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334 lines
11 KiB
Python
334 lines
11 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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app/core/qdrant_points.py
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Zweck
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- Gemeinsame Helfer zum Erzeugen von Qdrant-Points für Notes, Chunks und Edges.
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- Abwärtskompatibel zu altem Edge-Payload-Schema aus edges.py:
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- alt: {'edge_type','src_id','dst_id', ...}
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- neu: {'kind','source_id','target_id', ...}
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Version
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- 1.3 (2025-09-08)
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Änderungen (ggü. 1.2)
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- points_for_edges() akzeptiert jetzt beide Edge-Schemata.
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- Normalisiert alte Felder auf 'kind' / 'source_id' / 'target_id' und schreibt eine
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stabile 'edge_id' zurück in die Payload.
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- Verhindert, dass mehrere Edges dieselbe Point-ID erhalten (Root Cause deiner 1-Edge-Sammlung).
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Aufruf / Verwendung
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- Wird von Import-/Backfill-Skripten via:
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from app.core.qdrant_points import points_for_note, points_for_chunks, points_for_edges, upsert_batch
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eingebunden. Keine CLI.
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Hinweise
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- Edges bekommen absichtlich einen 1D-Dummy-Vektor [0.0], damit Qdrant das Objekt akzeptiert.
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- Die Point-IDs werden deterministisch aus stabilen Strings (UUIDv5) abgeleitet.
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"""
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from __future__ import annotations
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import uuid
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from typing import List, Tuple
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from qdrant_client.http import models as rest
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def _names(prefix: str) -> Tuple[str, str, str]:
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return f"{prefix}_notes", f"{prefix}_chunks", f"{prefix}_edges"
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def _to_uuid(stable_key: str) -> str:
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"""Stabile UUIDv5 aus einem String-Key (deterministisch)."""
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return str(uuid.uuid5(uuid.NAMESPACE_URL, stable_key))
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def points_for_note(
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prefix: str,
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note_payload: dict,
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note_vec: List[float] | None,
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dim: int,
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) -> Tuple[str, List[rest.PointStruct]]:
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"""Notes-Collection: falls kein Note-Embedding -> Nullvektor der Länge dim."""
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notes_col, _, _ = _names(prefix)
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vector = note_vec if note_vec is not None else [0.0] * int(dim)
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raw_note_id = note_payload.get("note_id") or note_payload.get("id") or "missing-note-id"
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point_id = _to_uuid(raw_note_id)
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pt = rest.PointStruct(id=point_id, vector=vector, payload=note_payload)
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return notes_col, [pt]
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def points_for_chunks(
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prefix: str,
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chunk_payloads: List[dict],
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vectors: List[List[float]],
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) -> Tuple[str, List[rest.PointStruct]]:
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"""
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Chunks-Collection: erwartet pro Chunk einen Vektor.
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Robustheit:
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- Fehlt 'chunk_id', nutze 'id', sonst baue '${note_id}#${i}' (1-basiert).
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- Schreibe die abgeleitete ID zurück in die Payload (pl['chunk_id']).
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"""
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_, chunks_col, _ = _names(prefix)
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points: List[rest.PointStruct] = []
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for i, (pl, vec) in enumerate(zip(chunk_payloads, vectors), start=1):
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chunk_id = pl.get("chunk_id") or pl.get("id")
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if not chunk_id:
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note_id = pl.get("note_id") or pl.get("parent_note_id") or "missing-note"
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chunk_id = f"{note_id}#{i}"
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pl["chunk_id"] = chunk_id
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point_id = _to_uuid(chunk_id)
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points.append(rest.PointStruct(id=point_id, vector=vec, payload=pl))
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return chunks_col, points
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def _normalize_edge_payload(pl: dict) -> dict:
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"""
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Sorgt für kompatible Feldnamen.
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akzeptiert:
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- neu: kind, source_id, target_id, seq?
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- alt: edge_type, src_id, dst_id, order?/index?
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schreibt zurück: kind, source_id, target_id, seq?
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"""
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# bereits neu?
