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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()
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