mindnet/app/core/chunking/chunking_strategies.py

145 lines
6.6 KiB
Python

"""
FILE: app/core/chunking/chunking_strategies.py
DESCRIPTION: Universelle Strategie für atomares Sektions-Chunking v3.5.0.
Garantiert Sektions-Integrität durch präventives Chunk-Management.
"""
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]:
"""
Universelles Sektions-Chunking: Packt Sektionen in Chunks.
Bei Überlauf wird die komplette Sektion in den nächsten Chunk geschoben.
"""
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] = []
# --- HILFSFUNKTION: Erzeugt einen Chunk aus einer Blockliste ---
def _create_chunk_from_blocks(block_list: List[RawBlock]):
if not block_list: return
txt = "\n\n".join([b.text for b in block_list])
idx = len(chunks)
title = block_list[0].section_title
path = block_list[0].section_path
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
))
# --- HILFSFUNKTION: Splittet eine einzelne Sektion, die > max ist ---
def _split_giant_section(sec_blocks: List[RawBlock]):
full_text = "\n\n".join([b.text for b in sec_blocks])
main_title = sec_blocks[0].section_title
main_path = sec_blocks[0].section_path
header_text = sec_blocks[0].text if sec_blocks[0].kind == "heading" else ""
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:
combined_text = " ".join(cur_sents)
_create_chunk_from_blocks([RawBlock("paragraph", combined_text, None, main_path, main_title)])
# Context Injection: Überschrift für den nächsten Teil-Chunk
ov_s = [header_text] if header_text else []
ov_l = estimate_tokens(header_text) if header_text else 0
for os in reversed(cur_sents):
if os == header_text: continue
t_len = estimate_tokens(os)
if ov_l + t_len < overlap:
ov_s.insert(len(ov_s)-1 if header_text else 0, os)
ov_l += t_len
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:
_create_chunk_from_blocks([RawBlock("paragraph", " ".join(cur_sents), None, main_path, main_title)])
# 1. SCHRITT: Gruppierung in atomare Sektions-Einheiten
sections: List[List[RawBlock]] = []
curr_sec: List[RawBlock] = []
for b in blocks:
# Eine neue Überschrift auf oder unter dem split_level startet eine neue Sektion
if b.kind == "heading" and b.level <= split_level:
if curr_sec: sections.append(curr_sec)
curr_sec = [b]
else:
curr_sec.append(b)
if curr_sec: sections.append(curr_sec)
# 2. SCHRITT: Sektionen in Chunks packen (Das universelle Pack-Verfahren)
candidate_chunk: List[RawBlock] = []
candidate_tokens = 0
for sec in sections:
sec_text = "\n\n".join([b.text for b in sec])
sec_tokens = estimate_tokens(sec_text)
# Passt diese gesamte Sektion noch in den laufenden Chunk?
if candidate_tokens + sec_tokens <= max_tokens:
candidate_chunk.extend(sec)
candidate_tokens = estimate_tokens("\n\n".join([b.text for b in candidate_chunk]))
else:
# Falls der aktuelle Chunk nicht leer ist: Raus damit, bevor die neue Sektion kommt
if candidate_chunk:
_create_chunk_from_blocks(candidate_chunk)
candidate_chunk = []
candidate_tokens = 0
# Die neue Sektion ist nun allein. Ist sie selbst zu groß?
if sec_tokens > max_tokens:
_split_giant_section(sec)
else:
candidate_chunk = list(sec)
candidate_tokens = sec_tokens
# Letzten Rest wegschreiben
if candidate_chunk:
_create_chunk_from_blocks(candidate_chunk)
return chunks
def strategy_sliding_window(blocks: List[RawBlock], config: Dict[str, Any], note_id: str, context_prefix: str = "") -> List[Chunk]:
"""Standard-Sliding-Window für flache Texte ohne Sektionsfokus."""
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)
current_tokens = sum(estimate_tokens(x.text) for x in buf) if buf else 0
if current_tokens + b_tokens > max_tokens and buf:
txt = "\n\n".join([x.text for x 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=current_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 = 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))
return chunks