Display tooltip for PCA

src/callbacks/home/embeddings/callbacks.py

@@ -82,3 +82,16 @@ def display_embeddings(word, word_exists):
                 # TODO: add exception handling
                 raise PreventUpdate
         raise PreventUpdate
+
+    @app.callback(
+        Output('input-word-embeddings', 'children'),
+        Input('submitted-word', 'data'),
+        Input('word-exists', 'data')
+    )
+    def search_word(word, word_exists):
+        if word and word_exists:
+            df = get_word_db(API_URL, word)
+            if len(df) >= 1:
+                return word
+
+        raise PreventUpdate

src/callbacks/home/plot/callbacks.py

@@ -47,10 +47,11 @@ def display_word_in_the_source_plot_description(word, word_exists):
         Input('word-plot-source', 'n_clicks'),
         Input('word-plot-sense', 'n_clicks'),
         Input('word-plot-network', 'n_clicks'),
+        Input('word-plot-embeddings', 'n_clicks'),
         State('submitted-word', 'data')
     )
-    def display_word_tooltip_in_the_source_plot(source_n_clicks, sense_n_clicks, network_n_clicks, word):
-        if source_n_clicks > 0 or sense_n_clicks > 0 or network_n_clicks > 0:
+    def display_word_tooltip_in_the_source_plot(source_n_clicks, sense_n_clicks, network_n_clicks, embeddings_n_clicks, word):
+        if source_n_clicks > 0 or sense_n_clicks > 0 or network_n_clicks > 0 or embeddings_n_clicks > 0:
             df = get_word_db(API_URL, word)
             nlp_word_df = get_nlp_word(API_URL, word)
 

src/pages/home.py

@@ -260,8 +260,20 @@
     html.Br(),
     html.Br(),
     html.Div([
-        html.Div(
-            'Three-dimensional projection of word sense embeddings obtained via principal component analysis (PCA)'),
+        html.Div([
+            'Three-dimensional projection of the word sense embeddings of ',
+            html.Span(
+                children=[
+                    html.Span(' ', id='input-word-embeddings'),
+                    html.Span(' '),
+                    html.I(
+                        className='bi bi-info-circle',
+                    ),
+                    f' '
+                ],
+                id='word-plot-embeddings', n_clicks=0, style={'white-space': 'pre'}, className='fw-bold'),
+            ', obtained via principal component analysis (PCA)'
+        ]),
         html.Div(
             'Data processing is ongoing for senses marked with an asterisk (*)',
             className='small mt-3', style={'color': 'gray'}