Add nlp words to sample sentence base on sense plot

dlsucomet · Oct 31, 2023 · bd07f26 · bd07f26
1 parent 391b57d
commit bd07f26
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Showing 2 changed files with 57 additions and 36 deletions.
diff --git a/src/callbacks/home/api_query.py b/src/callbacks/home/api_query.py
@@ -33,6 +33,7 @@ def get_nlp_word(API_URL, word):
             word['example_sentences'] = util.sanitize_sample_sentences(word['example_sentences'])
 
         df = pd.DataFrame(word_db)  
+        df = df.sort_values(by=['sense_id'])
 
         return df
     except Exception as e:
@@ -46,6 +47,7 @@ def get_word_db(API_URL, word):
         word_db = res.json()
 
         df = pd.DataFrame(word_db)
+        df = df.sort_values(by=['sense_id'])
         return df
     except:
         return pd.DataFrame()

diff --git a/src/callbacks/home/plot/callbacks.py b/src/callbacks/home/plot/callbacks.py
@@ -106,29 +106,47 @@ def display_word_tooltip_in_the_source_plot(source_n_clicks, sense_n_clicks, wor
     def display_sense_dropdown(word, word_exists):
         if word and word_exists:
             df = get_word_db(API_URL, word)
+            nlp_word_df = get_nlp_word(API_URL, word)
 
-            if len(df) >= 1:
+            checklist_options = {}
+            num_sense = 0
 
-                checklist_options = {}
-                num_sense = 0
+            # netsci word 
+            if len(df) >= 1:
                 for i in range(len(df)):
                     sense_id = df.iloc[i]['sense_id']
 
                     pos = ''
-                    if 'pos' in df.columns:
-                        pos = df.iloc[i]['pos']
+                    #if 'pos' in df.columns:
+                    #    pos = df.iloc[i]['pos']
 
                     checklist_options[sense_id] = sense_and_pos_text(
                         f'Sense {num_sense+1}', pos)
                     num_sense = num_sense + 1
 
+            # nlp word
+            if len(nlp_word_df) >= 1:
+                for i in range(len(nlp_word_df)):
+                    sense_id = nlp_word_df.iloc[i]['sense_id']
+
+                    pos = ''
+                    #if 'pos' in nlp_word_df.columns:
+                    #    pos = nlp_word_df.iloc[i]['pos']
+
+                    checklist_options[sense_id] = sense_and_pos_text(
+                        f'Sense {num_sense+1}', pos) + "*"
+                    num_sense = num_sense + 1
+
+
+            if len(df) >= 1 or len(nlp_word_df) >= 1:
                 selected_option = None
                 if not checklist_options:
                     checklist_options = {None: None}
                 else:
                     selected_option = list(checklist_options.keys())[0]
 
                 return checklist_options, selected_option
+
             else:
                 # TODO: Handle case where word is not in database
                 raise PreventUpdate
@@ -145,40 +163,41 @@ def plot_update_sample_sentence_base_on_sense(sense_value, word, word_exists):
 
         if word and sense_value and word_exists:
             df = get_word_db(API_URL, word)  # get_definition_list(word)
-
+            
             if len(df) > 0:
                 sense_id_df = df.loc[df['sense_id'] == sense_value.lower()]
 
-                sample_sentence_list = sense_id_df.iloc[0]['example_sentences']
-
-                sample_sentence = ''
-                if len(sample_sentence_list) > 0:
-                    sample_sentence = sample_sentence_list[0]
-
-                sense_data = html.Div(
-                    children=[
-                        html.Br(),
-                        #html.Div(
-                        #    children=[
-                        #        html.Span('Definition: '),
-                        #        html.Span(
-                        #            'lorem ipsum',
-                        #            style={'color': 'gray'}
-                        #        )
-                        #    ]
-                        #),
-                        html.Div(
-                            children=[
-                                html.Span('Sample sentence: '),
-                                html.Span(
-                                    sample_sentence,
-                                    style={'color': 'gray'}
-                                )
-                            ]
-                        ),
-                    ]
-                )
-                return sense_data
+                if len(sense_id_df) >= 1:
+                    sample_sentence_list = sense_id_df.iloc[0]['example_sentences']
+
+                    sample_sentence = ''
+                    if len(sample_sentence_list) > 0:
+                        sample_sentence = sample_sentence_list[0]
+
+                    sense_data = html.Div(
+                        children=[
+                            html.Br(),
+                            #html.Div(
+                            #    children=[
+                            #        html.Span('Definition: '),
+                            #        html.Span(
+                            #            'lorem ipsum',
+                            #            style={'color': 'gray'}
+                            #        )
+                            #    ]
+                            #),
+                            html.Div(
+                                children=[
+                                    html.Span('Sample sentence: '),
+                                    html.Span(
+                                        sample_sentence,
+                                        style={'color': 'gray'}
+                                    )
+                                ]
+                            ),
+                        ]
+                    )
+                    return sense_data
 
         raise PreventUpdate