Update app.py

app.py

@@ -5,23 +5,15 @@ import torch
 # Load pre-trained model and tokenizer
 tokenizer = AutoTokenizer.from_pretrained("ahmed792002/alzheimers_memory_support_ai")
 model = AutoModelForCausalLM.from_pretrained("ahmed792002/alzheimers_memory_support_ai")
-device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-model.to(device)  # Send the model to the correct device
-
-# Function to clean input text
-def clean_text(text):
-    return text.strip()  # Simply remove leading/trailing spaces
 
 # Chatbot function
 def chatbot(query, history, system_message, max_length, temperature, top_k, top_p):
     """
     Processes a user query through the specified model to generate a response.
     """
-    # Clean the input query
-    query = clean_text(query)
     
     # Tokenize input query
-    input_ids = tokenizer.encode(query, return_tensors="pt").to(device)
+    input_ids = tokenizer.encode(query, return_tensors="pt")=
     
     # Generate text using the model
     final_outputs = model.generate(
@@ -48,8 +40,6 @@ demo = gr.ChatInterface(
         gr.Slider(1, 100, value=50, step=1, label="Top-K"),  # Slider for top_k
         gr.Slider(0.1, 1.0, value=0.95, step=0.05, label="Top-P"),  # Slider for top_p
     ],
-    title="Custom Alzheimer's Memory Support AI",
-    description="This chatbot uses the fine-tuned model 'ahmed792002/alzheimers_memory_support_ai'. Customize settings like max length, temperature, top-k, and top-p for better results.",
 )
 
 if __name__ == "__main__":