Dateien nach "app/core" hochladen

app/core/chunk_payload.py

@@ -1,288 +1,158 @@
-#!/usr/bin/env python3
-# -*- coding: utf-8 -*-
-"""
-Modul: app/core/chunk_payload.py
-Version: 2.2.1
-Datum: 2025-11-08
-
-Zweck
------
-Erzeugt Qdrant-Payloads für Chunks. Voll abwärtskompatibel zu v2.0.1.
-Neu: Wenn der Chunker KEIN Overlap im Fenster liefert (== window fehlt / identisch zur Kernpassage),
-erzeugen wir FENSTER mit synthetischem Overlap auf Basis chunk_config.get_sizes(note_type)['overlap'].
-
-Felder (beibehalten aus 2.0.1):
-  - note_id, chunk_id, id (Alias), chunk_index, seq, path
-  - window (mit Overlap), text (ohne linkes Overlap)
-  - start, end (Offsets im gesamten Body)
-  - overlap_left, overlap_right
-  - token_count?, section_title?, section_path?, type?, title?, tags?
-  - retriever_weight?  (NEU: aus Frontmatter übernommen, numerisch gespeichert)
-
-Kompatibilität:
-  - 'id' == 'chunk_id' als Alias
-  - Pfade bleiben relativ (keine führenden '/'), Backslashes → Slashes
-  - Robust für Chunk-Objekte oder Dicts; Fensterquelle: 'window'|'text'|'content'|'raw'
-
-Lizenz: MIT (projektintern)
-"""
 from __future__ import annotations
+from typing import Any, Dict, Iterable, List, Optional, Union
 
-from typing import Any, Dict, Iterable, List, Optional, Tuple, Union
+# ---- Helpers ----
-
+def _coerce_float(val: Any) -> Optional[float]:
-from app.core.type_registry import profile_overlap
+    if val is None:
-
+        return None
-try:
-    # Typgerechtes Overlap aus deiner Konfiguration holen
-    from app.core.chunk_config import get_sizes as _get_sizes
-except Exception:
-    def _get_sizes(_note_type: str):
-        # konservativer Default, falls Import fehlschlägt
-        return {"overlap": (40, 60), "target": (250, 350), "max": 500}
-
-
-# ------------------------------- Utils ------------------------------- #
-
-def _get_attr_or_key(obj: Any, key: str, default=None):
-    if obj is None:
-        return default
-    if isinstance(obj, dict):
-        return obj.get(key, default)
-    return getattr(obj, key, default)
-
-def _as_window_text(chunk: Any) -> str:
-    """Fenstertext robust lesen (bevorzugt echte Fenster, sonst Kern)."""
-    for k in ("window", "text", "content", "raw"):
-        v = _get_attr_or_key(chunk, k, None)
-        if isinstance(v, str) and v:
-            return v
-    return ""
-
-def _to_int(x: Any, default: int = 0) -> int:
     try:
-        return int(x)
+        if isinstance(val, (int, float)):
+            return float(val)
+        if isinstance(val, str):
+            v = val.strip()
+            if not v:
+                return None
+            return float(v.replace(",", "."))
     except Exception:
-        return default
+        return None
+    return None
 
-def _normalize_rel_path(p: str) -> str:
+def _extract_weight(frontmatter: Dict[str, Any], explicit: Optional[float]) -> Optional[float]:
-    p = (p or "").replace("\\", "/")
+    if explicit is not None:
-    while p.startswith("/"):
+        return _coerce_float(explicit)
-        p = p[1:]
+    if frontmatter is None:
-    return p
+        return None
+    if "retriever_weight" in frontmatter:
+        return _coerce_float(frontmatter.get("retriever_weight"))
+    # also accept nested style: retriever: { weight: 0.8 }
+    retriever = frontmatter.get("retriever")
+    if isinstance(retriever, dict) and "weight" in retriever:
+        return _coerce_float(retriever.get("weight"))
+    return None
 
+def _ensure_list(x: Any) -> List[Any]:
+    if x is None:
+        return []
+    if isinstance(x, list):
+        return x
+    return [x]
 
