| from ._graph import identifier |
| from .config import TARGETS |
|
|
|
|
| def create_indexes(graph, targets, prop, timeout): |
| for name in targets: |
| target = TARGETS[name] |
| field = prop or target.property |
| index = f'{target.label}_{field}_vector' if prop else target.index |
| dims = graph.run(f'MATCH (n:{target.label}) WHERE n.{identifier(field)} IS NOT NULL RETURN DISTINCT size(n.{identifier(field)}) AS dim') |
| if len(dims) != 1 or not 1 <= dims[0]['dim'] <= 4096: |
| raise ValueError(f'{name}: requires nonempty vectors with one dimension in 1..4096.') |
| existing = graph.run('SHOW INDEXES YIELD name,type,labelsOrTypes,properties,options WHERE name=$name RETURN type,labelsOrTypes,properties,options', name=index) |
| if existing: |
| row = existing[0] |
| if (row['type'], row['labelsOrTypes'], row['properties']) != ('VECTOR', [target.label], [field]) or row['options']['indexConfig'].get('vector.dimensions') != dims[0]['dim']: |
| raise ValueError('Existing index conflicts with requested vectors: ' + index) |
| else: |
| graph.run(f'CREATE VECTOR INDEX {identifier(index)} FOR (n:{target.label}) ON (n.{identifier(field)}) OPTIONS {{indexConfig: {{`vector.dimensions`: $dim, `vector.similarity_function`: "cosine"}}}}', dim=dims[0]['dim']) |
| graph.run('CALL db.awaitIndex($name,$timeout)', name=index, timeout=timeout) |
| print('Index ready:', index, flush=True) |
|
|
|
|
| def inspect_graph(graph): |
| return { |
| 'nodes': graph.run('MATCH (n) UNWIND labels(n) AS label RETURN label,count(*) AS count ORDER BY label'), |
| 'relationships': graph.run('MATCH ()-[r]->() RETURN type(r) AS type,count(*) AS count ORDER BY type'), |
| 'vectors': {name: graph.run(f'MATCH (n:{target.label}) RETURN count(n.{target.property}) AS count')[0]['count'] for name, target in TARGETS.items()}, |
| 'indexes': graph.run('SHOW INDEXES YIELD name,type,state RETURN name,type,state'), |
| } |
|
|
