Update app.py

app.py

@@ -93,7 +93,7 @@ out=grad.Textbox(lines=1, label="Genereated Question")
 grad.Interface(text2text, inputs=[context,ans], outputs=out).launch()
 '''
 
-#5.21
+'''5.21
 from transformers import AutoTokenizer, AutoModelWithLMHead
 import gradio as grad
 text2text_tkn = AutoTokenizer.from_pretrained("deep-learning-analytics/wikihow-t5-small")
@@ -118,4 +118,70 @@ def text2text_summary(para):
 
 para=grad.Textbox(lines=10, label="Paragraph", placeholder="Copy paragraph")
 out=grad.Textbox(lines=1, label="Summary")
-grad.Interface(text2text_summary, inputs=para, outputs=out).launch()
+grad.Interface(text2text_summary, inputs=para, outputs=out).launch()
+'''
+
+#5.28
+from transformers import AutoModelForCausalLM, AutoTokenizer,BlenderbotForConditionalGeneration
+import torch
+
+
+chat_tkn = AutoTokenizer.from_pretrained("microsoft/DialoGPT-medium")
+mdl = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-medium")
+
+
+#chat_tkn = AutoTokenizer.from_pretrained("facebook/blenderbot-400M-distill")
+#mdl = BlenderbotForConditionalGeneration.from_pretrained("facebook/blenderbot-400M-distill")
+
+def converse(user_input, chat_history=[]):
+    
+    user_input_ids = chat_tkn(user_input + chat_tkn.eos_token, return_tensors='pt').input_ids
+
+    # keep history in the tensor
+    bot_input_ids = torch.cat([torch.LongTensor(chat_history), user_input_ids], dim=-1)
+
+    # get response 
+    chat_history = mdl.generate(bot_input_ids, max_length=1000, pad_token_id=chat_tkn.eos_token_id).tolist()
+    print (chat_history)
+
+    
+    response = chat_tkn.decode(chat_history[0]).split("<|endoftext|>")
+    
+    print("starting to print response")
+    print(response)
+    
+    # html for display
+    html = "<div class='mybot'>"
+    for x, mesg in enumerate(response):
+        if x%2!=0 :
+           mesg="Alicia:"+mesg
+           clazz="alicia"
+        else :
+           clazz="user"
+        
+        
+        print("value of x")
+        print(x)
+        print("message")
+        print (mesg)
+        
+        html += "<div class='mesg {}'> {}</div>".format(clazz, mesg)
+    html += "</div>"
+    print(html)
+    return html, chat_history
+
+import gradio as grad
+
+css = """
+.mychat {display:flex;flex-direction:column}
+.mesg {padding:5px;margin-bottom:5px;border-radius:5px;width:75%}
+.mesg.user {background-color:lightblue;color:white}
+.mesg.alicia {background-color:orange;color:white,align-self:self-end}
+.footer {display:none !important}
+"""
+text=grad.inputs.Textbox(placeholder="Lets chat")
+grad.Interface(fn=converse,
+             theme="default",
+             inputs=[text, "state"],
+             outputs=["html", "state"],
+             css=css).launch()