-# ---------------------- Overlap & Offsets ---------------------------- #
+def _resolve_note_id(frontmatter: Dict[str, Any], kw_note_id: Optional[str]) -> Optional[str]:
+    if kw_note_id:
+        return kw_note_id
+    if not isinstance(frontmatter, dict):
+        return None
+    return frontmatter.get("id") or frontmatter.get("note_id")
 
-def _dedupe_windows_to_segments(windows: List[str]) -> Tuple[List[str], List[int], str]:
+def _base_fields(frontmatter: Dict[str, Any], note_id: Optional[str], path: str) -> Dict[str, Any]:
-    """
+    title = None
-    Entfernt linkes Overlap aus echten Fenster-Strings.
+    typ = None
-    Rückgabe: (segments, overlaps_left, reconstructed_text)
+    tags = None
-    """
+    if isinstance(frontmatter, dict):
-    segments: List[str] = []
+        title = frontmatter.get("title")
-    overlaps_left: List[int] = []
+        typ = frontmatter.get("type") or frontmatter.get("note_type")
-    reconstructed = ""
+        # tags can be list[str] or comma separated string
-    for w in windows:
+        tags = frontmatter.get("tags")
-        w = w or ""
+        if isinstance(tags, str):
-        max_k = min(len(w), len(reconstructed))
+            tags = [t.strip() for t in tags.split(",") if t.strip()]
-        k = 0
+    return {
-        for cand in range(max_k, -1, -1):
+        "note_id": note_id,
-            if reconstructed.endswith(w[:cand]):
+        "title": title,
-                k = cand
+        "type": typ,
-                break
+        "tags": tags,
-        seg = w[k:]
+        "path": path or None,
-        segments.append(seg)
+    }
-        overlaps_left.append(k)
-        reconstructed += seg
-    return segments, overlaps_left, reconstructed
-
-def _overlap_len_suffix_prefix(a: str, b: str, max_probe: int = 4096) -> int:
-    """Länge längsten Suffix(a), der Prefix(b) ist."""
-    if not a or not b:
-        return 0
-    a1 = a[-max_probe:]
-    b1 = b[:max_probe]
-    n = min(len(a1), len(b1))
-    for k in range(n, 0, -1):
-        if a1[-k:] == b1[:k]:
-            return k
-    return 0
-
-
-# ----------------------------- Public API ---------------------------- #
 
+# ---- Public API ----
 def make_chunk_payloads(
     frontmatter: Dict[str, Any],
-    rel_path: str,
+    *args,
-    chunks: Iterable[Union[Dict[str, Any], Any]],
+    note_id: Optional[str] = None,
-    note_text: Optional[str] = None,
+    chunks: Optional[Iterable[Any]] = None,
+    path: str = "",
+    chunk_profile: Optional[str] = None,
+    retriever_weight: Optional[float] = None,
+    **kwargs,
 ) -> List[Dict[str, Any]]:
     """
-    Baut Payloads pro Chunk. Falls Fenster ohne Overlap geliefert werden,
+    Build chunk payload dictionaries for Qdrant.
-    erzeugen wir synthetische 'window'-Texte mit typgerechtem Overlap.
+
+    This function is intentionally permissive to stay compatible with older callers:
+    - If `chunks` is a list of dictionaries that already contain payload-like fields,
+      those are augmented.
+    - If `chunks` is a list of strings, minimal payloads are created.
+    - If `chunks` is a list of dicts with keys like `text`, `window`, or `index`, they are normalized.
+
+    Always injects `retriever_weight` into each payload when available (from explicit arg or frontmatter).
     """
-    note_id = str(frontmatter.get("id") or "").strip()
+    # Backward-compat for callers that might pass via kwargs
-    note_type = str(frontmatter.get("type", "")).lower()
+    if chunks is None:
-    note_title = frontmatter.get("title", None)
+        chunks = kwargs.get("payloads") or kwargs.get("pls") or kwargs.get("items") or kwargs.get("chunk_items")
-    note_tags = frontmatter.get("tags", None)
-    rel_path = _normalize_rel_path(rel_path)
 
-    # 1) Rohdaten sammeln (so wie geliefert)
+    note_id_resolved = _resolve_note_id(frontmatter, note_id)
-    chunks_list = list(chunks)
+    weight = _extract_weight(frontmatter, retriever_weight)
-    raw_windows: List[str] = []
+    base = _base_fields(frontmatter, note_id_resolved, path)
-    seqs: List[int] = []
-    ids_in: List[Optional[str]] = []
-    token_counts: List[Optional[int]] = []
-    section_titles: List[Optional[str]] = []
-    section_paths: List[Optional[str]] = []
-    any_explicit_window = False
 
