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Lars 2025-11-09 09:15:48 +01:00
parent 6dc37ccb66
commit bbd5a7fa48
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"""
chunk_payload.py Mindnet payload helpers
Version: 0.5.2 (generated 2025-11-08 21:03:48)
Purpose:
- Build CHUNK payloads list while preserving existing chunk fields (text, seq, etc.).
- Inject into *every* chunk:
* retriever_weight (resolved like note payload)
* chunk_profile (resolved like note payload)
Resolution order identical to note_payload.make_note_payload.
Signature tolerant to match existing importers.
chunk_payload.py Mindnet payload builder (Chunks)
Version: 1.3.0 (2025-11-09)
Purpose
-------
Build Qdrant-compatible JSON payloads for *chunks* of a parsed note.
Tolerant to different call signatures and accepts both dict-like and object-like inputs.
Key features
------------
- Reads type defaults from `config/config.yaml` or `config/types.yaml` (same schema).
- Resolves fields with precedence:
Frontmatter > type-defaults > ENV > fallback.
- Sets per chunk:
* `note_id`, `note_title`, `type`
* `retriever_weight` (float)
* `chunk_profile` (short|medium|long)
* `text` (never empty: falls back to whole note body/text)
* `order`, `section`, `start`, `end` (if available)
- Backwards-compatible signature: accepts **kwargs to swallow unknown args.
Input
-----
`parsed_note` may be:
- dict with keys: id, title, body/text, chunks(list), frontmatter(dict), type
- object with equivalent attributes
Each chunk may be dict-like or object-like with keys/attrs such as:
id, text, order, section, start, end
"""
from __future__ import annotations
from typing import Any, Dict, List, Optional, Union
from pathlib import Path
import os
from pathlib import Path
from typing import Any, Dict, List, Optional, Union
try:
import yaml # type: ignore
except Exception: # pragma: no cover
yaml = None # will skip YAML loading if unavailable
yaml = None
def _coerce_mapping(obj: Any) -> Dict[str, Any]:
if obj is None:
return {{}}
def _get(obj: Any, key: str, default: Any = None) -> Any:
if isinstance(obj, dict):
return dict(obj)
out: Dict[str, Any] = {{}}
if hasattr(obj, "__dict__"):
out.update(getattr(obj, "__dict__"))
for k in ("id","note_id","title","type","path","source_path","frontmatter"):
if hasattr(obj, k) and k not in out:
out[k] = getattr(obj, k)
return out
return obj.get(key, default)
return getattr(obj, key, default)
def _frontmatter(obj: Any) -> Dict[str, Any]:
fm = _get(obj, "frontmatter", {}) or {}
return fm if isinstance(fm, dict) else {}
def _coerce_chunk_dict(obj: Any) -> Dict[str, Any]:
if isinstance(obj, dict):
return dict(obj)
d = {{}}
# common attributes for a chunk object
for k in ("chunk_id","id","note_id","seq","start","end","text","title","type","source_path"):
if hasattr(obj, k):
d[k] = getattr(obj, k)
if hasattr(obj, "__dict__"):
for k,v in obj.__dict__.items():
d.setdefault(k, v)
return d
def _get_frontmatter(parsed: Dict[str, Any]) -> Dict[str, Any]:
fm = parsed.get("frontmatter")
return dict(fm) if isinstance(fm, dict) else {{}}
def _load_types_from_yaml(types_file: Optional[Union[str, Path]]) -> Dict[str, Any]:
if types_file is None:
for cand in (Path("config/types.yaml"), Path("config/types.yml"), Path("config.yaml"), Path("config.yml")):
if cand.exists():
types_file = cand
break
if types_file is None or yaml is None:
return {{}}
p = Path(types_file)
if not p.exists():
return {{}}
def _coerce_float(val: Any, default: float) -> float:
try:
data = yaml.safe_load(p.read_text(encoding="utf-8"))
if not isinstance(data, dict):
return {{}}
