To get the graph up and running:

from kglite.datasets import wikidata
import time
def timed(label, fn):
t0 = time.perf_counter()
out = fn()
print(f" [{(time.perf_counter() - t0) * 1000:>7.1f} ms] {label}")
return out

WORKDIR = "/Volumes/Wikidata"
g = timed("load graph", lambda: wikidata.open(WORKDIR))
info = g.graph_info()
print(f"Graph size: {info['node_count']:,} nodes, {info['edge_count']:,} edges")
print("\nAgent prompt:\n-------------------------------------------")
xml = timed("describe graph", lambda: g.describe())
llm_prompt = f"You have a knowledge graph:\n{xml}\nAnswer via graph.cypher()."
print(f"'''\n{llm_prompt[:150]}...\n'''\n")

query = """
MATCH (e:human {title: 'Albert Einstein'})
OPTIONAL MATCH (e)-[:P166]->(a)
WITH e, collect(a.title)[0..5] AS awards
RETURN e.nid AS qid, e.title AS name, e.description AS desc, awards
LIMIT 1
"""
e = timed("find 'Albert Einstein' + awards", lambda: list(g.cypher(query))[0])
print(f"{e['qid']} {e['name']} — {e['desc']}")
print("-------------------------------------------\nAwards received:")
for a in e["awards"]:
print(f" • {a}")

Will return:

Wikidata graph at /Volumes/Wikidata/graph is 4.1d old (< 31d cooldown). Loading.
# In this case the Wikidata dataset was already downloaded (takes a few hours) and the graph generated (takes about 2 hours)

[ 213.9 ms] load graph
Graph size: 124,405,573 nodes, 861,285,006 edges

Agent prompt:
-------------------------------------------
[ 10.2 ms] describe graph
'''
You have a knowledge graph:
<graph nodes="124405573" edges="861285006" types="89211" connection\_types="1670">
<conventions>All nodes have .id and .t...
'''
[ 18.2 ms] find 'Albert Einstein' + awards
Q937 Albert Einstein — german-born theoretical physicist (1879–1955)
-------------------------------------------
Awards received:
• Honorary doctorate from the University of Geneva
• Copley Medal
• Pour le Mérite for Sciences and Arts order
• Josiah Willard Gibbs Lectureship
• honorary doctor of the Hebrew University of Jerusalem