Rename cognify_text to cognify and update response model class name t…

…o ResponseBody

cognee/api/v1/responses/default_tools.py

@@ -37,7 +37,7 @@
     },
     {
         "type": "function",
-        "name": "cognify_text",
+        "name": "cognify",
         "description": "Convert text into a knowledge graph or process all added content",
         "parameters": {
             "type": "object",
@@ -46,13 +46,9 @@
                     "type": "string",
                     "description": "Text content to be converted into a knowledge graph",
                 },
-                "graph_model_name": {
+                "ontology_file_path": {
                     "type": "string",
-                    "description": "Name of the graph model to use",
-                },
-                "graph_model_file": {
-                    "type": "string",
-                    "description": "Path to a custom graph model file",
+                    "description": "Path to a custom ontology file",
                 },
             },
             "required": ["text"],

cognee/api/v1/responses/dispatch_function.py

@@ -36,7 +36,7 @@ async def dispatch_function(tool_call: Union[ToolCall, Dict[str, Any]]) -> str:
 
     if function_name == "search":
         return await handle_search(arguments, user)
-    elif function_name == "cognify_text":
+    elif function_name == "cognify":
         return await handle_cognify(arguments, user)
     elif function_name == "prune":
         return await handle_prune(arguments, user)
@@ -87,12 +87,12 @@ async def handle_search(arguments: Dict[str, Any], user) -> list:
 async def handle_cognify(arguments: Dict[str, Any], user) -> str:
     """Handle cognify function call"""
     text = arguments.get("text")
-    graph_model_file = arguments.get("graph_model_file")
+    ontology_file_path = arguments.get("ontology_file_path")
 
     if text:
         await add(data=text, user=user)
 
-    await cognify(user=user, ontology_file_path=graph_model_file if graph_model_file else None)
+    await cognify(user=user, ontology_file_path=ontology_file_path if ontology_file_path else None)
 
     return (
         "Text successfully converted into knowledge graph."

cognee/api/v1/responses/models.py

@@ -89,7 +89,7 @@ class ResponseToolCall(BaseModel):
     output: Optional[ToolCallOutput] = None
 
 
-class ResponseResponse(OutDTO):
+class ResponseBody(OutDTO):
     """Response body for the new responses endpoint"""
 
     id: str = Field(default_factory=lambda: f"resp_{uuid.uuid4().hex}")

cognee/api/v1/responses/routers/default_tools.py

@@ -37,7 +37,7 @@
     },
     {
         "type": "function",
-        "name": "cognify_text",
+        "name": "cognify",
         "description": "Convert text into a knowledge graph or process all added content",
         "parameters": {
             "type": "object",

cognee/api/v1/responses/routers/get_responses_router.py

@@ -9,7 +9,7 @@
 from fastapi import APIRouter, Depends
 from cognee.api.v1.responses.models import (
     ResponseRequest,
-    ResponseResponse,
+    ResponseBody,
     ResponseToolCall,
     ChatUsage,
     FunctionCall,
@@ -68,11 +68,11 @@ async def call_openai_api_for_model(
         logger.info(f"Response: {response}")
         return response.model_dump()
 
-    @router.post("/", response_model=ResponseResponse)
+    @router.post("/", response_model=ResponseBody)
     async def create_response(
         request: ResponseRequest,
         user: User = Depends(get_authenticated_user),
-    ) -> ResponseResponse:
+    ) -> ResponseBody:
         """
         OpenAI-compatible responses endpoint with function calling support
         """
@@ -133,7 +133,7 @@ async def create_response(
         usage = response.get("usage", {})
 
         # Create the response object with all processed tool calls
-        response_obj = ResponseResponse(
+        response_obj = ResponseBody(
             id=response_id,
             model=request.model,
             tool_calls=processed_tool_calls,

notebooks/cognee_openai_compatable_demo.ipynb

@@ -33,7 +33,7 @@
     {
      "data": {
       "text/plain": [
-       "Response(id='resp_6815e775ed1c8191a7c9e5cd7d18dd6d01678e9c98ad3fea', created_at=None, error=None, incomplete_details=None, instructions=None, metadata=None, model='cognee-v1', object='response', output=None, parallel_tool_calls=None, temperature=None, tool_choice=None, tools=None, top_p=None, max_output_tokens=None, previous_response_id=None, reasoning=None, status='completed', text=None, truncation=None, usage=ResponseUsage(input_tokens=None, output_tokens=None, output_tokens_details=None, total_tokens=242, prompt_tokens=207, completion_tokens=35), user=None, created=1746266008, toolCalls=[{'id': 'call_VPk6HLbJClOEeznVbLe5l5zJ', 'type': 'function', 'function': {'name': 'cognify_text', 'arguments': '{\"text\":\"Natural language processing (NLP) is an interdisciplinary subfield of computer science and information retrieval.\"}'}, 'output': {'status': 'success', 'data': {'result': 'Text successfully converted into knowledge graph.'}}}])"
+       "Response(id='resp_6815e775ed1c8191a7c9e5cd7d18dd6d01678e9c98ad3fea', created_at=None, error=None, incomplete_details=None, instructions=None, metadata=None, model='cognee-v1', object='response', output=None, parallel_tool_calls=None, temperature=None, tool_choice=None, tools=None, top_p=None, max_output_tokens=None, previous_response_id=None, reasoning=None, status='completed', text=None, truncation=None, usage=ResponseUsage(input_tokens=None, output_tokens=None, output_tokens_details=None, total_tokens=242, prompt_tokens=207, completion_tokens=35), user=None, created=1746266008, toolCalls=[{'id': 'call_VPk6HLbJClOEeznVbLe5l5zJ', 'type': 'function', 'function': {'name': 'cognify', 'arguments': '{\"text\":\"Natural language processing (NLP) is an interdisciplinary subfield of computer science and information retrieval.\"}'}, 'output': {'status': 'success', 'data': {'result': 'Text successfully converted into knowledge graph.'}}}])"
       ]
      },
      "execution_count": 29,