from __future__ import annotations import os 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 points_for_note(prefix: str, note_payload: dict, note_vec: List[float] | None, dim: int) -> Tuple[str, List[rest.PointStruct]]: """ Liefert (collection_name, [PointStruct]) für die Notes-Collection. Falls kein Note-Embedding übergeben wurde, wird ein Nullvektor der Länge `dim` verwendet. Hintergrund: Die Notes-Collection ist in ensure_collections mit Vektor-Dimension angelegt. """ notes_col, _, _ = _names(prefix) vector = note_vec if note_vec is not None else [0.0] * int(dim) pt = rest.PointStruct(id=note_payload["note_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]]: """ Liefert (collection_name, [PointStruct]) für die Chunks-Collection. Erwartet für jeden Chunk einen Embedding-Vektor (oder Nullvektor, wenn --skip-embed). """ _, chunks_col, _ = _names(prefix) points: List[rest.PointStruct] = [] for pl, vec in zip(chunk_payloads, vectors): points.append(rest.PointStruct(id=pl["chunk_id"], vector=vec, payload=pl)) return chunks_col, points def points_for_edges(prefix: str, edge_payloads: List[dict]) -> Tuple[str, List[rest.PointStruct]]: """ Liefert (collection_name, [PointStruct]) für die Edges-Collection. Edges-Collection ist VEKTORENLOS angelegt → nur Payload. """ _, _, edges_col = _names(prefix) points: List[rest.PointStruct] = [] for pl in edge_payloads: points.append(rest.PointStruct(id=pl["edge_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)