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42fb3af 0ccfe4a 42fb3af 0ccfe4a 42fb3af | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 | #!/usr/bin/env python3
"""
Build the ALS knowledge graph from extracted entities + trials.
Run after scripts/extract_entities.py.
Usage:
uv run python scripts/build_graph.py
"""
from __future__ import annotations
import sys
from pathlib import Path
sys.path.insert(0, str(Path(__file__).parent.parent))
from dotenv import load_dotenv
load_dotenv()
from rich.console import Console
from config import ENTITIES_PATH, GRAPH_JSON_PATH, GRAPH_PICKLE_PATH, TRIALS_PATH
from graph.builder import build_graph
from graph.serializer import save_graph
console = Console()
def main() -> None:
console.print("[cyan]Building ALS knowledge graph...[/cyan]")
if not ENTITIES_PATH.exists():
console.print(
"[yellow]No entities.jsonl found — graph will be seeded only (no NER enrichment).[/yellow]"
)
console.print("[dim]Run first: uv run python scripts/extract_entities.py[/dim]\n")
G = build_graph(entities_path=ENTITIES_PATH, trials_path=TRIALS_PATH)
save_graph(G, pickle_path=GRAPH_PICKLE_PATH, json_path=GRAPH_JSON_PATH)
console.print(f"\n[bold green]Done![/bold green]")
console.print(f" Nodes: [bold]{G.number_of_nodes()}[/bold]")
console.print(f" Edges: [bold]{G.number_of_edges()}[/bold]")
console.print(f" Pickle: {GRAPH_PICKLE_PATH}")
console.print(f" JSON: {GRAPH_JSON_PATH}")
top = sorted(G.degree(), key=lambda x: x[1], reverse=True)[:5]
if top:
console.print("\n[dim]Most connected nodes:[/dim]")
for node_id, deg in top:
name = G.nodes[node_id].get("display_name", node_id)
console.print(f" [dim]{name} ({G.nodes[node_id].get('type', '?')}) — {deg} edges[/dim]")
console.print("\nTest a query with KG expansion:")
console.print(" [dim]uv run python main.py \"What is the role of C9orf72 in ALS?\"[/dim]")
if __name__ == "__main__":
main()
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