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from transformers import AutoModelForCausalLM, AutoTokenizer | |
import gradio as gr | |
import torch | |
tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-medium") | |
tokenizer.padding_side = 'left' | |
model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-medium") | |
class ChatBot: | |
def __init__(self): | |
self.history = [] | |
def predict(self, input): | |
new_user_input_ids = tokenizer.encode(input + tokenizer.eos_token, return_tensors="pt") | |
flat_history = [item for sublist in self.history for item in sublist] | |
flat_history_tensor = torch.tensor(flat_history).unsqueeze(dim=0) # convert list to 2-D tensor | |
bot_input_ids = torch.cat([flat_history_tensor, new_user_input_ids], dim=-1) if self.history else new_user_input_ids | |
chat_history_ids = model.generate(bot_input_ids, max_length=2000, pad_token_id=tokenizer.eos_token_id) | |
self.history.append(chat_history_ids[:, bot_input_ids.shape[-1]:].tolist()[0]) | |
response = tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True) | |
return response | |
bot = ChatBot() | |
title = "👋🏻Welcome to Tonic's EZ Chat🚀" | |
description = "You can use this Space to test out the current model (DialoGPT-medium) or duplicate this Space and use it for any other model on 🤗HuggingFace. Join me on [Discord](https://discord.gg/fpEPNZGsbt) to build together." | |
examples = [["How are you?"]] | |
iface = gr.Interface( | |
fn=bot.predict, | |
title=title, | |
description=description, | |
examples=examples, | |
inputs="text", | |
outputs="text", | |
theme="ParityError/Anime" | |
) | |
iface.launch() | |