Update translation.py

translation.py

@@ -1,4 +1,3 @@
-import streamlit as st
 from transformers import MarianTokenizer, MarianMTModel
 import torch
 
@@ -10,7 +9,7 @@ LANGUAGES = {
 
 @st.cache_resource
 def _load_default_model():
-    model_name = "Helsinki-NLP/opus-mt-en-hi"  
+    model_name = "Helsinki-NLP/opus-mt-en-hi"
     tokenizer = MarianTokenizer.from_pretrained(model_name)
     model = MarianMTModel.from_pretrained(model_name)
     return tokenizer, model
@@ -24,24 +23,17 @@ def load_model(source_lang, target_lang):
         tokenizer = MarianTokenizer.from_pretrained(model_name)
         model = MarianMTModel.from_pretrained(model_name)
         return tokenizer, model
-    except Exception as e:
-        st.warning(f"No direct model for {source_lang} to {target_lang}. Using en-hi fallback.")
+    except Exception:
         return _load_default_model()
 
-@st.cache_data(ttl=3600)
-def translate_cached(text, source_lang, target_lang):
-    tokenizer, model = load_model(source_lang, target_lang)
-    inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True, max_length=500)
-    with torch.no_grad():
-        translated = model.generate(**inputs, max_length=500, num_beams=2, early_stopping=True)
-    translated_text = tokenizer.decode(translated[0], skip_special_tokens=True)
-    return translated_text if translated_text.strip() and len(translated_text.split()) >= 2 else text
-
 def translate(text, source_lang, target_lang):
     if not text:
-        return "No text provided."
+        return ""
     try:
-        return translate_cached(text, source_lang, target_lang)
-    except Exception as e:
-        st.error(f"Translation error: {str(e)}. Using input as fallback.")
-        return text
+        tokenizer, model = load_model(source_lang, target_lang)
+        inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True, max_length=500)
+        with torch.no_grad():
+            translated = model.generate(**inputs, max_length=500, num_beams=2, early_stopping=True)
+        return tokenizer.decode(translated[0], skip_special_tokens=True)
+    except Exception:
+        return text