#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Name: app/core/qdrant.py Version: v1.4.0 (2025-09-09) Kurzbeschreibung: Qdrant-Client & Collection-Setup für mindnet. - Stellt sicher, dass {prefix}_notes / {prefix}_chunks / {prefix}_edges existieren. - Edges-Collection nutzt 1D Dummy-Vektor. - NEW: ensure_payload_indexes(...) legt sinnvolle Payload-Indizes an. Aufruf: from app.core.qdrant import QdrantConfig, get_client, ensure_collections, ensure_payload_indexes """ from __future__ import annotations import os from dataclasses import dataclass from typing import Optional, Tuple from qdrant_client import QdrantClient from qdrant_client.http import models as rest @dataclass class QdrantConfig: url: str api_key: Optional[str] prefix: str dim: int @staticmethod def from_env() -> "QdrantConfig": url = os.getenv("QDRANT_URL") if not url: host = os.getenv("QDRANT_HOST", "127.0.0.1") port = int(os.getenv("QDRANT_PORT", "6333")) url = f"http://{host}:{port}" api_key = os.getenv("QDRANT_API_KEY") or None prefix = os.getenv("COLLECTION_PREFIX", "mindnet") dim = int(os.getenv("VECTOR_DIM", "384")) return QdrantConfig(url=url, api_key=api_key, prefix=prefix, dim=dim) def get_client(cfg: QdrantConfig) -> QdrantClient: return QdrantClient(url=cfg.url, api_key=cfg.api_key) def _create_notes(client: QdrantClient, name: str, dim: int) -> None: if not client.collection_exists(name): client.create_collection( collection_name=name, vectors_config=rest.VectorParams(size=dim, distance=rest.Distance.COSINE), ) def _create_chunks(client: QdrantClient, name: str, dim: int) -> None: if not client.collection_exists(name): client.create_collection( collection_name=name, vectors_config=rest.VectorParams(size=dim, distance=rest.Distance.COSINE), ) def _create_edges(client: QdrantClient, name: str) -> None: if not client.collection_exists(name): client.create_collection( collection_name=name, vectors_config=rest.VectorParams(size=1, distance=rest.Distance.DOT), # 1D-Dummy ) def ensure_collections(client: QdrantClient, prefix: str, dim: int, destructive: bool = False) -> None: notes = f"{prefix}_notes" chunks = f"{prefix}_chunks" edges = f"{prefix}_edges" _create_notes(client, notes, dim) _create_chunks(client, chunks, dim) if client.collection_exists(edges): try: info = client.get_collection(edges) vectors_cfg = getattr(getattr(info.result, "config", None), "params", None) has_vectors = getattr(vectors_cfg, "vectors", None) is not None except Exception: has_vectors = True if not has_vectors: if destructive: client.delete_collection(edges) _create_edges(client, edges) else: print(f"[ensure_collections] WARN: '{edges}' ohne VectorConfig; destructive=False.", flush=True) else: _create_edges(client, edges) def collection_names(prefix: str) -> Tuple[str, str, str]: return (f"{prefix}_notes", f"{prefix}_chunks", f"{prefix}_edges") # ------------------------------- # NEW: Payload-Indexing # ------------------------------- def _safe_create_index(client: QdrantClient, col: str, field: str, schema: rest.PayloadSchemaType): try: client.create_payload_index( collection_name=col, field_name=field, field_schema=schema, ) except Exception: # bereits vorhanden oder nicht unterstütztes Schema → ignorieren pass def ensure_payload_indexes(client: QdrantClient, prefix: str) -> None: notes, chunks, edges = collection_names(prefix) # Notes _safe_create_index(client, notes, "note_id", rest.PayloadSchemaType.KEYWORD) # Chunks _safe_create_index(client, chunks, "note_id", rest.PayloadSchemaType.KEYWORD) _safe_create_index(client, chunks, "chunk_index", rest.PayloadSchemaType.INTEGER) # Edges for f in ("kind", "scope", "source_id", "target_id", "note_id"): _safe_create_index(client, edges, f, rest.PayloadSchemaType.KEYWORD)