feat(abstractions): enforcing silence by default

__init__.py

@@ -1,6 +1,9 @@
 import os, sys
 sys.path = [os.path.dirname(os.path.abspath(__file__))] + sys.path
 
+import logging
+logging.basicConfig(level=logging.ERROR)
+
 from benchmark.framework import JudgeBase, ExamineeBase
 from benchmark.dummies import DummyJudge
 from challenges.follow import FollowJudge

src/abstractions/data.py

@@ -235,9 +235,11 @@ def transform(
         """
         out_path = f"{root}/output/datasets/{result_data_name}.json"
         if self.data_name == result_data_name or self.data_path == out_path:
-            warnings.warn(
-                f"Data name {result_data_name} is the same as the current data name. The old instance will be invalidated."
-            )
+            if eval(os.environ.get('LOUD_BACKEND', 'False')):
+                warnings.warn(
+                    f"Data name {result_data_name} is the same as the current data name. The old instance will be invalidated."
+                )
+
             return self.copy("temp_transform_artifact").transform(
                 transformation,
                 result_data_name,
@@ -532,9 +534,6 @@ def manage_llama_factory_registration(
 
             print(f"Successfully completed de-registration of data {self.data_name}.")
 
-        else:
-            print("No actions taken.")
-
         return return_val
 
     def set_key_fields(

src/path.py

@@ -1,3 +1,4 @@
 import os, sys
 root = "src".join(os.path.dirname(os.path.abspath(__file__)).split("src")[:-1]).rstrip("/").rstrip("\\")
-print(f"Library root directory: {root}")
+if eval(os.environ.get('LOUD_BACKEND', 'False')):
+    print(f"Library root directory: {root}")

src/utils/data_utils/rw_utils.py

@@ -36,9 +36,11 @@ def transformation(dic: Dict) -> Dict:
         forced_rewrite=True,
     )
 
-    print(
-        f"Truncated dataset {data.data_name} from size {original_size} to {len(list(truncated_data.all_passages()))}."
-    )
+    if eval(os.environ.get("LOUD_BACKEND", "False")):
+        print(
+            f"Truncated dataset {data.data_name} from size {original_size} to {len(list(truncated_data.all_passages()))}."
+        )
+
     return truncated_data