chunker korrigiert zu scmart edges
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@ -1,11 +1,11 @@
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"""
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FILE: app/core/chunker.py
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DESCRIPTION: Zerlegt Texte in Chunks (Sliding Window oder nach Headings). Orchestriert die Smart-Edge-Allocation via SemanticAnalyzer.
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VERSION: 2.5.0
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VERSION: 2.6.0 (Fix: Strict Heading Split & Header Retention)
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STATUS: Active
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DEPENDENCIES: app.services.semantic_analyzer, app.core.derive_edges, markdown_it, yaml, asyncio
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EXTERNAL_CONFIG: config/types.yaml
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LAST_ANALYSIS: 2025-12-15
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LAST_ANALYSIS: 2025-12-16
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"""
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from __future__ import annotations
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@ -15,8 +15,6 @@ import re
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import math
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import yaml
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from pathlib import Path
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from markdown_it import MarkdownIt
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from markdown_it.token import Token
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import asyncio
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import logging
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@ -27,7 +25,7 @@ from app.services.semantic_analyzer import get_semantic_analyzer
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try:
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from app.core.derive_edges import build_edges_for_note
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except ImportError:
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# Mock für Tests
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# Mock für Tests, falls Module fehlen
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def build_edges_for_note(note_id, chunks, note_level_references=None, include_note_scope_refs=False): return []
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logger = logging.getLogger(__name__)
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@ -103,7 +101,7 @@ class Chunk:
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suggested_edges: Optional[List[str]] = None
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# ==========================================
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# 3. PARSING & STRATEGIES (SYNCHRON)
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# 3. PARSING & STRATEGIES
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# ==========================================
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def parse_blocks(md_text: str) -> Tuple[List[RawBlock], str]:
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@ -125,6 +123,8 @@ def parse_blocks(md_text: str) -> Tuple[List[RawBlock], str]:
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for line in lines:
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stripped = line.strip()
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if stripped.startswith('# '):
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# H1 wird für den Titel genutzt, aber nicht als Block für sliding window
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# (Außer es ist H1 im Body, aber wir ignorieren H1 hier meist als Title)
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continue
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elif stripped.startswith('## '):
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if buffer:
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@ -134,6 +134,7 @@ def parse_blocks(md_text: str) -> Tuple[List[RawBlock], str]:
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buffer = []
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current_h2 = stripped[3:].strip()
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section_path = f"/{current_h2}"
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# WICHTIG: Die Überschrift selbst als Block speichern!
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blocks.append(RawBlock("heading", stripped, 2, section_path, current_h2))
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elif not stripped:
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if buffer:
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@ -151,6 +152,15 @@ def parse_blocks(md_text: str) -> Tuple[List[RawBlock], str]:
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return blocks, h1_title
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def _create_chunk_obj(chunks_list: List[Chunk], note_id: str, txt: str, win: str, sec: Optional[str], path: str):
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idx = len(chunks_list)
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chunks_list.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=sec, section_path=path, neighbors_prev=None, neighbors_next=None,
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suggested_edges=[]
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))
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def _strategy_sliding_window(blocks: List[RawBlock], config: Dict[str, Any], note_id: str, doc_title: str = "", context_prefix: str = "") -> List[Chunk]:
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target = config.get("target", 400)
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max_tokens = config.get("max", 600)
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@ -158,15 +168,6 @@ def _strategy_sliding_window(blocks: List[RawBlock], config: Dict[str, Any], not
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overlap = sum(overlap_val) // 2 if isinstance(overlap_val, tuple) else overlap_val
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chunks = []; buf = []
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def _create_chunk(txt, win, sec, path):
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idx = len(chunks)
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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=sec, section_path=path, neighbors_prev=None, neighbors_next=None,
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suggested_edges=[]
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))
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def flush_buffer():
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nonlocal buf
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if not buf: return
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@ -175,18 +176,24 @@ def _strategy_sliding_window(blocks: List[RawBlock], config: Dict[str, Any], not
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win_body = f"{context_prefix}\n{text_body}".strip() if context_prefix else text_body
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if estimate_tokens(text_body) <= max_tokens:
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_create_chunk(text_body, win_body, buf[-1].section_title, buf[-1].section_path)
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sec = buf[0].section_title if buf else None
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path = buf[0].section_path if buf else "/"
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_create_chunk_obj(chunks, note_id, text_body, win_body, sec, path)
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else:
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sentences = split_sentences(text_body)
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current_chunk_sents = []
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current_len = 0
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# Basis-Info vom ersten Block im Buffer
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sec = buf[0].section_title if buf else None
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path = buf[0].section_path if buf else "/"
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for sent in sentences:
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sent_len = estimate_tokens(sent)
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if current_len + sent_len > target and current_chunk_sents:
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c_txt = " ".join(current_chunk_sents)
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c_win = f"{context_prefix}\n{c_txt}".strip() if context_prefix else c_txt
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_create_chunk(c_txt, c_win, buf[-1].section_title, buf[-1].section_path)
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_create_chunk_obj(chunks, note_id, c_txt, c_win, sec, path)
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overlap_sents = []
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ov_len = 0
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@ -207,27 +214,81 @@ def _strategy_sliding_window(blocks: List[RawBlock], config: Dict[str, Any], not
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if current_chunk_sents:
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c_txt = " ".join(current_chunk_sents)
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c_win = f"{context_prefix}\n{c_txt}".strip() if context_prefix else c_txt
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_create_chunk(c_txt, c_win, buf[-1].section_title, buf[-1].section_path)
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_create_chunk_obj(chunks, note_id, c_txt, c_win, sec, path)
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buf = []
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for b in blocks:
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if b.kind == "heading": continue
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# Bei Sliding Window ignorieren wir Heading-Blocks als Split-Trigger NICHT zwingend,
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# aber wir wollen Headings oft nicht "allein" stehen haben.
