Update app.py

app.py

@@ -28,78 +28,11 @@ def predict(input, history=[]):
     # convert the tokens to text, and then split the responses into lines
     response = tokenizer.decode(history[0]).split("<|endoftext|>")
     response = [(response[i], response[i+1]) for i in range(0, len(response)-1, 2)]  # convert to tuples of list
-    #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 response, history
-    #return html, history
     
-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;margin-right:10px}
-.msg.bot {background-color:lightgray;align-self:self-end;margin-left:10px}
-.footer {display:none !important}
-"""
-
 gr.Interface(fn=predict,
-    theme="grass",
     title="DialoGPT-large",
     inputs=["text", "state"],
     outputs=["chatbot", "state"],
-    #css=css
-    ).launch()
-
-'''
-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
-    new_user_input_ids = tokenizer.encode(input + tokenizer.eos_token, return_tensors='pt')
-
-    # append the new user input tokens to the chat history
-    bot_input_ids = torch.cat([torch.LongTensor(history), new_user_input_ids], dim=-1)
-
-    # generate a response 
-    history = model.generate(bot_input_ids, max_length=1000, pad_token_id=tokenizer.eos_token_id).tolist()
-
-    # 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
-
-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()
-'''
-                     
+    ).launch()