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

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Lars merged 71 commits from WP24c into main 2026-01-12 10:53:20 +01:00
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app/core/ingestion/ingestion_processor.py
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@ -2,19 +2,18 @@
FILE: app/core/ingestion/ingestion_processor.py FILE: app/core/ingestion/ingestion_processor.py
DESCRIPTION: Der zentrale IngestionService (Orchestrator). DESCRIPTION: Der zentrale IngestionService (Orchestrator).
WP-24c: Integration der Symmetrie-Logik (Automatische inverse Kanten). WP-24c: Integration der Symmetrie-Logik (Automatische inverse Kanten).
WP-25a: Mixture of Experts (MoE) - LLM Edge Validation. WP-25a: Integration der Mixture of Experts (MoE) Architektur.
WP-15b: Two-Pass Workflow mit globalem Kontext-Cache. WP-15b: Two-Pass Workflow mit globalem Kontext-Cache.
WP-20/22: Cloud-Resilienz und Content-Lifecycle integriert. WP-20/22: Cloud-Resilienz und Content-Lifecycle integriert.
AUDIT v3.2.0: Fix für KeyError 'target_id', stabiles Logging AUDIT v3.2.0: Fix für KeyError 'target_id', TypeError (Sync-Check)
und Priorisierung expliziter User-Kanten. und Business-Centric Logging.
VERSION: 3.2.0 (WP-24c: Stability & Business Logging) VERSION: 3.2.0 (WP-24c: Stability & Full Feature Set)
STATUS: Active STATUS: Active
""" """
import logging import logging
import asyncio import asyncio
import os import os
import re import re
import sys
from typing import Dict, List, Optional, Tuple, Any from typing import Dict, List, Optional, Tuple, Any
# Core Module Imports # Core Module Imports
@ -23,7 +22,7 @@ from app.core.parser import (
validate_required_frontmatter, NoteContext validate_required_frontmatter, NoteContext
) )
from app.core.chunking import assemble_chunks from app.core.chunking import assemble_chunks
# WP-24c: Import für die deterministische ID-Vorabberechnung (UUID-basiert) # WP-24c: Import für die deterministische ID-Vorabberechnung
from app.core.graph.graph_utils import _mk_edge_id from app.core.graph.graph_utils import _mk_edge_id
# MODULARISIERUNG: Neue Import-Pfade für die Datenbank-Ebene # MODULARISIERUNG: Neue Import-Pfade für die Datenbank-Ebene
@ -43,7 +42,7 @@ from .ingestion_validation import validate_edge_candidate
from .ingestion_note_payload import make_note_payload from .ingestion_note_payload import make_note_payload
from .ingestion_chunk_payload import make_chunk_payloads from .ingestion_chunk_payload import make_chunk_payloads
# Fallback für Edges # Fallback für Edges (Struktur-Verknüpfung)
try: try:
from app.core.graph.graph_derive_edges import build_edges_for_note from app.core.graph.graph_derive_edges import build_edges_for_note
except ImportError: except ImportError:
@ -53,17 +52,20 @@ logger = logging.getLogger(__name__)
class IngestionService: class IngestionService:
def __init__(self, collection_prefix: str = None): def __init__(self, collection_prefix: str = None):
"""Initialisiert den Service und bereinigt das Logging von technischem Lärm.""" """Initialisiert den Service und nutzt die neue database-Infrastruktur."""
from app.config import get_settings from app.config import get_settings
self.settings = get_settings() self.settings = get_settings()
# --- LOGGING CLEANUP (Business Focus) --- # --- LOGGING CLEANUP ---
# Unterdrückt technische Bibliotheks-Meldungen im Log-File und Konsole # Unterdrückt Bibliotheks-Lärm in Konsole und Datei
for lib in ["httpx", "httpcore", "qdrant_client", "urllib3", "openai"]: logging.getLogger("httpx").setLevel(logging.WARNING)
logging.getLogger(lib).setLevel(logging.WARNING) logging.getLogger("httpcore").setLevel(logging.WARNING)
logging.getLogger("qdrant_client").setLevel(logging.WARNING)
logging.getLogger("urllib3").setLevel(logging.WARNING)
self.prefix = collection_prefix or self.settings.COLLECTION_PREFIX self.prefix = collection_prefix or self.settings.COLLECTION_PREFIX
self.cfg = QdrantConfig.from_env() self.cfg = QdrantConfig.from_env()
# Synchronisierung der Konfiguration mit dem Instanz-Präfix
self.cfg.prefix = self.prefix self.cfg.prefix = self.prefix
self.client = get_client(self.cfg) self.client = get_client(self.cfg)
@ -75,6 +77,7 @@ class IngestionService:
embed_cfg = self.llm.profiles.get("embedding_expert", {}) embed_cfg = self.llm.profiles.get("embedding_expert", {})
self.dim = embed_cfg.get("dimensions") or self.settings.VECTOR_SIZE self.dim = embed_cfg.get("dimensions") or self.settings.VECTOR_SIZE
# Festlegen, welcher Hash für die Change-Detection maßgeblich ist
self.active_hash_mode = self.settings.CHANGE_DETECTION_MODE self.active_hash_mode = self.settings.CHANGE_DETECTION_MODE
self.batch_cache: Dict[str, NoteContext] = {} # WP-15b LocalBatchCache self.batch_cache: Dict[str, NoteContext] = {} # WP-15b LocalBatchCache
@ -91,33 +94,35 @@ class IngestionService:
def _is_valid_note_id(self, text: str, provenance: str = "explicit") -> bool: def _is_valid_note_id(self, text: str, provenance: str = "explicit") -> bool:
""" """
WP-24c: Prüft Ziel-Strings auf Validität. WP-24c: Prüft Ziel-Strings auf Validität.
