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 = "