WP24c - Agentic Edge Validation & Chunk-Aware Multigraph-System (v4.5.8) #22
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@ -50,6 +50,7 @@ def is_explicit_edge_present(client: QdrantClient, prefix: str, edge_id: str) ->
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"""
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_, _, edges_col = collection_names(prefix)
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try:
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# retrieve erwartet eine Liste von IDs
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res = client.retrieve(
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collection_name=edges_col,
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ids=[edge_id],
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@ -83,7 +84,7 @@ def purge_artifacts(client: QdrantClient, prefix: str, note_id: str):
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# Dies umfasst:
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# - Alle ausgehenden Kanten (A -> B)
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# - Alle inversen Kanten, die diese Note in anderen Notizen "deponiert" hat (B -> A)
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# Fremde inverse Kanten (C -> A) bleiben erhalten.
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# Fremde inverse Kanten (C -> A), die von anderen Notizen stammen, bleiben erhalten.
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edges_filter = rest.Filter(must=[
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rest.FieldCondition(key="origin_note_id", match=rest.MatchValue(value=note_id))
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])
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@ -5,9 +5,9 @@ DESCRIPTION: Der zentrale IngestionService (Orchestrator).
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WP-25a: Integration der Mixture of Experts (MoE) Architektur.
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WP-15b: Two-Pass Workflow mit globalem Kontext-Cache.
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WP-20/22: Cloud-Resilienz und Content-Lifecycle integriert.
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AUDIT v3.3.0: Einführung des 2-Phasen-Upserts. Garantiert, dass
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explizite Kanten niemals durch Symmetrien überschrieben werden.
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VERSION: 3.3.0 (WP-24c: Two-Phase Writing Strategy)
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AUDIT v3.3.1: Strikte Trennung von Explicit-Write (Phase 1) und
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Symmetry-Validation (Phase 2). 100% Datenhoheit für den Nutzer.
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VERSION: 3.3.1 (WP-24c: Authority-First Ingestion)
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STATUS: Active
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"""
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import logging
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@ -22,7 +22,7 @@ from app.core.parser import (
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validate_required_frontmatter, NoteContext
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)
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from app.core.chunking import assemble_chunks
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# WP-24c: Import für die deterministische ID-Vorabberechnung
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# WP-24c: Import für die deterministische UUID-Vorabberechnung
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from app.core.graph.graph_utils import _mk_edge_id
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# MODULARISIERUNG: Neue Import-Pfade für die Datenbank-Ebene
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@ -79,7 +79,7 @@ class IngestionService:
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# Festlegen, welcher Hash für die Change-Detection maßgeblich ist
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self.active_hash_mode = self.settings.CHANGE_DETECTION_MODE
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self.batch_cache: Dict[str, NoteContext] = {} # WP-15b LocalBatchCache
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self.batch_cache: Dict[str, NoteContext] = {} # Globaler Kontext-Cache (Pass 1)
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try:
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# Aufruf der modularisierten Schema-Logik
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@ -90,13 +90,13 @@ class IngestionService:
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def _is_valid_note_id(self, text: str) -> bool:
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"""
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WP-24c: Prüft Ziel-Strings auf Validität.
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Filtert Begriffe wie 'insight' oder 'event' aus, um Müll-Kanten zu vermeiden.
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WP-24c: Prüft Ziel-Strings auf fachliche Validität.
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Verhindert das Anlegen von Kanten zu reinen System-Platzhaltern.
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"""
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if not text or len(text.strip()) < 2:
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return False
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# Symmetrie-Filter gegen Typ-Strings
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# Blacklist für Begriffe, die keine echten Notizen sind
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blacklisted = {"insight", "event", "source", "task", "project", "person", "concept", "related_to", "referenced_by"}
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if text.lower().strip() in blacklisted:
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return False
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@ -106,12 +106,12 @@ class IngestionService:
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async def run_batch(self, file_paths: List[str], vault_root: str) -> List[Dict[str, Any]]:
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"""
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WP-15b: Implementiert den Two-Pass Ingestion Workflow.
