Adding plotly plot

app.py

@@ -29,61 +29,55 @@ title = "HanmunRoBERTa Century Classifier"
 st.set_page_config(page_title=title, page_icon="📚")
 st.title(title)
 
-# Create a two-column layout
-col1, col2 = st.columns([2, 3])  # Adjust the width ratio as needed
+# Checkbox to remove punctuation
+remove_punct = st.checkbox(label="Remove punctuation", value=True)
 
-with col1:
-    # Checkbox to remove punctuation
-    remove_punct = st.checkbox(label="Remove punctuation", value=True)
+# Text area for user input
+input_str = st.text_area("Input text", height=275)
 
-    # Text area for user input
-    input_str = st.text_area("Input text", height=275)
+# Remove punctuation if checkbox is selected
+if remove_punct and input_str:
+    # Specify the characters to remove
+    characters_to_remove = "○□()〔〕:\"。·, ?ㆍ" + punctuation
+    translating = str.maketrans('', '', characters_to_remove)
+    input_str = input_str.translate(translating)
 
-    # Remove punctuation if checkbox is selected
-    if remove_punct and input_str:
-        # Specify the characters to remove
-        characters_to_remove = "○□()〔〕:\"。·, ?ㆍ" + punctuation
-        translating = str.maketrans('', '', characters_to_remove)
-        input_str = input_str.translate(translating)
+# Display the input text after processing
+st.write("Processed input:", input_str)
 
-        # Display the input text after processing
-        st.write("Processed input:", input_str)
+# Predict and display the classification scores if input is provided
+if st.button("Classify"):
+    if input_str:
+        predictions = model_pipeline(input_str)
+        data = pd.DataFrame(predictions)
+        data=data.sort_values(by='score', ascending=True)
+        data.label = data.label.astype(str)
 
-    # Button for prediction
-    classify_button = st.button("Classify")
+        
+        # Displaying predictions as a bar chart
+        fig = go.Figure(
+            go.Bar(
+                x=data.score.values,
+                y=[f'{i}th Century' for i in data.label.values],
+                orientation='h', 
+                text=[f'{score:.3f}' for score in data['score'].values],  # Format text with 2 decimal points
+                textposition='outside',  # Position the text outside the bars
+                hoverinfo='text',  # Use custom text for hover info
+                hovertext=[f'{i}th Century<br>Score: {score:.3f}' for i, score in zip(data['label'], data['score'])],  # Custom hover text
+                marker=dict(color=[colors[i % len(colors)] for i in range(len(data))]),  # Cycle through colors
 
-# Predict and display the classification scores if input is provided and button is clicked
-if classify_button and input_str:
-    predictions = model_pipeline(input_str)
-    data = pd.DataFrame(predictions)
-    data = data.sort_values(by='score', ascending=True)
-    data.label = data.label.astype(str)
-    
-    # Displaying predictions as a bar chart
-    fig = go.Figure(
-        go.Bar(
-            x=data.score.values,
-            y=[f'{i}th Century' for i in data.label.values],
-            orientation='h', 
-            text=[f'{score:.3f}' for score in data['score'].values],
-            textposition='outside',
-            hoverinfo='text',
-            hovertext=[f'{i}th Century<br>Score: {score:.3f}' for i, score in zip(data['label'], data['score'])],
-            marker=dict(color=[colors[i % len(colors)] for i in range(len(data))]),
-        ))
-    fig.update_traces(width=0.4)
-    fig.update_layout(
-        height=300,  # Custom height
-        xaxis_title='Score',
-        yaxis_title='',
-        title='Model predictions and scores',
-        margin=dict(l=100, r=200, t=50, b=50),
-        uniformtext_minsize=8, 
-        uniformtext_mode='hide',
-    )
-    
-    with col2:
+            ))
+        fig.update_traces(width=0.4)
+
+        fig.update_layout(
+            height=300,  # Custom height
+            xaxis_title='Score',
+            yaxis_title='',
+            title='Model predictions and scores',
+            margin=dict(l=100, r=200, t=50, b=50),
+            uniformtext_minsize=8, 
+            uniformtext_mode='hide',
+        )
         st.plotly_chart(figure_or_data=fig, use_container_width=True)
-else:
-    with col2:
-        st.write("Please enter some text to classify and click 'Classify'.")
+    else:
+        st.write("Please enter some text to classify.")