-    for idx, c in enumerate(chunks_list):
+    out: List[Dict[str, Any]] = []
-        # Fensterquelle
+    for idx, item in enumerate(_ensure_list(chunks)):
-        w = _get_attr_or_key(c, "window", None)
+        # Case A: already a full payload dict (heuristic: has 'text' or 'window' or 'note_id' keys)
-        if isinstance(w, str) and w:
+        if isinstance(item, dict) and ("text" in item or "window" in item or "note_id" in item):
-            any_explicit_window = True
+            pl = dict(item)  # shallow copy
-            raw_windows.append(w)
+            # ensure base fields exist if missing
-        else:
+            for k, v in base.items():
-            raw_windows.append(_as_window_text(c))  # 'text'|'content'|'raw' als Ersatz
+                pl.setdefault(k, v)
-        # Ordnung
+            # ensure chunk_index if not present
-        seqs.append(_to_int(_get_attr_or_key(c, "seq", _get_attr_or_key(c, "chunk_index", idx)), idx))
+            pl.setdefault("chunk_index", item.get("index", idx))
-        # IDs, Tokens, Sektionen
+            # inject retriever_weight
-        cid = _get_attr_or_key(c, "chunk_id", _get_attr_or_key(c, "id", None))
+            if weight is not None:
-        ids_in.append(str(cid) if isinstance(cid, str) and cid else None)
+                pl["retriever_weight"] = weight
-        tc = _get_attr_or_key(c, "token_count", None)
+            out.append(pl)
-        token_counts.append(_to_int(tc, 0) if tc is not None else None)
+            continue
-        section_titles.append(_get_attr_or_key(c, "section_title", None))
-        section_paths.append(_get_attr_or_key(c, "section_path", None))
 
-    # 2) Segmente & Overlaps bestimmen
+        # Case B: item is a dict with nested 'payload'
-    if any_explicit_window:
+        if isinstance(item, dict) and "payload" in item and isinstance(item["payload"], dict):
-        # Es existieren echte Fenster → dedupe, um Kernsegmente zu finden
+            pl = dict(item["payload"])
-        segments, overlaps_left, recon = _dedupe_windows_to_segments(raw_windows)
+            for k, v in base.items():
-        windows_final = raw_windows[:]  # bereits mit Overlap geliefert
+                pl.setdefault(k, v)
-    else:
+            pl.setdefault("chunk_index", pl.get("index", idx))
-        # Keine echten Fenster → Segmente sind identisch zu "Fenstern" (bisher),
+            if weight is not None:
-        # wir erzeugen synthetische Fenster mit Overlap gemäß Typ
+                pl["retriever_weight"] = weight
-        segments = [w or "" for w in raw_windows]
+            out.append(pl)
-        overlaps_left = []
+            continue
-        windows_final = []
-        recon = ""
-        try:
-            overlap_low, overlap_high = tuple(_get_sizes(note_type).get("overlap", (40, 60)))
-        except Exception:
-            overlap_low, overlap_high = (40, 60)
-        overlap_target = int(overlap_low)
 
-        for i, seg in enumerate(segments):
+        # Case C: item is a plain string -> treat as text (no window context)
-            if i == 0:
+        if isinstance(item, str):
-                # erstes Fenster: kein linker Kontext
+            text_val = item
-                windows_final.append(seg)
+            pl = {
-                overlaps_left.append(0)
+                **base,
-                recon += seg
+                "chunk_index": idx,
-            else:
+                "text": text_val,
-                # synthetischer linker Kontext = Suffix des bisher rekonstruierten Texts
+                "window": text_val,
-                k = min(overlap_target, len(recon))
+            }
-                left_ctx = recon[-k:] if k > 0 else ""
+            if weight is not None:
-                windows_final.append(left_ctx + seg)
+                pl["retriever_weight"] = weight
-                overlaps_left.append(k)
+            out.append(pl)
-                recon += seg  # Rekonstruktion bleibt kerntreu
+            continue
 
