WP4d #16
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@ -1,9 +1,7 @@
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"""
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FILE: app/core/chunking/chunking_propagation.py
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DESCRIPTION: Injiziert Sektions-Kanten physisch in den Text (Embedding-Enrichment).
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Stellt die "Gold-Standard"-Qualität von v3.1.0 wieder her.
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VERSION: 3.3.1
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STATUS: Active
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Fix v3.3.5: Erkennt Wikilink-Targets, um Dopplungen zu verhindern.
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"""
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from typing import List, Dict, Set
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from .chunking_models import Chunk
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@ -12,7 +10,7 @@ from .chunking_parser import parse_edges_robust
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def propagate_section_edges(chunks: List[Chunk]) -> List[Chunk]:
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"""
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Sammelt Kanten pro Sektion und schreibt sie hart in den Text und das Window.
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Dies ist essenziell für die Vektorisierung der Beziehungen.
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Verhindert Dopplungen, wenn Kanten bereits via [!edge] Callout vorhanden sind.
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"""
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# 1. Sammeln: Alle expliziten Kanten pro Sektions-Pfad aggregieren
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section_map: Dict[str, Set[str]] = {} # path -> set(kind:target)
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@ -39,18 +37,21 @@ def propagate_section_edges(chunks: List[Chunk]) -> List[Chunk]:
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injections = []
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for e_str in edges_to_add:
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kind, target = e_str.split(':', 1)
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# Nur injizieren, wenn die Kante nicht bereits im Text steht
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token = f"[[rel:{kind}|{target}]]"
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if token not in ch.text:
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injections.append(token)
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# DER FIX: Wir prüfen, ob das Ziel (target) bereits im Text vorkommt.
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# Wir suchen nach [[target]] (Callout-Stil) oder |target]] (Rel-Stil).
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if f"[[{target}]]" in ch.text or f"|{target}]]" in ch.text:
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continue
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injections.append(f"[[rel:{kind}|{target}]]")
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if injections:
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# Physische Anreicherung (Der v3.1.0 Qualitäts-Fix)
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# Physische Anreicherung
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# Triple-Newline für saubere Trennung im Embedding-Fenster
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block = "\n\n\n" + " ".join(injections)
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ch.text += block
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# ENTSCHEIDEND: Auch ins Window schreiben, da Qdrant hier sucht!
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# Auch ins Window schreiben, da Qdrant hier sucht!
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if ch.window:
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ch.window += block
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else:
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@ -3,9 +3,8 @@ FILE: app/core/ingestion/ingestion_note_payload.py
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DESCRIPTION: Baut das JSON-Objekt für mindnet_notes.
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FEATURES:
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- Multi-Hash (body/full) für flexible Change Detection.
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- Fix v2.4.4: Integration der zentralen Registry (WP-14) für konsistente Defaults.
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VERSION: 2.4.4
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STATUS: Active
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- Fix v2.4.5: Präzise Hash-Logik für Profil-Änderungen.
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- Integration der zentralen Registry (WP-14).
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"""
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from __future__ import annotations
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from typing import Any, Dict, Tuple, Optional
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@ -45,14 +44,22 @@ def _compute_hash(content: str) -> str:
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return hashlib.sha256(content.encode("utf-8")).hexdigest()
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def _get_hash_source_content(n: Dict[str, Any], mode: str) -> str:
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"""Generiert den Hash-Input-String basierend auf Body oder Metadaten."""
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body = str(n.get("body") or "")
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"""
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Generiert den Hash-Input-String basierend auf Body oder Metadaten.
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Fix: Inkludiert nun alle entscheidungsrelevanten Profil-Parameter.
