Dateien nach "app/core" hochladen

app/core/chunk_payload.py

@@ -1,33 +1,12 @@
 #!/usr/bin/env python3
 # -*- coding: utf-8 -*-
 """
-app/core/chunk_payload.py  (Mindnet V2 — robust)
+app/core/chunk_payload.py  (Mindnet V2 — robust v2)
-
-Aufgabe
--------
-Erzeugt Chunk-Payloads aus den vom Chunker gelieferten "Chunk"-Objekten.
-- Spiegelt `retriever_weight` und `chunk_profile` in **jedem** Chunk-Payload.
-- Werteauflösung: Frontmatter > types.yaml > Defaults.
-- Lädt `config/types.yaml` selbst, wenn `types_cfg` nicht übergeben wurde.
-
-Eingang
--------
-- note: Dict mit mind. { frontmatter: {...}, id, type, title, path }
-- note_path: Pfad der Note (für Payload-Feld `path`)
-- chunks_from_chunker: Liste von Objekten mit Attributen/Feldern:
-  id, note_id, index, text, window, neighbors_prev, neighbors_next
-- note_text: voller Text der Note (optional, kann leer sein)
-- types_cfg: optional; wenn None → config wird intern geladen
-- file_path: optional, für Debug/Tracing im Payload
-
-Ausgang (pro Chunk)
--------------------
-- Pflichtfelder: note_id, chunk_id, index (0-basiert), ord (1-basiert), type, tags
-- Texte: text, window
-- Nachbarn: neighbors_prev, neighbors_next
-- Spiegelungen: retriever_weight, chunk_profile
-- Meta: source_path, path, section (leer), created/updated opt. aus Frontmatter
 
+Änderungen ggü. v1:
+- neighbors_prev / neighbors_next werden als **Array** persistiert ([], [id]).
+- retriever_weight / chunk_profile werden je Chunk aufgelöst (Frontmatter > types.yaml > Defaults).
+- Lädt config/types.yaml selbst, wenn types_cfg nicht übergeben wurde.
 """
 from __future__ import annotations
 from typing import Any, Dict, List, Optional
@@ -60,10 +39,8 @@ def _load_types_local() -> dict:
         return {}
 
 def _effective_chunk_profile(note_type: str, fm: Dict[str, Any], reg: dict) -> Optional[str]:
-    # Frontmatter zuerst
     if isinstance(fm.get("chunk_profile"), str):
         return fm.get("chunk_profile")
-    # Registry
     types = reg.get("types") if isinstance(reg.get("types"), dict) else reg
     if isinstance(types, dict):
         v = types.get(note_type, {})
@@ -74,12 +51,10 @@ def _effective_chunk_profile(note_type: str, fm: Dict[str, Any], reg: dict) -> O
     return None
 
 def _effective_retriever_weight(note_type: str, fm: Dict[str, Any], reg: dict) -> float:
-    # Frontmatter zuerst
     if fm.get("retriever_weight") is not None:
         v = _as_float(fm.get("retriever_weight"))
         if v is not None:
             return float(v)
-    # Registry-Pfade
     types = reg.get("types") if isinstance(reg.get("types"), dict) else reg
     candidates = [
         f"{note_type}.retriever_weight",
@@ -91,16 +66,21 @@ def _effective_retriever_weight(note_type: str, fm: Dict[str, Any], reg: dict) -
         "global.retriever.weight",
     ]
     for path in candidates:
-        # Wenn types == reg-root (flatten), erlauben sowohl "types.X" als auch "X"
         val = _deep_get(types, path) if "." in path else (types.get(path) if isinstance(types, dict) else None)
         if val is None and isinstance(reg, dict):
-            # versuche absolute Pfade
             val = _deep_get(reg, f"types.{path}")
         v = _as_float(val)
         if v is not None:
             return float(v)
     return 1.0
 
+def _as_list(x):
+    if x is None:
+        return []
+    if isinstance(x, list):
+        return x
+    return [x]
+
 def make_chunk_payloads(note: Dict[str, Any],
                         note_path: str,
                         chunks_from_chunker: List[Any],
@@ -108,11 +88,10 @@ def make_chunk_payloads(note: Dict[str, Any],
                         note_text: str = "",
                         types_cfg: Optional[dict] = None,
                         file_path: Optional[str] = None) -> List[Dict[str, Any]]:
-    fm = (note or {}).get("frontmatter", {})
+    fm = (note or {}).get("frontmatter", {}) or {}
     note_type = fm.get("type") or note.get("type") or "concept"
     reg = types_cfg if isinstance(types_cfg, dict) else _load_types_local()
 
-    # Effektive Werte bestimmen
     cp = _effective_chunk_profile(note_type, fm, reg)
     rw = _effective_retriever_weight(note_type, fm, reg)
 
@@ -121,9 +100,8 @@ def make_chunk_payloads(note: Dict[str, Any],
         tags = [tags]
 
     out: List[Dict[str, Any]] = []
-
     for idx, ch in enumerate(chunks_from_chunker):
-        # Chunk-Grunddaten (Attribute oder Keys)
+        # Attribute oder Keys (Chunk-Objekt oder Dict)
         cid = getattr(ch, "id", None) or (ch.get("id") if isinstance(ch, dict) else None)
         nid = getattr(ch, "note_id", None) or (ch.get("note_id") if isinstance(ch, dict) else fm.get("id"))
         index = getattr(ch, "index", None) or (ch.get("index") if isinstance(ch, dict) else idx)
@@ -141,8 +119,8 @@ def make_chunk_payloads(note: Dict[str, Any],
             "tags": tags,
             "text": text,
             "window": window,
-            "neighbors_prev": prev_id,
+            "neighbors_prev": _as_list(prev_id),
-            "neighbors_next": next_id,
+            "neighbors_next": _as_list(next_id),
             "section": getattr(ch, "section", None) or (ch.get("section") if isinstance(ch, dict) else ""),
             "path": note_path,
             "source_path": file_path or note_path,
@@ -151,10 +129,9 @@ def make_chunk_payloads(note: Dict[str, Any],
         if cp is not None:
             pl["chunk_profile"] = cp
 
-        # Aufräumen: keine historischen Aliasfelder
+        # Aufräumen
         for alias in ("chunk_num", "Chunk_Number"):
-            if alias in pl:
+            pl.pop(alias, None)
-                pl.pop(alias, None)
 
         out.append(pl)