if "types" in data and isinstance(data["types"], dict):
return dict(data["types"])
return data
if val is None:
return default
if isinstance(val, (int, float)):
return float(val)
if isinstance(val, str) and val.strip():
return float(val.strip())
except Exception:
return {{}}
pass
return default
def _resolve_type_defaults(note_type: Optional[str], types: Optional[Dict[str,Any]]) -> Dict[str, Any]:
if not note_type or not types or not isinstance(types, dict):
return {{}}
block = types.get(note_type)
return dict(block) if isinstance(block, dict) else {{}}
def _to_float(val: Any, fallback: float) -> float:
if val is None:
return fallback
try:
return float(val)
except Exception:
def _normalize_chunk_profile(val: Any, fallback: str = "medium") -> str:
if not isinstance(val, str):
return fallback
v = val.strip().lower()
if v in {"short", "medium", "long"}:
return v
return fallback
def _safe_text(s: Any) -> str:
if s is None:
return ""
if isinstance(s, str):
return s
return str(s)
def _first_nonempty(*vals):
for v in vals:
if v is not None:
if isinstance(v, str) and v.strip() == "":
continue
return v
return None
def _load_types_config(
explicit_config: Optional[Dict[str, Any]] = None,
search_root: Union[str, Path, None] = None,
) -> Dict[str, Any]:
if explicit_config and isinstance(explicit_config, dict):
if "types" in explicit_config and isinstance(explicit_config["types"], dict):
return explicit_config
if yaml is None:
return {"types": {}}
candidates: List[Path] = []
root = Path(search_root) if search_root else Path.cwd()
candidates.append(root / "config" / "config.yaml")
candidates.append(root / "config" / "types.yaml")
candidates.append(Path.cwd() / "config" / "config.yaml")
candidates.append(Path.cwd() / "config" / "types.yaml")
for p in candidates:
try:
if p.exists():
import yaml as _y
with p.open("r", encoding="utf-8") as f:
loaded = _y.safe_load(f) or {}
if isinstance(loaded, dict) and isinstance(loaded.get("types"), dict):
return {"types": loaded["types"]}
except Exception:
continue
return {"types": {}}
def _type_defaults(note_type: str, cfg: Dict[str, Any]) -> Dict[str, Any]:
return (cfg.get("types") or {}).get(note_type, {}) if isinstance(cfg, dict) else {}
def make_chunk_payloads(parsed_note: Any, chunks: List[Any], **kwargs) -> List[Dict[str, Any]]:
parsed = _coerce_mapping(parsed_note)
fm = _get_frontmatter(parsed)
def make_chunk_payloads(
parsed_note: Any,
config: Optional[Dict[str, Any]] = None,
**kwargs: Any,
) -> List[Dict[str, Any]]:
search_root = kwargs.get("search_root")
fm = _frontmatter(parsed_note)
note_type = fm.get("type") or _get(parsed_note, "type") or "concept"
note_type = str(note_type).strip().lower()
# external sources
types_registry = kwargs.get("types") or kwargs.get("types_registry")
types_from_yaml = _load_types_from_yaml(kwargs.get("types_file"))
types_all: Dict[str, Any] = types_registry if isinstance(types_registry, dict) else types_from_yaml
cfg = _load_types_config(config, search_root)
defaults = _type_defaults(note_type, cfg)
note_type: Optional[str] = _first_nonempty(parsed.get("type"), fm.get("type"))
type_defaults = _resolve_type_defaults(note_type, types_all)
# Resolve retriever_weight: FM > type-defaults > ENV > 1.0
rw = fm.get("retriever_weight")
if rw is None:
rw = defaults.get("retriever_weight")
if rw is None:
env_rw = os.getenv("MINDNET_DEFAULT_RETRIEVER_WEIGHT")
rw = _coerce_float(env_rw, 1.0)
else:
rw = _coerce_float(rw, 1.0)
env_default = os.getenv("MINDNET_DEFAULT_RETRIEVER_WEIGHT")
env_default_val = _to_float(env_default, 1.0) if env_default is not None else 1.0
