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from transformers import AutoModelForCausalLM, AutoTokenizer
from transformers import BlenderbotForConditionalGeneration
import torch
imprt gradio as gr
# model_name = "facebook/blenderbot-400M-distill"
model_name = "microsoft/DialoGPT-medium"
chat_tokenizer = 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
# maintain history in the tensor
chatbot_input_ids = torch.cat([torch.LongTensor(chat_hostory), 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()
print(chat_history)
response = chat_tokeniser.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
class = "bot"
else:
class = "user"
print("Value of x:")
print(x)
print("Message:")
print(msg)
html += "<div class='msg {}'></div>".format(class, msg)
html += "</div>"
print(html)
return html, chat_history
# UX
css = """
.mychat {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
"""
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() |