Update translator.py

translator.py

@@ -1,40 +1,22 @@
-import logging
 from transformers import pipeline
 
-logger = logging.getLogger(__name__)
-
 class Translator:
     def __init__(self):
-        self.model_en_mul = "Helsinki-NLP/opus-mt-en-mul"
-        self.model_mul_en = "Helsinki-NLP/opus-mt-mul-en"
-        self.engines = {"to_indian": None, "to_english": None}
-        print("[System] Translator initialized. Engines will load on first use to save RAM.")
+        # This is the model that gave you the "perfect" results earlier
+        self.model_name = "Helsinki-NLP/opus-mt-mul-en"
+        self.translator = None
 
     def translate(self, text, target_lang):
         if not text or not text.strip(): return ""
         
-        lang_codes = {
-            "English": ">>eng<<", "Hindi": ">>hin<<", "Telugu": ">>tel<<",
-            "Tamil": ">>tam<<", "Bengali": ">>ben<<", "Marathi": ">>mar<<",
-            "Gujarati": ">>guj<<", "Kannada": ">>kan<<", "Malayalam": ">>mal<<",
-            "Punjabi": ">>pan<<", "Urdu": ">>urd<<", "Odia": ">>ori<<",
-            "Assamese": ">>asm<<", "Spanish": ">>spa<<", "French": ">>fra<<"
-        }
-
+        # If the user wants English, use the high-quality model
         try:
-            if target_lang == "English":
-                if self.engines["to_english"] is None:
-                    print("[Status] Loading Engine: Indian -> English (Hold on...)")
-                    self.engines["to_english"] = pipeline("text2text-generation", model=self.model_mul_en)
-                res = self.engines["to_english"](text)
-                return res[0]['generated_text']
-            else:
-                if self.engines["to_indian"] is None:
-                    print("[Status] Loading Engine: English -> Indian (Hold on...)")
-                    self.engines["to_indian"] = pipeline("text2text-generation", model=self.model_en_mul)
-                prefix = lang_codes.get(target_lang, ">>hin<<")
-                res = self.engines["to_indian"](f"{prefix} {text}")
-                return res[0]['generated_text']
+            if self.translator is None:
+                print("[Status] Loading High-Accuracy English Model...")
+                self.translator = pipeline("text2text-generation", model=self.model_name)
+            
+            # Simple, direct translation for better grammar
+            res = self.translator(text)
+            return res[0]['generated_text']
         except Exception as e:
-            print(f"[Critical Error] Translation failed: {e}")
-            return f"[Error: {str(e)}]"
+            return f"[Translation error: {str(e)}]"