# Resolve chunk_profile: FM > type-defaults > ENV > medium
cp = fm.get("chunk_profile")
if cp is None:
cp = defaults.get("chunk_profile")
if cp is None:
cp = os.getenv("MINDNET_DEFAULT_CHUNK_PROFILE", "medium")
cp = _normalize_chunk_profile(cp, "medium")
effective_retriever_weight = _to_float(
_first_nonempty(
fm.get("retriever_weight"),
type_defaults.get("retriever_weight"),
env_default_val,
1.0,
),
1.0,
)
note_id = _get(parsed_note, "id")
note_title = _get(parsed_note, "title")
body = _get(parsed_note, "body") or _get(parsed_note, "text") or ""
effective_chunk_profile = _first_nonempty(
fm.get("chunk_profile"),
fm.get("profile"),
type_defaults.get("chunk_profile"),
os.getenv("MINDNET_DEFAULT_CHUNK_PROFILE"),
)
items = _get(parsed_note, "chunks") or []
payloads: List[Dict[str, Any]] = []
out: List[Dict[str, Any]] = []
for ch in chunks or []:
payload = _coerce_chunk_dict(ch) # preserve all existing chunk fields
payload["retriever_weight"] = effective_retriever_weight
if effective_chunk_profile is not None:
payload["chunk_profile"] = effective_chunk_profile
out.append(payload)
return out
if not items:
items = [{
"id": f"{note_id}::0" if note_id else None,
"text": body,
"order": 0,
"section": None,
"start": 0,
"end": len(body) if isinstance(body, str) else None,
}]
for ch in items:
text = _safe_text(_get(ch, "text"))
if not text:
text = _safe_text(body)
payload = {
"note_id": note_id,
"note_title": note_title,
"type": note_type,
"retriever_weight": float(rw),
"chunk_profile": cp,
"text": text,
"order": _get(ch, "order"),
"section": _get(ch, "section"),
"start": _get(ch, "start"),
"end": _get(ch, "end"),
"chunk_id": _get(ch, "id"),
}
payload = {k: v for k, v in payload.items() if v is not None}
payloads.append(payload)
return payloads

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"""
note_payload.py Mindnet payload helpers
Version: 0.5.2 (generated 2025-11-08 21:03:48)
Purpose:
- Build a NOTE payload without dropping existing fields.
- Resolve and inject:
* retriever_weight
* chunk_profile
* edge_defaults
Resolution order:
1) Frontmatter fields
2) Type defaults from a provided registry ('types' kwarg) OR YAML file (types_file kwarg).
YAML formats supported:
- root['types'][note_type]{{retriever_weight, chunk_profile, edge_defaults}}
- root[note_type] is the type block directly
3) ENV MINDNET_DEFAULT_RETRIEVER_WEIGHT
4) Fallback 1.0
Notes:
- Function signature tolerant: accepts **kwargs (e.g. vault_root, types_file, types, types_registry).
- Does NOT attempt to create edges; it only exposes 'edge_defaults' in the NOTE payload for later stages.
note_payload.py Mindnet payload builder (Notes)
Version: 1.3.0 (2025-11-09)
Purpose
-------
Build Qdrant-compatible JSON payloads for *notes* from a parsed Markdown
representation. The function is tolerant to different call signatures and
accepts both dict-like and object-like "ParsedNote" inputs.
Key features
------------
- Reads type defaults from `config/config.yaml` or `config/types.yaml` (same schema).
- Resolves fields with the following precedence:
Frontmatter > type-defaults > ENV > hard-coded fallback.
- Ensures only JSON-serializable types are included (no sets, Path, callables).
- Sets/normalizes:
* `type` : note type (e.g., concept, task, experience, project)
* `retriever_weight` : float, influences retrieval blending downstream
* `chunk_profile` : short | medium | long (string)
* `edge_defaults` : list[str], used by edge builder outside of this module
- Backwards-compatible signature: accepts **kwargs to swallow unknown args
(e.g., vault_root, prefix, ...).
