Upload app.py

app.py

@@ -0,0 +1,27 @@
+import streamlit as st
+import pandas as pd
+import re
+import tensorflow as tf
+import tensorflow_hub as hub
+import joblib
+
+def load_model():
+    # Correct the path to your model
+    return tf.keras.models.load_model('path_to_my_model', custom_objects={'KerasLayer': hub.KerasLayer})
+
+model = load_model()
+
+# Correct the path to your label encoder
+label_encoder = joblib.load('label_encoder.joblib')
+
+st.title('Transaction Category Predictor')
+
+user_input = st.text_input("Enter a transaction description:")
+
+if user_input:
+    processed_input = re.sub(r'\d+', '', user_input)
+    input_df = pd.DataFrame([processed_input], columns=['transaction_desc'])
+    prediction = model.predict(input_df['transaction_desc'])
+    predicted_category_index = prediction.argmax()
+    predicted_category = label_encoder.inverse_transform([predicted_category_index])[0]
+    st.write(f"Predicted Category: {predicted_category}")