Update app.py

app.py

@@ -1,52 +1,58 @@
-from transformers import AutoModelForCausalLM, AutoTokenizer
-from transformers import BlenderbotForConditionalGeneration
+from transformers import AutoModelForCausalLM, AutoTokenizer,BlenderbotForConditionalGeneration
 import torch
 import gradio as gr
 
-# model_name = "facebook/blenderbot-400M-distill"
+#model_name = "facebook/blenderbot-400M-distill"
 model_name = "microsoft/DialoGPT-medium"
-chat_tokenizer = AutoTokenizer.from_pretrained(model_name)
+chat_token = AutoTokenizer.from_pretrained(model_name)
 model = AutoModelForCausalLM.from_pretrained(model_name)
 
-def conversation(user_input, chat_history=[]):
-    user_input_ids = chat_tokenizer(user_input+chat_tokenizer.eos_token, return_tensors="pt").input_ids
+def converse(user_input, chat_history=[]):
+    user_input_ids = chat_token(user_input + chat_token.eos_token, return_tensors='pt').input_ids
 
-    # maintain history in the tensor
-    chatbot_input_ids = torch.cat([torch.LongTensor(chat_hostory), user_input_ids], dim=-1)
+    # keep history in the tensor
+    chatbot_input_ids = torch.cat([torch.LongTensor(chat_history), user_input_ids], dim=-1)
 
-    # ger response
-    chat_history = model.generate(chatbot_input_ids, max_length=1000, pad_token_id=chat_tokenizer.eos_token_id).tolist()
+    # get response 
+    chat_history = mdl.generate(chatbot_input_ids, max_length=1000, pad_token_id=chat_token.eos_token_id).tolist()
     print(chat_history)
 
-    response = chat_tokenizer.decode(chat_history[0]).split("<|endoftext|>")
-    print("Starting to print response")
+    response = chat_token.decode(chat_history[0]).split("<|endoftext|>")
+    
+    print("Starting to print response...")
     print(response)
-
+    
     # html for display
-    html = "<div class='mychatbot'>"
-    for x, msg in enumerate(response):
-        if x%2 !=0:
-            msg = "ChatBot:" + msg
-            clazz = "bot"
-        else:
-            clazz = "user"
-
-        print("Value of x:")
+    html = "<div class='mybot'>"
+    for x, mesg in enumerate(response):
+        if x%2!=0 :
+           mesg="Bot:" + mesg
+           clazz = "bot" 
+        else :
+           clazz = "user"
+        
+        print("value of x")
         print(x)
-        print("Message:")
-        print(msg)
-        html += "<div class='msg {}'></div>".format(clazz, msg)
+        print("message")
+        print (mesg)
+        
+        html += "<div class='mesg {}'> {}</div>".format(clazz, mesg)
     html += "</div>"
     print(html)
     return html, chat_history
 
-# UX
+
+
 css = """
-.mychatbot {display:flex;flex-direction:column}
-.msg {padding:5px;margin-bottom:5px;border-radius:5px;width:75%}
-.msg.user {background-color:lightblue;color:white}
-.msg.bot {background-color:orange;color:white,align-self:self-end}
-.footer
+.mybot {display:flex;flex-direction:column}
+.mesg {padding:5px;margin-bottom:5px;border-radius:5px;width:75%}
+.mesg.user {background-color:lightblue;color:white}
+.mesg.bot {background-color:orange;color:white,align-self:self-end}
+.footer {display:none !important}
 """
-in_text = gr.inputs.Textbox(placeholder="Let's start a chat...")
-gr.Interface(fn=conversation, theme="default", inputs=[in_text, "state"], outputs=["html", "state"], css=css).launch()
+in_text = gr.inputs.Textbox(placeholder="Let's start a chat")
+gr.Interface(fn=converse,
+             theme="default",
+             inputs=[in_text, "state"],
+             outputs=["html", "state"],
+             css=css).launch()