Try to fix piclking error

app.py

@@ -110,6 +110,8 @@ reduce_umap_model = UMAP(
     random_state=42,
 )
 
+global_topic_model = None
+
 
 def get_parquet_urls(dataset, config, split):
     parquet_files = session.get(
@@ -138,6 +140,8 @@ def calculate_embeddings(docs):
 
 @spaces.GPU
 def fit_model(docs, embeddings):
+    global global_topic_model
+
     new_model = BERTopic(
         "english",
         # Sub-models
@@ -151,10 +155,13 @@ def fit_model(docs, embeddings):
         verbose=True,
         min_topic_size=15,  # TODO: Should this value be coherent with N_NEIGHBORS?
     )
-    logging.debug("Fitting new model")
+    logging.info("Fitting new model")
     new_model.fit(docs, embeddings)
-    logging.debug("End fitting new model")
-    return new_model
+    logging.info("End fitting new model")
+
+    global_topic_model = new_model
+
+    logging.info("Global model updated")
 
 
 def generate_topics(dataset, config, split, column, nested_column):
@@ -180,12 +187,12 @@ def generate_topics(dataset, config, split, column, nested_column):
         )
 
         embeddings = calculate_embeddings(docs)
-        new_model = fit_model(docs, embeddings)
+        fit_model(docs, embeddings)
 
         if base_model is None:
-            base_model = new_model
+            base_model = global_topic_model
         else:
-            updated_model = BERTopic.merge_models([base_model, new_model])
+            updated_model = BERTopic.merge_models([base_model, global_topic_model])
             nr_new_topics = len(set(updated_model.topics_)) - len(
                 set(base_model.topics_)
             )