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from transformers import AutoModelForCausalLM, AutoTokenizer |
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import torch |
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tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-medium") |
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model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-medium") |
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def predict(input, history=[]): |
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new_user_input_ids = tokenizer.encode(input + tokenizer.eos_token, return_tensors='pt') |
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bot_input_ids = torch.cat([torch.LongTensor(history), new_user_input_ids], dim=-1) |
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history = model.generate(bot_input_ids, max_length=1000, pad_token_id=tokenizer.eos_token_id).tolist() |
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response = tokenizer.decode(history[0]).split("<|endoftext|>") |
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response.remove("") |
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html = "<div class='chatbot'>" |
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for m, msg in enumerate(response): |
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cls = "user" if m%2 == 0 else "bot" |
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html += "<div class='msg {}'> {}</div>".format(cls, msg) |
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html += "</div>" |
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return html, history |
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import gradio as gr |
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css = """ |
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.chatbox {display:flex;flex-direction:column} |
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.msg {padding:4px;margin-bottom:4px;border-radius:4px;width:80%} |
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.msg.user {background-color:cornflowerblue;color:white} |
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.msg.bot {background-color:lightgray;align-self:self-end} |
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.footer {display:none !important} |
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""" |
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gr.Interface(fn=predict, |
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theme="default", |
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inputs=[gr.inputs.Textbox(placeholder="How are you?"), "state"], |
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outputs=["html", "state"], |
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css=css).launch() |
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