#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
app/core/chunk_payload.py  (Mindnet V2 — robust v2)

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
import os, yaml

def _env(n: str, d: Optional[str]=None) -> str:
    v = os.getenv(n)
    return v if v is not None else (d or "")

def _deep_get(root: Any, path: str) -> Any:
    cur = root
    for key in path.split("."):
        if not isinstance(cur, dict) or key not in cur:
            return None
        cur = cur[key]
    return cur

def _as_float(x: Any):
    try:
        return float(x)
    except Exception:
        return None

def _load_types_local() -> dict:
    p = _env("MINDNET_TYPES_FILE", "./config/types.yaml")
    try:
        with open(p, "r", encoding="utf-8") as f:
            return yaml.safe_load(f) or {}
    except Exception:
        return {}

def _effective_chunk_profile(note_type: str, fm: Dict[str, Any], reg: dict) -> Optional[str]:
    if isinstance(fm.get("chunk_profile"), str):
        return fm.get("chunk_profile")
    types = reg.get("types") if isinstance(reg.get("types"), dict) else reg
    if isinstance(types, dict):
        v = types.get(note_type, {})
        if isinstance(v, dict):
            cp = v.get("chunk_profile")
            if isinstance(cp, str):
                return cp
    return None

def _effective_retriever_weight(note_type: str, fm: Dict[str, Any], reg: dict) -> float:
    if fm.get("retriever_weight") is not None:
        v = _as_float(fm.get("retriever_weight"))
        if v is not None:
            return float(v)
    types = reg.get("types") if isinstance(reg.get("types"), dict) else reg
    candidates = [
        f"{note_type}.retriever_weight",
        f"{note_type}.retriever.weight",
        f"{note_type}.retrieval.weight",
        "defaults.retriever_weight",
        "defaults.retriever.weight",
        "global.retriever_weight",
        "global.retriever.weight",
    ]
    for path in candidates:
        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):
            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],
                        *,
                        note_text: str = "",
                        types_cfg: Optional[dict] = None,
                        file_path: Optional[str] = None) -> List[Dict[str, Any]]:
    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()

    cp = _effective_chunk_profile(note_type, fm, reg)
    rw = _effective_retriever_weight(note_type, fm, reg)

    tags = fm.get("tags") or []
    if isinstance(tags, str):
        tags = [tags]

    out: List[Dict[str, Any]] = []
    for idx, ch in enumerate(chunks_from_chunker):
        # 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)
        text = getattr(ch, "text", None) or (ch.get("text") if isinstance(ch, dict) else "")
        window = getattr(ch, "window", None) or (ch.get("window") if isinstance(ch, dict) else text)
        prev_id = getattr(ch, "neighbors_prev", None) or (ch.get("neighbors_prev") if isinstance(ch, dict) else None)
        next_id = getattr(ch, "neighbors_next", None) or (ch.get("neighbors_next") if isinstance(ch, dict) else None)

        pl: Dict[str, Any] = {
            "note_id": nid,
            "chunk_id": cid,
            "index": int(index),
            "ord": int(index) + 1,
            "type": note_type,
            "tags": tags,
            "text": text,
            "window": window,
            "neighbors_prev": _as_list(prev_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,
            "retriever_weight": float(rw),
        }
        if cp is not None:
            pl["chunk_profile"] = cp

        # Aufräumen
        for alias in ("chunk_num", "Chunk_Number"):
            pl.pop(alias, None)

        out.append(pl)

    return out