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kind = pl.get("kind") or pl.get("edge_type") or "edge"
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source_id = pl.get("source_id") or pl.get("src_id") or "unknown-src"
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target_id = pl.get("target_id") or pl.get("dst_id") or "unknown-tgt"
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seq = pl.get("seq") or pl.get("order") or pl.get("index")
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# in Payload zurückschreiben (ohne alte Felder zu entfernen → maximal kompatibel)
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pl.setdefault("kind", kind)
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pl.setdefault("source_id", source_id)
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pl.setdefault("target_id", target_id)
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if seq is not None and "seq" not in pl:
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pl["seq"] = seq
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return pl
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def points_for_edges(prefix: str, edge_payloads: List[dict]) -> Tuple[str, List[rest.PointStruct]]:
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"""
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Edges-Collection mit 1D-Dummy-Vektor.
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- Akzeptiert sowohl neues als auch altes Edge-Schema (siehe _normalize_edge_payload).
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- Fehlt 'edge_id', wird sie stabil aus (kind, source_id, target_id, seq) konstruiert.
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"""
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_, _, edges_col = _names(prefix)
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points: List[rest.PointStruct] = []
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for raw in edge_payloads:
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pl = _normalize_edge_payload(raw)
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edge_id = pl.get("edge_id")
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if not edge_id:
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kind = pl.get("kind", "edge")
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s = pl.get("source_id", "unknown-src")
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t = pl.get("target_id", "unknown-tgt")
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seq = pl.get("seq") or ""
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edge_id = f"{kind}:{s}->{t}#{seq}"
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pl["edge_id"] = edge_id
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point_id = _to_uuid(edge_id)
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points.append(rest.PointStruct(id=point_id, vector=[0.0], payload=pl))
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return edges_col, points
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def upsert_batch(client, collection: str, points: List[rest.PointStruct]) -> None:
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if not points:
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return
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client.upsert(collection_name=collection, points=points, wait=True)
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# --- WP-04 Ergänzungen: Graph/Retriever Hilfsfunktionen ---
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from typing import Optional, Dict, Any, Iterable
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from qdrant_client import QdrantClient
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def _filter_any(field: str, values: Iterable[str]) -> rest.Filter:
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"""Erzeuge OR-Filter: payload[field] == any(values)."""
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return rest.Filter(
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should=[
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rest.FieldCondition(key=field, match=rest.MatchValue(value=v))
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for v in values
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]
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)
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def _merge_filters(*filters: Optional[rest.Filter]) -> Optional[rest.Filter]:
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"""Fasst mehrere Filter zu einem AND zusammen (None wird ignoriert)."""
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fs = [f for f in filters if f is not None]
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if not fs:
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return None
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if len(fs) == 1:
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return fs[0]
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# rest.Filter hat must/should; wir kombinieren als must=[...]
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must = []
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for f in fs:
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# Überführe vorhandene Bedingungen in must
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if getattr(f, "must", None):
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must.extend(f.must)
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if getattr(f, "should", None):
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# "should" als eigene Gruppe beilegen (Qdrant interpretiert OR)
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must.append(rest.Filter(should=f.should))
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if getattr(f, "must_not", None):
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# negative Bedingungen weiterreichen
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if "must_not" not in locals():
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pass
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return rest.Filter(must=must)
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def _filter_from_dict(filters: Optional[Dict[str, Any]]) -> Optional[rest.Filter]:
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"""
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Einfache Filterumsetzung:
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- Bei Listenwerten: OR über mehrere MatchValue (field == any(values))
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- Bei Skalarwerten: Gleichheit (field == value)
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Für komplexere Filter (z. B. tags ∈ payload.tags) bitte erweitern.
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"""
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if not filters:
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return None
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parts = []
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for k, v in filters.items():
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if isinstance(v, (list, tuple, set)):
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parts.append(_filter_any(k, [str(x) for x in v]))
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else:
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parts.append(rest.Filter(must=[rest.FieldCondition(key=k, match=rest.MatchValue(value=v))]))
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return _merge_filters(*parts)
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def search_chunks_by_vector(
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client: QdrantClient,
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prefix: str,
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vector: list[float],
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top: int = 10,
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filters: Optional[Dict[str, Any]] = None,
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) -> list[tuple[str, float, dict]]:
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"""
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Vektorielle Suche in {prefix}_chunks.
