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Runtime error
yentinglin
commited on
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•
ab13bd6
1
Parent(s):
be6cc22
Create app.py
Browse files
app.py
ADDED
@@ -0,0 +1,115 @@
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import gradio as gr
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from text_generation import Client
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# text-generation 0.6.0
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eos_token = "</s>"
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def _concat_messages(messages):
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message_text = ""
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for message in messages:
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if message["role"] == "system":
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message_text += "<|system|>\n" + message["content"].strip() + "\n"
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elif message["role"] == "user":
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message_text += "<|user|>\n" + message["content"].strip() + "\n"
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elif message["role"] == "assistant":
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message_text += "<|assistant|>\n" + message["content"].strip() + eos_token + "\n"
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else:
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raise ValueError("Invalid role: {}".format(message["role"]))
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return message_text
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endpoint_url = "http://ec2-52-193-118-191.ap-northeast-1.compute.amazonaws.com:8080"
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client = Client(endpoint_url, timeout=120)
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def generate_response(user_input, max_new_token: 100, top_p, temperature, top_k, do_sample, repetition_penalty):
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msg = _concat_messages([
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{"role": "system", "content": "你是一個由國立台灣大學的NLP實驗室開發的大型語言模型。你基於Transformer架構被訓練,並已經經過大量的台灣中文語料庫的訓練。你的設計目標是理解和生成優雅的繁體中文,並具有跨語境和跨領域的對話能力。使用者可以向你提問任何問題或提出任何話題,並期待從你那裡得到高質量的回答。你應該要盡量幫助使用者解決問題,提供他們需要的資訊,並在適當時候給予建議。"},
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{"role": "user", "content": user_input},
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])
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msg += "<|assistant|>\n"
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res = client.generate(msg, stop_sequences=["<|assistant|>", eos_token, "<|system|>", "<|user|>"],
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max_new_tokens=1000)
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return [("assistant", res.generated_text)]
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with gr.Blocks() as demo:
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# github_banner_path = 'https://raw.githubusercontent.com/ymcui/Chinese-LLaMA-Alpaca/main/pics/banner.png'
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# gr.HTML(f'<p align="center"><a href="https://github.com/ymcui/Chinese-LLaMA-Alpaca"><img src={github_banner_path} width="700"/></a></p>')
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# gr.Markdown("> 为了促进大模型在中文NLP社区的开放研究,本项目开源了中文LLaMA模型和指令精调的Alpaca大模型。这些模型在原版LLaMA的基础上扩充了中文词表并使用了中文数据进行二次预训练,进一步提升了中文基础语义理解能力。同时,中文Alpaca模型进一步使用了中文指令数据进行精调,显著提升了模型对指令的理解和执行能力。")
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chatbot = gr.Chatbot()
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with gr.Row():
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with gr.Column(scale=4):
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with gr.Column(scale=12):
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user_input = gr.Textbox(
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show_label=False,
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placeholder="Shift + Enter发送消息...",
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lines=10).style(
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container=False)
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with gr.Column(min_width=32, scale=1):
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submitBtn = gr.Button("Submit", variant="primary")
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with gr.Column(scale=1):
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emptyBtn = gr.Button("Clear History")
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max_new_token = gr.Slider(
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0,
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4096,
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value=512,
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step=1.0,
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label="Maximum New Token Length",
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interactive=True)
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top_p = gr.Slider(0, 1, value=0.9, step=0.01,
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label="Top P", interactive=True)
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temperature = gr.Slider(
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0,
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1,
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value=0.5,
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step=0.01,
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label="Temperature",
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interactive=True)
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top_k = gr.Slider(1, 40, value=40, step=1,
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label="Top K", interactive=True)
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do_sample = gr.Checkbox(
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value=True,
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label="Do Sample",
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info="use random sample strategy",
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interactive=True)
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repetition_penalty = gr.Slider(
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1.0,
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3.0,
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value=1.1,
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step=0.1,
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label="Repetition Penalty",
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interactive=True)
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params = [user_input, chatbot]
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predict_params = [
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chatbot,
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max_new_token,
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top_p,
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temperature,
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top_k,
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do_sample,
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repetition_penalty]
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submitBtn.click(
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generate_response,
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[user_input],
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[chatbot],
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queue=False).then(
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None,
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None,
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[user_input],
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queue=False)
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user_input.submit(
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generate_response,
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[user_input],
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[chatbot],
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queue=False).then(
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None,
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None,
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[user_input],
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queue=False)
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submitBtn.click(lambda: None, [], [user_input])
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emptyBtn.click(lambda: chatbot.reset(), outputs=[chatbot], show_progress=True)
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demo.launch(share=True)
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