Update app.py

app.py

@@ -21,6 +21,7 @@ models = ["Helsinki-NLP",
           "t5-small", "t5-base", "t5-large",
           "google/flan-t5-small", "google/flan-t5-base", "google/flan-t5-large", "google/flan-t5-xl",
           "Argos", "Google",
+          "HuggingFaceTB/SmolLM3-3B",
           "utter-project/EuroLLM-1.7B", "utter-project/EuroLLM-1.7B-Instruct",
           "Unbabel/Tower-Plus-2B", "Unbabel/TowerInstruct-7B-v0.2", "Unbabel/TowerInstruct-Mistral-7B-v0.2",
           "openGPT-X/Teuken-7B-instruct-commercial-v0.4", "openGPT-X/Teuken-7B-instruct-v0.6"
@@ -63,10 +64,17 @@ def argos(sl, tl, input_text):
         print(error)
     return translated_text
 
-def google(sl, tl, input_text):  
-    url = os.environ['GCLIENT'] + f'sl={sl}&tl={tl}&q={input_text}'
-    response = requests.get(url)
-    return response.json()[0][0][0]
+class Translators:
+    def __init__(self, model_name: str, sl: str, tl: str, input_text: str):
+        print(self.get_class_method_callables())
+        self.model_name = model_name
+        self.sl, self.tl = sl, tl
+        self.input_text = input_text
+        
+    def google(self):  
+        url = os.environ['GCLIENT'] + f'sl={self.sl}&tl={self.tl}&q={self.input_text}'
+        response = requests.get(url)
+        return response.json()[0][0][0]
 
 def mtom(model_name, sl, tl, input_text):
     from transformers import M2M100ForConditionalGeneration, M2M100Tokenizer
@@ -100,8 +108,8 @@ def HelsinkiNLP(sl, tl, input_text):
     try: # Standard bilingual model
         model_name = f"Helsinki-NLP/opus-mt-{sl}-{tl}"
         pipe = pipeline("translation", model=model_name, device=-1)
-        # translation = pipe(input_text)
-        # return translation[0]['translation_text'], f'Translated from {sl} to {tl} with {model_name}.'
+        translation = pipe(input_text)
+        return translation[0]['translation_text'], f'Translated from {sl} to {tl} with {model_name}.'
     except EnvironmentError:
         try: # Tatoeba models
             model_name = f"Helsinki-NLP/opus-tatoeba-{sl}-{tl}"
@@ -120,6 +128,27 @@ def HelsinkiNLP(sl, tl, input_text):
     except KeyError as error:
         return f"Error: Translation direction {sl} to {tl} is not supported by Helsinki Translation Models", error     
 
+def smollm(model_name, sl, tl, input_text):
+    tokenizer = AutoTokenizer.from_pretrained(model_name)
+    model = AutoModelForCausalLM.from_pretrained(model_name)
+    prompt = f"""Translate the following {sl} text to {tl}, maintaining the original meaning and tone:
+    {input_text}
+    Translation:"""
+    inputs = tokenizer(prompt, return_tensors="pt")
+    outputs = model.generate(
+        inputs.input_ids,
+        max_length=len(inputs.input_ids[0]) + 150,
+        temperature=0.3,
+        do_sample=True
+    ) 
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return response.split("Translation:")[-1].strip()
+
+# Example usage
+english_text = "The weather today is beautiful and perfect for a picnic."
+spanish_translation = translate_text(english_text, "English", "Spanish")
+print(f"Spanish: {spanish_translation}")
+
 def flan(model_name, sl, tl, input_text):
     tokenizer = T5Tokenizer.from_pretrained(model_name, legacy=False)
     model = T5ForConditionalGeneration.from_pretrained(model_name)
@@ -303,7 +332,7 @@ def translate_text(input_text: str, sselected_language: str, tselected_language:
             translated_text = argos(sl, tl, input_text)
     
         elif model_name == 'Google':
-            translated_text = google(sl, tl, input_text)
+            translated_text = Translators('Google', sl, tl, input_text).google()
     
         elif "m2m" in model_name.lower():
             translated_text = mtom(model_name, sl, tl, input_text)
@@ -344,11 +373,14 @@ def translate_text(input_text: str, sselected_language: str, tselected_language:
         
         elif model_name.startswith('t5'):
             translated_text = tfive(model_name, sselected_language, tselected_language, input_text)
-    
+            
+        elif model_name == "HuggingFaceTB/SmolLM3-3B":
+            translated_text = smollm(model_name, sselected_language, tselected_language, input_text)
+            
     except Exception as error:
         translated_text = error
     finally:
-        print(translated_text, message_text)
+        print(input_text, translated_text, message_text)
         return translated_text, message_text
 
 # Function to swap dropdown values