mindnet/app/core/qdrant_points.py

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)