DUT_BioLLM / app.py
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from typing import Iterator
import gradio as gr
import torch
MAX_MAX_NEW_TOKENS = 4096
DEFAULT_MAX_NEW_TOKENS = 1024
MAX_INPUT_TOKEN_LENGTH = 4000
with gr.Blocks(css='style.css') as demo: # 使用gr.Blocks库创建的Web界面的开始。css='style.css'指定了界面的样式表。
gr.Markdown(DESCRIPTION) # 使用Markdown格式显示描述文本:DESCRIPTION
gr.DuplicateButton(value='Duplicate Space for private use', # 复制按钮,允许复制作为私人使用
elem_id='duplicate-button')
with gr.Group(): # 这是一个组,用于将一组元素组织在一起。
chatbot = gr.Chatbot(label='Chatbot')
with gr.Row(): # 这是一个行元素,将其中的元素排成一排
# 这是一个文本框,用户可以在其中输入消息。
textbox = gr.Textbox(
container=False,
show_label=False,
placeholder='Type a message...',
scale=10,
)
# 这是一个提交按钮,用户可以点击它来发送消息。
submit_button = gr.Button('Submit',
variant='primary',
scale=1,
min_width=0)
with gr.Row(): # 另一个行元素
retry_button = gr.Button('🔄 Retry', variant='secondary')
undo_button = gr.Button('↩️ Undo', variant='secondary')
clear_button = gr.Button('🗑️ Clear', variant='secondary')
saved_input = gr.State() # 这是一个状态变量,用于保存用户输入的消息
with gr.Accordion(label='Advanced options', open=False): # 是一个可折叠的高级选项部分,用户可以展开或收起,可调节训练中参数值。
system_prompt = gr.Textbox(label='System prompt',
value=DEFAULT_SYSTEM_PROMPT,
lines=6)
max_new_tokens = gr.Slider( # 滑块
label='Max new tokens',
minimum=1,
maximum=MAX_MAX_NEW_TOKENS,
step=1,
value=DEFAULT_MAX_NEW_TOKENS,
)
temperature = gr.Slider( # 预热值
label='Temperature',
minimum=0.1,
maximum=4.0,
step=0.1,
value=0.1,
)
top_p = gr.Slider(
label='Top-p (nucleus sampling)',
minimum=0.05,
maximum=1.0,
step=0.05,
value=0.9,
)
top_k = gr.Slider(
label='Top-k',
minimum=1,
maximum=1000,
step=1,
value=10,
)
repetition_penalty = gr.Slider(
label = 'Repetition_penalty',
minimum = 0.1,
maximum = 3.0,
step = 0.1,
value = 1.0,
)
gr.Examples(
examples=[
'What is the Fibonacci sequence?',
'Can you explain briefly what Python is good for?',
'How can I display a grid of images in SwiftUI?',
],
inputs=textbox,
outputs=[textbox, chatbot],
fn=process_example,
cache_examples=True,
)
demo.queue(max_size=20).launch()