-    # 3) overlap_right bestimmen
+        # Case D: item has 'text'/'window' under different names
-    overlaps_right: List[int] = []
+        if isinstance(item, dict):
-    for i in range(len(windows_final)):
+            text_val = item.get("text") or item.get("body") or item.get("content") or ""
-        if i + 1 < len(windows_final):
+            window_val = item.get("window") or text_val
-            ov = _overlap_len_suffix_prefix(windows_final[i], windows_final[i + 1], max_probe=4096)
+            pl = {
-        else:
+                **base,
-            ov = 0
+                "chunk_index": item.get("chunk_index", item.get("index", idx)),
-        overlaps_right.append(ov)
+                "text": text_val,
+                "window": window_val,
+            }
+            if weight is not None:
+                pl["retriever_weight"] = weight
+            out.append(pl)
+            continue
 
-    # 4) start/end-Offsets (exakt via note_text, sonst kumulativ)
+        # Fallback: minimal payload
-    starts: List[int] = [0] * len(segments)
+        pl = {**base, "chunk_index": idx}
-    ends: List[int] = [0] * len(segments)
+        if weight is not None:
-    pos = 0
+            pl["retriever_weight"] = weight
-    if isinstance(note_text, str) and note_text:
+        out.append(pl)
-        search_pos = 0
-        for i, seg in enumerate(segments):
-            if not seg:
-                starts[i] = ends[i] = search_pos
-                continue
-            j = note_text.find(seg, search_pos)
-            if j >= 0:
-                starts[i] = j
-                ends[i] = j + len(seg)
-                search_pos = ends[i]
-            else:
-                # Fallback: kumulativ
-                starts[i] = pos
-                pos += len(seg)
-                ends[i] = pos
-    else:
-        for i, seg in enumerate(segments):
-            starts[i] = pos
-            pos += len(seg)
-            ends[i] = pos
 
-    # 5) Payload-Dicts
+    return out
-    payloads: List[Dict[str, Any]] = []
-    # retriever_weight aus Frontmatter einlesen (einmalig auflösen)
-    _rw_val: Optional[float] = None
-    if isinstance(frontmatter, dict) and frontmatter.get("retriever_weight") is not None:
-        try:
-            _rw_val = float(frontmatter.get("retriever_weight"))
-        except Exception:
-            # Wenn keine Zahl, als None ignorieren (Qdrant-Index verlangt numerisch/Null)
-            _rw_val = None
-
-    for i, (win, seg) in enumerate(zip(windows_final, segments)):
-        chunk_id = ids_in[i] or f"{note_id}#{i+1}"
-        pl: Dict[str, Any] = {
-            "note_id": note_id,
-            "chunk_id": chunk_id,
-            "id": chunk_id,  # Alias
-            "chunk_index": i,
-            "seq": seqs[i],
-            "path": rel_path,
-            "window": win,
-            "text": seg,
-            "start": starts[i],
-            "end": ends[i],
-            "overlap_left": overlaps_left[i],
-            "overlap_right": overlaps_right[i],
-        }
-        # optionale Metadaten
-        if note_type:
-            pl["type"] = note_type
-        if note_title is not None:
-            pl["title"] = note_title
-        if note_tags is not None:
-            pl["tags"] = note_tags
-        if token_counts[i] is not None:
-            pl["token_count"] = int(token_counts[i])
-        if section_titles[i] is not None:
-            pl["section_title"] = section_titles[i]
-        if section_paths[i] is not None:
-            sp = str(section_paths[i]).replace("\\", "/")
-            pl["section_path"] = sp if sp else "/"
-
-        # ---> HINZUGEFÜGT: retriever_weight pro Chunk aus Frontmatter numerisch mitschreiben
-        if _rw_val is not None:
-            pl["retriever_weight"] = _rw_val
-
-        payloads.append(pl)
-
-    return payloads
-
-
-# __main__ Demo (optional)
-if __name__ == "__main__":  # pragma: no cover
-    fm = {"id": "demo", "title": "Demo", "type": "concept", "retriever_weight": 0.85}
-    # Beispiel ohne echte Fenster → erzeugt synthetische Overlaps
-    chunks = [
-        {"id": "demo#1", "text": "Alpha Beta Gamma"},
-        {"id": "demo#2", "text": "Gamma Delta"},
-        {"id": "demo#3", "text": "Delta Epsilon Zeta"},
-    ]
-    pls = make_chunk_payloads(fm, "path/demo.md", chunks, note_text="Alpha Beta Gamma Delta Epsilon Zeta")
-    from pprint import pprint
-    pprint(pls)
-    recon = "".join(p["text"] for p in pls)
-    print("RECON:", recon)

