feat: enhance LLM model creation with optional default pipeline setting

- Updated create_llm_model method to include auto_set_to_default_pipeline parameter.
- Adjusted ModelManager to set auto_set_to_default_pipeline to False when creating models.
- Improved logic for setting the default pipeline model based on the new parameter.

src/langbot/pkg/api/http/service/model.py

@@ -64,7 +64,9 @@ class LLMModelsService:
         models = result.all()
         return [self.ap.persistence_mgr.serialize_model(persistence_model.LLMModel, m) for m in models]
 
-    async def create_llm_model(self, model_data: dict, preserve_uuid: bool = False) -> str:
+    async def create_llm_model(
+        self, model_data: dict, preserve_uuid: bool = False, auto_set_to_default_pipeline: bool = True
+    ) -> str:
         """Create a new LLM model"""
         if not preserve_uuid:
             model_data['uuid'] = str(uuid.uuid4())
@@ -95,6 +97,7 @@ class LLMModelsService:
         )
         self.ap.model_mgr.llm_models.append(runtime_llm_model)
 
+        if auto_set_to_default_pipeline:
             # set the default pipeline model to this model
             result = await self.ap.persistence_mgr.execute_async(
                 sqlalchemy.select(persistence_pipeline.LegacyPipeline).where(

src/langbot/pkg/provider/modelmgr/modelmgr.py

@@ -149,6 +149,7 @@ class ModelManager:
                         'prefered_ranking': space_model.featured_order,
                     },
                     preserve_uuid=True,
+                    auto_set_to_default_pipeline=False,
                 )
 
             elif space_model.category == 'embedding':