scripts/import_markdown.py aktualisiert
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@ -2,81 +2,83 @@
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# -*- coding: utf-8 -*-
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"""
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Script: scripts/import_markdown.py
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Version: 0.6.0 (2025-09-06)
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Version: 0.7.1 (2025-09-06)
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Autor: mindnet / Architektur Datenimporte & Sync
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Kurzbeschreibung
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---------------
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Importiert Markdown-Notizen aus einem Obsidian-ähnlichen Vault in Qdrant:
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- Validiert Frontmatter / Note-Payload.
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- Validiert Frontmatter / Note-Payload (gegen note.schema.json).
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- Chunking + Embeddings.
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- Leitet Edges direkt beim Import aus [[Wikilinks]] ab:
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- 'references' (Note→Note)
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- 'references_at' (Chunk→Note)
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- 'backlink' (Note←Note) nur für Note→Note-Kanten.
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- 'backlink' (Note←Note) (symmetrisch zu 'references')
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- Idempotente Upserts (deterministische IDs über qdrant_points).
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Neu in 0.6.0
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Neu in 0.7.1
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------------
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- Option `--purge-before-upsert`: löscht für die jeweils verarbeitete Note
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*vor* dem Upsert alle zugehörigen Chunks und Edges in Qdrant (selektiv!),
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um Leichen nach Re-Chunking zu vermeiden.
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- Robuste Link-Auflösung via Note-Index (ID / Titel-Slug / Datei-Slug)
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konsistent zu `derive_edges.py`.
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- Korrekte Änderungsdetektion via SHA-256 über die **komplette Datei** (Frontmatter+Body):
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- Feld: payload.hash_fulltext
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- Vergleicht neuen Hash gegen bestehenden Hash in Qdrant.
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- Nur bei Änderung → Verarbeitung/Upsert; sonst "skip".
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- `--purge-before-upsert` wird **nur** ausgeführt, wenn sich die Note **wirklich geändert** hat.
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- Robuste Qdrant-Scroll-Kompatibilität (2- oder 3-Tupel Rückgaben).
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Aufrufbeispiele
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---------------
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Dry-Run (keine Schreibzugriffe):
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Dry-Run (nur prüfen, nichts schreiben):
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python3 -m scripts.import_markdown --vault ./vault
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Nur eine bestimmte Note:
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Nur eine spezifische Note:
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python3 -m scripts.import_markdown --vault ./vault --note-id 20250821-foo
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Apply (schreiben) mit Purge:
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Apply (schreiben) mit Purge (nur geänderte Noten werden bereinigt + neu geschrieben):
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python3 -m scripts.import_markdown --vault ./vault --apply --purge-before-upsert
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Parameter
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---------
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--vault PATH : Pflicht. Root-Verzeichnis des Vaults.
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--apply : Wenn gesetzt, werden Upserts durchgeführt (sonst Dry-Run).
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--purge-before-upsert : Wenn gesetzt, werden vor dem Upsert (nur bei --apply)
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alte Chunks und Edges dieser Note in Qdrant gelöscht.
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--purge-before-upsert : Vor Upsert alte Chunks/Edges der **geänderten** Note löschen.
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--note-id ID : Optional, verarbeitet nur diese eine Note.
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Umgebungsvariablen (.env)
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-------------------------
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QDRANT_URL, QDRANT_API_KEY, COLLECTION_PREFIX, VECTOR_DIM
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Standard: url=http://127.0.0.1:6333, prefix=mindnet, dim=384
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Defaults: url=http://127.0.0.1:6333, prefix=mindnet, dim=384
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Kompatibilität
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--------------
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- Nutzt die bestehenden Kernmodule:
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- Bestehende Kernmodule werden weiterverwendet:
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app.core.parser (read_markdown, normalize_frontmatter, validate_required_frontmatter)
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app.core.validate_note (validate_note_payload)
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app.core.chunker (assemble_chunks)
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app.core.chunk_payload (make_chunk_payloads)
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app.core.embed (embed_texts)
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app.core.qdrant (QdrantConfig, get_client, ensure_collections)
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app.core.qdrant (QdrantConfig, ensure_collections, get_client, collection_names)
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app.core.qdrant_points (points_for_note, points_for_chunks, points_for_edges, upsert_batch)
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app.core.derive_edges (build_note_index, derive_wikilink_edges)
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Änderungshinweise vs. früherer Importer
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---------------------------------------
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- Alte, globale Lösch-Workarounds entfallen. Selektives Purge ist jetzt optional und sicher.
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- Edges werden nur noch in der neuen, einheitlichen Struktur erzeugt.
