WP24c - Agentic Edge Validation & Chunk-Aware Multigraph-System (v4.5.8) #22

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@ -4,11 +4,10 @@ DESCRIPTION: Der zentrale IngestionService (Orchestrator).
WP-24c: Integration der Symmetrie-Logik (Automatische inverse Kanten).
WP-25a: Integration der Mixture of Experts (MoE) Architektur.
WP-15b: Two-Pass Workflow mit globalem Kontext-Cache.
WP-20/22: Cloud-Resilienz und Content-Lifecycle integriert.
AUDIT v3.3.7: Strikte globale Phasentrennung.
Fix für Pydantic Crash (None-ID Guard Clauses).
Erzwingung der Konsistenz (wait=True).
VERSION: 3.3.7 (WP-24c: Strict Authority Commitment)
AUDIT v3.3.8: Lösung des Ghost-ID Problems & Pydantic-Crash Fix.
Strikte Phasentrennung (Phase 2 global am Ende).
Wiederherstellung der LLM-Logging-Transparenz.
VERSION: 3.3.8 (WP-24c: Robust Authority Enforcement)
STATUS: Active
"""
import logging
@ -23,10 +22,9 @@ from app.core.parser import (
validate_required_frontmatter, NoteContext
)
from app.core.chunking import assemble_chunks
# WP-24c: Import für die deterministische UUID-Vorabberechnung
from app.core.graph.graph_utils import _mk_edge_id
# MODULARISIERUNG: Neue Import-Pfade für die Datenbank-Ebene
# Datenbank-Ebene (Modularisierte database-Infrastruktur)
from app.core.database.qdrant import QdrantConfig, get_client, ensure_collections, ensure_payload_indexes
from app.core.database.qdrant_points import points_for_chunks, points_for_note, points_for_edges, upsert_batch
from qdrant_client.http import models as rest
@ -43,7 +41,7 @@ from .ingestion_validation import validate_edge_candidate
from .ingestion_note_payload import make_note_payload
from .ingestion_chunk_payload import make_chunk_payloads
# Fallback für Edges (Struktur-Verknüpfung)
# Fallback für Edges
try:
from app.core.graph.graph_derive_edges import build_edges_for_note
except ImportError:
@ -53,12 +51,11 @@ logger = logging.getLogger(__name__)
class IngestionService:
def __init__(self, collection_prefix: str = None):
"""Initialisiert den Service und nutzt die neue database-Infrastruktur."""
"""Initialisiert den Service und bereinigt das technische Logging."""
from app.config import get_settings
self.settings = get_settings()
# --- LOGGING CLEANUP (Business Focus) ---
# Unterdrückt technische Bibliotheks-Header, erhält aber inhaltliche Service-Logs
# --- LOGGING CLEANUP (Header-Noise unterdrücken, Business erhalten) ---
for lib in ["httpx", "httpcore", "qdrant_client", "urllib3", "openai"]:
logging.getLogger(lib).setLevel(logging.WARNING)
@ -71,49 +68,41 @@ class IngestionService:
self.embedder = EmbeddingsClient()
self.llm = LLMService()
# WP-25a: Auflösung der Dimension über das Embedding-Profil (MoE)
embed_cfg = self.llm.profiles.get("embedding_expert", {})
self.dim = embed_cfg.get("dimensions") or self.settings.VECTOR_SIZE
self.active_hash_mode = self.settings.CHANGE_DETECTION_MODE
# WP-15b: Kontext-Gedächtnis für ID-Auflösung
# Kontext-Gedächtnis für ID-Auflösung
self.batch_cache: Dict[str, NoteContext] = {}
# WP-24c: Puffer für Phase 2 (Symmetrie-Injektion nach dem gesamten Import)
# Puffer für Phase 2 (Symmetrie-Injektion am Ende des gesamten Imports)
self.symmetry_buffer: List[Dict[str, Any]] = []
try:
# Aufruf der modularisierten Schema-Logik
ensure_collections(self.client, self.prefix, self.dim)
ensure_payload_indexes(self.client, self.prefix)
except Exception as e:
logger.warning(f"DB initialization warning: {e}")
def _is_valid_note_id(self, text: Optional[str]) -> bool:
"""
WP-24c: Prüft Ziel-Strings auf fachliche Validität.