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Führt nun zusätzlich das 2-Phasen-Schreiben aus.
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WP-15b: Two-Pass Ingestion Workflow mit 2-Phasen-Schreibstrategie.
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"""
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self.batch_cache.clear()
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logger.info(f"--- 🔍 START BATCH IMPORT ({len(file_paths)} Dateien) ---")
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# 1. Schritt: Context-Cache füllen
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# SCHRITT 1: Pre-Scan (Context-Cache füllen)
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for path in file_paths:
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try:
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ctx = pre_scan_markdown(path, registry=self.registry)
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@ -121,32 +121,36 @@ class IngestionService:
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fname = os.path.splitext(os.path.basename(path))[0]
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self.batch_cache[fname] = ctx
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except Exception as e:
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logger.warning(f"⚠️ Pre-scan failed for {path}: {e}")
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logger.warning(f" ⚠️ Pre-scan fehlgeschlagen für {path}: {e}")
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# 2. Schritt: Verarbeitung & Schreiben (PHASE 1: AUTHORITY)
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# Wir sammeln alle Symmetrie-Kandidaten, um sie in Phase 2 zu prüfen.
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# SCHRITT 2: PHASE 1 (Authority-Schreiben)
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# Wir verarbeiten alle Dateien und schreiben NUR explizite Kanten in die DB.
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results = []
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all_virtual_candidates = []
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for p in file_paths:
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res, candidates = await self.process_file(p, vault_root, apply=True, purge_before=True, skip_virtuals=True)
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# process_file liefert in dieser Version (res, virtual_candidates) zurück
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res, candidates = await self.process_file(p, vault_root, apply=True, purge_before=True)
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results.append(res)
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all_virtual_candidates.extend(candidates)
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# 3. Schritt: Symmetrie-Einspeisung (PHASE 2: SYMMETRY)
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# SCHRITT 3: PHASE 2 (Symmetrie-Ergänzung)
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# Nachdem alle expliziten Kanten fest in Qdrant liegen, prüfen wir die Inversen.
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if all_virtual_candidates:
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logger.info(f"🔄 PHASE 2: Prüfe {len(all_virtual_candidates)} Symmetrie-Kanten gegen die Datenbank...")
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logger.info(f"🔄 PHASE 2: Validiere {len(all_virtual_candidates)} Symmetrie-Kandidaten gegen Live-DB...")
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final_virtuals = []
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for v_edge in all_virtual_candidates:
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# Eindeutige ID für diese Symmetrie-Kante berechnen
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# Eindeutige ID berechnen (muss exakt der ID in Phase 1 entsprechen)
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v_id = _mk_edge_id(v_edge["kind"], v_edge["note_id"], v_edge["target_id"], "note")
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# Wenn in Phase 1 KEINE manuelle Kante mit dieser ID geschrieben wurde, darf die Symmetrie rein
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# Check: Liegt dort bereits eine manuelle Kante?
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if not is_explicit_edge_present(self.client, self.prefix, v_id):
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final_virtuals.append(v_edge)
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else:
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logger.debug(f" 🛡️ Symmetrie übersprungen (Manuelle Kante hat Vorrang): {v_id}")
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if final_virtuals:
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logger.info(f"📤 Schreibe {len(final_virtuals)} validierte Symmetrie-Kanten in den Graphen.")
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logger.info(f"📤 Schreibe {len(final_virtuals)} geschützte Symmetrie-Kanten.")
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e_pts = points_for_edges(self.prefix, final_virtuals)[1]
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upsert_batch(self.client, f"{self.prefix}_edges", e_pts)
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@ -156,12 +160,15 @@ class IngestionService:
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async def process_file(self, file_path: str, vault_root: str, **kwargs) -> Tuple[Dict[str, Any], List[Dict[str, Any]]]:
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"""
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Transformiert eine Markdown-Datei.
