Update app.py

app.py

@@ -16,19 +16,19 @@ Additionally, the model was tasked with finding the topic of each cluster.
 """)
 
 @st.cache_data
-def load_data(min_score=1, max_score=10):
+def load_data(min=1, max=10):
     ds = load_dataset("HuggingFaceTB/FW_clusters_free_topics", split="train", token=HF_TOKEN, num_proc=2)
     ds = ds.filter(lambda x: x['educational_score'] <= max_score and x['educational_score'] >= min_score)
     return ds
 
 st.subheader("Cluster information")
-min_score, max_score = st.columns(2)
-with min_score:
+col_1, col_2 = st.columns(2)
+with col_1:
     min_value = st.slider('Select minimum educational score', 1, 10, 1, key='min_score')
-with max_score:
+with col_2:
     max_value = st.slider('Select maximum educational score', 1, 10, 10, key='max_score')
 
-ds = load_data(min_score, max_score)
+ds = load_data(min_value, max_value)
 selected_category_type = st.selectbox("Select a topic", categories)
 categories = list(set(ds["category"]))
 selected_cluster = ds.filter(lambda x: x['category'] == selected_category)