Update app.py

app.py

@@ -1,37 +1,34 @@
-import gradio as gr
-import torch
-from transformers import AutoModelWithLMHead, AutoTokenizer
-
 tokenizer = AutoTokenizer.from_pretrained('microsoft/DialoGPT-small', padding_side='right')
 model = AutoModelWithLMHead.from_pretrained('tomkr000/scottbotai')
 
-def chat(message, history):
-    new_user_input_ids = tokenizer.encode(message + tokenizer.eos_token, return_tensors='pt')
-    bot_input_ids = torch.cat([chat_history_ids, new_user_input_ids], dim=-1) if step > 0 else new_user_input_ids
-    
-    chat_history_ids = model.generate(
-    bot_input_ids, max_length=200,
-    pad_token_id=tokenizer.eos_token_id,  
-    no_repeat_ngram_size=3,       
-    do_sample=True, 
-    top_k=100, 
-    top_p=0.7,
-    temperature = 0.8
-    )
-
-    response = tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)
 
+def chat(message, history=[]):
+            
+    inputs = tokenizer.encode(message + tokenizer.eos_token, return_tensors="pt")
+                
+    reply_ids = model.generate(
+                        inputs, max_length=1000,
+                        pad_token_id=tokenizer.eos_token_id,  
+                        no_repeat_ngram_size=3,       
+                        do_sample=True, 
+                        top_k=100, 
+                        top_p=0.7,
+                        temperature = 0.8
+                        )
+        
+    response = tokenizer.decode(reply_ids[:,inputs.shape[1]:][0], skip_special_tokens=True)
+        
     history.append((message, response))
-
+    
     return history, history
+         
 
-chatbot = gr.Chatbot().style(color_map=("green", "pink"))
+# chatbot = gr.Chatbot().style(color_map=("green", "pink"))
 
 demo = gr.Interface(
-    chat,
-    ["text", "state"],
-    [chatbot, "state"],
+    fn=chat,
+    inputs = ["text", "state"],
+    outputs = ['chatbot', "state"],
     allow_flagging="never",
-)
+        ).launch()
 
-demo.launch()