Update app.py

app.py

@@ -1,36 +1,31 @@
-from transformers import AutoModelForSeq2SeqLM, pipeline
+import streamlit as st
+from transformers import pipeline
 
-# Load the previously trained and saved model
-model_path = r'C:\Users\muham\OneDrive\Desktop\certificates\product_model'
-model = AutoModelForSeq2SeqLM.from_pretrained(r'C:\Users\muham\OneDrive\Desktop\certificates\product_model')
-
-# Load the translation models
+# Load the translation models and the custom chatbot model
 translator_ar_en = pipeline('translation_ar_to_en', model='Helsinki-NLP/opus-mt-ar-en')
 translator_en_ar = pipeline('translation_en_to_ar', model='Helsinki-NLP/opus-mt-en-ar')
-# Create the custom model pipeline
-custom_model = pipeline('text2text-generation', model=r'C:\Users\muham\OneDrive\Desktop\certificates\product_model')
+custom_model = pipeline('text2text-generation', model='Mohamed2002/product_model')
 
 def translate(text, translator):
     return translator(text)[0]['translation_text']
-def chat_with_bot():
-    print("(:اهلا بحضرتك في تطبيق السمسار الالكتروني")
-    while True:
-        # Get user input
-        user_input = input("العميل: ")
-        if user_input.lower() == 'quit':
-            break
-        
-        # Translate user input from Arabic to English
-        try:
-            translated_input = translate(user_input, translator_ar_en)
-            
-            # Generate prediction
-            prediction = custom_model(translated_input)[0]['generated_text']         
-            # Translate response from English to Arabic
-            translated_response = translate(prediction, translator_en_ar)
-            print("السمسار:", translated_response)
-        except Exception as e:
-            print(f"An error occurred: {str(e)}")
 
-# Start chatting with the bot
-chat_with_bot()
+# Streamlit app
+st.title("Arabic Chatbot")
+
+st.write("(:اهلا بحضرتك في تطبيق السمسار الالكتروني")
+
+user_input = st.text_input("العميل:")
+
+if st.button("Submit"):
+    try:
+        # Translate user input from Arabic to English
+        translated_input = translate(user_input, translator_ar_en)
+        
+        # Generate prediction
+        prediction = custom_model(translated_input)[0]['generated_text']
+        
+        # Translate response from English to Arabic
+        translated_response = translate(prediction, translator_en_ar)
+        st.write("السمسار:", translated_response)
+    except Exception as e:
+        st.write(f"An error occurred: {str(e)}")