Update app.py

app.py

@@ -1,33 +1,31 @@
-
 import streamlit as st
-from transformers import MBartForConditionalGeneration, MBart50TokenizerFast
-
-# Load the multilingual translation model and tokenizer
-model_name = "facebook/mbart-large-50"  # Choose a suitable model
-tokenizer = MBart50TokenizerFast.from_pretrained(model_name)
-model = MBartForConditionalGeneration.from_pretrained(model_name)
-
-# Create the Streamlit app interface
-st.title("Multilingual Translator")
+from transformers import pipeline
 
-source_text = st.text_area("Enter text to translate")
-target_language = st.selectbox("Choose target language", tokenizer.lang_codes.keys())
+st.title("Multilingual Translator Chatbot")
 
-if st.button("Translate"):
-    translated_text = translate_text(model, tokenizer, source_text, target_language)
-    st.write("Translated text:", translated_text)
-
-# Define the translation function
-def translate_text(model, tokenizer, source_text, target_language):
-    inputs = tokenizer(source_text, return_tensors="pt")
-    outputs = model.generate(**inputs, forced_bos_token_id=tokenizer.lang_code_to_id[target_language])
-    translated_text = tokenizer.batch_decode(outputs, skip_special_tokens=True)[0]
-    return translated_text
-from transformers import AutoConfig, AutoModelForSeq2SeqLM, AutoTokenizer
+# Choose the translation model from Hugging Face
+translation_model = st.selectbox("Select translation model", ["Helsinki-NLP/opus-mt-en-de", "Helsinki-NLP/opus-mt-en-fr"])
 
-model_name = "facebook/mbart-large-50"
-AutoConfig.from_pretrained(model_name).clear_cache()
-AutoModelForSeq2SeqLM.from_pretrained(model_name).clear_cache()
-AutoTokenizer.from_pretrained(model_name).clear_cache()
+# Load the translation pipeline
+translator = pipeline(task="translation", model=translation_model)
 
+# User input for translation
+user_input = st.text_area("Enter text for translation:", "")
 
+if st.button("Translate"):
+    if user_input:
+        # Perform translation
+        translated_text = translator(user_input, max_length=500)[0]['translation_text']
+        st.success(f"Translated Text: {translated_text}")
+    else:
+        st.warning("Please enter text for translation.")
+
+st.markdown("---")
+
+st.subheader("About")
+st.write(
+    "This is a simple Multilingual Translator chatbot that uses the Hugging Face Transformers library."
+)
+st.write(
+    "Select a translation model from the dropdown, enter text, and click 'Translate' to see the translation."
+)