Added some logging code

ucsinfer/__main__.py

@@ -1,6 +1,7 @@
 import os
 import sys
 import csv
+import logging
 
 from sentence_transformers import SentenceTransformer
 import tqdm
@@ -13,12 +14,23 @@ from .util import ffmpeg_description, parse_ucs
 
 @click.group(epilog="For more information see "
              "<https://git.squad51.us/jamie/ucsinfer>")
-# @click.option('--verbose', flag_value='verbose', help='Verbose output')
-def ucsinfer():
+@click.option('--verbose', '-v', flag_value='verbose', help='Verbose output')
+def ucsinfer(verbose):
     """
     Tools for applying UCS categories to sounds using large-language Models 
     """
-    pass
+    
+    if verbose:
+        logging.basicConfig(format="%(levelname)s: %(message)s", 
+                            level=logging.DEBUG)
+    else:
+        import warnings
+        warnings.filterwarnings(
+                action='ignore', module='torch', category=FutureWarning, 
+                message=r"`encoder_attention_mask` is deprecated.*")
+
+        logging.basicConfig(format="%(levelname)s: %(message)s", 
+                            level=logging.WARN)
 
 
 @ucsinfer.command('recommend')
@@ -44,7 +56,7 @@ def recommend(text, paths, model, interactive, skip_ucs):
     "Description" text metadata is extracted from audio files given as PATHS,
     or text can be provided directly using the "--text" option. The selected 
     model is then used to attempt to classify the given text according to 
-    the synonyms and explanations definied for each UCS subcategory. A list 
+    the synonyms an explanations definied for each UCS subcategory. A list 
     of ranked subcategories is printed to the terminal for each PATH.
     """
     m = SentenceTransformer(model)
@@ -246,10 +258,4 @@ def evaluate(dataset, offset, limit, model, no_foley):
 if __name__ == '__main__':
     os.environ['TOKENIZERS_PARALLELISM'] = 'false'
 
-    # sentence_transformers generates an error in PyTorch upon loading
-    import warnings
-    warnings.filterwarnings(action='ignore', module='torch', 
-                            category=FutureWarning, 
-                            message=r"`encoder_attention_mask` is deprecated.*")
-
     ucsinfer()