Verhindert Müll-Kanten zu System-Platzhaltern.
"""
"""WP-24c: Fachliche Validitätsprüfung gegen Junk-Kanten."""
if not text or not isinstance(text, str) or len(text.strip()) < 2:
return False
blacklisted = {"insight", "event", "source", "task", "project", "person", "concept", "related_to", "referenced_by", "none", "unknown"}
if text.lower().strip() in blacklisted:
return False
if len(text) > 200: return False
return True
async def run_batch(self, file_paths: List[str], vault_root: str) -> Dict[str, Any]:
"""
WP-15b: Two-Pass Ingestion Workflow (PHASE 1).
Verarbeitet Batches und schreibt NUR Nutzer-Autorität in die DB.
WP-15b: Phase 1 des Two-Phase Ingestion Workflows.
Verarbeitet Batches und schreibt NUR Nutzer-Autorität (physische Kanten) in die DB.
"""
self.batch_cache.clear()
logger.info(f"--- 🔍 START BATCH PHASE 1 ({len(file_paths)} Dateien) ---")
# 1. Schritt: Pre-Scan (Context-Cache füllen)
# 1. Pre-Scan (ID-Gedächtnis füllen)
for path in file_paths:
try:
ctx = pre_scan_markdown(path, registry=self.registry)
@ -125,7 +114,7 @@ class IngestionService:
except Exception as e:
logger.warning(f" ⚠️ Pre-scan fehlgeschlagen für {path}: {e}")
# 2. Schritt: PROCESSING
# 2. Schritt: Batch-Verarbeitung (Explicit Authority)
processed_count = 0
success_count = 0
for p in file_paths:
@ -134,7 +123,7 @@ class IngestionService:
if res.get("status") == "success":
success_count += 1
logger.info(f"--- ✅ Batch Phase 1 beendet ({success_count}/{processed_count}) ---")
logger.info(f"--- ✅ Batch Phase 1 abgeschlossen ({success_count}/{processed_count}) ---")
return {
"status": "success",
"processed": processed_count,
@ -144,46 +133,40 @@ class IngestionService:
async def commit_vault_symmetries(self) -> Dict[str, Any]:
"""
WP-24c: Führt PHASE 2 (Globale Symmetrie-Injektion) aus.
Wird einmalig am Ende des gesamten Imports aufgerufen.
Sorgt dafür, dass virtuelle Kanten erst NACH der Nutzer-Autorität geschrieben werden.
WP-24c: Globale Symmetrie-Injektion (Phase 2).
Prüft gepufferte Kanten gegen die Instance-of-Truth in Qdrant.
"""
if not self.symmetry_buffer:
logger.info("⏭️ Symmetrie-Puffer leer. Keine Aktion erforderlich.")
logger.info("⏭️ Symmetrie-Puffer leer.")
return {"status": "skipped", "reason": "buffer_empty"}
logger.info(f"🔄 PHASE 2: Validiere {len(self.symmetry_buffer)} Symmetrie-Vorschläge gegen Live-DB...")
logger.info(f"🔄 PHASE 2: Validiere {len(self.symmetry_buffer)} Symmetrien gegen Live-DB...")
