Aktualisierung der atomaren Sektions-Chunking-Strategie auf Version 3.9.5 mit Implementierung des 'Pack-and-Carry-Over' Verfahrens. Einführung neuer Konfigurationsoptionen für Smart-Edge und strikte Überschriftenteilung. Verbesserte Handhabung von leeren Überschriften und Anpassungen an der Warteschlangen-Verarbeitung zur Optimierung der Chunk-Erstellung.
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@ -8,19 +8,13 @@ from typing import List, Tuple, Set
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from .chunking_models import RawBlock
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from .chunking_utils import extract_frontmatter_from_text
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def split_sentences(text: str) -> list[str]:
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"""Teilt Text in Sätze auf unter Berücksichtigung deutscher Interpunktion."""
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text = re.sub(r'\s+', ' ', text.strip())
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if not text: return []
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# Splittet bei Satzzeichen, gefolgt von Leerzeichen und Großbuchstaben
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return [s.strip() for s in re.split(r'(?<=[.!?])\s+(?=[A-ZÄÖÜ0-9„(])', text) if s.strip()]
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def parse_blocks(md_text: str) -> Tuple[List[RawBlock], str]:
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"""Zerlegt Text in logische Einheiten (RawBlocks), inklusive H1-H6."""
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blocks = []
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h1_title = "Dokument"; section_path = "/"; current_section_title = None
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fm, text_without_fm = extract_frontmatter_from_text(md_text)
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# H1 für Metadaten extrahieren
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h1_match = re.search(r'^#\s+(.*)', text_without_fm, re.MULTILINE)
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if h1_match: h1_title = h1_match.group(1).strip()
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@ -32,20 +26,26 @@ def parse_blocks(md_text: str) -> Tuple[List[RawBlock], str]:
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heading_match = re.match(r'^(#{1,6})\s+(.*)', stripped)
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if heading_match:
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# Vorherigen Text-Block abschließen
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if buffer:
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content = "\n".join(buffer).strip()
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if content:
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blocks.append(RawBlock("paragraph", content, None, section_path, current_section_title))
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buffer = []
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level = len(heading_match.group(1))
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title = heading_match.group(2).strip()
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# Pfad- und Titel-Update
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if level == 1:
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current_section_title = title; section_path = "/"
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elif level == 2:
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current_section_title = title; section_path = f"/{current_section_title}"
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blocks.append(RawBlock("heading", stripped, level, section_path, current_section_title))
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continue
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# Trenner oder Leerzeilen beenden Blöcke, außer innerhalb von Callouts
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if (not stripped or stripped == "---") and not line.startswith('>'):
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if buffer:
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content = "\n".join(buffer).strip()
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@ -60,28 +60,12 @@ def parse_blocks(md_text: str) -> Tuple[List[RawBlock], str]:
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if buffer:
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content = "\n".join(buffer).strip()
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if content: blocks.append(RawBlock("paragraph", content, None, section_path, current_section_title))
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return blocks, h1_title
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def parse_edges_robust(text: str) -> Set[str]:
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"""Extrahiert Kanten-Kandidaten aus Wikilinks und Callouts."""
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found_edges = set()
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inlines = re.findall(r'\[\[rel:([^\|\]]+)\|?([^\]]*)\]\]', text)
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for kind, target in inlines:
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k = kind.strip().lower(); t = target.strip()
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if k and t: found_edges.add(f"{k}:{t}")
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lines = text.split('\n'); current_edge_type = None
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for line in lines:
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stripped = line.strip()
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callout_match = re.match(r'>\s*\[!edge\]\s*([^:\s]+)', stripped)
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if callout_match:
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current_edge_type = callout_match.group(1).strip().lower()
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links = re.findall(r'\[\[([^\]]+)\]\]', stripped)
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for l in links:
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if "rel:" not in l: found_edges.add(f"{current_edge_type}:{l}")
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continue
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if current_edge_type and stripped.startswith('>'):
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links = re.findall(r'\[\[([^\]]+)\]\]', stripped)
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for l in links:
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if "rel:" not in l: found_edges.add(f"{current_edge_type}:{l}")
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elif not stripped.startswith('>'): current_edge_type = None
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return found_edges
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def split_sentences(text: str) -> list[str]:
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"""Teilt Text in Sätze auf unter Berücksichtigung deutscher Interpunktion."""
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text = re.sub(r'\s+', ' ', text.strip())
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if not text: return []
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# Splittet bei Satzzeichen, gefolgt von Leerzeichen und Großbuchstaben
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return [s.strip() for s in re.split(r'(?<=[.!?])\s+(?=[A-ZÄÖÜ0-9„(])', text) if s.strip()]
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@ -1,7 +1,7 @@
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"""
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FILE: app/core/chunking/chunking_strategies.py
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DESCRIPTION: Universelle Strategie für atomares Sektions-Chunking v3.9.0.