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Liefert zusätzlich eine Liste von virtuellen Kanten-Kandidaten zurück.
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Schreibt Notes/Chunks/Explicit Edges sofort (Phase 1).
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Gibt potenzielle Symmetrien für Phase 2 zurück.
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"""
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apply = kwargs.get("apply", False)
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force_replace = kwargs.get("force_replace", False)
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purge_before = kwargs.get("purge_before", False)
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skip_virtuals = kwargs.get("skip_virtuals", False)
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note_scope_refs = kwargs.get("note_scope_refs", False)
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hash_source = kwargs.get("hash_source", "parsed")
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hash_normalize = kwargs.get("hash_normalize", "canonical")
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result = {"path": file_path, "status": "skipped", "changed": False, "error": None}
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virtual_candidates = []
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@ -184,24 +191,34 @@ class IngestionService:
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# 2. Payload & Change Detection
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note_type = resolve_note_type(self.registry, fm.get("type"))
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note_pl = make_note_payload(parsed, vault_root=vault_root, file_path=file_path, types_cfg=self.registry)
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note_pl = make_note_payload(
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parsed, vault_root=vault_root, file_path=file_path,
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hash_source=hash_source, hash_normalize=hash_normalize,
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types_cfg=self.registry
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)
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note_id = note_pl["note_id"]
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logger.info(f"📄 Bearbeite: '{note_id}' (Typ: {note_type})")
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old_payload = None if force_replace else fetch_note_payload(self.client, self.prefix, note_id)
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check_key = f"{self.active_hash_mode}:{note_pl.get('hashes', {}).get('hash_source', 'parsed')}:{note_pl.get('hashes', {}).get('hash_normalize', 'canonical')}"
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# (Hashing Logik hier vereinfacht zur Lesbarkeit, entspricht aber Ihrer Codebasis)
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check_key = f"{self.active_hash_mode}:{hash_source}:{hash_normalize}"
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old_hash = (old_payload or {}).get("hashes", {}).get(check_key)
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new_hash = note_pl.get("hashes", {}).get(check_key)
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c_miss, e_miss = artifacts_missing(self.client, self.prefix, note_id)
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if not (force_replace or not old_payload or c_miss or e_miss):
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if not (force_replace or not old_payload or old_hash != new_hash or c_miss or e_miss):
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return {**result, "status": "unchanged", "note_id": note_id}, []
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if not apply:
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return {**result, "status": "dry-run", "changed": True, "note_id": note_id}, []
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# 3. Deep Processing (Chunking, Validation, Embedding)
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try:
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body_text = getattr(parsed, "body", "") or ""
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edge_registry.ensure_latest()
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profile = note_pl.get("chunk_profile", "sliding_standard")
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chunk_cfg = get_chunk_config_by_profile(self.registry, profile, note_type)
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enable_smart = chunk_cfg.get("enable_smart_edge_allocation", False)
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@ -215,8 +232,8 @@ class IngestionService:
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is_valid = await validate_edge_candidate(
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ch.text, cand, self.batch_cache, self.llm, profile_name="ingest_validator"
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)
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label = cand.get('target_id') or cand.get('note_id') or "Unknown"
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logger.info(f" 🧠 [SMART EDGE] {label} -> {'✅ OK' if is_valid else '❌ SKIP'}")
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t_id = cand.get('target_id') or cand.get('note_id') or "Unknown"
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logger.info(f" 🧠 [SMART EDGE] {t_id} -> {'✅ OK' if is_valid else '❌ SKIP'}")
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if is_valid: new_pool.append(cand)
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else:
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new_pool.append(cand)
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@ -225,29 +242,33 @@ class IngestionService:
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chunk_pls = make_chunk_payloads(fm, note_pl["path"], chunks, file_path=file_path, types_cfg=self.registry)
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vecs = await self.embedder.embed_documents([c.get("window") or "" for c in chunk_pls]) if chunk_pls else []
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# Kanten-Extraktion
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raw_edges = build_edges_for_note(note_id, chunk_pls, note_level_references=note_pl.get("references", []))
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# Aggregation aller Kanten