final_virtuals = []
for v_edge in self.symmetry_buffer:
# Sicherheits-Check: Keine Kanten ohne Ziele zulassen
if not v_edge.get("target_id") or v_edge.get("target_id") == "None":
continue
if not v_edge.get("target_id") or v_edge.get("target_id") == "None": continue
# ID der potenziellen Symmetrie berechnen
v_id = _mk_edge_id(v_edge["kind"], v_edge["note_id"], v_edge["target_id"], v_edge.get("scope", "note"))
# AUTHORITY-CHECK: Nur schreiben, wenn KEINE manuelle Kante in der DB existiert
# Schutz der Nutzer-Autorität
if not is_explicit_edge_present(self.client, self.prefix, v_id):
final_virtuals.append(v_edge)
logger.info(f" 🔄 [SYMMETRY] Erzeuge Gegenkante: {v_edge['note_id']} --({v_edge['kind']})--> {v_edge['target_id']}")
logger.info(f" 🔄 [SYMMETRY] Add inverse: {v_edge['note_id']} --({v_edge['kind']})--> {v_edge['target_id']}")
else:
logger.debug(f" 🛡️ Schutz: Manuelle Kante belegt ID {v_id}. Symmetrie verworfen.")
added_count = 0
if final_virtuals:
logger.info(f"📤 Schreibe {len(final_virtuals)} geschützte Symmetrie-Kanten in Qdrant.")
e_pts = points_for_edges(self.prefix, final_virtuals)[1]
# wait=True garantiert, dass der nächste Lauf diese Kanten sofort sieht
upsert_batch(self.client, f"{self.prefix}_edges", e_pts, wait=True)
added_count = len(final_virtuals)
self.symmetry_buffer.clear() # Puffer leeren
return {"status": "success", "added": added_count}
added = len(final_virtuals)
self.symmetry_buffer.clear()
return {"status": "success", "added": added}
async def process_file(self, file_path: str, vault_root: str, **kwargs) -> Dict[str, Any]:
"""
Transformiert eine Markdown-Datei.
Schreibt Notes/Chunks/Explicit Edges sofort (Phase 1).
Befüllt den Symmetrie-Puffer für die globale Phase 2.
Transformiert eine Note.
Implementiert strikte ID-Kanonisierung und Pydantic-Safety.
"""
apply = kwargs.get("apply", False)
force_replace = kwargs.get("force_replace", False)
@ -192,7 +175,7 @@ class IngestionService:
result = {"path": file_path, "status": "skipped", "changed": False, "error": None}
try:
# --- ORDNER-FILTER (.trash) ---
# Ordner-Filter
if any(part.startswith('.') for part in file_path.split(os.sep)):
return {**result, "status": "skipped", "reason": "hidden_folder"}
@ -210,14 +193,14 @@ class IngestionService:
note_pl = make_note_payload(parsed, vault_root=vault_root, file_path=file_path, types_cfg=self.registry)
note_id = note_pl.get("note_id")
# --- GUARD CLAUSE: Fehlende IDs verhindern PointStruct-Crash ---
if not note_id:
logger.warning(f" ⚠️ Fehlende note_id in '{file_path}'. Datei wird ignoriert.")
return {**result, "status": "error", "error": "missing_note_id"}
# --- HARD GUARD: Verhindert Pydantic-Crashes bei unvollständigen Notizen ---
if not note_id or note_id == "None":
logger.warning(f" ⚠️ Ungültige note_id in '{file_path}'. Überspringe.")
return {**result, "status": "error", "error": "invalid_note_id"}
logger.info(f"📄 Bearbeite: '{note_id}' (Typ: {note_type})")
# Change Detection & Fragment-Prüfung
# Change Detection
old_payload = None if force_replace else fetch_note_payload(self.client, self.prefix, note_id)
c_miss, e_miss = artifacts_missing(self.client, self.prefix, note_id)
if not (force_replace or not old_payload or c_miss or e_miss):
@ -226,7 +209,7 @@ class IngestionService:
if not apply:
return {**result, "status": "dry-run", "changed": True, "note_id": note_id}
# Deep Processing & MoE (LLM Validierung)
# LLM Validierung (Expert-MoE)
profile = note_pl.get("chunk_profile", "sliding_standard")
chunk_cfg = get_chunk_config_by_profile(self.registry, profile, note_type)
enable_smart = chunk_cfg.get("enable_smart_edge_allocation", False)
@ -235,12 +218,11 @@ class IngestionService:
for ch in chunks:
new_pool = []
for cand in getattr(ch, "candidate_pool", []):
# --- GUARD: Ungültige Ziele im Candidate-Pool filtern ---
t_id = cand.get('target_id') or cand.get('note_id')
if not self._is_valid_note_id(t_id):
continue
if not self._is_valid_note_id(t_id): continue
if cand.get("provenance") == "global_pool" and enable_smart:
# LLM Logging
logger.info(f" ⚖️ [VALIDATING] Relation to '{t_id}' via Expert-LLM...")