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# Hier einfache Logik:
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if b.kind == "heading":
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# Optional: Buffer flushen bei neuem Header, um Kontextwechsel sauberer zu machen
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flush_buffer()
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current_buf_text = "\n\n".join([x.text for x in buf])
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if estimate_tokens(current_buf_text) + estimate_tokens(b.text) >= target:
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if buf and (estimate_tokens(current_buf_text) + estimate_tokens(b.text) >= target):
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flush_buffer()
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buf.append(b)
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if estimate_tokens(b.text) >= target:
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flush_buffer()
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flush_buffer()
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return chunks
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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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return _strategy_sliding_window(blocks, config, note_id, doc_title, context_prefix=f"# {doc_title}")
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"""
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STRICT HEADING SPLIT (Fix v2.6.0):
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Trennt den Text konsequent an jeder Überschrift der definierten Ebene.
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Behält Überschriften als Teil (erste Zeile) des Chunks bei.
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Kein Merging kleiner Abschnitte über Header-Grenzen hinweg.
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"""
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split_level = config.get("split_level", 2)
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chunks = []
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# Temporärer Speicher für den aktuellen Chunk
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current_chunk_blocks = []
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context_prefix = f"# {doc_title}"
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def flush_current_chunk():
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nonlocal current_chunk_blocks
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if not current_chunk_blocks:
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return
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# Text zusammenbauen
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text_body = "\n\n".join([b.text for b in current_chunk_blocks])
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# Window bauen (hier einfach Text, da Kontext via Header implizit ist)
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win_body = f"{context_prefix}\n{text_body}".strip()
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# Metadaten vom ersten Block (üblicherweise der Header) nehmen
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first_b = current_chunk_blocks[0]
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sec = first_b.section_title
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path = first_b.section_path
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_create_chunk_obj(chunks, note_id, text_body, win_body, sec, path)
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current_chunk_blocks = []
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for b in blocks:
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# Prüfen, ob dieser Block ein Trenner (Header auf Split-Level) ist
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is_splitter = (b.kind == "heading" and b.level == split_level)
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if is_splitter:
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# 1. Den bisherigen Chunk abschließen (falls vorhanden)
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flush_current_chunk()
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# 2. Den neuen Chunk mit diesem Header beginnen
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current_chunk_blocks.append(b)
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else:
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# Einfach anhängen
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current_chunk_blocks.append(b)
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# Letzten Rest flushen
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flush_current_chunk()
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return chunks
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# ==========================================
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# 4. ORCHESTRATION (ASYNC) - WP-15 CORE
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# 4. ORCHESTRATION (ASYNC)
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# ==========================================
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async def assemble_chunks(note_id: str, md_text: str, note_type: str, config: Optional[Dict] = None) -> List[Chunk]:
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@ -240,12 +301,14 @@ async def assemble_chunks(note_id: str, md_text: str, note_type: str, config: Op
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primary_strategy = config.get("strategy", "sliding_window")
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enable_smart_edges = config.get("enable_smart_edge_allocation", False)
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# Performance/Cost-Guard: Bei Entwürfen keine Smart Edges
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if enable_smart_edges and note_status in ["draft", "initial_gen"]:
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logger.info(f"Chunker: Skipping Smart Edges for draft '{note_id}'.")
