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import streamlit as st | |
from streamlit_option_menu import option_menu | |
from core.search_index import index, search | |
from interface.components import component_show_search_result, component_text_input | |
def page_landing_page(container): | |
with container: | |
st.header("π§ Neural Search π") | |
st.markdown( | |
"This is a tool to allow indexing & search content using neural capabilities" | |
) | |
def page_search(container): | |
with container: | |
st.title("Query me!") | |
## SEARCH ## | |
query = st.text_input("Query") | |
if st.button("Search"): | |
st.session_state['search_results'] = search( | |
queries=[query], | |
pipeline=st.session_state['search_pipeline'], | |
) | |
if 'search_results' in st.session_state: | |
component_show_search_result( | |
container=container, | |
results=st.session_state['search_results'][0] | |
) | |
def page_index(container): | |
with container: | |
st.title("Index time!") | |
input_funcs = { | |
"Raw Text": (component_text_input, "card-text"), | |
} | |
selected_input = option_menu( | |
"Input Text", | |
list(input_funcs.keys()), | |
icons=[f[1] for f in input_funcs.values()], | |
menu_icon="list", | |
default_index=0, | |
orientation="horizontal", | |
) | |
corpus = input_funcs[selected_input][0](container) | |
if len(corpus) > 0: | |
index_results = None | |
if st.button("Index"): | |
index_results = index( | |
corpus, | |
st.session_state['index_pipeline'], | |
) | |
if index_results: | |
st.write(index_results) |