feat: Improving ui messages for non-technical comm

app.py

@@ -63,11 +63,12 @@ def draw_interactive_scatter_plot(
 
 # Up to here
 def generate_plot(
-    df: List[str],
+    tws: List[str],
     model: SentenceTransformer,
+    tw_user: str
 ) -> Figure:
-    with st.spinner(text="Embedding text..."):
-        embeddings = embed_text(df, model)
+    with st.spinner(text=f"Trying to understand '{tw_user}' tweets..."):
+        embeddings = embed_text(tws, model)
     # encoded_labels = encode_labels(labels)
     cluster = hdbscan.HDBSCAN(
         min_cluster_size=5,
@@ -75,16 +76,17 @@ def generate_plot(
         cluster_selection_method='eom'
     ).fit(embeddings)
     encoded_labels = cluster.labels_
-    with st.spinner("Reducing dimensionality..."):
+    with st.spinner("Now trying to express them with my own words..."):
         embeddings_2d = get_tsne_embeddings(embeddings)
     plot = draw_interactive_scatter_plot(
-        df, embeddings_2d[:, 0], embeddings_2d[:, 1], encoded_labels, encoded_labels, 'text', 'label'
+        tws, embeddings_2d[:, 0], embeddings_2d[:, 1], encoded_labels, encoded_labels, 'text', 'label'
     )
     return plot
 
 
 st.title("Tweet-SNEst")
 st.write("Visualize tweets embeddings in 2D using colors for topics labels.")
+st.caption('Please beware this is using Twitter free version of their API and might be needed to wait sometimes.')
 col1, col2 = st.columns(2)
 with col1:
     tw_user = st.text_input("Twitter handle", "huggingface")
@@ -117,5 +119,5 @@ if tw_user:
         tweets_objs += tweets_response.data
     tweets_txt = [tweet.text for tweet in tweets_objs]    
     # plot = generate_plot(df, text_column, label_column, sample, dimensionality_reduction_function, model)
-    plot = generate_plot(tweets_txt, model)
+    plot = generate_plot(tweets_txt, model, tw_user)
     st.bokeh_chart(plot)