""" FILE: app/core/chunking/chunking_strategies.py DESCRIPTION: Korrigierte Splitting-Strategien für Mindnet v3.3.3. - Fix: Erhalt von Überschriften im Chunk-Text. - Fix: Atomares Buffering (Blöcke fallen als Ganzes in den nächsten Chunk). - Fix: Korrekte Zuordnung von Sektions-Metadaten. """ 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_context_win(doc_title: str, sec_title: Optional[str], text: str) -> str: """Baut den Breadcrumb-Kontext für das Embedding-Fenster.""" parts = [] if doc_title: parts.append(doc_title) 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]: """ Splittet Text basierend auf Markdown-Überschriften mit atomarem Block-Erhalt. """ 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 = sum(config.get("overlap", (50, 80))) // 2 chunks: List[Chunk] = [] buf: List[RawBlock] = [] cur_tokens = 0 def _add_to_chunks(txt, title, path): idx = len(chunks) win = _create_context_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 )) def _flush(): nonlocal buf, cur_tokens if not buf: return # Metadaten stammen immer vom ersten Block im Puffer (meist die Überschrift) main_title = buf[0].section_title main_path = buf[0].section_path full_text = "\n\n".join([b.text for b in buf]) # Falls der gesamte Puffer in einen Chunk passt if estimate_tokens(full_text) <= max_tokens: _add_to_chunks(full_text, main_title, main_path) else: # Nur wenn ein einzelner Abschnitt größer als 'max' ist, wird intern gesplittet sents = split_sentences(full_text) cur_sents = []; sub_len = 0 for s in sents: slen = estimate_tokens(s) if sub_len + slen > target and cur_sents: _add_to_chunks(" ".join(cur_sents), main_title, main_path) ov_s = []; ov_l = 0 for os in reversed(cur_sents): if ov_l + estimate_tokens(os) < overlap: ov_s.insert(0, os); ov_l += estimate_tokens(os) else: break cur_sents = list(ov_s); cur_sents.append(s); sub_len = ov_l + slen else: cur_sents.append(s); sub_len += slen if cur_sents: _add_to_chunks(" ".join(cur_sents), main_title, main_path) buf = []; cur_tokens = 0 for b in blocks: b_tokens = estimate_tokens(b.text) # Prüfung auf Split-Trigger (Überschriften) is_split_trigger = False if b.kind == "heading": if b.level < split_level: is_split_trigger = True elif b.level == split_level: if strict or cur_tokens >= target: is_split_trigger = True if is_split_trigger: _flush() # Vorherigen Puffer leeren buf.append(b) # Neue Überschrift in den neuen Puffer aufnehmen cur_tokens = b_tokens else: # Atomarer Check: Wenn der neue Block den aktuellen Chunk sprengen würde if cur_tokens + b_tokens > max_tokens and buf: _flush() # Puffer leeren, Block 'b' wird Teil des nächsten Chunks buf.append(b) cur_tokens += b_tokens _flush() # Letzten Puffer leeren return chunks def strategy_sliding_window(blocks: List[RawBlock], config: Dict[str, Any], note_id: str, context_prefix: str = "") -> List[Chunk]: """ Standard Sliding Window mit Korrektur für Heading-Retention. """ target = config.get("target", 400) max_tokens = config.get("max", 600) overlap_val = config.get("overlap", (50, 80)) overlap = sum(overlap_val) // 2 if isinstance(overlap_val, tuple) else overlap_val chunks: List[Chunk] = [] buf: List[RawBlock] = [] def _flush_window(): nonlocal buf if not buf: return txt = "\n\n".join([b.text for b in buf]) idx = len(chunks) win = f"{context_prefix}\n{txt}".strip() if context_prefix else 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 )) buf = [] for b in blocks: # Auch hier: Überschriften mitnehmen b_tokens = estimate_tokens(b.text) current_buf_tokens = estimate_tokens("\n\n".join([x.text for x in buf])) if buf else 0 if current_buf_tokens + b_tokens >= target and buf: _flush_window() buf.append(b) _flush_window() return chunks