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| # https://ai-brewery.medium.com/conversational-chatbot-using-transformers-and-streamlit-73d621afde9 | |
| import streamlit as st | |
| import torch | |
| import transformers | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| def load_data(): | |
| tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-medium") | |
| model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-medium") | |
| return tokenizer, model | |
| tokenizer, model = load_data() | |
| st.write("Welcome to the Chatbot. I am still learning, please be patient") | |
| input = st.text_input('User:') | |
| if 'count' not in st.session_state or st.session_state.count == 6: | |
| st.session_state.count = 0 | |
| st.session_state.chat_history_ids = None | |
| st.session_state.old_response = '' | |
| else: | |
| st.session_state.count += 1 | |
| new_user_input_ids = tokenizer.encode(input + tokenizer.eos_token, return_tensors='pt') | |
| bot_input_ids = torch.cat([st.session_state.chat_history_ids, new_user_input_ids], dim=-1) if st.session_state.count > 1 else new_user_input_ids | |
| st.session_state.chat_history_ids = model.generate(bot_input_ids, max_length=5000, pad_token_id=tokenizer.eos_token_id) | |
| response = tokenizer.decode(st.session_state.chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True) | |
| if st.session_state.old_response == response: | |
| bot_input_ids = new_user_input_ids | |
| st.session_state.chat_history_ids = model.generate(bot_input_ids, max_length=5000, pad_token_id=tokenizer.eos_token_id) | |
| response = tokenizer.decode(st.session_state.chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True) | |
| st.write(f"Chatbot: {response}") | |
| st.session_state.old_response = response | |