Update app.py

app.py

@@ -5,9 +5,6 @@ from keras.preprocessing.text import Tokenizer
 
 # Load your custom Keras model
 model = load_model('/content/drive/MyDrive/best_model.h5')
-
-# Assuming 'source_tokenizer' is the tokenizer used during training
-# You may need to adapt this based on your actual tokenizer
 tokenizer = source_tokenizer
 
 # Function for transliteration
@@ -18,8 +15,8 @@ def transliterate_malayalam_to_english(malayalam_text):
     # Use the model for prediction
     output_sequence = model.predict(input_sequence)
     
-    # Decode the output sequence to get the transliterated text (adjust this based on your decoding logic)
-    predicted_text = decode_output_sequence(output_sequence)
+    # Use argmax to get the most likely characters
+    predicted_text = "".join([tokenizer.index_word[idx] for idx in np.argmax(output_sequence, axis=-1)[0] if idx != 0])
     
     return predicted_text