Update app.py

app.py

@@ -11,38 +11,29 @@ from flair.datasets import ColumnCorpus
 from flair.models import SequenceTagger
 from flair.trainers import ModelTrainer
 
-#input_data = st.text_area("Enter bengali text", value="", height=10)
+
 
 @st.cache_resource()
 def load_model(model_name):
     model = SequenceTagger.load(model_name)
     return (model)
 
-activity = ['File upload', 'Text Input']
-choice = st.selectbox('How would you like to process?',activity)
+activity = ['ফাইল আপলোড', 'টেক্সট ইনপুট']
+choice = st.selectbox('আপনি কিভাবে এটি প্রক্রিয়া করতে চান?',activity)
 #st.write('You selected:', option)
 
-if choice == 'Text Input':
-    input_data = st.text_area("Enter bengali text", value="", height=10)
+if choice == 'টেক্সট ইনপুট':
+    input_data = st.text_area("আপনার বাংলা বাক্য লিখুন", value="", height=10)
     if st.button('Process'):
-        # '''
+       
         data = BasicTokenizer().tokenize(input_data)
         
-        # fl = open('bengali_pos/test.txt', 'w')
-        # for i in data:
-        #     fl.write(i)
-        #     fl.write('\n')
-        # fl.close()
-        
-        # columns = {0: 'text'}
-        # corpus: Corpus = ColumnCorpus('bengali_pos/', columns, train_file='train.txt', test_file='test.txt', dev_file='valid.txt')
-        # '''
+       
         sentence = Sentence(data)
         model = load_model('best-model-002.pt')
         model.predict(sentence)
         my_list = []
-        # st.write(sentence.to_original_text())
-        # st.write(sentence.to_tagged_string())
+      
         for token in sentence:
             word = []
             word.append(token.text)
@@ -52,23 +43,5 @@ if choice == 'Text Input':
 
     
         
-        #print(input_data.to_tagged_string())
-        #result_mean = model.evaluate(corpus.test, gold_label_type='pos',mini_batch_size=32, out_path=f"pred_pos.txt")
-        
-        # st.write("Input Data: \n")
-        # st.write(input_data)
-        
-        # file1 = open('pred_pos.txt', 'r')
-        # Lines = file1.readlines()
-        
-        # my_list = []
-        # for line in Lines:
-        #     word = []
-        #     for j in line.split(' O '):
-        #         word.append(j)
-        #     my_list.append(tuple(word))
-            
-        # st.write("Output Data: \n")
-        # annotated_text(my_list)
-        # file1.close()
+