|
|
| """
|
| corpus_cache.py -- On-disk cache of embedding vectors per skill/agent.
|
|
|
| The intake similarity check needs an embedding per existing subject
|
| to rank a candidate against. Re-embedding the whole corpus on every
|
| ``skill_add`` is wasteful; this module caches each embedding keyed
|
| by (subject_id, content_sha256). Stale entries (body changed) miss
|
| silently and are re-computed on next access.
|
|
|
| Layout::
|
|
|
| <root>/
|
| <backend_key>/
|
| _manifest.json metadata only
|
| <subject_id>__<sha16>.npy raw float32 vector
|
|
|
| ``backend_key`` is derived from the embedder's ``name``. Switching
|
| embedders therefore lands in a separate directory and never mixes
|
| dimensions (ST=384 vs Ollama=768).
|
|
|
| Race-freeness: the content hash is encoded in the filename, not
|
| just the manifest. A concurrent ``put`` cannot replace a file under
|
| a reader — the new vector lands at a different path.
|
|
|
| Security:
|
| - ``subject_id`` is validated against a strict regex (prevents
|
| path traversal via crafted IDs like ``../evil``).
|
| - Vector files are written atomically (``os.replace`` from a
|
| sibling tempfile).
|
| - Manifest writes are serialised via ``_file_lock.file_lock`` so
|
| concurrent processes don't clobber each other's entries.
|
| """
|
|
|
| from __future__ import annotations
|
|
|
| import hashlib
|
| import json
|
| import os
|
| import re
|
| import shutil
|
| import tempfile
|
| from dataclasses import dataclass
|
| from pathlib import Path
|
| from typing import Iterator
|
|
|
| import numpy as np
|
|
|
| from ctx.utils._file_lock import file_lock
|
|
|
|
|
| DEFAULT_CACHE_ROOT = Path(os.path.expanduser("~/.claude/skills/_embeddings"))
|
|
|
|
|
|
|
|
|
| _SUBJECT_ID_RE = re.compile(r"^[a-zA-Z0-9][a-zA-Z0-9_\-\.]{0,127}$")
|
|
|
|
|
|
|
|
|
| _BACKEND_UNSAFE_RE = re.compile(r"[^a-zA-Z0-9_\-\.]")
|
|
|
|
|
|
|
|
|
| _SHA_FILENAME_LEN = 16
|
|
|
|
|
| def _slug_backend_key(backend_name: str) -> str:
|
| """Turn an ``Embedder.name`` into a filesystem-safe directory name."""
|
| if not isinstance(backend_name, str) or not backend_name:
|
| raise ValueError("backend_name must be a non-empty string")
|
| slug = _BACKEND_UNSAFE_RE.sub("_", backend_name).strip("_")
|
| if not slug or not slug[0].isalnum():
|
| raise ValueError(f"backend name yields unsafe slug: {backend_name!r}")
|
| return slug[:64]
|
|
|
|
|
| def _sha256_text(text: str) -> str:
|
| return hashlib.sha256(text.encode("utf-8")).hexdigest()
|
|
|
|
|
| @dataclass(frozen=True)
|
| class CacheEntry:
|
| """Manifest row for one cached vector."""
|
|
|
| content_sha256: str
|
| dim: int
|
|
|
|
|
| class CorpusCache:
|
| """Per-subject embedding cache.
|
|
|
| Instances are cheap — they only touch disk on ``get``/``put``/
|
| ``invalidate``. Safe under concurrent writers within a process
|
| and across processes via ``file_lock`` on the manifest.
|
| """
|
|
|
| def __init__(self, backend_name: str, *, root: Path | None = None) -> None:
|
| self._root = (root or DEFAULT_CACHE_ROOT).expanduser()
|
| self._backend_dir = self._root / _slug_backend_key(backend_name)
|
| self._manifest_path = self._backend_dir / "_manifest.json"
|
|
|
| @property
|
| def backend_dir(self) -> Path:
|
| return self._backend_dir
|
|
|
| @property
|
| def manifest_path(self) -> Path:
|
| return self._manifest_path
|
|
|
| def _ensure_dir(self) -> None:
|
| self._backend_dir.mkdir(parents=True, exist_ok=True)
|
|
|
| @staticmethod
|
| def _validate_subject_id(subject_id: str) -> None:
|
| if not isinstance(subject_id, str) or not _SUBJECT_ID_RE.match(subject_id):
|
| raise ValueError(f"invalid subject_id: {subject_id!r}")
|
|
|
| def _vector_path(self, subject_id: str, content_sha: str) -> Path:
|
|
|
|
|
|
|
| return self._backend_dir / f"{subject_id}__{content_sha[:_SHA_FILENAME_LEN]}.npy"
|
|
|
| def _read_manifest(self) -> dict[str, dict[str, object]]:
|
| try:
|
| with open(self._manifest_path, encoding="utf-8") as fh:
|
| data = json.load(fh)
|
| except FileNotFoundError:
|
| return {}
|
| except json.JSONDecodeError:
|
|
|
|
|
|
|
|
|
| return {}
|
| if not isinstance(data, dict):
|
| return {}
|
| return data
|
|
|
| def _write_manifest(self, data: dict[str, dict[str, object]]) -> None:
|
| self._ensure_dir()
|
|
|
|
|
| fd, tmp = tempfile.mkstemp(
|
| prefix="_manifest.", suffix=".json.tmp", dir=self._backend_dir
|
| )
|
| try:
|
| with os.fdopen(fd, "w", encoding="utf-8") as fh:
|
| json.dump(data, fh, ensure_ascii=False, sort_keys=True, indent=2)
|
| os.replace(tmp, self._manifest_path)
|
| except Exception:
|
| try:
|
| Path(tmp).unlink()
|
| except FileNotFoundError:
|
| pass
|
| raise
|
|
|
| def get(self, subject_id: str, content: str) -> np.ndarray | None:
|
| """Return the cached vector iff the content hash matches.