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Rückgabe: Liste von (point_id, score, payload)
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"""
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_, chunks_col, _ = _names(prefix)
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flt = _filter_from_dict(filters)
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res = client.search(
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collection_name=chunks_col,
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query_vector=vector,
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limit=top,
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with_payload=True,
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with_vectors=False,
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query_filter=flt,
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)
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out: list[tuple[str, float, dict]] = []
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for r in res:
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out.append((str(r.id), float(r.score), dict(r.payload or {})))
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return out
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def get_edges_for_sources(
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client: QdrantClient,
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prefix: str,
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source_ids: list[str],
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edge_types: Optional[list[str]] = None,
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limit: int = 2048,
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) -> list[dict]:
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"""
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Hole Edges aus {prefix}_edges mit source_id ∈ source_ids (und optional kind ∈ edge_types).
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Liefert Payload-Dicts inkl. edge_id/source_id/target_id/kind/seq (falls vorhanden).
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"""
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_, _, edges_col = _names(prefix)
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f_src = _filter_any("source_id", source_ids)
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f_kind = _filter_any("kind", edge_types) if edge_types else None
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flt = _merge_filters(f_src, f_kind)
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collected: list[dict] = []
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next_page = None
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while True:
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points, next_page = client.scroll(
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collection_name=edges_col,
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scroll_filter=flt,
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limit=min(512, limit - len(collected)),
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with_payload=True,
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with_vectors=False,
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offset=next_page,
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)
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for p in points:
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pl = dict(p.payload or {})
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# füge die deterministische ID hinzu (nützlich für Clients)
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pl.setdefault("id", str(p.id))
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collected.append(pl)
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if len(collected) >= limit:
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return collected
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if next_page is None:
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break
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return collected
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def get_note_payload(
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client: QdrantClient,
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prefix: str,
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note_id: str,
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) -> Optional[dict]:
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"""
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Hole eine Note anhand ihres payload.note_id (nicht internal UUID!).
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"""
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notes_col, _, _ = _names(prefix)
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flt = rest.Filter(must=[rest.FieldCondition(key="note_id", match=rest.MatchValue(value=note_id))])
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points, _ = client.scroll(
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collection_name=notes_col,
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scroll_filter=flt,
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limit=1,
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with_payload=True,
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with_vectors=False,
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)
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if not points:
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return None
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pl = dict(points[0].payload or {})
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pl.setdefault("id", str(points[0].id))
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return pl
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def get_neighbor_nodes(
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client: QdrantClient,
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prefix: str,
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target_ids: list[str],
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limit_per_collection: int = 2048,
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) -> dict[str, dict]:
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"""
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Hole Payloads der Zielknoten (Notes/Chunks) zu den angegebenen IDs.
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IDs sind die stabilen payload-IDs (note_id/chunk_id), nicht internal UUIDs.
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Rückgabe: Mapping target_id -> payload
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"""
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notes_col, chunks_col, _ = _names(prefix)
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out: dict[str, dict] = {}
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# Notes
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flt_notes = _filter_any("note_id", target_ids)
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next_page = None
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while True:
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pts, next_page = client.scroll(
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collection_name=notes_col,
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scroll_filter=flt_notes,
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limit=256,
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with_payload=True,
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with_vectors=False,
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offset=next_page,
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)
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for p in pts:
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pl = dict(p.payload or {})
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nid = pl.get("note_id")
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if nid and nid not in out:
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pl.setdefault("id", str(p.id))
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out[nid] = pl
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if next_page is None or len(out) >= limit_per_collection:
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break
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# Chunks
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flt_chunks = _filter_any("chunk_id", target_ids)
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next_page = None
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while True:
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pts, next_page = client.scroll(
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collection_name=chunks_col,
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scroll_filter=flt_chunks,
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limit=256,
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with_payload=True,
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with_vectors=False,
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offset=next_page,
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)
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for p in pts:
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pl = dict(p.payload or {})
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cid = pl.get("chunk_id")
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if cid and cid not in out:
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pl.setdefault("id", str(p.id))
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out[cid] = pl
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if next_page is None or len(out) >= limit_per_collection:
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break
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return out
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