diff --git a/app/core/config.py b/app/core/config.py
index c7425f1..3ba1998 100644
--- a/app/core/config.py
+++ b/app/core/config.py
@@ -95,7 +95,6 @@ def get_settings() -> Settings:
     return Settings()
 
 
-# Create settings instance
 settings = get_settings()
 
 # Set environment variables for third-party libraries
diff --git a/app/main.py b/app/main.py
index f303ca2..3d95da2 100644
--- a/app/main.py
+++ b/app/main.py
@@ -11,33 +11,32 @@ from app.services.vector_stores import PGVectorStore
 
 logger = get_logger()
 
-# Load environment variables from .env file
 load_dotenv()
 
-# Dictionary to hold our application state, including the RAG service instance
 app_state = {}
 
 
 @asynccontextmanager
-async def lifespan(app: FastAPI):
+async def lifespan(app: FastAPI):  # noqa: ARG001
     config_service = ConfigService()
     await config_service.initialize_models()
     app_state["config_service"] = config_service
 
-    # This code runs on startup
     logger.info("Application starting up...")
-    # Initialize the RAG Service and store it in the app_state
+    embedding_model = config_service.get_current_embedding_model()
+    reranker = config_service.get_current_reranker_model()
+    if embedding_model is None:
+        raise RuntimeError("Embedding model failed to initialize")
     app_state["rag_service"] = RAGService(
-        embedding_model=config_service.get_current_embedding_model(),
+        embedding_model=embedding_model,
         vector_db=PGVectorStore(),
-        reranker=config_service.get_current_reranker_model(),
+        reranker=reranker,
     )
     yield
 
 
 app = FastAPI(lifespan=lifespan)
 
-# Include the API router
 app.include_router(endpoints.router)
 
 
diff --git a/app/schemas/enums.py b/app/schemas/enums.py
new file mode 100644
index 0000000..acfc3bb
--- /dev/null
+++ b/app/schemas/enums.py
@@ -0,0 +1,9 @@
+from enum import Enum
+
+
+class EmbeddingModelName(str, Enum):
+    MiniLMEmbeddingModel = "MiniLMEmbeddingModel"
+
+
+class RerankerModelName(str, Enum):
+    MiniLMReranker = "MiniLMReranker"
diff --git a/app/services/config_service.py b/app/services/config_service.py
index d7d06a5..f9a8470 100644
--- a/app/services/config_service.py
+++ b/app/services/config_service.py
@@ -3,6 +3,7 @@ import logging
 from app.core.config import settings
 from app.core.interfaces import EmbeddingModel, Reranker
 from app.core.registry import embedding_model_registry, reranker_registry
+from app.schemas.enums import EmbeddingModelName, RerankerModelName
 from app.services.embedding_providers import MiniLMEmbeddingModel
 from app.services.rerankers import MiniLMReranker
 
@@ -26,24 +27,41 @@ class ConfigService:
         reranker_registry.register("MiniLMReranker", MiniLMReranker)
 
     async def initialize_models(self):
+        """
+        Initialize embedding and reranker mode,
+        if not a valid name then fallback to default one.
+        Will get call on first time starting the app.
+        """
         logger.info("Initializing default models...")
-        # Initialize default embedding model
-        default_embedding_model_name = settings.EMBEDDING_MODEL
-        await self.set_embedding_model(default_embedding_model_name)
-        logger.info(
-            "Default embedding model initialized: %s", default_embedding_model_name
-        )
+        embedding_model_name = settings.EMBEDDING_MODEL
+        if embedding_model_name not in EmbeddingModelName.__members__:
+            logger.warning(
+                "Embedding model '%s' is not valid. Falling back to default '%s'",
+                embedding_model_name,
+                EmbeddingModelName.MiniLMEmbeddingModel.value,
+            )
+            embedding_model_name = (
+                EmbeddingModelName.MiniLMEmbeddingModel.value
+            )  # use minilm as default
+        await self.set_embedding_model(embedding_model_name)
+        logger.info("Default embedding model initialized: %s", embedding_model_name)
 
-        # Initialize default reranker model (if any)
-        # Assuming a default reranker can be set in settings if needed
-        # For now, let's assume MiniLMReranker is the default if not specified
-        default_reranker_model_name = "MiniLMReranker"  # Or from settings
-        await self.set_reranker_model(default_reranker_model_name)
-        logger.info(
-            "Default reranker model initialized: %s", default_reranker_model_name
+        reranker_model_name = (
+            getattr(settings, "RERANKER_MODEL", None)
+            or RerankerModelName.MiniLMReranker.value
         )
+        if reranker_model_name not in RerankerModelName.__members__:
+            logger.warning(
+                "Reranker model '%s' is not valid. Falling back to default '%s'",
+                reranker_model_name,
+                RerankerModelName.MiniLMReranker.value,
+            )
+            reranker_model_name = RerankerModelName.MiniLMReranker.value
+        await self.set_reranker_model(reranker_model_name)
+        logger.info("Default reranker model initialized: %s", reranker_model_name)
 
     async def set_embedding_model(self, model_name: str) -> str:
+        """Set system embedding model based on provide model_name"""
         if (
             self._current_embedding_model
             and self._current_embedding_model.__class__.__name__ == model_name
@@ -75,6 +93,7 @@ class ConfigService:
             self._loading_status["embedding_model"] = False
 
     async def set_reranker_model(self, model_name: str) -> str:
+        """Set system reranker model based on provide model_name"""
         if (
             self._current_reranker_model
             and self._current_reranker_model.__class__.__name__ == model_name