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Hinweise
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--------
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- Bitte im aktivierten venv laufen lassen: source .venv/bin/activate
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"""
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from __future__ import annotations
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import argparse
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import glob
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import hashlib
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import json
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import os
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import sys
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from typing import List, Dict
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from typing import List, Dict, Tuple, Optional
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from dotenv import load_dotenv
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from qdrant_client.http import models as rest
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from qdrant_client import QdrantClient
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# Kern-Bausteine (vorhanden in eurem Projekt)
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# Kern-Bausteine (aus eurem Projekt)
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from app.core.parser import (
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read_markdown,
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normalize_frontmatter,
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@ -105,17 +107,54 @@ def iter_md(root: str) -> List[str]:
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out: List[str] = []
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for p in patterns:
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out.extend(glob.glob(os.path.join(root, p), recursive=True))
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return sorted(list(dict.fromkeys(out))) # de-dupe + sort
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# de-dupe + sort
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return sorted(list(dict.fromkeys(out)))
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def file_sha256(path: str) -> str:
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"""SHA256 über die **Rohdatei** (Frontmatter + Body)."""
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h = hashlib.sha256()
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with open(path, "rb") as f:
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for chunk in iter(lambda: f.read(8192), b""):
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h.update(chunk)
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return h.hexdigest()
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def qdrant_scroll(client: QdrantClient, **kwargs) -> Tuple[List, Optional[str]]:
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"""
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Wrapper, der sowohl (points, next_offset) als auch (points, next_page, _) Signaturen abdeckt.
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"""
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res = client.scroll(**kwargs)
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if isinstance(res, tuple):
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if len(res) == 2:
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return res[0], res[1]
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if len(res) >= 3:
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return res[0], res[1]
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return res, None
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def fetch_existing_note_hash(client: QdrantClient, prefix: str, note_id: str) -> Optional[str]:
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"""Liest hash_fulltext aus mindnet_notes.payload für eine Note."""
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notes_col, _, _ = collection_names(prefix)
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f = rest.Filter(must=[rest.FieldCondition(key="note_id", match=rest.MatchValue(value=note_id))])
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pts, _ = qdrant_scroll(
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client,
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collection_name=notes_col,
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scroll_filter=f,
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with_payload=True,
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with_vectors=False,
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limit=1
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)
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if not pts:
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return None
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pl = getattr(pts[0], "payload", {}) or {}
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return pl.get("hash_fulltext")
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def make_note_stub(abs_path: str, vault_root: str) -> Dict:
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"""
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Erstellt einen minimalen Note-Stub für den Index (build_note_index):
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{ note_id, title, path }
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"""
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"""Minimaler Stub (id/title/path) für build_note_index."""
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parsed = read_markdown(abs_path)
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fm = normalize_frontmatter(parsed.frontmatter or {})
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# Validierung minimal: wir brauchen id + title (title optional für Slug-Auflösung)
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if "id" not in fm or not fm["id"]:
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raise ValueError(f"Missing id in frontmatter: {abs_path}")
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rel = os.path.relpath(abs_path, vault_root)
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@ -123,48 +162,37 @@ def make_note_stub(abs_path: str, vault_root: str) -> Dict:
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def build_vault_index(vault_root: str) -> tuple[Dict, Dict, Dict]:
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"""
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Liest alle Noten ein und baut den Dreifach-Index für Wikilink-Auflösung.
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"""
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files = iter_md(vault_root)
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"""Index für robuste Wikilink-Auflösung über alle Noten im Vault."""
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stubs = []
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for p in files:
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for p in iter_md(vault_root):
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try:
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stubs.append(make_note_stub(p, vault_root))
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except Exception:
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# Notiz ohne id → wird vom Importer später ohnehin übersprungen
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continue
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return build_note_index(stubs)
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def purge_for_note(client, prefix: str, note_id: str, chunk_ids: List[str]) -> Dict[str, int]:
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def purge_for_note(client: QdrantClient, prefix: str, note_id: str, chunk_ids: List[str]) -> None:
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"""
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Selektives Purge für die aktuelle Note:
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- Chunks: alle mit payload.note_id == note_id
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- Edges: alle mit payload.source_id == note_id ODER == einem der chunk_ids
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- Notes: werden nicht gelöscht (Upsert überschreibt Payload/Vektor)
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Selektives Purge der alten Daten für **diese** Note:
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- löscht Chunks (payload.note_id == note_id)
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- löscht Edges, deren source_id == note_id ODER in chunk_ids
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Notes selbst werden nicht gelöscht (Upsert reicht).