|
|
|
| Reads the vector file directly by content-hash-encoded path.
|
| No manifest round-trip — a concurrent ``put`` for the same
|
| subject lands at a different filename and cannot poison the
|
| read.
|
| """
|
| self._validate_subject_id(subject_id)
|
| path = self._vector_path(subject_id, _sha256_text(content))
|
| try:
|
| vec = np.load(path, allow_pickle=False)
|
| except (FileNotFoundError, ValueError, OSError):
|
| return None
|
| if vec.ndim != 1:
|
| return None
|
| if vec.dtype != np.float32:
|
| vec = vec.astype(np.float32, copy=False)
|
| return vec
|
|
|
| def put(self, subject_id: str, content: str, vector: np.ndarray) -> None:
|
| """Store ``vector`` for ``subject_id`` keyed by content hash.
|
|
|
| Writes the vector to a content-addressed filename, then
|
| updates the manifest inside a file lock. Prior vector files
|
| for the same subject are removed (orphan sweep).
|
| """
|
| self._validate_subject_id(subject_id)
|
| if not isinstance(vector, np.ndarray) or vector.ndim != 1:
|
| raise ValueError(f"vector must be a 1-D numpy array, got {vector!r}")
|
| vec = np.ascontiguousarray(vector, dtype=np.float32)
|
| sha = _sha256_text(content)
|
|
|
| self._ensure_dir()
|
| vec_path = self._vector_path(subject_id, sha)
|
|
|
|
|
|
|
|
|
| fd, tmp = tempfile.mkstemp(prefix=".", suffix=".npy", dir=self._backend_dir)
|
| try:
|
| os.close(fd)
|
| np.save(tmp, vec, allow_pickle=False)
|
| os.replace(tmp, vec_path)
|
| except Exception:
|
| try:
|
| Path(tmp).unlink()
|
| except FileNotFoundError:
|
| pass
|
| raise
|
|
|
|
|
| with file_lock(self._manifest_path):
|
| manifest = self._read_manifest()
|
| prev = manifest.get(subject_id)
|
| prev_sha = prev.get("content_sha256") if isinstance(prev, dict) else None
|
| manifest[subject_id] = {
|
| "content_sha256": sha,
|
| "dim": int(vec.shape[0]),
|
| }
|
| self._write_manifest(manifest)
|
| if isinstance(prev_sha, str) and prev_sha != sha:
|
| old = self._vector_path(subject_id, prev_sha)
|
| try:
|
| old.unlink()
|
| except FileNotFoundError:
|
| pass
|
|
|
| def invalidate(self, subject_id: str) -> bool:
|
| """Remove an entry. Returns True iff something was removed."""
|
| self._validate_subject_id(subject_id)
|
| removed = False
|
| with file_lock(self._manifest_path):
|
| manifest = self._read_manifest()
|
| entry = manifest.pop(subject_id, None)
|
| if entry is not None:
|
| self._write_manifest(manifest)
|
| removed = True
|
| sha = entry.get("content_sha256") if isinstance(entry, dict) else None
|
| if isinstance(sha, str):
|
| try:
|
| self._vector_path(subject_id, sha).unlink()
|
| except FileNotFoundError:
|
| pass
|
| return removed
|
|
|
| def entry(self, subject_id: str) -> CacheEntry | None:
|
| """Return the manifest entry for ``subject_id`` if present."""
|
| self._validate_subject_id(subject_id)
|
| data = self._read_manifest().get(subject_id)
|
| if not isinstance(data, dict):
|
| return None
|
| sha = data.get("content_sha256")
|
| dim = data.get("dim")
|
| if not isinstance(sha, str) or not isinstance(dim, int):
|
| return None
|
| return CacheEntry(content_sha256=sha, dim=dim)
|
|
|
| def subjects(self) -> Iterator[str]:
|
| """Yield subject IDs currently in the manifest."""
|
| return iter(sorted(self._read_manifest().keys()))
|
|
|
| def load_all(self) -> dict[str, np.ndarray]:
|
| """Load every cached vector. Skips any whose ``.npy`` is missing.
|
|
|
| Returns a plain ``dict`` — callers stacking into a matrix
|
| should order keys explicitly before ``np.vstack`` to keep
|
| row order stable.
|
| """
|
| out: dict[str, np.ndarray] = {}
|
| manifest = self._read_manifest()
|
| for sid, meta in manifest.items():
|
| if not isinstance(meta, dict):
|
| continue
|
| sha = meta.get("content_sha256")
|
| if not isinstance(sha, str):
|
| continue
|
| try:
|
| vec = np.load(
|
| self._vector_path(sid, sha), allow_pickle=False
|
| )
|
| except (FileNotFoundError, ValueError, OSError):
|
| continue
|
| if vec.ndim != 1:
|
| continue
|
| if vec.dtype != np.float32:
|
| vec = vec.astype(np.float32, copy=False)
|
| out[sid] = vec
|
| return out
|
|
|
| def size(self) -> int:
|
| return len(self._read_manifest())
|
|
|
| def clear(self) -> None:
|
| """Wipe this backend's cache directory. Destructive by design.
|
|
|
| Exposed because users who switch embedding models may want to
|
| reclaim disk; the caller must be explicit.
|
| """
|
| if self._backend_dir.exists():
|
| shutil.rmtree(self._backend_dir)
|
|
|