pydantic import BaseModel
 from cognitive_architecture.infrastructure.llm.get_llm_client import get_llm_client
-
+from cognitive_architecture.shared.data_models import KnowledgeGraph
 
 async def generate_graph(text_input:str,system_prompt_path:str, response_model: Type[BaseModel]):
     doc_path = "cognitive_architecture/infrastructure/llm/prompts/generate_graph_prompt.txt"
     llm_client = get_llm_client()
+
     return await llm_client.generate_graph(text_input,system_prompt_path, response_model)
 
+
+if __name__ == "__main__":
+    generate_graph("test", "test", response_model=KnowledgeGraph)
+
diff --git a/cognitive_architecture/shared/data_models.py b/cognitive_architecture/shared/data_models.py
index 928fcf26a..2cfc7e92e 100644
--- a/cognitive_architecture/shared/data_models.py
+++ b/cognitive_architecture/shared/data_models.py
@@ -166,3 +166,16 @@ class ContentPrediction(BaseModel):
 
     label: Union[TextContent, AudioContent, ImageContent, VideoContent, MultimediaContent, Model3DContent, ProceduralContent]
 
+
+class CognitiveLayerSubgroup(BaseModel):
+    """ CognitiveLayerSubgroup in a general layer """
+    id: int
+    name:str
+    description: str
+
+
+class CognitiveLayer(BaseModel):
+    """Cognitive  layer"""
+    category_name:str
+    cognitive_layers: List[CognitiveLayerSubgroup] = Field(..., default_factory=list)
+