Update app.py

app.py

@@ -20,28 +20,30 @@ examples = [["How are you?"]]
     
 tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-medium")  
 tokenizer.padding_side = 'left'    
+model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-medium")  
   
-model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-medium")     
-    
-def predict(input, history=[]):    
-    new_user_input_ids = tokenizer.encode(input, return_tensors="pt")    
-    
-    bot_input_ids = torch.cat([torch.tensor(history), new_user_input_ids], dim=-1) if history else new_user_input_ids    
-    
-    chat_history_ids = model.generate(bot_input_ids, max_length=4000, pad_token_id=tokenizer.eos_token_id)    
-    
-    response = tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)    
-        
-    return response    
-    
-iface = gr.Interface(    
-    fn=predict,    
-    title=title,    
-    description=description,    
-    examples=examples,    
-    inputs="text",    
-    outputs="text",    
-    theme="ParityError/Anime",    
-)    
-    
-iface.launch()    
+class ChatBot:  
+    def __init__(self):  
+        self.history = []  
+  
+    def predict(self, input):  
+        new_user_input_ids = tokenizer.encode(input + tokenizer.eos_token, return_tensors="pt")  
+        bot_input_ids = torch.cat([torch.tensor(self.history), new_user_input_ids], dim=-1) if self.history else new_user_input_ids  
+        chat_history_ids = model.generate(bot_input_ids, max_length=4000, pad_token_id=tokenizer.eos_token_id)  
+        self.history.append(chat_history_ids[:, bot_input_ids.shape[-1]:].tolist())  
+        response = tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)  
+        return response  
+  
+bot = ChatBot()  
+  
+iface = gr.Interface(  
+    fn=bot.predict,  
+    title=title,  
+    description=description,  
+    examples=examples,  
+    inputs="text",  
+    outputs="text",  
+    theme="ParityError/Anime",  
+)  
+  
+iface.launch()