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Update app.py
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app.py
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import gradio as gr
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def
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with gr.Blocks() as demo:
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chatbot = gr.Chatbot(
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)
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demo.launch()
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from transformers import AutoModel, AutoTokenizer
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import gradio as gr
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tokenizer = AutoTokenizer.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True)
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model = AutoModel.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True)
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#.half().cuda()
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model = model.eval()
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# def add_text(history, text):
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# history = history + [(text, None)]
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# return history, ""
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# def add_file(history, file):
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# history = history + [((file.name,), None)]
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# return history
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# def bot(history):
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# response = "**That's cool!**"
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# history[-1][1] = response
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# return history
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def predict(input, history=None):
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if history is None:
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history = []
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response, history = model.chat(tokenizer, input, history)
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return history, history
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with gr.Blocks() as demo:
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chatbot = gr.Chatbot()
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msg = gr.Textbox()
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clear = gr.Button("Clear")
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def user(user_message, history):
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return "", history + [[user_message, None]]
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def bot(msg, history):
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# bot_message = random.choice(["How are you?", "I love you", "I'm very hungry"])
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bot_message = predict(msg, history)
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history[-1][1] = ""
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for character in bot_message:
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history[-1][1] += character
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time.sleep(0.05)
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yield history
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msg.submit(user, [msg, chatbot], [msg, chatbot], queue=False).then(
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bot, [msg, chatbot], [msg, chatbot]
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clear.click(lambda: None, None, chatbot, queue=False)
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demo.queue()
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demo.launch()
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# txt.submit(predict, [txt, state], [chatbot, state])
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# button.click(predict, [txt, state], [chatbot, state])
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# btn.upload(add_file, [chatbot, btn], [chatbot]).then(
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# bot, chatbot, chatbot
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# )
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demo.launch()
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