Merge pull request #15632 from brendanhoar/bgh-handle-metadata-issues-more-cleanly

QOL Items - handle metadata issues more cleanly for SD models, Loras and embeddings

extensions-builtin/Lora/ui_edit_user_metadata.py

@@ -21,7 +21,9 @@ re_comma = re.compile(r" *, *")
 def build_tags(metadata):
     tags = {}
 
-    for _, tags_dict in metadata.get("ss_tag_frequency", {}).items():
+    ss_tag_frequency = metadata.get("ss_tag_frequency", {})
+    if ss_tag_frequency is not None and hasattr(ss_tag_frequency, 'items'):
+        for _, tags_dict in ss_tag_frequency.items():
             for tag, tag_count in tags_dict.items():
                 tag = tag.strip()
                 tags[tag] = tags.get(tag, 0) + int(tag_count)

modules/sd_models.py

@@ -282,10 +282,12 @@ def read_metadata_from_safetensors(filename):
         json_start = file.read(2)
 
         assert metadata_len > 2 and json_start in (b'{"', b"{'"), f"{filename} is not a safetensors file"
-        json_data = json_start + file.read(metadata_len-2)
-        json_obj = json.loads(json_data)
 
         res = {}
+
+        try:
+            json_data = json_start + file.read(metadata_len-2)
+            json_obj = json.loads(json_data)
             for k, v in json_obj.get("__metadata__", {}).items():
                 res[k] = v
                 if isinstance(v, str) and v[0:1] == '{':
@@ -293,6 +295,8 @@ def read_metadata_from_safetensors(filename):
                         res[k] = json.loads(v)
                     except Exception:
                         pass
+        except Exception:
+             errors.report(f"Error reading metadata from file: {filename}", exc_info=True)
 
         return res
 

modules/textual_inversion/textual_inversion.py

@@ -181,12 +181,16 @@ class EmbeddingDatabase:
         else:
             return
 
+        if data is not None:
             embedding = create_embedding_from_data(data, name, filename=filename, filepath=path)
 
             if self.expected_shape == -1 or self.expected_shape == embedding.shape:
                 self.register_embedding(embedding, shared.sd_model)
             else:
                 self.skipped_embeddings[name] = embedding
+        else:
+            print(f"Unable to load Textual inversion embedding due to data issue: '{name}'.")
+
 
     def load_from_dir(self, embdir):
         if not os.path.isdir(embdir.path):