new val changes

src/webapp/databricks.py

@@ -202,7 +202,7 @@ def delete_inst(self, inst_name: str) -> None:
     def fetch_table_data(
         self,
         catalog_name: str,
-        schema_name: str,
+        inst_name: str,
         table_name: str,
         warehouse_id: str,
         limit: int = 1000,
@@ -221,7 +221,10 @@ def fetch_table_data(
             raise ValueError(f"Failed to initialize WorkspaceClient: {e}")
 
         # Construct the fully qualified table name
-        fully_qualified_table = f"`{catalog_name}`.`{schema_name}`.`{table_name}`"
+        schema_name = databricksify_inst_name(inst_name)
+        fully_qualified_table = (
+            f"`{catalog_name}`.`{schema_name}__silver`.`{table_name}`"
+        )
         sql_query = f"SELECT * FROM {fully_qualified_table} LIMIT {limit}"
 
         try:

src/webapp/routers/data.py

@@ -1023,28 +1023,6 @@ def get_upload_url(
         raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail=str(ve))
 
 
-# Get SHAP Values for Inference
-@router.get("/inference/test")
-def test() -> Any:
-    """Returns a signed URL for uploading data to a specific institution."""
-    # raise error at this level instead bc otherwise it's getting wrapped as a 200
-
-    try:
-        dbc = DatabricksControl()
-        rows = dbc.fetch_table_data(
-            catalog_name="dev_sst_02",
-            schema_name="default",
-            table_name="test_dataset",
-            warehouse_id="28e1cbabfe6deb87",
-            limit=500,
-        )
-
-        return rows
-    except ValueError as ve:
-        # Return a 400 error with the specific message from ValueError
-        raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail=str(ve))
-
-
 # Get SHAP Values for Inference
 @router.get("/{inst_id}/inference/top-features/{run_id}", response_model=str)
 def get_top_features(
@@ -1077,7 +1055,7 @@ def get_top_features(
         dbc = DatabricksControl()
         rows = dbc.fetch_table_data(
             catalog_name=env_vars["CATALOG_NAME"],
-            schema_name=f"{query_result[0][0].name}_silver",
+            inst_name=f"{query_result[0][0].name}",
             table_name=f"sample_inference_{run_id}_features_with_most_impact",
             warehouse_id=env_vars["SQL_WAREHOUSE_ID"],
             limit=500,
@@ -1121,7 +1099,7 @@ def get_support_overview(
         dbc = DatabricksControl()
         rows = dbc.fetch_table_data(
             catalog_name=env_vars["CATALOG_NAME"],
-            schema_name=f"{query_result[0][0].name}_silver",
+            inst_name=f"{query_result[0][0].name}",
             table_name=f"sample_inference_{run_id}_support_overview",
             warehouse_id=env_vars["SQL_WAREHOUSE_ID"],
             limit=500,
@@ -1164,7 +1142,7 @@ def get_feature_value(
         dbc = DatabricksControl()
         rows = dbc.fetch_table_data(
             catalog_name=env_vars["CATALOG_NAME"],
-            schema_name=f"{query_result[0][0].name}_silver",
+            inst_name=f"{query_result[0][0].name}",
             table_name=f"sample_inference_{run_id}_shap_feature_importance",
             warehouse_id=env_vars["SQL_WAREHOUSE_ID"],
             limit=500,
@@ -1207,7 +1185,7 @@ def get_confusion_matrix(
         dbc = DatabricksControl()
         rows = dbc.fetch_table_data(
             catalog_name=env_vars["CATALOG_NAME"],
-            schema_name=f"{query_result[0][0].name}_silver",
+            inst_name=f"{query_result[0][0].name}",
             table_name=f"sample_training_{run_id}_confusion_matrix",
             warehouse_id=env_vars["SQL_WAREHOUSE_ID"],
             limit=500,
@@ -1250,7 +1228,7 @@ def get_roc_curve(
         dbc = DatabricksControl()
         rows = dbc.fetch_table_data(
             catalog_name=env_vars["CATALOG_NAME"],
-            schema_name=f"{query_result[0][0].name}_silver",
+            inst_name=f"{query_result[0][0].name}",
             table_name=f"sample_training_{run_id}_roc_curve",
             warehouse_id=env_vars["SQL_WAREHOUSE_ID"],
             limit=500,