Update app.py

app.py

@@ -314,23 +314,17 @@ registration_interface = gr.Interface(
 #     outputs="text",
 # )
 
-# Load the model and tokenizer
-tokenizer = AutoTokenizer.from_pretrained("ahmed-7124/dgptAW")
-model = AutoModelForCausalLM.from_pretrained("ahmed-7124/dgptAW")
-
-def answer_medical_query(query):
-    try:
-        # Tokenize the input query
-        inputs = tokenizer(query, return_tensors="pt")
-        
-        # Generate a response
-        outputs = model.generate(**inputs, max_new_tokens=150, temperature=0.7, top_k=50)
-        
-        # Decode the response
-        response = tokenizer.decode(outputs[0], skip_special_tokens=True)
-        return response
-    except Exception as e:
-        return f"An error occurred while generating a response: {e}"
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+try:
+    tokenizer = AutoTokenizer.from_pretrained("ahmed-7124/dgptAW")
+    model = AutoModelForCausalLM.from_pretrained("ahmed-7124/dgptAW")
+    print("Model and tokenizer loaded successfully!")
+except Exception as e:
+    print(f"Error loading tokenizer or model: {e}")
+    print("Trying with GPT-2 tokenizer as a fallback...")
+    tokenizer = AutoTokenizer.from_pretrained("gpt2")
+    model = AutoModelForCausalLM.from_pretrained("ahmed-7124/dgptAW")