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import streamlit as st
from ..form import form_controller
from typing import Dict, List, Union
from .options import PIPELINE_OPTIONS, CKIP_VISUALIZERS, CWN_VISUALIZERS
# from .options import JEFF_VISUALIZERS
def remove_input_data():
if "input_data" in st.session_state:
del st.session_state["input_data"]
def format_option(option: Union[str, Dict[str, str]]) -> str:
"""The format_options function formats each option in a list of options.
If `option` is a dict, the function will extract the value from the dict.
Args:
option (str or dict)
Returns:
a str
"""
if isinstance(option, dict):
return list(option.values())[0]
return option
def visualize_side_bar(ckip_nlp_models: List[str]):
with st.sidebar:
cols = st.columns(1)
cols[0].image(image=[
"https://avatars.githubusercontent.com/u/21136511?s=200&v=4",
"https://ckip.iis.sinica.edu.tw/files/ckip_logo.png",
"https://cool.ntu.edu.tw/images/thumbnails/1026478/4b4hIhKX9yZPOlnar6J5c3LItwwDlj9FhCw1kRzc",
],
width=100,
)
pipeline_options = form_controller(
control="select-box",
title="中文 NLP 管線處理：",
options=PIPELINE_OPTIONS,
on_change=remove_input_data,
)
model_options = None
if pipeline_options == "CKIP":
model_options = form_controller(
control="select-box",
title="NLP 模型：",
options=ckip_nlp_models,
key="model",
)
visualizers = {
"CKIP": CKIP_VISUALIZERS,
"CWN": CWN_VISUALIZERS,
# "JEFF": JEFF_VISUALIZERS,
}
active_visualizers = form_controller(
control="multi-select",
title="功能：",
options=visualizers[pipeline_options],
format_func=format_option,
)
st.markdown(
"## 📝 TODO 😢 ##"'\n'
"1. [ ] 自動爬文章 "'\n'
" （自動更新，登入問題？）"'\n'
"2. [ ] 分析不同語意並 cluster"'\n'
"3. [ ] 新的 NLP pipeline （用別的套件）"'\n'
"4. [ ] 語音和多模態"'\n'
)
return model_options, pipeline_options, active_visualizers
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