Adding plotly plot

app.py

@@ -21,6 +21,14 @@ colors = px.colors.qualitative.Plotly
 # from huggingface_hub import InferenceClient
 # client = InferenceClient(model="bdsl/HanmunRoBERTa")
 
+def strip_input_str(x):
+    # Specify the characters to remove
+    characters_to_remove = "○□()〔〕:\"。·, ?ㆍ" + punctuation
+    translating = str.maketrans('', '', characters_to_remove)
+    input_str = input_str.translate(translating)
+
+    return input_str.strip()
+
 # Load the pipeline with the HanmunRoBERTa model
 model_pipeline = pipeline(task="text-classification", model="bdsl/HanmunRoBERTa")
 
@@ -33,22 +41,22 @@ st.title(title)
 remove_punct = st.checkbox(label="Remove punctuation", value=True)
 
 # Text area for user input
-input_str = st.text_area("Input text", height=275)
+input_str = st.text_area(
+    "Input text", 
+    height=150, 
+    value=" 權知 高麗 國事臣某言。 伏惟小邦, 自 恭愍王 無嗣薨逝之後, 辛旽 子 禑 冒姓竊位者.")
 
 # 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)
+    input_str = strip_input_str(input_str)
 
-# 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)
+        predictions = model_pipeline(input_str, top_k=None)
         data = pd.DataFrame(predictions)
         data=data.sort_values(by='score', ascending=True)
         data.label = data.label.astype(str)
@@ -67,17 +75,13 @@ if st.button("Classify"):
                 marker=dict(color=[colors[i % len(colors)] for i in range(len(data))]),  # Cycle through colors
 
             ))
-        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:
-        st.write("Please enter some text to classify.")