Update app.py

app.py

@@ -1,4 +1,5 @@
 import json
+
 import gradio as gr
 from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
 
@@ -6,18 +7,18 @@ from format.format_output import format_output
 from validate.validate_ingredients import validate_ingredients
 from device.get_device_id import get_device_id
 
-# Initialize the model and pipeline
 tokenizer = AutoTokenizer.from_pretrained("Ashikan/dut-recipe-generator")
 model = AutoModelForCausalLM.from_pretrained("Ashikan/dut-recipe-generator")
 pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=get_device_id())
 
 def perform_model_inference(ingredients_list):
-    # Clean up the ingredients
-    ingredients_list = [ingredient.strip() for ingredient in ingredients_list]
+    for ingredient_index in range(len(ingredients_list)):
+        ingredients_list[ingredient_index] = ingredients_list[ingredient_index].strip()
+
     input_text = '{"prompt": ' + json.dumps(ingredients_list)
 
-    # Perform model inference
     output = pipe(input_text, max_length=1024, temperature=0.1, do_sample=True, truncation=True)[0]["generated_text"]
+
     return format_output(output)
 
 def chat_function(history, user_input):