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raw_edges = build_edges_for_note(
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note_id, chunk_pls,
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note_level_references=note_pl.get("references", []),
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include_note_scope_refs=note_scope_refs
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)
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# PHASE 1: Authority Edges (Explizit)
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# PHASE 1: Authority-Check & Kanonisierung
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explicit_edges = []
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for e in raw_edges:
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target_raw = e.get("target_id")
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# ID-Resolution über den Context-Cache (Titel -> Note_ID)
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target_ctx = self.batch_cache.get(target_raw)
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target_id = target_ctx.note_id if target_ctx else target_raw
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# Junk-Filter
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if not self._is_valid_note_id(target_id): continue
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resolved_kind = edge_registry.resolve(e.get("kind", "related_to"), provenance=e.get("provenance", "explicit"))
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# Echte physische Kante markieren
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# Echte explizite Kante für Phase 1
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e.update({
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"kind": resolved_kind, "target_id": target_id,
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"origin_note_id": note_id, "virtual": False, "confidence": 1.0
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})
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explicit_edges.append(e)
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# Kandidat für Symmetrie (Phase 2)
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# Symmetrie-Kandidat für Phase 2 vorbereiten
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inv_kind = edge_registry.get_inverse(resolved_kind)
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if inv_kind and target_id != note_id:
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v_edge = e.copy()
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@ -260,13 +281,20 @@ class IngestionService:
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# 4. DB Upsert (Phase 1)
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if apply:
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if purge_before and old_payload: purge_artifacts(self.client, self.prefix, note_id)
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upsert_batch(self.client, f"{self.prefix}_notes", points_for_note(self.prefix, note_pl, None, self.dim)[1])
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if chunk_pls and vecs: upsert_batch(self.client, f"{self.prefix}_chunks", points_for_chunks(self.prefix, chunk_pls, vecs)[1])
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if explicit_edges: upsert_batch(self.client, f"{self.prefix}_edges", points_for_edges(self.prefix, explicit_edges)[1])
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if purge_before and old_payload:
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purge_artifacts(self.client, self.prefix, note_id)
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logger.info(f" ✨ Fertig: {len(chunk_pls)} Chunks, {len(explicit_edges)} explizite Kanten geschrieben.")
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return {"status": "success", "note_id": note_id, "edges_count": len(explicit_edges)}, virtual_candidates
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upsert_batch(self.client, f"{self.prefix}_notes", points_for_note(self.prefix, note_pl, None, self.dim)[1])
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if chunk_pls and vecs:
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upsert_batch(self.client, f"{self.prefix}_chunks", points_for_chunks(self.prefix, chunk_pls, vecs)[1])
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if explicit_edges:
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upsert_batch(self.client, f"{self.prefix}_edges", points_for_edges(self.prefix, explicit_edges)[1])
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logger.info(f" ✨ Phase 1 fertig: {len(chunk_pls)} Chunks, {len(explicit_edges)} explizite Kanten.")
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return {
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"path": file_path, "status": "success", "changed": True, "note_id": note_id,
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"chunks_count": len(chunk_pls), "edges_count": len(explicit_edges)
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}, virtual_candidates
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except Exception as e:
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logger.error(f"❌ Fehler bei {file_path}: {e}", exc_info=True)
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@ -276,7 +304,8 @@ class IngestionService:
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"""Erstellt eine Note aus einem Textstream."""
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target_path = os.path.join(vault_root, folder, filename)
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os.makedirs(os.path.dirname(target_path), exist_ok=True)
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with open(target_path, "w", encoding="utf-8") as f: f.write(markdown_content)
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with open(target_path, "w", encoding="utf-8") as f:
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f.write(markdown_content)
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await asyncio.sleep(0.1)
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res, _ = await self.process_file(file_path=target_path, vault_root=vault_root, apply=True, force_replace=True, purge_before=True)
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return res
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Block a user