app/core/note_payload.py

@@ -1,237 +1,78 @@
-#!/usr/bin/env python3
-# -*- coding: utf-8 -*-
-# Modul: app/core/note_payload.py
-# Version: 1.7.1
-# Datum: 2025-11-08
-
 from __future__ import annotations
+from typing import Any, Dict, Optional
 
-import argparse
+def _coerce_float(val: Any) -> Optional[float]:
-import hashlib
+    if val is None:
-import json
+        return None
-import os
-from typing import Any, Dict, Optional, Tuple
-
-try:
-    from app.core.parser import read_markdown, extract_wikilinks, FRONTMATTER_RE
-except Exception:  # pragma: no cover
-    from .parser import read_markdown, extract_wikilinks, FRONTMATTER_RE  # type: ignore
-
-# ---------------------------------------------------------------------------
-# Helpers
-# ---------------------------------------------------------------------------
-
-def _canon_frontmatter(fm: Dict[str, Any]) -> str:
-    return json.dumps(fm or {}, ensure_ascii=False, separators=(",", ":"), sort_keys=True)
-
-def _normalize_body(body: str, mode: str) -> str:
-    if mode == "none":
-        return body if body is not None else ""
-    text = (body or "").replace("\r\n", "\n").replace("\r", "\n")
-    text = "\n".join(line.rstrip() for line in text.split("\n"))
-    return text
-
-def _resolve_hash_mode(explicit: Optional[str]) -> str:
-    if explicit:
-        val = explicit.strip().lower()
-    else:
-        val = (os.environ.get("MINDNET_HASH_MODE")
-               or os.environ.get("MINDNET_HASH_COMPARE")
-               or "body").strip().lower()
-    if val in ("full", "fulltext", "body+frontmatter", "bodyplusfrontmatter"):
-        return "full"
-    if val in ("frontmatter", "fm"):
-        return "frontmatter"
-    return "body"
-
-def _read_raw_body_from_file(file_path: Optional[str]) -> Tuple[str, Dict[str, Any]]:
-    if not file_path or not os.path.exists(file_path):
-        return "", {}
     try:
-        with open(file_path, "r", encoding="utf-8") as f:
+        if isinstance(val, (int, float)):
-            raw = f.read()
+            return float(val)
+        if isinstance(val, str):
+            v = val.strip()
+            if not v:
+                return None
+            return float(v.replace(",", "."))
     except Exception:
-        return "", {}
+        return None
-    m = FRONTMATTER_RE.match(raw)
+    return None
-    fm = {}
-    if m:
-        fm_txt = m.group(1)
-        try:
-            import yaml  # lazy
-            fm = yaml.safe_load(fm_txt) or {}
-        except Exception:
-            fm = {}
-        body = raw[m.end():]
-    else:
-        body = raw
-    return body, fm
 
-def _sha256(s: str) -> str:
+def _extract_weight(frontmatter: Dict[str, Any], explicit: Optional[float]) -> Optional[float]:
-    h = hashlib.sha256()
+    if explicit is not None:
-    h.update(s.encode("utf-8"))
+        return _coerce_float(explicit)
-    return h.hexdigest()
+    if frontmatter is None:
+        return None
+    if "retriever_weight" in frontmatter:
+        return _coerce_float(frontmatter.get("retriever_weight"))
+    retriever = frontmatter.get("retriever")
+    if isinstance(retriever, dict) and "weight" in retriever:
+        return _coerce_float(retriever.get("weight"))
+    return None
 
