Update app.py

app.py

@@ -10,31 +10,34 @@ nlp = spacy.load("en_core_web_sm")
 def text_analysis(text):
     doc = nlp(text)
     dependency_parsing = displacy.render(doc, style="dep", page=True)
-    
     visual1 = (
         "<div style='max-width:100%; overflow:auto'>"
         + dependency_parsing
         + "</div>"
     )
-      
     rows = []
     for token in doc:
         rows.append((token.text, token.lemma_, token.pos_, token.tag_, token.dep_,
             token.shape_, token.is_alpha, token.is_stop))
-  
     table = pd.DataFrame(rows, columns = ["TEXT", "LEMMA","POS","TAG","DEP","SHAPE","ALPHA","STOP"])
-
     return table, visual1
 
-
-demo = gr.Interface(
-    text_analysis,
-    inputs = gr.Textbox(placeholder="Enter sentence here..."),
-    outputs = [ gr.Dataframe(), "html"],
-    examples=[
+with gr.Blocks() as demo:
+    with gr.Row():
+      inp = gr.Textbox(placeholder="Enter text to analyze...")
+    btn = gr.Button("Analyze Text")
+    gr.Markdown("""### Analysis""")
+    with gr.Row():
+      table = gr.Dataframe()
+    gr.Markdown("""### Dependency Parsing""")
+    with gr.Row():
+      visual1 = gr.HTML()
+    with gr.Row():
+      gr.Examples(
+                examples=[
         ["Data Science Dojo is the leading platform providing training in data science, data analytics, and machine learning."],
         ["It's the best time to execute the plan."],
-    ],
-)
+    ], fn=text_analysis, inputs=inp, outputs=[table, visual1], cache_examples=True)
+    btn.click(fn=text_analysis, inputs=inp, outputs=[table, visual1])
 
 demo.launch()