diff --git a/dataherald/services/sql_generations.py b/dataherald/services/sql_generations.py
index b1890443..413101ca 100644
--- a/dataherald/services/sql_generations.py
+++ b/dataherald/services/sql_generations.py
@@ -63,9 +63,9 @@ def update_the_initial_sql_generation(
         initial_sql_generation.intermediate_steps = sql_generation.intermediate_steps
         return self.sql_generation_repository.update(initial_sql_generation)
 
-    def create(
+    def create(  # noqa: PLR0912
         self, prompt_id: str, sql_generation_request: SQLGenerationRequest
-    ) -> SQLGeneration:
+    ) -> SQLGeneration:  # noqa: PLR0912
         initial_sql_generation = SQLGeneration(
             prompt_id=prompt_id,
             created_at=datetime.now(),
diff --git a/dataherald/sql_generator/__init__.py b/dataherald/sql_generator/__init__.py
index e997920e..6612332b 100644
--- a/dataherald/sql_generator/__init__.py
+++ b/dataherald/sql_generator/__init__.py
@@ -179,7 +179,7 @@ def generate_response(
         """Generates a response to a user question."""
         pass
 
-    def stream_agent_steps(  # noqa: C901
+    def stream_agent_steps(  # noqa: PLR0912, C901
         self,
         question: str,
         agent_executor: AgentExecutor,
@@ -187,7 +187,7 @@ def stream_agent_steps(  # noqa: C901
         sql_generation_repository: SQLGenerationRepository,
         queue: Queue,
         metadata: dict = None,
-    ):
+    ):  # noqa: PLR0912
         try:
             with get_openai_callback() as cb:
                 for chunk in agent_executor.stream(
diff --git a/dataherald/sql_generator/dataherald_finetuning_agent.py b/dataherald/sql_generator/dataherald_finetuning_agent.py
index 536a4e17..fe54dcf4 100644
--- a/dataherald/sql_generator/dataherald_finetuning_agent.py
+++ b/dataherald/sql_generator/dataherald_finetuning_agent.py
@@ -595,7 +595,7 @@ def generate_response(
                 f"Finetuning should have the status {FineTuningStatus.SUCCEEDED.value} to generate SQL queries."
             )
         self.database = SQLDatabase.get_sql_engine(database_connection)
-        if self.llm.openai_api_type == "azure":
+        if self.system.settings["azure_api_key"] is not None:
             embedding = AzureOpenAIEmbeddings(
                 openai_api_key=database_connection.decrypt_api_key(),
                 model=EMBEDDING_MODEL,
@@ -708,7 +708,7 @@ def stream_response(
                 f"Finetuning should have the status {FineTuningStatus.SUCCEEDED.value} to generate SQL queries."
             )
         self.database = SQLDatabase.get_sql_engine(database_connection)
-        if self.llm.openai_api_type == "azure":
+        if self.system.settings["azure_api_key"] is not None:
             embedding = AzureOpenAIEmbeddings(
                 openai_api_key=database_connection.decrypt_api_key(),
                 model=EMBEDDING_MODEL,
diff --git a/dataherald/sql_generator/dataherald_sqlagent.py b/dataherald/sql_generator/dataherald_sqlagent.py
index 0c898f34..414ab089 100644
--- a/dataherald/sql_generator/dataherald_sqlagent.py
+++ b/dataherald/sql_generator/dataherald_sqlagent.py
@@ -710,13 +710,13 @@ def create_sql_agent(
         )
 
     @override
-    def generate_response(
+    def generate_response(  # noqa: PLR0912
         self,
         user_prompt: Prompt,
         database_connection: DatabaseConnection,
         context: List[dict] = None,
         metadata: dict = None,
-    ) -> SQLGeneration:
+    ) -> SQLGeneration:  # noqa: PLR0912
         context_store = self.system.instance(ContextStore)
         storage = self.system.instance(DB)
         response = SQLGeneration(
@@ -754,7 +754,7 @@ def generate_response(
         logger.info(f"Generating SQL response to question: {str(user_prompt.dict())}")
         self.database = SQLDatabase.get_sql_engine(database_connection)
         # Set Embeddings class depending on azure / not azure
-        if self.llm.openai_api_type == "azure":
+        if self.system.settings["azure_api_key"] is not None:
             toolkit = SQLDatabaseToolkit(
                 db=self.database,
                 context=context,
@@ -874,7 +874,7 @@ def stream_response(
             number_of_samples = 0
         self.database = SQLDatabase.get_sql_engine(database_connection)
         # Set Embeddings class depending on azure / not azure
-        if self.llm.openai_api_type == "azure":
+        if self.system.settings["azure_api_key"] is not None:
             embedding = AzureOpenAIEmbeddings(
                 openai_api_key=database_connection.decrypt_api_key(),
                 model=EMBEDDING_MODEL,