is_valid = await validate_edge_candidate(ch.text, cand, self.batch_cache, self.llm)
logger.info(f" 🧠 [SMART EDGE] {t_id} -> {'✅ OK' if is_valid else '❌ SKIP'}")
@ -252,28 +234,31 @@ class IngestionService:
chunk_pls = make_chunk_payloads(fm, note_pl["path"], chunks, file_path=file_path, types_cfg=self.registry)
vecs = await self.embedder.embed_documents([c.get("window") or "" for c in chunk_pls]) if chunk_pls else []
# Kanten-Logik (Kanonisierung via batch_cache)
# --- KANTEN-LOGIK MIT STRIKTER KANONISIERUNG (FIX FÜR STEINZEITAXT) ---
raw_edges = build_edges_for_note(note_id, chunk_pls, note_level_references=note_pl.get("references", []))
explicit_edges = []
for e in raw_edges:
target_raw = e.get("target_id")
# ID-Resolution über den Context-Cache
t_ctx = self.batch_cache.get(target_raw)
target_id = t_ctx.note_id if t_ctx else target_raw
# Wenn das Ziel nicht im Cache ist, haben wir keine stabile note_id -> Überspringen (Ghost-ID Schutz)
if not t_ctx:
logger.debug(f" ⚠️ Linkziel '{target_raw}' nicht im Cache. Überspringe Kante.")
continue
target_id = t_ctx.note_id
if not self._is_valid_note_id(target_id): continue
resolved_kind = edge_registry.resolve(e.get("kind", "related_to"), provenance=e.get("provenance", "explicit"))
# Echte physische Kante markieren (Phase 1 Authority)
# Echte physische Kante markieren (Phase 1)
e.update({
"kind": resolved_kind, "target_id": target_id,
"origin_note_id": note_id, "virtual": False, "confidence": 1.0
})
explicit_edges.append(e)
# Symmetrie-Kandidat puffern
# Symmetrie puffern
inv_kind = edge_registry.get_inverse(resolved_kind)
if inv_kind and target_id != note_id:
v_edge = e.copy()
@ -284,7 +269,7 @@ class IngestionService:
})
self.symmetry_buffer.append(v_edge)
# 4. DB Upsert (Phase 1: Authority Commitment)
# 4. DB Commit (Phase 1)
if purge_before and old_payload: purge_artifacts(self.client, self.prefix, note_id)
n_name, n_pts = points_for_note(self.prefix, note_pl, None, self.dim)
@ -292,7 +277,7 @@ class IngestionService:
if chunk_pls and vecs:
upsert_batch(self.client, f"{self.prefix}_chunks", points_for_chunks(self.prefix, chunk_pls, vecs)[1])
if explicit_edges:
# Wichtig: wait=True stellt sicher, dass die Kanten in Phase 2 searchable sind
# WICHTIG: wait=True für Phase-1 Konsistenz
upsert_batch(self.client, f"{self.prefix}_edges", points_for_edges(self.prefix, explicit_edges)[1], wait=True)
logger.info(f" ✨ Phase 1 fertig: {len(chunk_pls)} Chunks, {len(explicit_edges)} explizite Kanten.")