Update app.py

app.py

@@ -1,11 +1,15 @@
+import gradio as gr
 from transformers import AutoModelForCausalLM, AutoTokenizer
 import torch
 
 tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-medium")
 model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-medium")
 
+
 def predict(input, history=[]):
     # tokenize the new input sentence
+    print(input)
+    print(tokenizer.eos_token)
     new_user_input_ids = tokenizer.encode(input + tokenizer.eos_token, return_tensors='pt')
 
     # append the new user input tokens to the chat history
@@ -16,30 +20,17 @@ def predict(input, history=[]):
 
     # convert the tokens to text, and then split the responses into lines
     response = tokenizer.decode(history[0]).split("<|endoftext|>")
-    response.remove("")
-    
-    # write some HTML
-    html = "<div class='chatbot'>"
-    for m, msg in enumerate(response):
-        cls = "user" if m%2 == 0 else "bot"
-        html += "<div class='msg {}'> {}</div>".format(cls, msg)
-    html += "</div>"
-    
-    return html, history
+    response = [(response[i], response[i+1]) for i in range(0, len(response)-1, 2)]  # convert to tuples of list
+    return response, history
 
-import gradio as gr
-
-css = """
-.chatbox {display:flex;flex-direction:column}
-.msg {padding:4px;margin-bottom:4px;border-radius:4px;width:80%}
-.msg.user {background-color:cornflowerblue;color:white}
-.msg.bot {background-color:lightgray;align-self:self-end}
-.footer {display:none !important}
-"""
-
-gr.Interface(fn=predict,
-             theme="default",
-             inputs=[gr.inputs.Textbox(placeholder="How are you?"), "state"],
-             outputs=["html", "state"],
-             css=css).launch()
-                     
+with gr.Blocks() as demo:
+    chatbot = gr.Chatbot()
+    state = gr.State([])
+    
+    with gr.Row():
+        txt = gr.Textbox(show_label=False, placeholder="Enter text and press enter").style(container=False)
+            
+    txt.submit(predict, [txt, state], [chatbot, state])
+            
+if __name__ == "__main__":
+    demo.launch()