feat: optimization calls (#2417)

# Description

Please include a summary of the changes and the related issue. Please
also include relevant motivation and context.

## Checklist before requesting a review

Please delete options that are not relevant.

- [ ] My code follows the style guidelines of this project
- [ ] I have performed a self-review of my code
- [ ] I have commented hard-to-understand areas
- [ ] I have ideally added tests that prove my fix is effective or that
my feature works
- [ ] New and existing unit tests pass locally with my changes
- [ ] Any dependent changes have been merged

## Screenshots (if appropriate):

backend/modules/brain/entity/integration_brain.py

@@ -10,6 +10,7 @@ class IntegrationType(str, Enum):
     SYNC = "sync"
     DOC = "doc"
 
+
 class IntegrationBrainTag(str, Enum):
     NEW = "new"
     RECOMMENDED = "recommended"

backend/modules/brain/service/brain_service.py

@@ -59,9 +59,7 @@ class BrainService:
         return self.brain_repository.get_brain_by_id(brain_id)
 
     def get_integration_brain(self, brain_id) -> IntegrationEntity | None:
-        return self.integration_brains_repository.get_integration_brain(
-            brain_id
-        )
+        return self.integration_brains_repository.get_integration_brain(brain_id)
 
     def find_brain_from_question(
         self,
@@ -105,6 +103,7 @@ class BrainService:
         if brain_id_to_use and not brain_to_use:
             brain_to_use = self.get_brain_by_id(brain_id_to_use)
 
+        else:
             # Calculate the closest brains to the question
             list_brains = vector_store.find_brain_closest_query(user.id, question)
 
@@ -323,7 +322,9 @@ class BrainService:
     def update_brain_last_update_time(self, brain_id: UUID):
         self.brain_repository.update_brain_last_update_time(brain_id)
 
-    def get_brain_details(self, brain_id: UUID, user_id: UUID = None) -> BrainEntity | None:
+    def get_brain_details(
+        self, brain_id: UUID, user_id: UUID = None
+    ) -> BrainEntity | None:
         brain = self.brain_repository.get_brain_details(brain_id)
         if brain == None:
             return None
@@ -335,7 +336,7 @@ class BrainService:
                 )
             )
 
-            if (brain.integration):
+            if brain.integration:
                 brain.integration_description = (
                     self.integration_description_repository.get_integration_description(
                         brain.integration.integration_id

backend/modules/chat/controller/chat_routes.py

@@ -61,7 +61,6 @@ def get_answer_generator(
     current_user: UserIdentity,
 ):
     chat_instance = BrainfulChat()
-    chat_instance.validate_authorization(user_id=current_user.id, brain_id=brain_id)
 
     user_usage = UserUsage(
         id=current_user.id,
@@ -247,11 +246,6 @@ async def create_stream_question_handler(
     chat_instance = BrainfulChat()
     chat_instance.validate_authorization(user_id=current_user.id, brain_id=brain_id)
 
-    user_usage = UserUsage(
-        id=current_user.id,
-        email=current_user.email,
-    )
-
     logger.info(
         f"Creating question for chat {chat_id} with brain {brain_id} of type {type(brain_id)}"
     )

backend/modules/user/controller/user_controller.py

@@ -1,10 +1,7 @@
-import time
-
 from fastapi import APIRouter, Depends, Request
 from middlewares.auth import AuthBearer, get_current_user
 from models import UserUsage
 from modules.brain.service.brain_user_service import BrainUserService
-from modules.brain.service.brain_vector_service import BrainVectorService
 from modules.user.dto.inputs import UserUpdatableProperties
 from modules.user.entity.user_identity import UserIdentity
 from modules.user.repository.users import Users
@@ -37,26 +34,16 @@ async def get_user_endpoint(
     user_settings = user_daily_usage.get_user_settings()
     max_brain_size = user_settings.get("max_brain_size", 1000000000)
 
-    date = time.strftime("%Y%m%d")
     monthly_chat_credit = user_settings.get("monthly_chat_credit", 10)
 
     user_daily_usage = UserUsage(id=current_user.id)
-    requests_stats = user_daily_usage.get_user_usage()
-    default_brain = brain_user_service.get_user_default_brain(current_user.id)
-
-    if default_brain:
-        defaul_brain_size = BrainVectorService(default_brain.brain_id).brain_size
-    else:
-        defaul_brain_size = 0
 
     return {
         "email": current_user.email,
         "max_brain_size": max_brain_size,
-        "current_brain_size": defaul_brain_size,
+        "current_brain_size": 0,
         "monthly_chat_credit": monthly_chat_credit,
-        "requests_stats": requests_stats,
         "models": user_settings.get("models", []),
-        "date": date,
         "id": current_user.id,
         "is_premium": user_settings["is_premium"],
     }

frontend/app/App.tsx

@@ -39,7 +39,7 @@ if (
 
 // This wrapper is used to make effect calls at a high level in app rendering.
 const App = ({ children }: PropsWithChildren): JSX.Element => {
-  const { fetchAllBrains, fetchPublicPrompts } = useBrainContext();
+  const { fetchAllBrains } = useBrainContext();
   const { onClickOutside } = useOutsideClickListener();
   const { session } = useSupabase();
 
@@ -49,7 +49,6 @@ const App = ({ children }: PropsWithChildren): JSX.Element => {
     if (session?.user) {
       void fetchAllBrains();
 
-      void fetchPublicPrompts();
       posthog.identify(session.user.id, { email: session.user.email });
       posthog.startSessionRecording();
     }