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Regelkonforme Implementierung: Pack-Sections, Trust Estimation, Carry-Over.
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DESCRIPTION: Strategie für atomares Sektions-Chunking v3.9.5.
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Implementiert das 'Pack-and-Carry-Over' Verfahren nach Nutzerwunsch.
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"""
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from typing import List, Dict, Any, Optional
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from .chunking_models import RawBlock, Chunk
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@ -15,7 +15,14 @@ def _create_win(doc_title: str, sec_title: Optional[str], text: str) -> str:
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return f"{prefix}\n{text}".strip() if prefix else text
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def strategy_by_heading(blocks: List[RawBlock], config: Dict[str, Any], note_id: str, doc_title: str = "") -> List[Chunk]:
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"""
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Universelle Sektions-Strategie:
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- Smart-Edge=True: Packt Sektionen basierend auf Schätzung (Regel 1-3).
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- Smart-Edge=False: Hard Split an Überschriften (außer leere Header).
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- Strict=True erzwingt Hard Split Verhalten innerhalb der Smart-Logik.
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"""
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smart_edge = config.get("enable_smart_edge_allocation", True)
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strict = config.get("strict_heading_split", False)
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target = config.get("target", 400)
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max_tokens = config.get("max", 600)
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split_level = config.get("split_level", 2)
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@ -33,65 +40,72 @@ def strategy_by_heading(blocks: List[RawBlock], config: Dict[str, Any], note_id:
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section_title=title, section_path=path, neighbors_prev=None, neighbors_next=None
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))
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# --- FALL A: HARD SPLIT (enable_smart_edge_allocation: false) ---
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if not smart_edge:
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buf = []
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for b in blocks:
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# Trenne hart bei Überschrift <= split_level
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if b.kind == "heading" and b.level <= split_level:
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# Prüfe, ob Puffer mehr als nur Überschriften enthält (keine leeren Chunks)
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has_content = any(x.kind != "heading" for x in buf)
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if buf and has_content:
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_emit("\n\n".join([x.text for x in buf]), buf[0].section_title, buf[0].section_path)
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buf = []
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buf.append(b)
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if buf: _emit("\n\n".join([x.text for x in buf]), buf[0].section_title, buf[0].section_path)
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return chunks
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# --- FALL B: SMART EDGE ALLOCATION (Pack-and-Carry-Over) ---
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# 1. Gruppierung in atomare Einheiten (Sektions-Isolation)
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# --- SCHRITT 1: Gruppierung in atomare Sektions-Einheiten ---
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sections: List[Dict[str, Any]] = []
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curr_blocks = []
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for b in blocks:
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if b.kind == "heading" and b.level <= split_level:
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if curr_blocks:
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sections.append({"text": "\n\n".join([x.text for x in curr_blocks]), "meta": curr_blocks[0]})
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sections.append({"text": "\n\n".join([x.text for x in curr_blocks]),
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"meta": curr_blocks[0], "is_empty": len(curr_blocks) == 1})
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curr_blocks = [b]
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else: curr_blocks.append(b)
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if curr_blocks:
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sections.append({"text": "\n\n".join([x.text for x in curr_blocks]), "meta": curr_blocks[0]})
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sections.append({"text": "\n\n".join([x.text for x in curr_blocks]),
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"meta": curr_blocks[0], "is_empty": len(curr_blocks) == 1})
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# 2. Warteschlangen-Verarbeitung (Regel 1-3)
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# Wir nutzen eine Liste als Queue für Carry-Over-Reste
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# --- SCHRITT 2: Verarbeitung der Queue ---
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queue = list(sections)
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current_chunk_text = ""
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current_meta = {"title": None, "path": "/"}
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# Hard-Split-Bedingung: Entweder Smart-Edge aus ODER Profil ist Strict
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is_hard_split_mode = (not smart_edge) or (strict)
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while queue:
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item = queue.pop(0)
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item_text = item["text"]
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# Initialisiere Metadaten für einen neuen Chunk
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# Initialisierung für neuen Chunk
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if not current_chunk_text:
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current_meta["title"] = item["meta"].section_title
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current_meta["path"] = item["meta"].section_path
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# Schätzung (Regel 2: Wir verlassen uns darauf)
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# FALL A: Hard Split Modus (Regel: Trenne bei jeder Sektion <= Level)
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if is_hard_split_mode:
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# Regel: Leere Überschriften verbleiben am nächsten Chunk
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if item.get("is_empty", False) and queue:
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current_chunk_text = (current_chunk_text + "\n\n" + item_text).strip()
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continue # Nimm das nächste Item dazu
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combined = (current_chunk_text + "\n\n" + item_text).strip()
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if estimate_tokens(combined) > max_tokens and current_chunk_text:
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# Falls es trotz Hard-Split zu groß wird, flashen wir erst den alten Teil
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_emit(current_chunk_text, current_meta["title"], current_meta["path"])
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current_chunk_text = item_text
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else:
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current_chunk_text = combined
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# Im Hard Split flashen wir nach jeder Sektion, die nicht leer ist
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_emit(current_chunk_text, current_meta["title"], current_meta["path"])
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current_chunk_text = ""
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continue
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# FALL B: Smart Mode (Regel 1-3)
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combined_text = (current_chunk_text + "\n\n" + item_text).strip() if current_chunk_text else item_text
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combined_est = estimate_tokens(combined_text)
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if combined_est <= max_tokens:
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# Regel 1: Vollständiger Abschnitt passt -> Aufnehmen
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# Regel 1 & 2: Passt nach Schätzung -> Aufnehmen
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current_chunk_text = combined_text
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else:
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# Er passt nicht ganz rein.