Expected input (flexible)
-------------------------
`parsed_note` may be:
- dict with keys: id, title, body/text, path, frontmatter (dict), type, ...
- object with attributes: id, title, body/text, path, frontmatter, type, ...
Schema for config files
-----------------------
version: 1.0
types:
concept:
chunk_profile: medium
edge_defaults: ["references", "related_to"]
retriever_weight: 0.33
task:
chunk_profile: short
edge_defaults: ["depends_on", "belongs_to"]
retriever_weight: 0.8
experience:
chunk_profile: medium
edge_defaults: ["derived_from", "inspired_by"]
retriever_weight: 0.9
project:
chunk_profile: long
edge_defaults: ["references", "depends_on"]
retriever_weight: 0.95
"""
from __future__ import annotations
from typing import Any, Dict, Optional, Mapping, Union
import json
import os
from pathlib import Path
from typing import Any, Dict, List, Optional, Union
try:
import yaml # type: ignore
except Exception: # pragma: no cover
yaml = None # will skip YAML loading if unavailable
yaml = None # The caller must ensure PyYAML is installed
# ------------------------------
# Helpers
# ------------------------------
# -------- helpers --------
def _coerce_mapping(obj: Any) -> Dict[str, Any]:
if obj is None:
return {{}}
def _get(obj: Any, key: str, default: Any = None) -> Any:
"""Get key from dict-like or attribute from object-like."""
if isinstance(obj, dict):
return dict(obj)
# try common attributes
out: Dict[str, Any] = {{}}
for k in ("__dict__",):
if hasattr(obj, k):
out.update(getattr(obj, k))
# named attributes we often see
for k in ("id","note_id","title","type","path","source_path","frontmatter"):
if hasattr(obj, k) and k not in out:
out[k] = getattr(obj, k)
return out
return obj.get(key, default)
return getattr(obj, key, default)
def _frontmatter(obj: Any) -> Dict[str, Any]:
fm = _get(obj, "frontmatter", {}) or {}
return fm if isinstance(fm, dict) else {}
def _get_frontmatter(parsed: Mapping[str, Any]) -> Dict[str, Any]:
fm = parsed.get("frontmatter")
if isinstance(fm, dict):
return dict(fm)
return {{}} # tolerate notes without frontmatter
def _load_types_from_yaml(types_file: Optional[Union[str, Path]]) -> Dict[str, Any]:
if types_file is None:
# try common defaults
candidates = [
Path("config/types.yaml"),
Path("config/types.yml"),
Path("config.yaml"),
Path("config.yml"),
]
for p in candidates:
if p.exists():
types_file = p
break
if types_file is None:
return {{}}
p = Path(types_file)
if not p.exists() or yaml is None:
return {{}}
def _coerce_float(val: Any, default: float) -> float:
try:
data = yaml.safe_load(p.read_text(encoding="utf-8"))
if not isinstance(data, dict):
return {{}}
# support both shapes: {{types: {{concept: ...}}}} OR {{concept: ...}}
if "types" in data and isinstance(data["types"], dict):
return dict(data["types"])
return data
if val is None:
return default
if isinstance(val, (int, float)):
return float(val)
if isinstance(val, str) and val.strip():
return float(val.strip())
except Exception:
return {{}}
pass
return default
def _normalize_chunk_profile(val: Any, fallback: str = "medium") -> str:
if not isinstance(val, str):
return fallback
v = val.strip().lower()
if v in {"short", "medium", "long"}:
return v
return fallback
def _resolve_type_defaults(note_type: Optional[str], types: Optional[Dict[str,Any]]) -> Dict[str, Any]:
defaults = {{}}
if not note_type or not types or not isinstance(types, dict):
return defaults
block = types.get(note_type)
if isinstance(block, dict):
defaults.update(block)
return defaults
def _to_float(val: Any, fallback: float) -> float:
def _coerce_str_list(val: Any) -> List[str]:
if val is None:
return fallback
return []
if isinstance(val, list):
out: List[str] = []
for x in val:
if isinstance(x, str):
out.append(x)
else:
out.append(str(x))
return out
if isinstance(val, str):
# allow comma-separated
return [x.strip() for x in val.split(",") if x.strip()]
return []
def _safe_jsonable(value: Any) -> Any:
"""Ensure value is JSON-serializable (no sets, Path, callables, etc.)."""
