151 lines
7.2 KiB
Python
151 lines
7.2 KiB
Python
"""
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FILE: app/core/chunking/chunking_strategies.py
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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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from .chunking_utils import estimate_tokens
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from .chunking_parser import split_sentences
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def _create_win(doc_title: str, sec_title: Optional[str], text: str) -> str:
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parts = [doc_title] if doc_title else []
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if sec_title and sec_title != doc_title: parts.append(sec_title)
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prefix = " > ".join(parts)
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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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overlap_cfg = config.get("overlap", (50, 80))
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overlap = sum(overlap_cfg) // 2 if isinstance(overlap_cfg, (list, tuple)) else overlap_cfg
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chunks: List[Chunk] = []
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def _emit(txt, title, path):
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idx = len(chunks)
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win = _create_win(doc_title, title, txt)
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chunks.append(Chunk(
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id=f"{note_id}#c{idx:02d}", note_id=note_id, index=idx,
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text=txt, window=win, token_count=estimate_tokens(txt),
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section_title=title, section_path=path, neighbors_prev=None, neighbors_next=None
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))
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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]),
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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]),
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"meta": curr_blocks[0], "is_empty": len(curr_blocks) == 1})
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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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# 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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# 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 & 2: Passt nach Schätzung -> Aufnehmen
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current_chunk_text = combined_text
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else:
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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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_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) # Item für neuen Chunk zurücklegen
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else:
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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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take_sents = []; take_len = 0
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while sents:
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s = sents.pop(0)
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slen = estimate_tokens(s)
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if take_len + slen > target and take_sents:
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sents.insert(0, s); break
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take_sents.append(s); take_len += slen
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_emit(" ".join(take_sents), current_meta["title"], current_meta["path"])
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# Carry-Over: Rest wird vorne in die Queue geschoben
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if sents:
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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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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, 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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b_tokens = estimate_tokens(b.text)
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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, 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, 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 |