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from matplotlib.pyplot import get
from matplotlib.style import available
import streamlit as st
import numpy as np
import pandas as pd
import streamlit.components.v1 as components
from millify import millify
from utils.utils_display import get_current_date, get_json_from_date, get_available_dates, render_st_from_chapter_number, get_current_global_step
from utils.constants import preface_disclaimer
st.set_page_config(page_title="Bloom Book",layout='wide')
BATCH_SIZE=2048
SEQ_LENGTH=2048
curr_date = get_current_date()
# set_png_as_page_bg("data/image/bloom-book-bg.png") #
st.markdown("<h1 style='text-align: center; color: grey;'>📖 BLOOM Book 📖 </h1>", unsafe_allow_html=True)
available_dates = get_available_dates()
available_chapters = ("Preface", ) + tuple(available_dates)
st.sidebar.image(
"https://assets.website-files.com/6139f3cdcbbff3a68486761d/613cd8997b270da063e230c5_Tekengebied%201-p-2000.png",
use_column_width=True
)
st.sidebar.title(
"Chapters browser"
)
st.sidebar.markdown(
"You can freely browse the different chapters - ie example prompts from different people - and see the results."
)
selected_date = st.sidebar.selectbox(
"Please select the chapter you want to read:",
available_chapters
)
if selected_date != "Preface":
current_global_step = get_current_global_step(selected_date)
seen_tokens = BATCH_SIZE * SEQ_LENGTH * current_global_step
st.markdown("<h2 style='text-align: center; color: grey;'> Chapter {} </h2>".format(selected_date), unsafe_allow_html=True)
st.markdown("<h3 style='text-align: center; color: grey;'> Global step: {} - Seen tokens: {} </h3>".format(current_global_step, millify(seen_tokens)), unsafe_allow_html=True)
st.markdown("<h5 style='text-align: center; color: grey;'> Click into the text cards to visualize the answers </h5>", unsafe_allow_html=True)
selected_format = st.sidebar.selectbox('Visualize as:', ["HTML","JSON"])
suffixes = ["greedy", "nucleus"]
if selected_format == "HTML":
user_input = st.sidebar.text_input("Search for a specific prompt: ", "")
render_st_from_chapter_number(selected_date, suffixes, user_input)
elif selected_format == "JSON":
suffix = st.sidebar.selectbox('Decoding strategy:', ["greedy","nucleus"])
json_output = get_json_from_date(selected_date, suffix)
st.json(json_output)
else:
st.markdown("<h3 style='text-align: center; color: grey;'> Welcome to the <i> BLOOM Book </i>. Here you can read generations from the main model based on prompts provided by the community. </h3> ", unsafe_allow_html=True)
st.markdown("""<h3 style='text-align: center; color: grey;'> Follow the main model's training <a href='https://huggingface.co/bigscience/tr11-176B-ml-logs' target="_blank"> here </a> </h3> """, unsafe_allow_html=True)
st.markdown("""<h3 style='text-align: center; color: grey;'> Try your own prompts? Check the <a href='https://forms.gle/2L7jkZt8MS8VDy2ZA' target="_blank"> Google Form </a> </h3> """, unsafe_allow_html=True)
st.markdown("{}".format(preface_disclaimer), unsafe_allow_html=True)
final_html =""" """ #TODO: add preface
chapter = components.html(
final_html,
height=600,
) |