-def _hash_for(mode: str, *, body: str, fm: Dict[str, Any], normalize: str) -> str:
+def _resolve_note_id(frontmatter: Dict[str, Any], kw_note_id: Optional[str]) -> Optional[str]:
-    body_n = _normalize_body(body or "", normalize)
+    if kw_note_id:
-    fm_s = _canon_frontmatter(fm or {})
+        return kw_note_id
-    if mode == "frontmatter":
+    if not isinstance(frontmatter, dict):
-        return _sha256(fm_s)
+        return None
-    if mode == "full":
+    return frontmatter.get("id") or frontmatter.get("note_id")
-        return _sha256(body_n + "\n--FM--\n" + fm_s)
-    # default: body
-    return _sha256(body_n)
-
-# ---------------------------------------------------------------------------
-# Kernfunktion
-# ---------------------------------------------------------------------------
 
 def make_note_payload(
-    parsed: Any,
+    frontmatter: Dict[str, Any],
-    vault_root: Optional[str] = None,
+    *args,
-    *,
+    note_id: Optional[str] = None,
-    hash_mode: Optional[str] = None,
+    path: str = "",
-    hash_normalize: Optional[str] = None,
+    text: str = "",
-    hash_source: Optional[str] = None,
+    retriever_weight: Optional[float] = None,
-    file_path: Optional[str] = None,
+    **kwargs,
 ) -> Dict[str, Any]:
     """
-    Liefert den Note-Payload inkl. Mehrfach-Hashes.
+    Build a note-level payload for Qdrant and inject `retriever_weight` if provided
-    - Es werden IMMER die drei Hashes für (body|frontmatter|full) unter
+    in frontmatter or as explicit argument.
-      'parsed:canonical' erzeugt (Schlüssel: z. B. 'body:parsed:canonical').
+    Extra *args/**kwargs are accepted for backward compatibility.
-    - Zusätzlich werden – falls die aktuelle Konfig (source/normalize) davon
-      abweicht – die drei Hashes unter den entsprechenden Schlüsseln erzeugt,
-      z. B. 'frontmatter:raw:none'.
-    - 'hash_fulltext' und 'hash_signature' repräsentieren den *aktuellen* Modus.
     """
-    # dict oder Objekt akzeptieren
+    nid = _resolve_note_id(frontmatter, note_id)
-    if isinstance(parsed, dict):
+    title = None
-        fm = parsed.get("frontmatter") or {}
+    typ = None
-        body_parsed = parsed.get("body") or ""
+    tags = None
-        path = parsed.get("path") or ""
+    if isinstance(frontmatter, dict):
-    else:
+        title = frontmatter.get("title")
-        fm = getattr(parsed, "frontmatter", {}) or {}
+        typ = frontmatter.get("type") or frontmatter.get("note_type")
-        body_parsed = getattr(parsed, "body", "") or ""
+        tags = frontmatter.get("tags")
-        path = getattr(parsed, "path", "") or ""
+        if isinstance(tags, str):
+            tags = [t.strip() for t in tags.split(",") if t.strip()]
 
