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from transformers import BlenderbotTokenizer, BlenderbotForConditionalGeneration |
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import torch |
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import gradio as gr |
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device = "cuda" if torch.cuda.is_available() else "cpu" |
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model_name = "./blenderbot-1B-distill" |
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tokenizer = BlenderbotTokenizer.from_pretrained(model_name) |
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model = BlenderbotForConditionalGeneration.from_pretrained(model_name) |
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model.to(device) |
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def get_reply(response, history = []): |
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response = input("You: ") |
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history.append(response) |
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if response.endswith(("bye", "Bye", "bye.", "Bye.")): |
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return "<div class='chatbot'>Chatbot restarted</div>", [] |
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if len(history) > 4: history = history[-4:] |
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inputs = tokenizer(" ".join(history), return_tensors="pt") |
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inputs.to(device) |
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outputs = model.generate(**inputs) |
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reply = tokenizer.decode(outputs[0][1:-1]).strip() |
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history.append(reply) |
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html = "<div class='chatbot'>" |
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for m, msg in enumerate(history): |
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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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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=get_reply, |
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theme="default", |
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inputs=[gr.inputs.Textbox(placeholder="How are you?"), |
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"state"], |
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outputs=["html", "state"], |
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enable_queue=True, |
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css=css).launch(debug=True) |