Refactor validation logic into JsonService

Moved model and search validation logic from app_kernel.py into JsonService, consolidating related methods and removing redundant service classes. Updated endpoints to use JsonService for model and search validation, and improved configuration handling. Added DATASET_PATH to .env.example.

Author: Fr4nc3

src/backend/app_kernel.py

@@ -39,8 +39,6 @@
     TeamConfiguration,
 )
 from services.json_service import JsonService
-from services.model_validation_service import ModelValidationService
-from services.search_validation_service import SearchValidationService
 
 
 # Updated import for KernelArguments
@@ -1565,17 +1563,6 @@ async def upload_team_config_endpoint(request: Request, file: UploadFile = File(
     responses:
       200:
         description: Team configuration uploaded successfully
-        schema:
-          type: object
-          properties:
-            status:
-              type: string
-            config_id:
-              type: string
-            team_id:
-              type: string
-            name:
-              type: string
       400:
         description: Invalid request or file format
       401:
@@ -1611,7 +1598,6 @@ async def upload_team_config_endpoint(request: Request, file: UploadFile = File(
         # Validate content with RAI before processing
         rai_valid, rai_error = await rai_validate_team_config(json_data)
         if not rai_valid:
-            # Track RAI validation failure
             track_event_if_configured(
                 "Team configuration RAI validation failed",
                 {
@@ -1623,29 +1609,24 @@ async def upload_team_config_endpoint(request: Request, file: UploadFile = File(
             )
             raise HTTPException(status_code=400, detail=rai_error)
 
-        # Track successful RAI validation
         track_event_if_configured(
             "Team configuration RAI validation passed",
-            {
-                "status": "passed",
-                "user_id": user_id,
-                "filename": file.filename,
-            },
+            {"status": "passed", "user_id": user_id, "filename": file.filename},
         )
 
+        # Initialize memory store and service
+        kernel, memory_store = await initialize_runtime_and_context("", user_id)
+        json_service = JsonService(memory_store)
+
         # Validate model deployments
-        model_validator = ModelValidationService()
-        models_valid, missing_models = await model_validator.validate_team_models(
+        models_valid, missing_models = await json_service.validate_team_models(
             json_data
         )
-
         if not models_valid:
             error_message = (
                 f"The following required models are not deployed in your Azure AI project: {', '.join(missing_models)}. "
                 f"Please deploy these models in Azure AI Foundry before uploading this team configuration."
             )
-
-            # Track model validation failure
             track_event_if_configured(
                 "Team configuration model validation failed",
                 {
@@ -1655,32 +1636,22 @@ async def upload_team_config_endpoint(request: Request, file: UploadFile = File(
                     "missing_models": missing_models,
                 },
             )
-
             raise HTTPException(status_code=400, detail=error_message)
 
-        # Track successful model validation
         track_event_if_configured(
             "Team configuration model validation passed",
-            {
-                "status": "passed",
-                "user_id": user_id,
-                "filename": file.filename,
-            },
+            {"status": "passed", "user_id": user_id, "filename": file.filename},
         )
 
         # Validate search indexes
-        search_validator = SearchValidationService()
-        search_valid, search_errors = (
-            await search_validator.validate_team_search_indexes(json_data)
+        search_valid, search_errors = await json_service.validate_team_search_indexes(
+            json_data
         )
-
         if not search_valid:
             error_message = (
                 f"Search index validation failed:\n\n{chr(10).join([f'• {error}' for error in search_errors])}\n\n"
                 f"Please ensure all referenced search indexes exist in your Azure AI Search service."
             )
-
-            # Track search validation failure
             track_event_if_configured(
                 "Team configuration search validation failed",
                 {
@@ -1690,23 +1661,13 @@ async def upload_team_config_endpoint(request: Request, file: UploadFile = File(
                     "search_errors": search_errors,
                 },
             )
-
             raise HTTPException(status_code=400, detail=error_message)
 
-        # Track successful search validation
         track_event_if_configured(
             "Team configuration search validation passed",
-            {
-                "status": "passed",
-                "user_id": user_id,
-                "filename": file.filename,
-            },
+            {"status": "passed", "user_id": user_id, "filename": file.filename},
         )
 
-        # Initialize memory store and service
-        kernel, memory_store = await initialize_runtime_and_context("", user_id)
-        json_service = JsonService(memory_store)
-
         # Validate and parse the team configuration
         try:
             team_config = await json_service.validate_and_parse_team_config(
@@ -1723,7 +1684,6 @@ async def upload_team_config_endpoint(request: Request, file: UploadFile = File(
                 status_code=500, detail=f"Failed to save configuration: {str(e)}"
             )
 
-        # Track the event
         track_event_if_configured(
             "Team configuration uploaded",
             {
@@ -1745,10 +1705,8 @@ async def upload_team_config_endpoint(request: Request, file: UploadFile = File(
         }
 
     except HTTPException:
-        # Re-raise HTTP exceptions
         raise
     except Exception as e:
-        # Log and return generic error for unexpected exceptions
         logging.error(f"Unexpected error uploading team configuration: {str(e)}")
         raise HTTPException(status_code=500, detail="Internal server error occurred")
 
@@ -2006,12 +1964,10 @@ async def get_model_deployments_endpoint(request: Request):
         )
 
     try:
-        model_validator = ModelValidationService()
-        deployments = await model_validator.list_model_deployments()
-        summary = await model_validator.get_deployment_status_summary()
-
+        json_service = JsonService()
+        deployments = await json_service.list_model_deployments()
+        summary = await json_service.get_deployment_status_summary()
         return {"deployments": deployments, "summary": summary}
-
     except Exception as e:
         logging.error(f"Error retrieving model deployments: {str(e)}")
         raise HTTPException(status_code=500, detail="Internal server error occurred")
@@ -2040,11 +1996,9 @@ async def get_search_indexes_endpoint(request: Request):
         )
 
     try:
-        search_validator = SearchValidationService()
-        summary = await search_validator.get_search_index_summary()
-
+        json_service = JsonService()
+        summary = await json_service.get_search_index_summary()
         return {"search_summary": summary}
-
     except Exception as e:
         logging.error(f"Error retrieving search indexes: {str(e)}")
         raise HTTPException(status_code=500, detail="Internal server error occurred")