""" FILE: app/core/chunking/chunking_strategies.py DESCRIPTION: Strategie für atomares Sektions-Chunking v3.9.5. Implementiert das 'Pack-and-Carry-Over' Verfahren nach Nutzerwunsch. """ from typing import List, Dict, Any, Optional from .chunking_models import RawBlock, Chunk from .chunking_utils import estimate_tokens from .chunking_parser import split_sentences def _create_win(doc_title: str, sec_title: Optional[str], text: str) -> str: parts = [doc_title] if doc_title else [] if sec_title and sec_title != doc_title: parts.append(sec_title) prefix = " > ".join(parts) return f"{prefix}\n{text}".strip() if prefix else text def strategy_by_heading(blocks: List[RawBlock], config: Dict[str, Any], note_id: str, doc_title: str = "") -> List[Chunk]: """ Universelle Sektions-Strategie: - Smart-Edge=True: Packt Sektionen basierend auf Schätzung (Regel 1-3). - Smart-Edge=False: Hard Split an Überschriften (außer leere Header). - Strict=True erzwingt Hard Split Verhalten innerhalb der Smart-Logik. """ smart_edge = config.get("enable_smart_edge_allocation", True) strict = config.get("strict_heading_split", False) target = config.get("target", 400) max_tokens = config.get("max", 600) split_level = config.get("split_level", 2) overlap_cfg = config.get("overlap", (50, 80)) overlap = sum(overlap_cfg) // 2 if isinstance(overlap_cfg, (list, tuple)) else overlap_cfg chunks: List[Chunk] = [] def _emit(txt, title, path): idx = len(chunks) win = _create_win(doc_title, title, txt) 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=title, section_path=path, neighbors_prev=None, neighbors_next=None )) # --- SCHRITT 1: Gruppierung in atomare Sektions-Einheiten --- sections: List[Dict[str, Any]] = [] curr_blocks = [] for b in blocks: if b.kind == "heading" and b.level <= split_level: if curr_blocks: sections.append({"text": "\n\n".join([x.text for x in curr_blocks]), "meta": curr_blocks[0], "is_empty": len(curr_blocks) == 1}) curr_blocks = [b] else: curr_blocks.append(b) if curr_blocks: sections.append({"text": "\n\n".join([x.text for x in curr_blocks]), "meta": curr_blocks[0], "is_empty": len(curr_blocks) == 1}) # --- SCHRITT 2: Verarbeitung der Queue --- queue = list(sections) current_chunk_text = "" current_meta = {"title": None, "path": "/"} # Hard-Split-Bedingung: Entweder Smart-Edge aus ODER Profil ist Strict is_hard_split_mode = (not smart_edge) or (strict) while queue: item = queue.pop(0) item_text = item["text"] # Initialisierung für neuen Chunk if not current_chunk_text: current_meta["title"] = item["meta"].section_title current_meta["path"] = item["meta"].section_path # FALL A: Hard Split Modus (Regel: Trenne bei jeder Sektion <= Level) if is_hard_split_mode: # Regel: Leere Überschriften verbleiben am nächsten Chunk if item.get("is_empty", False) and queue: current_chunk_text = (current_chunk_text + "\n\n" + item_text).strip() continue # Nimm das nächste Item dazu combined = (current_chunk_text + "\n\n" + item_text).strip() if estimate_tokens(combined) > max_tokens and current_chunk_text: # Falls es trotz Hard-Split zu groß wird, flashen wir erst den alten Teil _emit(current_chunk_text, current_meta["title"], current_meta["path"]) current_chunk_text = item_text else: current_chunk_text = combined # Im Hard Split flashen wir nach jeder Sektion, die nicht leer ist _emit(current_chunk_text, current_meta["title"], current_meta["path"]) current_chunk_text = "" continue # FALL B: Smart Mode (Regel 1-3) combined_text = (current_chunk_text + "\n\n" + item_text).strip() if current_chunk_text else item_text combined_est = estimate_tokens(combined_text) if combined_est <= max_tokens: # Regel 1 & 2: Passt nach Schätzung -> Aufnehmen current_chunk_text = combined_text else: # Regel 3: Passt nicht -> Entweder Puffer flashen oder Item zerlegen if current_chunk_text: _emit(current_chunk_text, current_meta["title"], current_meta["path"]) current_chunk_text = "" queue.insert(0, item) # Item für neuen Chunk zurücklegen else: # Einzelne Sektion zu groß -> Smart Zerlegung sents = split_sentences(item_text) header_prefix = item["meta"].text if item["meta"].kind == "heading" else "" take_sents = []; take_len = 0 while sents: s = sents.pop(0) slen = estimate_tokens(s) if take_len + slen > target and take_sents: sents.insert(0, s); break take_sents.append(s); take_len += slen _emit(" ".join(take_sents), current_meta["title"], current_meta["path"]) # Carry-Over: Rest wird vorne in die Queue geschoben if sents: remainder = " ".join(sents) if header_prefix and not remainder.startswith(header_prefix): remainder = header_prefix + "\n\n" + remainder queue.insert(0, {"text": remainder, "meta": item["meta"], "is_split": True}) if current_chunk_text: _emit(current_chunk_text, current_meta["title"], current_meta["path"]) return chunks def strategy_sliding_window(blocks: List[RawBlock], config: Dict[str, Any], note_id: str, doc_title: str = "") -> List[Chunk]: """Standard Sliding Window Strategie.""" target = config.get("target", 400); max_tokens = config.get("max", 600) chunks: List[Chunk] = []; buf: List[RawBlock] = [] for b in blocks: b_tokens = estimate_tokens(b.text) curr_tokens = sum(estimate_tokens(x.text) for x in buf) if buf else 0 if curr_tokens + b_tokens > max_tokens and buf: txt = "\n\n".join([x.text for x in buf]); idx = len(chunks) win = _create_win(doc_title, buf[0].section_title, txt) 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)) buf = [] buf.append(b) if buf: txt = "\n\n".join([x.text for x in buf]); idx = len(chunks) win = _create_win(doc_title, buf[0].section_title, txt) 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)) return chunks