feat: add form input

app.py

@@ -1,3 +1,4 @@
+from operator import setitem
 from pathlib import Path
 
 import streamlit as st
@@ -8,7 +9,7 @@ from transformers import TextClassificationPipeline
 
 
 @st.cache_data()
-def get_pipe():
+def load_model():
     model = AutoModelForSequenceClassification.from_pretrained(
         "issai/rembert-sentiment-analysis-polarity-classification-kazakh")
     tokenizer = AutoTokenizer.from_pretrained("issai/rembert-sentiment-analysis-polarity-classification-kazakh")
@@ -22,10 +23,16 @@ assert static_folder.exists()
 st.write((static_folder / 'description.txt').read_text())
 st.image(str(static_folder / 'kazsandra.jpg'))
 
-input_text = st.text_area('Input text', placeholder='Provide your text', value='Осы кітап қызық сияқты.')
+pipe = load_model()
+
+with st.form('main_form'):
+    input_text = st.text_area('Input text', placeholder='Provide your text, e.g. "Осы кітап қызық сияқты".')
+    is_submitted = st.form_submit_button(label='Submit')
+    if is_submitted:
+        if input_text:
+            out = pipe(input_text)[0]
+            st.text("Label: {label}\nScore: {score}".format(**out))
+        else:
+            st.text("Please provide your text first.")
+
 # reviews = ["Бұл бейнефильм маған түк ұнамады.", "Осы кітап қызық сияқты."]
-pipe = get_pipe()
-# for review in reviews:
-if input_text:
-    out = pipe(input_text)[0]
-    st.text("Label: {label}\nScore: {score}".format(**out))