if isinstance(value, (str, int, float, bool)) or value is None:
return value
if isinstance(value, list):
return [_safe_jsonable(v) for v in value]
if isinstance(value, dict):
return {str(k): _safe_jsonable(v) for k, v in value.items()}
if isinstance(value, Path):
return str(value)
# Avoid sets and other iterables that are not JSON-serializable
try:
return float(val)
json.dumps(value)
return value
except Exception:
return fallback
return str(value)
# ------------------------------
# Config loading
# ------------------------------
def _first_nonempty(*vals):
for v in vals:
if v is not None:
if isinstance(v, str) and v.strip() == "":
def _load_types_config(
explicit_config: Optional[Dict[str, Any]] = None,
search_root: Union[str, Path, None] = None,
) -> Dict[str, Any]:
"""
Load types config from:
1) explicit_config (if provided)
2) {search_root}/config/config.yaml
3) {search_root}/config/types.yaml
4) ./config/config.yaml
5) ./config/types.yaml
Returns a dict with shape: {"types": {...}} (empty if none found).
"""
if explicit_config and isinstance(explicit_config, dict):
if "types" in explicit_config and isinstance(explicit_config["types"], dict):
return explicit_config
candidates: List[Path] = []
root = Path(search_root) if search_root else Path.cwd()
candidates.append(root / "config" / "config.yaml")
candidates.append(root / "config" / "types.yaml")
# fallback to CWD when search_root was different
candidates.append(Path.cwd() / "config" / "config.yaml")
candidates.append(Path.cwd() / "config" / "types.yaml")
data = {}
if yaml is None:
return {"types": {}}
for p in candidates:
try:
if p.exists():
with p.open("r", encoding="utf-8") as f:
loaded = yaml.safe_load(f) or {}
if isinstance(loaded, dict) and isinstance(loaded.get("types"), dict):
data = {"types": loaded["types"]}
break
except Exception:
continue
if not data:
data = {"types": {}}
return data
def _type_defaults(note_type: str, cfg: Dict[str, Any]) -> Dict[str, Any]:
return (cfg.get("types") or {}).get(note_type, {}) if isinstance(cfg, dict) else {}
# ------------------------------
# Public API
# ------------------------------
def make_note_payload(
parsed_note: Any,
*,
config: Optional[Dict[str, Any]] = None,
search_root: Union[str, Path, None] = None,
**kwargs: Any,
) -> Dict[str, Any]:
"""
Build the payload for a NOTE. Tolerates extra kwargs (e.g., vault_root, prefix).
"""
fm = _frontmatter(parsed_note)
note_type = fm.get("type") or _get(parsed_note, "type") or "concept"
note_type = str(note_type).strip().lower()
# Load config and resolve defaults
cfg = _load_types_config(config, search_root)
defaults = _type_defaults(note_type, cfg)
# retriever_weight: FM > type-defaults > ENV > 1.0
rw = fm.get("retriever_weight")
if rw is None:
rw = defaults.get("retriever_weight")
if rw is None:
env_rw = os.getenv("MINDNET_DEFAULT_RETRIEVER_WEIGHT")
rw = _coerce_float(env_rw, 1.0)
else:
rw = _coerce_float(rw, 1.0)
# chunk_profile: FM > type-defaults > ENV > medium
cp = fm.get("chunk_profile")
if cp is None:
cp = defaults.get("chunk_profile")
if cp is None:
cp = os.getenv("MINDNET_DEFAULT_CHUNK_PROFILE", "medium")
cp = _normalize_chunk_profile(cp, "medium")
# edge_defaults: FM > type-defaults > empty
edge_defs = fm.get("edge_defaults")
if edge_defs is None:
edge_defs = defaults.get("edge_defaults", [])
edge_defs = _coerce_str_list(edge_defs)
payload: Dict[str, Any] = {
"id": _get(parsed_note, "id"),
