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import streamlit as st | |
import json | |
from datasets import load_dataset | |
st.set_page_config(page_title="Bot Issues", layout="wide") | |
st.title("Bot Issues") | |
def load_data(): | |
ds = load_dataset("loubnabnl/bot_issues", split="train") | |
return ds | |
def print_issue(events): | |
for event in events: | |
st.markdown("""---""") | |
masked_author = f"masked as {event['masked_author']}" if "masked_author" in event else "" | |
st.markdown(f"**Author:** {event['author']} {masked_author}, {event['action']} {event['type']} with title: {event['title']}") | |
st.markdown("Text:") | |
st.code(f"{event['text']}", language="html") | |
samples = load_data() | |
col1, _ = st.columns([2, 4]) | |
with col1: | |
index_example = st.number_input(f"Index of the chosen conversation from the existing {len(samples)}", min_value=0, max_value=len(samples)-1, value=0, step=1) | |
st.write(f"Issue size: {samples[index_example]['text_size_bots']}\n\n") | |
print_issue(samples[index_example]["old_events"]) | |