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chatbot / app.py

Update app.py

83d0216 almost 2 years ago

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	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 the right format
	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
	return response, history

	import gradio as gr

	demo = gr.Blocks()

	with demo:
	with gr.Row():
	output_chatbot = gr.outputs.Chatbot()
	output_state = gr.outputs.State()

	with gr.Row():
	input_text = gr.inputs.Textbox(label="write some text")
	input_state = gr.inputs.State()

	submit_button = gr.Button("Send")

	submit_button.click(predict, inputs=[input_text, input_state], outputs=[output_chatbot, output_state])

	demo.launch()