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"""
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notes_col, chunks_col, edges_col = collection_names(prefix)
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counts = {"chunks_deleted": 0, "edges_deleted": 0}
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# Chunks löschen (Filter must: note_id == X)
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f_chunks = rest.Filter(
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must=[rest.FieldCondition(key="note_id", match=rest.MatchValue(value=note_id))]
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)
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res_chunks = client.delete(collection_name=chunks_col, points_selector=f_chunks, wait=True)
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counts["chunks_deleted"] = getattr(res_chunks, "status", None) and 0 or 0 # Qdrant liefert keine count hier
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# Chunks löschen
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f_chunks = rest.Filter(must=[rest.FieldCondition(key="note_id", match=rest.MatchValue(value=note_id))])
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client.delete(collection_name=chunks_col, points_selector=f_chunks, wait=True)
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# Edges löschen: OR über Note-ID und alle Chunk-IDs
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# Edges löschen (OR über source_id Werte)
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should_conds = [rest.FieldCondition(key="source_id", match=rest.MatchValue(value=note_id))]
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for cid in chunk_ids:
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should_conds.append(rest.FieldCondition(key="source_id", match=rest.MatchValue(value=cid)))
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f_edges = rest.Filter(should=should_conds) if should_conds else None
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if f_edges is not None:
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if should_conds:
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f_edges = rest.Filter(should=should_conds)
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client.delete(collection_name=edges_col, points_selector=f_edges, wait=True)
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return counts
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# -------------------------------------------------
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# Main
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ap.add_argument(
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"--purge-before-upsert",
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action="store_true",
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help="Vor Upsert alte Chunks/Edges der aktuellen Note löschen (nur mit --apply wirksam).",
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help="Vor Upsert alte Chunks/Edges **nur für geänderte** Noten löschen.",
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)
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ap.add_argument("--note-id", help="Optional: nur diese Note verarbeiten")
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args = ap.parse_args()
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print("Keine Markdown-Dateien gefunden.", file=sys.stderr)
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sys.exit(2)
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# 1) Note-Index über den gesamten Vault (für robuste Link-Auflösung)
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# Index einmal bauen (für Linkauflösung bei geänderten Noten)
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note_index = build_vault_index(vault_root)
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processed = 0
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@ -215,57 +243,74 @@ def main():
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processed += 1
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# --- Note-Payload ---
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from app.core.note_payload import make_note_payload # lazy import (bestehende Funktion)
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# Änderungsdetektion (Datei-Hash vs. Qdrant)
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new_hash = file_sha256(abs_path)
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old_hash = fetch_existing_note_hash(client, cfg.prefix, fm["id"])
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changed = (old_hash != new_hash)
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decision = "skip"
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if changed:
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decision = "apply" if args.apply else "dry-run"
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# Bei "skip" kein teures Chunking/Embedding/Edges nötig
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if not changed:
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print(json.dumps({
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"note_id": fm["id"],
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"title": fm.get("title"),
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"changed": False,
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"decision": "skip",
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"path": os.path.relpath(abs_path, vault_root),
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}, ensure_ascii=False))
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continue
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# --- Ab hier: Nur für geänderte Noten ---
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# Note-Payload erzeugen
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from app.core.note_payload import make_note_payload # lazy import
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note_pl = make_note_payload(parsed, vault_root=vault_root)
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# Hash im Payload mitschreiben (Schema erlaubt hash_fulltext)
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note_pl["hash_fulltext"] = new_hash
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validate_note_payload(note_pl)
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# --- Chunking & Payloads ---
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# Chunking & Payloads
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chunks = assemble_chunks(fm["id"], parsed.body, fm.get("type", "concept"))
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chunk_pls = make_chunk_payloads(fm, note_pl["path"], chunks)
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# --- Embeddings ---
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# Embeddings
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texts = [c.get("text") or c.get("content") or "" for c in chunk_pls]
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vectors = embed_texts(texts)
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# --- Edge-Ableitung (direkt) ---
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# Edges ableiten (Note-/Chunk-Level)
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edges = derive_wikilink_edges(note_pl, chunk_pls, note_index)
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# --- Ausgabe je Note (Entscheidung) ---
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decision = "apply" if args.apply else "dry-run"
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# --- Purge vor Upsert (nur wenn --apply) ---
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# Purge (nur wenn apply + Option gesetzt)
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if args.apply and args.purge_before_upsert:
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# Chunk-IDs (neu) ermitteln → für Edge-Purge by source_id
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# Chunk-IDs bestimmen (für Edge-Purge by source_id)
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chunk_ids = []
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for i, ch in enumerate(chunk_pls, start=1):
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cid = ch.get("chunk_id") or ch.get("id") or f"{fm['id']}#{i}"
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ch["chunk_id"] = cid # sicherstellen
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chunk_ids.append(cid)
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purge_for_note(client, cfg.prefix, fm["id"], chunk_ids)
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# --- Upserts (nur bei --apply) ---
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# Upserts (nur Apply)
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if args.apply:
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# Note
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notes_col, note_pts = points_for_note(cfg.prefix, note_pl, note_vec=None, dim=cfg.dim)
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upsert_batch(client, notes_col, note_pts)
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# Chunks
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chunks_col, chunk_pts = points_for_chunks(cfg.prefix, chunk_pls, vectors)
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upsert_batch(client, chunks_col, chunk_pts)
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# Edges
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edges_col, edge_pts = points_for_edges(cfg.prefix, edges)
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upsert_batch(client, edges_col, edge_pts)
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# Logging pro Note
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# Logging geänderte Note
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print(json.dumps({
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"note_id": fm["id"],
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"title": fm.get("title"),
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"chunks": len(chunk_pls),
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"edges": len(edges),
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"changed": True, # Hash-/Zeitvergleich kann optional hier ergänzt werden
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"changed": True,
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"decision": decision,
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"path": note_pl["path"],
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}, ensure_ascii=False))
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