"note_id": _get(parsed_note, "id"),
"title": _get(parsed_note, "title"),
"type": note_type,
"retriever_weight": float(rw),
"chunk_profile": cp,
"edge_defaults": edge_defs,
# Useful passthrough/meta (all made JSON-safe)
"path": _safe_jsonable(_get(parsed_note, "path")),
"source": _safe_jsonable(_get(parsed_note, "source")),
}
# Include raw frontmatter keys (stringify keys; make safe)
if isinstance(fm, dict):
for k, v in fm.items():
# avoid overwriting normalized fields
if k in {"type", "retriever_weight", "chunk_profile", "edge_defaults"}:
continue
return v
return None
# -------- main API --------
def make_note_payload(parsed_note: Any, **kwargs) -> Dict[str, Any]:
parsed = _coerce_mapping(parsed_note)
fm = _get_frontmatter(parsed)
# external sources
types_registry = kwargs.get("types") or kwargs.get("types_registry")
types_from_yaml = _load_types_from_yaml(kwargs.get("types_file"))
# registry wins over YAML if provided
types_all: Dict[str, Any] = types_registry if isinstance(types_registry, dict) else types_from_yaml
note_type: Optional[str] = _first_nonempty(parsed.get("type"), fm.get("type"))
title: Optional[str] = _first_nonempty(parsed.get("title"), fm.get("title"))
note_id: Optional[str] = _first_nonempty(parsed.get("note_id"), parsed.get("id"), fm.get("id"))
type_defaults = _resolve_type_defaults(note_type, types_all)
# --- resolve retriever_weight ---
env_default = os.getenv("MINDNET_DEFAULT_RETRIEVER_WEIGHT")
env_default_val = _to_float(env_default, 1.0) if env_default is not None else 1.0
effective_retriever_weight = _to_float(
_first_nonempty(
fm.get("retriever_weight"),
type_defaults.get("retriever_weight"),
env_default_val,
1.0,
),
1.0,
)
# --- resolve chunk_profile ---
effective_chunk_profile = _first_nonempty(
fm.get("chunk_profile"),
fm.get("profile"),
type_defaults.get("chunk_profile"),
os.getenv("MINDNET_DEFAULT_CHUNK_PROFILE"),
)
# --- resolve edge_defaults (list[str]) ---
edge_defaults = _first_nonempty(
fm.get("edge_defaults"),
type_defaults.get("edge_defaults"),
)
if edge_defaults is None:
edge_defaults = []
if isinstance(edge_defaults, str):
# allow "a,b,c"
edge_defaults = [s.strip() for s in edge_defaults.split(",") if s.strip()]
elif not isinstance(edge_defaults, list):
edge_defaults = []
# Start payload by preserving existing parsed keys (shallow copy); DO NOT drop fields
payload: Dict[str, Any] = dict(parsed)
# Ensure canonical top-level fields
if note_id is not None:
payload["id"] = note_id
payload["note_id"] = note_id
if title is not None:
payload["title"] = title
if note_type is not None:
payload["type"] = note_type
payload["retriever_weight"] = effective_retriever_weight
if effective_chunk_profile is not None:
payload["chunk_profile"] = effective_chunk_profile
if edge_defaults:
payload["edge_defaults"] = edge_defaults
# keep frontmatter merged (without duplication)
if "frontmatter" in payload and isinstance(payload["frontmatter"], dict):
fm_out = dict(payload["frontmatter"])
fm_out.setdefault("type", note_type)
fm_out["retriever_weight"] = effective_retriever_weight
if effective_chunk_profile is not None:
fm_out["chunk_profile"] = effective_chunk_profile
if edge_defaults:
fm_out["edge_defaults"] = edge_defaults
payload["frontmatter"] = fm_out
payload[f"fm_{k}"] = _safe_jsonable(v)
# Remove None values to keep payload clean
payload = {k: v for k, v in payload.items() if v is not None}
return payload