fixed linting issues

backend/modules/nlp/api.py

@@ -11,7 +11,6 @@ from modules.auth.models import User
 from modules.nlp.service import process_request, ask_ai, save_chat_message, get_chat_history, MessageSender
 # Import the response schema and the new ChatMessage model for response type hinting
 from modules.nlp.schemas import ProcessCommandRequest, ProcessCommandResponse
-from modules.nlp.models import ChatMessage # Import ChatMessage model
 from modules.calendar.service import create_calendar_event, get_calendar_events, update_calendar_event, delete_calendar_event
 from modules.calendar.models import CalendarEvent
 from modules.calendar.schemas import CalendarEventCreate, CalendarEventUpdate
@@ -19,7 +18,18 @@ from modules.calendar.schemas import CalendarEventCreate, CalendarEventUpdate
 from modules.todo import service as todo_service
 from modules.todo.models import Todo
 from modules.todo.schemas import TodoCreate, TodoUpdate
+from pydantic import BaseModel
+from datetime import datetime
 
+class ChatMessageResponse(BaseModel):
+    id: int
+    sender: MessageSender # Use the enum directly
+    text: str
+    timestamp: datetime
+
+    class Config:
+        from_attributes = True # Allow Pydantic to work with ORM models
+        
 router = APIRouter(prefix="/nlp", tags=["nlp"])
 
 # Helper to format calendar events (expects list of CalendarEvent models)
@@ -217,20 +227,6 @@ def process_command(request_data: ProcessCommandRequest, current_user: User = De
         # ----------------------------------
         return ProcessCommandResponse(responses=[error_response])
 
-# --- New Endpoint for Chat History ---
-# Define a Pydantic schema for the response (optional but good practice)
-from pydantic import BaseModel
-from datetime import datetime
-
-class ChatMessageResponse(BaseModel):
-    id: int
-    sender: MessageSender # Use the enum directly
-    text: str
-    timestamp: datetime
-
-    class Config:
-        from_attributes = True # Allow Pydantic to work with ORM models
-
 @router.get("/history", response_model=List[ChatMessageResponse])
 def read_chat_history(current_user: User = Depends(get_current_user), db: Session = Depends(get_db)):
     """Retrieves the last 50 chat messages for the current user."""

backend/modules/nlp/models.py

@@ -1,6 +1,6 @@
 \
 # /home/cdp/code/MAIA/backend/modules/nlp/models.py
-from sqlalchemy import Column, Integer, String, Text, DateTime, ForeignKey, Enum as SQLEnum
+from sqlalchemy import Column, Integer, Text, DateTime, ForeignKey, Enum as SQLEnum
 from sqlalchemy.orm import relationship
 from sqlalchemy.sql import func
 import enum