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import streamlit as st | |
from .navigation import go_to_home | |
def welcome(): | |
st.markdown(''' | |
<h1 align='center'> TrendFlow</h1> | |
<p align='center'> | |
<a href = "https://github.com/leoxiang66/research-trends-analysis"> | |
<img src="https://img.shields.io/github/stars/leoxiang66/research-trends-analysis.svg?style=social"> | |
</a> | |
<a href = "https://leoxiang66.github.io/research-trends-analysis/"><img src="https://img.shields.io/website?label=documentation&up_message=online&url=https://leoxiang66.github.io/research-trends-analysis/"> </a> | |
<a href="https://pypi.org/project/TrendFlow/"><img src="https://badge.fury.io/py/trendflow.svg" alt="PyPI version" /> </a> | |
<a href="https://discord.gg/P5Y3FHgHRz"> | |
<img alt="chat on Discord" src="https://img.shields.io/discord/1091063040662843565?logo=discord"> | |
</a> | |
</p> | |
TrendFlow is an advanced framework that uses deep learning techniques to analyze research trends. This powerful framework offers a wide range of analytical capabilities, including literature clustering, trend generation, and trend summarization. With TrendFlow, you can gain insights into emerging research topics and stay up-to-date on the latest advancements in your field. | |
''', unsafe_allow_html=True) | |
st.markdown( | |
""" | |
<style> | |
div.stButton > button:first-child { | |
margin-left: auto; | |
margin-right: auto; | |
display: block; | |
} | |
</style> | |
""", | |
unsafe_allow_html=True, | |
) | |
# 添加一个居中的按钮 | |
st.button("Get Started", on_click=go_to_home) | |