Update app.py

app.py

@@ -27,23 +27,23 @@ def wingpt(model_name, sl, tl, input_text):
        device_map="auto"
     )
     tokenizer = AutoTokenizer.from_pretrained(model_name)
-    
+    input_json = '{"input_text": input_text}'
     messages = [
-       {"role": "system", "content": f"Translate this from {sl} to {tl} language"}, 
+       {"role": "system", "content": f"Translate this to {tl} language"}, 
        {"role": "user", "content": input_text}
     ]
     
     text = tokenizer.apply_chat_template(
        messages,
        tokenize=False,
-       add_generation_prompt=False
+       add_generation_prompt=True
     )
     model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
     
     generated_ids = model.generate(
        **model_inputs,
        max_new_tokens=512,
-       temperature=0
+       temperature=0.1
     )
     
     generated_ids = [
@@ -147,7 +147,7 @@ if submit_button:
         output_ids = model.generate(input_ids)
         # Decode the translated text
         translated_text = tokenizer.decode(output_ids[0], skip_special_tokens=True)
-    if 'Unbabel' in model_name:   
+    elif 'Unbabel' in model_name:   
         pipe = pipeline("text-generation", model=model_name, torch_dtype=torch.bfloat16, device_map="auto")
         # We use the tokenizer’s chat template to format each message - see https://huggingface.co/docs/transformers/main/en/chat_templating
         messages = [{"role": "user",
@@ -159,7 +159,7 @@ if submit_button:
         if start_marker in translated_text:
             translated_text = translated_text.split(start_marker)[1].strip()
         translated_text = translated_text.replace('Answer:', '').strip() if translated_text.startswith('Answer:') else translated_text
-    if 'Argos' in model_name:
+    elif 'Argos' in model_name:
         import argostranslate.translate       
         # Translate
         try:
@@ -169,7 +169,7 @@ if submit_button:
             translated_text = f"No Argos model for {sselected_language} to {tselected_language}. Try other model or languages combination!"
         except Exception as error:
             translated_text = error
-    if model_name == "winninghealth/WiNGPT-Babel-2":      
+    elif model_name == "winninghealth/WiNGPT-Babel-2":      
         translated_text = wingpt(model_name, sselected_language, tselected_language, input_text)
         
     # Display the translated text