Update app.py

app.py

@@ -62,19 +62,15 @@ demo = gr.ChatInterface(
 
 if __name__ == "__main__":
     demo.launch()
+
+from transformers import pipeline
 import gradio as gr
-from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM
-import torch
 
-model_dir = "./"  # your model folder
-tokenizer = AutoTokenizer.from_pretrained(model_dir)
-model = AutoModelForCausalLM.from_pretrained(model_dir)
+pipe = pipeline("text-generation", model="kberta2014/MedicalChatBot")
 
-generator = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if torch.cuda.is_available() else -1)
+def chat(message):
+    return pipe(message, max_new_tokens=100, do_sample=True)[0]['generated_text']
 
-def generate_answer(prompt):
-    output = generator(prompt, max_length=100, do_sample=True, top_p=0.95, temperature=0.7)
-    return output[0]['generated_text']
+gr.Interface(fn=chat, inputs="text", outputs="text", title="🩺 Medical ChatBot").launch()
 
-gr.Interface(fn=generate_answer, inputs="text", outputs="text", title="Medical Chatbot").launch()