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# Regel 3: Passt nicht -> Entweder Puffer flashen oder Item zerlegen
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if current_chunk_text:
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# Puffer ist bereits gefüllt -> Wegschreiben, Item zurück in die Queue
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_emit(current_chunk_text, current_meta["title"], current_meta["path"])
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current_chunk_text = ""
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queue.insert(0, item)
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queue.insert(0, item) # Item für neuen Chunk zurücklegen
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else:
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# Regel 3: Einzelner Abschnitt allein ist > max -> Smart Zerlegung
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# Einzelne Sektion zu groß -> Smart Zerlegung
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sents = split_sentences(item_text)
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header_prefix = item["meta"].text if item["meta"].kind == "heading" else ""
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@ -103,25 +117,22 @@ def strategy_by_heading(blocks: List[RawBlock], config: Dict[str, Any], note_id:
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sents.insert(0, s); break
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take_sents.append(s); take_len += slen
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# Ersten Teil emittieren
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_emit(" ".join(take_sents), current_meta["title"], current_meta["path"])
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# Rest als Carry-Over zurück in die Queue (Regel 3)
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# Carry-Over: Rest wird vorne in die Queue geschoben
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if sents:
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remainder_text = " ".join(sents)
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# Kontext-Erhalt: Überschrift für den Rest wiederholen
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if header_prefix and not remainder_text.startswith(header_prefix):
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remainder_text = header_prefix + "\n\n" + remainder_text
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queue.insert(0, {"text": remainder_text, "meta": item["meta"]})
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remainder = " ".join(sents)
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if header_prefix and not remainder.startswith(header_prefix):
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remainder = header_prefix + "\n\n" + remainder
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queue.insert(0, {"text": remainder, "meta": item["meta"], "is_split": True})
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# Letzten Rest wegschreiben
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if current_chunk_text:
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_emit(current_chunk_text, current_meta["title"], current_meta["path"])
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return chunks
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def strategy_sliding_window(blocks: List[RawBlock], config: Dict[str, Any], note_id: str, context_prefix: str = "") -> List[Chunk]:
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"""Sliding Window: Unverändert erhalten für Standard-Typen."""
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def strategy_sliding_window(blocks: List[RawBlock], config: Dict[str, Any], note_id: str, doc_title: str = "") -> List[Chunk]:
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"""Standard Sliding Window Strategie."""
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target = config.get("target", 400); max_tokens = config.get("max", 600)
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chunks: List[Chunk] = []; buf: List[RawBlock] = []
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for b in blocks:
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@ -129,12 +140,12 @@ def strategy_sliding_window(blocks: List[RawBlock], config: Dict[str, Any], note
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curr_tokens = sum(estimate_tokens(x.text) for x in buf) if buf else 0
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if curr_tokens + b_tokens > max_tokens and buf:
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txt = "\n\n".join([x.text for x in buf]); idx = len(chunks)
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win = _create_win(doc_title=context_prefix, sec_title=buf[0].section_title, text=txt)
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win = _create_win(doc_title, buf[0].section_title, txt)
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chunks.append(Chunk(id=f"{note_id}#c{idx:02d}", note_id=note_id, index=idx, text=txt, window=win, token_count=curr_tokens, section_title=buf[0].section_title, section_path=buf[0].section_path, neighbors_prev=None, neighbors_next=None))
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buf = []
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buf.append(b)
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if buf:
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txt = "\n\n".join([x.text for x in buf]); idx = len(chunks)
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win = _create_win(doc_title=context_prefix, sec_title=buf[0].section_title, text=txt)
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win = _create_win(doc_title, buf[0].section_title, txt)
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chunks.append(Chunk(id=f"{note_id}#c{idx:02d}", note_id=note_id, index=idx, text=txt, window=win, token_count=estimate_tokens(txt), section_title=buf[0].section_title, section_path=buf[0].section_path, neighbors_prev=None, neighbors_next=None))
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return chunks
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