Update app.py

app.py

@@ -130,7 +130,7 @@ def generate_charts(ner_output_bin: dict, ner_output_ext: dict) -> Tuple[go.Figu
     # Create pie chart for extended classification
     fig1 = go.Figure(data=[go.Pie(labels=ext_labels, values=ext_sizes, textinfo='label+percent', hole=.3, marker=dict(colors=ext_colors))])
     fig1.update_layout(
-        title_text='Extended Sequence Classification Subclasses',
+        #title_text='Extended Sequence Classification Subclasses',
         template='plotly_dark',
         plot_bgcolor='rgba(0,0,0,0)',
         paper_bgcolor='rgba(0,0,0,0)'
@@ -139,7 +139,7 @@ def generate_charts(ner_output_bin: dict, ner_output_ext: dict) -> Tuple[go.Figu
     # Create bar chart for binary classification
     fig2 = go.Figure(data=[go.Bar(x=bin_labels, y=bin_sizes, marker=dict(color=bin_colors))])
     fig2.update_layout(
-        title='Binary Sequence Classification Classes',
+        #title='Binary Sequence Classification Classes',
         xaxis_title='Entity Type',
         yaxis_title='Count',
         template='plotly_dark',
@@ -190,8 +190,8 @@ iface = gr.Interface(
         gr.Label(label="Internal Detail Count"),
         gr.Label(label="External Detail Count"),
         gr.Label(label="Approximated Internal Detail Ratio"),
-        gr.Plot(label="Entity Distribution Pie Chart"),
-        gr.Plot(label="Entity Count Bar Chart")
+        gr.Plot(label="Extended SeqClass Entity Distribution Pie Chart"),
+        gr.Plot(label="Binary SeqClass Entity Count Bar Chart")
     ],
     title="Scoring Demo",
     description="Autobiographical Memory Analysis: This demo combines two text - and two sequence classification models to showcase our automated Autobiographical Interview scoring method. Submit a narrative to see the results.",