User-Authority (explicit) wird weniger gefiltert als System-Strukturen. User-Links (explicit) werden weniger gefiltert als System-Symmetrien.
""" """
if not text or len(text.strip()) < 2: if not text or len(text.strip()) < 2:
return False return False
# Nur System-Kanten (Symmetrie) filtern wir gegen die Typ-Blacklist # Symmetrie-Filter gegen Typ-Strings
if provenance != "explicit": if provenance != "explicit":
blacklisted = {"insight", "event", "source", "task", "project", "person", "concept", "related_to", "referenced_by"} blacklisted = {"insight", "event", "source", "task", "project", "person", "concept", "related_to", "referenced_by"}
if text.lower().strip() in blacklisted: if text.lower().strip() in blacklisted:
return False return False
if len(text) > 150: return False # Vermutlich ein ganzer Satz if len(text) > 150: return False # Wahrscheinlich kein Titel
return True return True
async def run_batch(self, file_paths: List[str], vault_root: str) -> List[Dict[str, Any]]: async def run_batch(self, file_paths: List[str], vault_root: str) -> List[Dict[str, Any]]:
""" """
WP-15b: Two-Pass Ingestion Workflow. WP-15b: Implementiert den Two-Pass Ingestion Workflow.
Implementiert Batch-Import mit Symmetrie-Gedächtnis. Pass 1: Pre-Scan füllt den Context-Cache.
Pass 2: Verarbeitung nutzt den Cache für die semantische Prüfung.
""" """
self.processed_explicit_ids.clear() self.processed_explicit_ids.clear()
logger.info(f"--- 🔍 START BATCH IMPORT ({len(file_paths)} Dateien) ---") logger.info(f"--- 🔍 START BATCH IMPORT ({len(file_paths)} Dateien) ---")
for path in file_paths: for path in file_paths:
try: try:
# Übergabe der Registry für dynamische Scan-Tiefe
ctx = pre_scan_markdown(path, registry=self.registry) ctx = pre_scan_markdown(path, registry=self.registry)
if ctx: if ctx:
# Look-up Index für Note_IDs und Titel # Mehrfache Indizierung für robusten Look-up
self.batch_cache[ctx.note_id] = ctx self.batch_cache[ctx.note_id] = ctx
self.batch_cache[ctx.title] = ctx self.batch_cache[ctx.title] = ctx
fname = os.path.splitext(os.path.basename(path))[0] fname = os.path.splitext(os.path.basename(path))[0]
@ -203,9 +208,9 @@ class IngestionService:
is_valid = await validate_edge_candidate( is_valid = await validate_edge_candidate(
ch.text, cand, self.batch_cache, self.llm, profile_name="ingest_validator" ch.text, cand, self.batch_cache, self.llm, profile_name="ingest_validator"
) )
# Fix (v3.2.0): Symmetrisches Logging ohne KeyError-Risiko # Fix v3.2.0: Sicherer Zugriff via .get() verhindert Crash bei fehlender target_id
target_label = cand.get('target_id') or cand.get('note_id') or 'Unbekannt' t_id = cand.get('target_id') or cand.get('note_id') or "Unknown"
logger.info(f" 🧠 [SMART EDGE] {target_label} -> {'✅ OK' if is_valid else '❌ SKIP'}") logger.info(f" 🧠 [SMART EDGE] {t_id} -> {'✅ OK' if is_valid else '❌ SKIP'}")
if is_valid: new_pool.append(cand) if is_valid: new_pool.append(cand)
else: else:
new_pool.append(cand) new_pool.append(cand)
@ -214,7 +219,7 @@ class IngestionService:
chunk_pls = make_chunk_payloads(fm, note_pl["path"], chunks, file_path=file_path, types_cfg=self.registry) 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 [] vecs = await self.embedder.embed_documents([c.get("window") or "" for c in chunk_pls]) if chunk_pls else []
# Aggregation aller Kanten # Aggregation aller finalen Kanten (Edges)
raw_edges = build_edges_for_note( raw_edges = build_edges_for_note(
note_id, chunk_pls, note_id, chunk_pls,
note_level_references=note_pl.get("references", []), note_level_references=note_pl.get("references", []),
@ -230,12 +235,17 @@ class IngestionService:
if not self._is_valid_note_id(target_raw, provenance="explicit"): if not self._is_valid_note_id(target_raw, provenance="explicit"):