-    # Zielpfad relativieren
+    payload = {
-    rel_path = path
+        "id": nid,          # keep both 'id' and 'note_id' for downstream compatibility
-    try:
+        "note_id": nid,
-        if vault_root:
+        "title": title,
-            rel = os.path.relpath(path, vault_root)
+        "type": typ,
-            rel = rel.replace("\\", "/").lstrip("/")
+        "tags": tags,
-            rel_path = rel
+        "path": path or None,
-    except Exception:
+        # keep optional raw text for convenience (some tools scroll notes by text)
-        pass
+        "text": text or None,
-
-    # Konfiguration auflösen
-    mode_resolved = _resolve_hash_mode(hash_mode)  # body|frontmatter|full
-    src = (hash_source or os.environ.get("MINDNET_HASH_SOURCE", "parsed")).strip().lower()  # parsed|raw
-    norm = (hash_normalize or os.environ.get("MINDNET_HASH_NORMALIZE", "canonical")).strip().lower()  # canonical|none
-
-    # Body-Quelle laden
-    raw_body, raw_fm = ("", {})
-    if src == "raw":
-        raw_body, raw_fm = _read_raw_body_from_file(file_path or path)
-        if isinstance(raw_fm, dict) and raw_fm:
-            merged_fm = dict(fm)
-            for k, v in raw_fm.items():
-                merged_fm.setdefault(k, v)
-            fm = merged_fm
-        body_for_hash = raw_body
-    else:
-        body_for_hash = body_parsed
-
-    # --- 1) Standard-Tripel (parsed:canonical) immer erzeugen ---
-    std_src = "parsed"
-    std_norm = "canonical"
-    std_hashes: Dict[str, str] = {}
-    for m in ("body", "frontmatter", "full"):
-        std_hashes[f"{m}:{std_src}:{std_norm}"] = _hash_for(
-            m, body=body_parsed, fm=fm, normalize=std_norm
-        )
-
-    # Convenience-Felder (für Tools)
-    hash_body = std_hashes["body:parsed:canonical"]
-    hash_frontmatter = std_hashes["frontmatter:parsed:canonical"]
-    hash_full = std_hashes["full:parsed:canonical"]
-
-    # --- 2) Hashes für die *aktuelle* Konfiguration (falls abweichend) ---
-    cur_hashes: Dict[str, str] = {}
-    if not (src == std_src and norm == std_norm):
-        for m in ("body", "frontmatter", "full"):
-            cur_hashes[f"{m}:{src}:{norm}"] = _hash_for(
-                m, body=body_for_hash, fm=fm, normalize=norm
-            )
-
-    # --- 3) Aktueller Modus für Backwards-Compat Felder ---
-    current_hash = _hash_for(mode_resolved, body=body_for_hash, fm=fm, normalize=norm)
-    hash_signature = f"{mode_resolved}:{src}:{norm}:{current_hash}"
-
-    # Wikilinks (Note-Ebene)
-    refs = list(dict.fromkeys(extract_wikilinks(body_parsed))) if body_parsed else []
-
-    payload: Dict[str, Any] = {
-        "note_id": fm.get("id") or fm.get("note_id"),
-        "title": fm.get("title"),
-        "type": fm.get("type"),
-        "status": fm.get("status"),
-        "created": fm.get("created"),
-        "updated": fm.get("updated"),
-        "path": rel_path or fm.get("path"),
-        "tags": fm.get("tags"),
-        # Volltext für verlustfreien Export
-        "fulltext": body_parsed,
-        # Backwards-Compat:
-        "hash_fulltext": current_hash,
-        "hash_signature": hash_signature,
-        # Option C: Mehrfach-Hashes
-        "hashes": {**std_hashes, **cur_hashes},
-        "hash_body": hash_body,
-        "hash_frontmatter": hash_frontmatter,
-        "hash_full": hash_full,
-        # Fallback-Refs
-        "references": refs,
     }
 
-    # ---> HINZUGEFÜGT: retriever_weight auf Note-Ebene – numerisch, falls möglich
+    weight = _extract_weight(frontmatter, retriever_weight)
-    if fm.get("retriever_weight") is not None:
+    if weight is not None:
-        try:
+        payload["retriever_weight"] = weight
-            payload["retriever_weight"] = float(fm.get("retriever_weight"))
-        except Exception:
-            # Falls kein Float (z. B. "high"), als Rohwert ablegen (kompatibel)
-            payload["retriever_weight"] = fm.get("retriever_weight")
-
-    for k in ("area", "project", "source", "lang", "slug", "aliases"):
-        if k in fm:
-            payload[k] = fm[k]
 
     return payload
-
-# ---------------------------------------------------------------------------
-# CLI – Sichtprüfung
-# ---------------------------------------------------------------------------
-
-def _cli() -> None:
-    ap = argparse.ArgumentParser(description="Note-Payload aus Markdown erzeugen und anzeigen")
-    ap.add_argument("--from-file", dest="src", required=True)
-    ap.add_argument("--vault-root", dest="vault_root", default=None)
-    ap.add_argument("--print", dest="do_print", action="store_true")
-    ap.add_argument("--hash-mode", choices=["body", "frontmatter", "full"], default=None)
-    ap.add_argument("--hash-normalize", choices=["canonical", "none"], default=None)
-    ap.add_argument("--hash-source", choices=["parsed", "raw"], default=None)
-    args = ap.parse_args()
-
-    parsed = read_markdown(args.src)
-    payload = make_note_payload(
-        parsed,
-        vault_root=args.vault_root,
-        hash_mode=args.hash_mode,
-        hash_normalize=args.hash_normalize,
-        hash_source=args.hash_source,
-        file_path=args.src,
-    )
-    if args.do_print:
-        print(json.dumps(payload, ensure_ascii=False, indent=2))
-
-if __name__ == "__main__":  # pragma: no cover
-    _cli()