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from pyvis.network import Network
import streamlit as st
def explain(answer):
graph = Network(height="450px", width="100%")
sources_table = []
#all_reference_texts = ''
for nodewithscore in answer.source_nodes:
node = nodewithscore.node
from llama_index.core.schema import NodeRelationship
if NodeRelationship.SOURCE in node.relationships:
node_id = node.relationships[NodeRelationship.SOURCE].node_id
node_id = node_id.split('/')[-1]
title = node_id.split('.')[2].replace('_', ' ')
link = '.'.join(node_id.split('.')[:2])[:10]
link = f'https://arxiv.org/abs/{link}'
href = f'<a target="_blank" href="{link}">{title}</a>'
sources_table.extend([[href, node.text]])
#all_reference_texts = all_reference_texts + '\n' + node.text
else:
#st.write(node.text) TODO second level relationships
rel_map = node.metadata['kg_rel_map']
for concept in rel_map.keys():
#st.write(concept)
graph.add_node(concept, concept, title=concept)
rels = rel_map[concept]
for rel in rels:
graph.add_node(rel[1], rel[1], title=rel[1])
graph.add_edge(concept, rel[1], title=rel[0])
# --- display the query terms graph
st.session_state.graph_name = 'graph.html'
graph.save_graph(st.session_state.graph_name)
import streamlit.components.v1 as components
graphHtml = open(st.session_state.graph_name, 'r', encoding='utf-8')
source_code = graphHtml.read()
components.html(source_code, height = 500)
# --- display the reference texts table
import pandas as pd
df = pd.DataFrame(sources_table)
df.columns = ['paper', 'relevant text']
st.markdown(""" <style>
table[class*="dataframe"] {
font-size: 10px;
}
</style> """, unsafe_allow_html=True)
st.write(df.to_html(escape=False), unsafe_allow_html=True) |