minor changes

app.py

@@ -6,10 +6,10 @@ def load_models():
     tokenizer = MBart50Tokenizer.from_pretrained("facebook/mbart-large-50")
     model = AutoModelForSeq2SeqLM.from_pretrained("facebook/mbart-large-50")
     summarizer = pipeline("summarization", model=model, tokenizer=tokenizer)
-    translator = pipeline("translation", model=model, tokenizer=tokenizer)
-    return tokenizer, summarizer, translator
+    
+    return tokenizer, summarizer
 
-tokenizer, summarizer, translator = load_models()
+tokenizer, summarizer = load_models()
 
 import streamlit as st
 LANGUAGE_CODES = {
@@ -27,33 +27,6 @@ def detect_language(text):
     return lang_code
 
 
-def translate_to_english(text, src_lang):
-    # Define the target language as English
-    tgt_lang = "en_XX"
-    
-    # Tokenize the input text with the appropriate source and target language tokens
-    inputs = tokenizer(
-        text, 
-        return_tensors="pt", 
-        max_length=1024, 
-        truncation=True
-    )
-
-    # Specify the source language and target language in the generation call
-    translated_ids = translator.model.generate(
-        inputs["input_ids"], 
-        max_length=100, 
-        length_penalty=2.0, 
-        num_beams=4,
-        decoder_start_token_id=tokenizer.lang_code_to_id[tgt_lang],  # Explicitly set the target language
-        forced_bos_token_id=tokenizer.lang_code_to_id[src_lang]  # Set the source language
-    )
-    
-    # Decode the translated text
-    translated_text = tokenizer.decode(translated_ids[0], skip_special_tokens=True)
-    translated_text = re.sub(r"<[^>]+>", "", translated_text).strip()
-    
-    return translated_text
 
 
 def summarize_text(text, lang_code):
@@ -76,8 +49,8 @@ def summarize_text(text, lang_code):
     return summary
 
 
-st.title("Multilingual Summarization and Translation App")
-st.markdown("""This app detects the language of the input text, summarizes it in the same language, and translates it into English.""")
+st.title("Multilingual Summarization App")
+
 
 user_input = st.text_area("Enter text in any language:", "")
 
@@ -96,11 +69,6 @@ if st.button("Process Text"):
                 st.write(f"### Summarized Text ({lang_code}):")
                 st.write(summary)
 
-                # Then translate the summary to English
-                translation = translate_to_english(summary, LANGUAGE_CODES.get(lang_code, "en_XX"))
-                st.write("### Translated Text (English):")
-                st.write(translation)
-
             except Exception as e:
                 st.error(f"An error occurred during processing: {e}")
     else: