fix: Fixes the route input schemas for repos & guidelines (#25)

* fix: Fixes schemas

* fix: Fix router doc

* refactor: Refactors args

src/app/api/api_v1/router.py

@@ -9,7 +9,7 @@
 
 api_router = APIRouter()
 api_router.include_router(login.router, prefix="/login", tags=["login"])
-api_router.include_router(users.router, prefix="/users", tags=["access"])
+api_router.include_router(users.router, prefix="/users", tags=["users"])
 api_router.include_router(repos.router, prefix="/repos", tags=["repos"])
 api_router.include_router(guidelines.router, prefix="/guidelines", tags=["guidelines"])
 api_router.include_router(compute.router, prefix="/compute", tags=["compute"])

src/app/schemas/guidelines.py

@@ -7,8 +7,6 @@
 
 from pydantic import BaseModel, Field
 
-from app.schemas.base import _CreatedAt
-
 __all__ = ["GuidelineCreate", "GuidelineEdit", "ContentUpdate", "OrderUpdate"]
 
 
@@ -17,9 +15,8 @@ class GuidelineEdit(BaseModel):
     details: str = Field(..., min_length=6, max_length=1000)
 
 
-class GuidelineCreate(_CreatedAt, GuidelineEdit):
+class GuidelineCreate(GuidelineEdit):
     repo_id: int = Field(..., gt=0)
-    updated_at: datetime = Field(default_factory=datetime.utcnow, nullable=False)
     order: int = Field(..., ge=0, nullable=False)
 
 

src/app/schemas/repos.py

@@ -16,7 +16,6 @@
 class RepoCreate(_Id):
     owner_id: int = Field(..., gt=0)
     full_name: str = Field(..., example="frgfm/torch-cam")
-    installed_at: datetime = Field(default_factory=datetime.utcnow, nullable=False)
 
 
 class RepoCreation(RepoCreate):

src/app/services/openai.py

@@ -108,7 +108,11 @@ def __init__(
         )
 
     def analyze_multi(
-        self, code: str, guidelines: List[Guideline], timeout: int = 10, mode: ExecutionMode = ExecutionMode.SINGLE
+        self,
+        code: str,
+        guidelines: List[Guideline],
+        mode: ExecutionMode = ExecutionMode.SINGLE,
+        **kwargs: Any,
     ) -> List[ComplianceResult]:
         # Check args before sending a request
         if len(code) == 0 or len(guidelines) == 0 or any(len(guideline.details) == 0 for guideline in guidelines):
@@ -121,15 +125,19 @@ def analyze_multi(
                 MULTI_PROMPT,
                 {"code": code, "guidelines": [guideline.details for guideline in guidelines]},
                 MULTI_SCHEMA,
-                timeout,
+                **kwargs,
             )["result"]
             if len(parsed_response) != len(guidelines):
                 raise HTTPException(status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, detail="Invalid model response")
         elif mode == ExecutionMode.MULTI:
             with ThreadPoolExecutor() as executor:
                 tasks = [
                     executor.submit(
-                        self._analyze, MONO_PROMPT, {"code": code, "guideline": guideline.details}, MONO_SCHEMA, timeout
+                        self._analyze,
+                        MONO_PROMPT,
+                        {"code": code, "guideline": guideline.details},
+                        MONO_SCHEMA,
+                        **kwargs,
                     )
                     for guideline in guidelines
                 ]
@@ -145,17 +153,17 @@ def analyze_multi(
             for guideline, res in zip(guidelines, parsed_response)
         ]
 
-    def analyze_mono(self, code: str, guideline: Guideline, timeout: int = 10) -> ComplianceResult:
+    def analyze_mono(self, code: str, guideline: Guideline, **kwargs: Any) -> ComplianceResult:
         # Check args before sending a request
         if len(code) == 0 or len(guideline.details) == 0:
             raise HTTPException(
                 status_code=status.HTTP_422_UNPROCESSABLE_ENTITY, detail="No code or guideline provided for analysis."
             )
-        res = self._analyze(MONO_PROMPT, {"code": code, "guideline": guideline.details}, MONO_SCHEMA, timeout)
+        res = self._analyze(MONO_PROMPT, {"code": code, "guideline": guideline.details}, MONO_SCHEMA, **kwargs)
         # Return with pydantic validation
         return ComplianceResult(guideline_id=guideline.id, **res)
 
-    def _analyze(self, prompt: str, payload: Dict[str, Any], schema: ObjectSchema, timeout: int = 10) -> Dict[str, Any]:
+    def _analyze(self, prompt: str, payload: Dict[str, Any], schema: ObjectSchema, timeout: int = 20) -> Dict[str, Any]:
         # Prepare the request
         _payload = ChatCompletion(
             model=self.model,