continue continue
resolved_kind = edge_registry.resolve(e.get("kind", "related_to"), provenance=e.get("provenance", "explicit")) resolved_kind = edge_registry.resolve(
e.update({ e.get("kind", "related_to"),
"kind": resolved_kind, "origin_note_id": note_id, provenance=e.get("provenance", "explicit"),
"virtual": False, "confidence": 1.0 context={"file": file_path, "note_id": note_id}
}) )
e["kind"] = resolved_kind
e["origin_note_id"] = note_id
e["virtual"] = False
e["confidence"] = e.get("confidence", 1.0)
# Registrierung für Batch-Authority
edge_id = _mk_edge_id(resolved_kind, note_id, target_raw, e.get("scope", "note")) edge_id = _mk_edge_id(resolved_kind, note_id, target_raw, e.get("scope", "note"))
self.processed_explicit_ids.add(edge_id) self.processed_explicit_ids.add(edge_id)
final_edges.append(e) final_edges.append(e)
@ -254,6 +264,7 @@ class IngestionService:
is_in_batch = potential_id in self.processed_explicit_ids is_in_batch = potential_id in self.processed_explicit_ids
# Real-Time DB Check (Ohne 'await', da sync)
is_in_db = False is_in_db = False
if not is_in_batch: if not is_in_batch:
is_in_db = is_explicit_edge_present(self.client, self.prefix, potential_id) is_in_db = is_explicit_edge_present(self.client, self.prefix, potential_id)
@ -276,14 +287,23 @@ class IngestionService:
if purge_before and old_payload: if purge_before and old_payload:
purge_artifacts(self.client, self.prefix, note_id) purge_artifacts(self.client, self.prefix, note_id)
upsert_batch(self.client, f"{self.prefix}_notes", points_for_note(self.prefix, note_pl, None, self.dim)[1]) # Speichern
n_name, n_pts = points_for_note(self.prefix, note_pl, None, self.dim)
upsert_batch(self.client, n_name, n_pts)
if chunk_pls and vecs: if chunk_pls and vecs:
upsert_batch(self.client, f"{self.prefix}_chunks", points_for_chunks(self.prefix, chunk_pls, vecs)[1]) c_pts = points_for_chunks(self.prefix, chunk_pls, vecs)[1]
upsert_batch(self.client, f"{self.prefix}_chunks", c_pts)
if edges: if edges:
upsert_batch(self.client, f"{self.prefix}_edges", points_for_edges(self.prefix, edges)[1]) e_pts = points_for_edges(self.prefix, edges)[1]
upsert_batch(self.client, f"{self.prefix}_edges", e_pts)
logger.info(f" ✨ Fertig: {len(chunk_pls)} Chunks, {len(edges)} Kanten.") logger.info(f" ✨ Fertig: {len(chunk_pls)} Chunks, {len(edges)} Kanten.")
return {"status": "success", "note_id": note_id, "edges_count": len(edges)} return {
"path": file_path, "status": "success", "changed": True, "note_id": note_id,
"chunks_count": len(chunk_pls), "edges_count": len(edges)
}
except Exception as e: except Exception as e:
logger.error(f"❌ Fehler bei {file_path}: {e}", exc_info=True) logger.error(f"❌ Fehler bei {file_path}: {e}", exc_info=True)
return {**result, "error": str(e)} return {**result, "error": str(e)}
@ -292,7 +312,6 @@ class IngestionService:
"""Erstellt eine Note aus einem Textstream.""" """Erstellt eine Note aus einem Textstream."""
target_path = os.path.join(vault_root, folder, filename) target_path = os.path.join(vault_root, folder, filename)
os.makedirs(os.path.dirname(target_path), exist_ok=True) os.makedirs(os.path.dirname(target_path), exist_ok=True)
with open(target_path, "w", encoding="utf-8") as f: with open(target_path, "w", encoding="utf-8") as f: f.write(markdown_content)
f.write(markdown_content)
await asyncio.sleep(0.1) await asyncio.sleep(0.1)
return await self.process_file(file_path=target_path, vault_root=vault_root, apply=True, force_replace=True, purge_before=True) return await self.process_file(file_path=target_path, vault_root=vault_root, apply=True, force_replace=True, purge_before=True)