update app

app.py

@@ -17,9 +17,10 @@ def classify(_input):
     wrapper method to compute label 1 probability and explanation for given input
     """
     result = classifier(_input)[0]
-    score = result['score']
+    score = round(result['score'], 4)
+    print(score)
     if result['label'] == 'LABEL_0':
-        score = 1-score
+        score = 1 - score
 
     # getting visualization
     attributions = explainer(_input)
@@ -34,8 +35,12 @@ def classify(_input):
 app = gr.Blocks()
 
 with app:
-    gr.Markdown("# Transformation Intensity Classifier")
-    gr.Markdown("## Detect Transformation Sentences in Quarterly Earnings Conference Calls")
+    gr.Markdown(
+        """
+        # Transformation Talk Classifier
+        ## Detect Transformation-Related Sentences in Quarterly Earnings Calls
+        """
+    )
     with gr.Row():
         with gr.Column():
             text_in = gr.Textbox(lines=1, placeholder="Insert text", label="Input Sentence")
@@ -43,11 +48,23 @@ with app:
                 compute_bt = gr.Button("Classify")
             score_out = gr.Number(label="Score", interactive=False)
             html_out = gr.HTML(label="Explanation")
+            gr.Examples(
+                examples=[
+                    ["If we look at the plans for 2018, it is to introduce 650 new products, which is an absolute all- time high."],
+                    ["We have been doing kind of an integrated campaign, so it's TV, online, we do the Google Ad Words - all those different elements together."],
+                    ["So that turned out to be beneficial for us, and I think, we'll just see how the market and interest rates move over the course of the year,"]
+                ],
+                label="Examples (click to start detection)",
+                inputs=[text_in],
+                outputs=[score_out, html_out],
+                fn=classify,
+                cache_examples=True
+            )
         with gr.Column():
             gr.Markdown(
                 """
                 #### Project Description
-                Placeholder
+                Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren, no sea takimata sanctus est Lorem ipsum dolor sit amet. Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren, no sea takimata sanctus est Lorem ipsum dolor sit amet.
                 """
             )
             gr.Markdown(
@@ -58,17 +75,6 @@ with app:
                 In addition, the app returns the tokenized version of the sentence, alongside word importances that are indicated by color codes. Those visuals illustrates the ability of the context-aware classifier to simultaneously pay attention to various parts in the input sentence to derive a final label.                
                 """
             )
-            gr.Examples(
-                examples=[
-                    ["If we look at the plans for 2018, it is to introduce 650 new products, which is an absolute all- time high."],
-                    ["We have been doing kind of an integrated campaign, so it's TV, online, we do the Google Ad Words - all those different elements together."],
-                    ["So that turned out to be beneficial for us, and I think, we'll just see how the market and interest rates move over the course of the year,"]
-                ],
-                inputs=[text_in],
-                outputs=[score_out, html_out],
-                fn=classify,
-                cache_examples=True
-            )
     gr.Markdown(
         """
         <p style="text-align: center;">
@@ -81,7 +87,5 @@ with app:
     compute_bt.click(classify, inputs=[text_in], outputs=[score_out, html_out])
 
 
-app.launch()
-
-
-
+if __name__ == "__main__":
+    app.launch()