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import streamlit as st
settings = {}
def app():
st.markdown("""
<style>
div[data-testid="stForm"] {
border: 0;
}
.footer-custom {
position: fixed;
bottom: 0;
width: 100%;
color: var(--text-color);
max-width: 698px;
font-size: 14px;
height: 50px;
padding: 10px 0;
z-index: 50;
}
footer {
display: none !important;
}
.footer-custom a {
color: var(--text-color);
}
button[kind="formSubmit"]{
margin-top: 40px;
border-radius: 20px;
padding: 5px 20px;
font-size: 18px;
background-color: var(--primary-color);
}
#lfqa-model-parameters {
margin-bottom: 50px;
font-size: 36px;
}
#tts-model-parameters {
font-size: 36px;
margin-top: 50px;
}
.stAlert {
width: 250px;
margin-top: 32px;
}
</style>
""", unsafe_allow_html=True)
with st.form("settings"):
footer = """
<div class="footer-custom">
Streamlit app - <a href="https://www.linkedin.com/in/danijel-petkovic-573309144/" target="_blank">Danijel Petkovic</a> |
LFQA/DPR models - <a href="https://www.linkedin.com/in/blagojevicvladimir/" target="_blank">Vladimir Blagojevic</a> |
Guidance & Feedback - <a href="https://yjernite.github.io/" target="_blank">Yacine Jernite</a>
</div>
"""
st.markdown(footer, unsafe_allow_html=True)
st.title("LFQA model parameters")
settings["min_length"] = st.slider("Min length", 20, 80, st.session_state["min_length"],
help="Min response length (words)")
st.markdown("""<hr></hr>""", unsafe_allow_html=True)
settings["max_length"] = st.slider("Max length", 128, 320, st.session_state["max_length"],
help="Max response length (words)")
st.markdown("""<hr></hr>""", unsafe_allow_html=True)
col1, col2 = st.columns(2)
with col1:
settings["do_sample"] = st.checkbox("Use sampling", st.session_state["do_sample"],
help="Whether or not to use sampling ; use greedy decoding otherwise.")
with col2:
settings["early_stopping"] = st.checkbox("Early stopping", st.session_state["early_stopping"],
help="Whether to stop the beam search when at least num_beams sentences are finished per batch or not.")
st.markdown("""<hr></hr>""", unsafe_allow_html=True)
settings["num_beams"] = st.slider("Num beams", 1, 16, st.session_state["num_beams"],
help="Number of beams for beam search. 1 means no beam search.")
st.markdown("""<hr></hr>""", unsafe_allow_html=True)
settings["temperature"] = st.slider("Temperature", 0.0, 1.0, st.session_state["temperature"], step=0.1,
help="The value used to module the next token probabilities")
st.title("TTS model parameters")
settings["tts"] = st.selectbox(label="Engine", options=("Google", "HuggingFace"),
index=["Google", "HuggingFace"].index(st.session_state["tts"]),
help="Answer text-to-speech engine")
# Every form must have a submit button.
col3, col4, col5, col6 = st.columns(4)
with col3:
submitted = st.form_submit_button("Save")
with col4:
if submitted:
for k, v in settings.items():
st.session_state[k] = v
st.success('App settings saved successfully.')
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