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enable_smart_edges = False
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blocks, doc_title = parse_blocks(md_text)
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# Strategie-Auswahl
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if primary_strategy == "by_heading":
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chunks = await asyncio.to_thread(_strategy_by_heading, blocks, config, note_id, doc_title)
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else:
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@ -254,10 +317,11 @@ async def assemble_chunks(note_id: str, md_text: str, note_type: str, config: Op
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if not chunks:
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return []
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# Smart Edge Allocation (WP-15)
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if enable_smart_edges:
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# Hier rufen wir nun die Smart Edge Allocation auf
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chunks = await _run_smart_edge_allocation(chunks, md_text, note_id, note_type)
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# Verkettung der Chunks (next/prev)
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for i, ch in enumerate(chunks):
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ch.neighbors_prev = chunks[i-1].id if i > 0 else None
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ch.neighbors_next = chunks[i+1].id if i < len(chunks)-1 else None
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@ -269,30 +333,25 @@ def _extract_all_edges_from_md(md_text: str, note_id: str, note_type: str) -> Li
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Hilfsfunktion: Erstellt einen Dummy-Chunk für den gesamten Text und ruft
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den Edge-Parser auf, um ALLE Kanten der Notiz zu finden.
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"""
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# 1. Dummy Chunk erstellen, der den gesamten Text enthält
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# Das ist notwendig, da build_edges_for_note Kanten nur aus Chunks extrahiert.
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dummy_chunk = {
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"chunk_id": f"{note_id}#full",
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"text": md_text,
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"content": md_text, # Sicherstellen, dass der Parser Text findet
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"content": md_text,
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"window": md_text,
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"type": note_type
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}
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# 2. Aufruf des Parsers (Signatur-Fix!)
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# derive_edges.py: build_edges_for_note(note_id, chunks, note_level_references=None, include_note_scope_refs=False)
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# Parsing aller Kanten (Inline, Wikilinks, Callouts)
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raw_edges = build_edges_for_note(
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note_id,
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[dummy_chunk],
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note_level_references=None,
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include_note_scope_refs=False
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)
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# 3. Kanten extrahieren
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all_candidates = set()
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for e in raw_edges:
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kind = e.get("kind")
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target = e.get("target_id")
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# Struktur-Kanten ignorieren wir für die Verteilung
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if target and kind not in ["belongs_to", "next", "prev", "backlink"]:
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all_candidates.add(f"{kind}:{target}")
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@ -301,7 +360,7 @@ def _extract_all_edges_from_md(md_text: str, note_id: str, note_type: str) -> Li
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async def _run_smart_edge_allocation(chunks: List[Chunk], full_text: str, note_id: str, note_type: str) -> List[Chunk]:
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analyzer = get_semantic_analyzer()
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# A. Alle potenziellen Kanten der Notiz sammeln (über den Dummy-Chunk Trick)
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# A. Alle potenziellen Kanten der Notiz sammeln
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candidate_list = _extract_all_edges_from_md(full_text, note_id, note_type)
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if not candidate_list:
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@ -314,7 +373,7 @@ async def _run_smart_edge_allocation(chunks: List[Chunk], full_text: str, note_i
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results_per_chunk = await asyncio.gather(*tasks)
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# C. Injection & Fallback
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# C. Injection & Fallback Tracking
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assigned_edges_global = set()
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for i, confirmed_edges in enumerate(results_per_chunk):
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@ -322,14 +381,18 @@ async def _run_smart_edge_allocation(chunks: List[Chunk], full_text: str, note_i
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chunk.suggested_edges = confirmed_edges
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assigned_edges_global.update(confirmed_edges)
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# Injection: Wir hängen die bestätigten Edges unsichtbar (fürs Embedding) oder sichtbar an
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# Hier als "Pseudo-Code" im Text, damit sie embedded werden.
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if confirmed_edges:
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# Format: [[rel:kind|target]]
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injection_str = "\n" + " ".join([f"[[rel:{e.split(':')[0]}|{e.split(':')[1]}]]" for e in confirmed_edges if ':' in e])
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chunk.text += injection_str
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chunk.window += injection_str
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# D. Fallback: Unassigned Kanten überall hin
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# D. Fallback: Kanten, die NIRGENDS zugewiesen wurden, werden JEDEM Chunk angehängt (Sicherheit)
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unassigned = set(candidate_list) - assigned_edges_global
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if unassigned:
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logger.info(f"Chunker: {len(unassigned)} unassigned edges in {note_id}. Distributing to all chunks.")
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fallback_str = "\n" + " ".join([f"[[rel:{e.split(':')[0]}|{e.split(':')[1]}]]" for e in unassigned if ':' in e])
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for chunk in chunks:
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chunk.text += fallback_str
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