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"""
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body = str(n.get("body") or "").strip()
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if mode == "body": return body
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if mode == "full":
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fm = n.get("frontmatter") or {}
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meta_parts = []
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# Sortierte Liste für deterministische Hashes
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for k in sorted(["title", "type", "status", "tags", "chunking_profile", "chunk_profile", "retriever_weight"]):
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# Wir inkludieren alle Felder, die das Chunking oder Retrieval beeinflussen
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keys = [
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"title", "type", "status", "tags",
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"chunking_profile", "chunk_profile",
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"retriever_weight", "split_level", "strict_heading_split"
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]
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for k in sorted(keys):
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val = fm.get(k)
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if val is not None: meta_parts.append(f"{k}:{val}")
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return f"{'|'.join(meta_parts)}||{body}"
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@ -79,11 +86,11 @@ def _cfg_defaults(reg: dict) -> dict:
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def make_note_payload(note: Any, *args, **kwargs) -> Dict[str, Any]:
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"""
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Baut das Note-Payload inklusive Multi-Hash und Audit-Validierung.
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WP-14: Nutzt nun die zentrale Registry für alle Fallbacks.
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WP-14: Nutzt die zentrale Registry für alle Fallbacks.
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"""
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n = _as_dict(note)
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# Nutzt übergebene Registry oder lädt sie global
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# Registry & Context Settings
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reg = kwargs.get("types_cfg") or load_type_registry()
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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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@ -96,7 +103,6 @@ def make_note_payload(note: Any, *args, **kwargs) -> Dict[str, Any]:
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ingest_cfg = reg.get("ingestion_settings", {})
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# --- retriever_weight Audit ---
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# Priorität: Frontmatter -> Typ-Config -> globale Config -> Env-Var
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default_rw = float(os.environ.get("MINDNET_DEFAULT_RETRIEVER_WEIGHT", 1.0))
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retriever_weight = fm.get("retriever_weight")
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if retriever_weight is None:
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@ -107,14 +113,13 @@ def make_note_payload(note: Any, *args, **kwargs) -> Dict[str, Any]:
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retriever_weight = default_rw
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# --- chunk_profile Audit ---
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# Nutzt nun primär die ingestion_settings aus der Registry
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chunk_profile = fm.get("chunking_profile") or fm.get("chunk_profile")
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if chunk_profile is None:
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chunk_profile = cfg_type.get("chunking_profile") or cfg_type.get("chunk_profile")
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if chunk_profile is None:
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chunk_profile = ingest_cfg.get("default_chunk_profile", cfg_def.get("chunking_profile", "sliding_standard"))
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# --- edge_defaults ---
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# --- edge_defaults Audit ---
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edge_defaults = fm.get("edge_defaults")
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if edge_defaults is None:
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edge_defaults = cfg_type.get("edge_defaults", cfg_def.get("edge_defaults", []))
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@ -138,21 +143,23 @@ def make_note_payload(note: Any, *args, **kwargs) -> Dict[str, Any]:
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}
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# --- MULTI-HASH ---
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# Generiert Hashes für Change Detection
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for mode in ["body", "full"]:
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content = _get_hash_source_content(n, mode)
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payload["hashes"][f"{mode}:{hash_source}:{hash_normalize}"] = _compute_hash(content)
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# Metadaten Anreicherung
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# Metadaten Anreicherung (Tags, Aliases, Zeitstempel)
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tags = fm.get("tags") or fm.get("keywords") or n.get("tags")
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if tags: payload["tags"] = _ensure_list(tags)
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if fm.get("aliases"): payload["aliases"] = _ensure_list(fm.get("aliases"))
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aliases = fm.get("aliases")
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if aliases: payload["aliases"] = _ensure_list(aliases)
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for k in ("created", "modified", "date"):
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v = fm.get(k) or n.get(k)
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if v: payload[k] = str(v)
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if n.get("body"): payload["fulltext"] = str(n["body"])
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if n.get("body"):
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payload["fulltext"] = str(n["body"])
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# Final JSON Validation Audit
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json.loads(json.dumps(payload, ensure_ascii=False))
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|
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Reference in New Issue
Block a user