Update app.py
Browse files
app.py
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@@ -1,30 +1,25 @@
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from transformers import pipeline
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import gradio as gr
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# 使用公開支援中文的 GPT2 模型
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generator = pipeline("text-generation", model="ckiplab/gpt2-base-chinese",
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tokenizer="ckiplab/gpt2-base-chinese")
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def chat_fn(message, history):
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history = history or []
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input_text = "\n".join(history + [f"你: {message}", "AI:"])
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-
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output = generator(input_text, max_new_tokens=80, pad_token_id=0)[0]["generated_text"]
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response = output.split("AI:")[-1].strip().split("你:")[0].strip()
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history.append(f"你: {message}")
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history.append(f"AI: {response}")
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# 將歷史轉換成 [(user, bot), ...] 格式
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messages = [(history[i], history[i+1]) for i in range(0, len(history)-1, 2)]
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return messages, history
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with gr.Blocks() as demo:
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chatbot = gr.Chatbot(label="中文聊天機器人", type="
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state = gr.State([])
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textbox = gr.Textbox(placeholder="請輸入訊息")
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textbox.submit(chat_fn, [textbox, state], [chatbot, state])
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textbox.submit(lambda: "", None, textbox)
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demo.launch()
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from transformers import pipeline
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import gradio as gr
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generator = pipeline("text-generation", model="ckiplab/gpt2-base-chinese",
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tokenizer="ckiplab/gpt2-base-chinese")
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def chat_fn(message, history):
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history = history or []
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input_text = "\n".join(history + [f"你: {message}", "AI:"])
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output = generator(input_text, max_new_tokens=80, pad_token_id=0)[0]["generated_text"]
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response = output.split("AI:")[-1].strip().split("你:")[0].strip()
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history.append(f"你: {message}")
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history.append(f"AI: {response}")
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messages = [(history[i], history[i+1]) for i in range(0, len(history)-1, 2)]
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return messages, history
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with gr.Blocks() as demo:
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chatbot = gr.Chatbot(label="中文聊天機器人", type="tuples")
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state = gr.State([])
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textbox = gr.Textbox(placeholder="請輸入訊息")
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textbox.submit(chat_fn, [textbox, state], [chatbot, state])
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textbox.submit(lambda: "", None, textbox)
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demo.launch()
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