from __future__ import annotations import uuid from typing import List, Tuple from qdrant_client.http import models as rest def _names(prefix: str) -> Tuple[str, str, str]: return f"{prefix}_notes", f"{prefix}_chunks", f"{prefix}_edges" def _to_uuid(stable_key: str) -> str: """ Erzeuge eine stabile UUIDv5 aus einem stabilen String-Key (z. B. note_id, chunk_id, edge_id). Wir verwenden NAMESPACE_URL, damit die UUIDs deterministisch sind. """ return str(uuid.uuid5(uuid.NAMESPACE_URL, stable_key)) def points_for_note( prefix: str, note_payload: dict, note_vec: List[float] | None, dim: int, ) -> Tuple[str, List[rest.PointStruct]]: """ (collection_name, [PointStruct]) für die Notes-Collection. Falls kein Note-Embedding vorhanden -> Nullvektor der Länge `dim`. """ notes_col, _, _ = _names(prefix) vector = note_vec if note_vec is not None else [0.0] * int(dim) # Qdrant-Point-ID MUSS int oder UUID sein -> aus note_id eine UUIDv5 machen point_id = _to_uuid(note_payload["note_id"]) pt = rest.PointStruct(id=point_id, vector=vector, payload=note_payload) return notes_col, [pt] def points_for_chunks( prefix: str, chunk_payloads: List[dict], vectors: List[List[float]], ) -> Tuple[str, List[rest.PointStruct]]: """ (collection_name, [PointStruct]) für die Chunks-Collection. Erwartet pro Chunk einen Vektor (oder Nullvektor, wenn --skip-embed). """ _, chunks_col, _ = _names(prefix) points: List[rest.PointStruct] = [] for pl, vec in zip(chunk_payloads, vectors): point_id = _to_uuid(pl["chunk_id"]) points.append(rest.PointStruct(id=point_id, vector=vec, payload=pl)) return chunks_col, points def points_for_edges(prefix: str, edge_payloads: List[dict]) -> Tuple[str, List[rest.PointStruct]]: """ (collection_name, [PointStruct]) für die Edges-Collection. Edges-Collection ist ohne Vektor angelegt -> nur Payload + UUID-IDs. """ _, _, edges_col = _names(prefix) points: List[rest.PointStruct] = [] for pl in edge_payloads: point_id = _to_uuid(pl["edge_id"]) points.append(rest.PointStruct(id=point_id, payload=pl)) return edges_col, points def upsert_batch(client, collection: str, points: List[rest.PointStruct]) -> None: if not points: return client.upsert(collection_name=collection, points=points, wait=True)