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import json | |
import random | |
import streamlit as st | |
from datasets import load_from_disk | |
class Visualization: | |
def __init__(self, path_web_documents_dataset): | |
self.path_web_documents_dataset = path_web_documents_dataset | |
def visualization(self): | |
self.set_title() | |
self.load_dataset() | |
self.choose_document() | |
self.display_document() | |
def set_title(self): | |
st.title("Visualization of web documents") | |
def load_dataset(self): | |
st.header("Select the size of the dataset") | |
self.dataset = load_from_disk(self.path_web_documents_dataset) | |
opt_sizes = ["100", "300", "1000", "3000"] | |
size_dataset = st.selectbox( | |
"Select the size of the dataset", | |
options=opt_sizes, | |
) | |
self.dataset = self.dataset.select(range(int(size_dataset))) | |
def choose_document(self): | |
st.header("Choose a document") | |
if st.button("Select a random document"): | |
dct_idx = random.randint(a=0, b=self.dataset.num_rows - 1) | |
else: | |
dct_idx = 0 | |
idx = st.number_input( | |
f"Select a document among the first {self.dataset.num_rows} ones", | |
min_value=0, | |
max_value=self.dataset.num_rows - 1, | |
value=dct_idx, | |
step=1, | |
help=f"Index between 0 and {self.dataset.num_rows-1}", | |
) | |
self.current_doc = self.dataset[idx] | |
def display_document(self): | |
st.header("Document") | |
texts = self.current_doc["texts"] | |
images = self.current_doc["images"] | |
metadata = json.loads(self.current_doc["metadata"]) | |
for text, image, meta in zip(texts, images, metadata): | |
if text: | |
st.text(f"{text}\n\n") | |
elif image: | |
st.markdown(f"\n\n") | |
if __name__ == "__main__": | |
st.set_page_config(layout="wide") | |
path_web_documents_dataset = "./web_docs_final" # Find at s3://m4-datasets/trash/web_docs_final/ | |
visualization = Visualization(path_web_documents_dataset=path_web_documents_dataset) | |
visualization.visualization() | |