From 77039a6894aeba2db3f92643d4f7e3fa1de840c1 Mon Sep 17 00:00:00 2001 From: alphakenz Date: Thu, 27 Aug 2026 10:46:01 +0100 Subject: [PATCH 1/6] feat: optional derived vector index (#49) - VectorIndex protocol + NullVectorIndex default (zero vector deps) - Optional ChromaVectorIndex backend (lazy import, hotmem[vector] extra) - Index supplies oversampled cosine candidates; SQLite re-scores with the identical hybrid formula, preserving the /v1/search ranking contract - Rebuild reads SQLite only (embeddings reused, never recomputed, no file I/O); rebuild marker records the store fingerprint for staleness - Admin endpoints: POST /v1/vector-index/rebuild (emits index.rebuilt), GET /v1/vector-index/status, DELETE /v1/vector-index - hotmem serve --vector-index {none,chroma}; CI vector job; docs + changelog --- .github/workflows/ci.yml | 18 + CHANGELOG.md | 28 + docs/api.md | 41 +- docs/architecture.md | 7 + pyproject.toml | 3 + src/hotmem/cli.py | 17 +- src/hotmem/db.py | 72 +- src/hotmem/events.py | 1 + src/hotmem/search.py | 71 +- src/hotmem/server.py | 130 +- src/hotmem/vector_index.py | 507 ++++++ tests/golden/test_golden_additive.py | 47 + tests/test_vector_index.py | 657 ++++++++ uv.lock | 2256 +++++++++++++++++++++++++- 14 files changed, 3843 insertions(+), 12 deletions(-) create mode 100644 src/hotmem/vector_index.py create mode 100644 tests/test_vector_index.py diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index c7eb476..d0db3b8 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -30,6 +30,24 @@ jobs: files: coverage.xml fail_ci_if_error: false + vector: + runs-on: ubuntu-latest + strategy: + matrix: + python-version: ["3.13"] + steps: + - uses: actions/checkout@v4 + - uses: actions/setup-python@v5 + with: + python-version: ${{ matrix.python-version }} + - uses: astral-sh/setup-uv@v4 + - run: uv venv + - run: uv pip install -e ".[dev,vector]" + - run: uv run ruff check src/ tests/ + - run: uv run ruff format --check src/ tests/ + - name: Run tests (exercises the Chroma vector index path) + run: uv run --extra vector pytest -q + adapters: runs-on: ubuntu-latest strategy: diff --git a/CHANGELOG.md b/CHANGELOG.md index 10280b7..0c92bbb 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -4,6 +4,34 @@ All notable changes to HotMem will be documented in this file. Format follows [Keep a Changelog](https://keepachangelog.com/). +## [Unreleased] + +### Added — Optional derived vector index (#49) +- Pluggable vector index for search acceleration: `VectorIndex` protocol with + a no-op `NullVectorIndex` (default — HotMem runs with zero vector + dependencies) and an optional `ChromaVectorIndex` backend + (`uv pip install 'hotmem[vector]'`, lazily imported; degrades to the null + backend with a warning when chromadb is not installed). +- The index is disposable and rebuildable: SQLite, files, bundles, and + manifests remain canonical storage. Index loss never loses memory — + search falls back to the deterministic SQLite cosine+FTS scan whenever + the index is absent or stale. +- Ranking contract preserved: the index only supplies oversampled candidate + ids which are re-scored in SQLite with the identical hybrid formula + (cosine + FTS + importance), so `/v1/search` responses are identical with + or without acceleration (stores larger than the oversample window are + approximate by design; the fallback remains the correctness floor). +- Rebuild reads only SQLite rows (embeddings reused, never recomputed) — + backing files are never read; file-backed memories are indexed from + eligible inline summaries/metadata only, preserving lazy content reads. +- Rebuild marker records the store fingerprint (count, max rowid, max event + seq) for cheap staleness detection; staleness, missing dependencies, and + rebuild state are observable via `GET /v1/vector-index/status`. +- New admin endpoints: `POST /v1/vector-index/rebuild` (emits an + `index.rebuilt` event), `GET /v1/vector-index/status`, and + `DELETE /v1/vector-index` (clear). `/v1/search` response shape unchanged. +- `hotmem serve --vector-index {none,chroma}` CLI flag (default `none`). + ## [0.2.3] - 2026-08-07 ### Changed diff --git a/docs/api.md b/docs/api.md index c928f4a..81a2412 100644 --- a/docs/api.md +++ b/docs/api.md @@ -81,7 +81,46 @@ Content-Type: application/json Exports all memories to a JSONL or JSONL.GZ swap file. -## 8. OpenAPI Spec +## 8. Vector Index (optional, derived) + +The vector index is an **optional acceleration layer** — it is disposable, +rebuildable, and **never canonical storage**. SQLite, files, bundles, and +manifests remain the source of truth. Losing or deleting the index never +loses memory: search transparently falls back to the deterministic SQLite +cosine scan, and the index can be fully rebuilt from canonical storage. + +Enable it at server start (`hotmem serve --vector-index chroma`, requires the +optional `hotmem[vector]` extra). The index only supplies candidate ids; final +ranking is always recomputed with the canonical hybrid scorer, so the +`/v1/search` response shape and ranking are identical with or without +acceleration. + +```http +POST /v1/vector-index/rebuild +``` + +Rebuilds the index from SQLite rows (embeddings are reused, never recomputed). +Reads no backing files. Returns `indexed_count`, `db_count`, +`skipped_no_embedding`, `rebuilt_at`, and `trace_ms`. Returns +`400 vector_index_disabled` when no backend is configured, or +`400 vector_dependency_missing` when the backend package is not installed. +Emits an `index.rebuilt` event. + +```http +GET /v1/vector-index/status +``` + +Returns `backend`, `requested_backend`, `dependency_available`, +`indexed_count`, `db_count`, `stale`, `rebuilt_at`, `path`, and `trace_ms`. +`stale: true` means search is currently served by the deterministic fallback. + +```http +DELETE /v1/vector-index +``` + +Clears the index (entries + rebuild marker). Canonical storage is untouched. + +## 9. OpenAPI Spec Export the machine-readable spec: diff --git a/docs/architecture.md b/docs/architecture.md index 32aaada..eb7ee09 100644 --- a/docs/architecture.md +++ b/docs/architecture.md @@ -34,6 +34,13 @@ HotMem combines deterministic text embeddings, keyword overlap, and importance to rank local memories. Read-only inspectors provide lightweight metadata for CSV, JSONL, and Parquet files without turning the runtime into a query engine. +An optional derived vector index can accelerate candidate retrieval. The index +is disposable and rebuildable from SQLite, sits in front of the canonical +hybrid ranker rather than replacing it, and search falls back to the +deterministic SQLite scan whenever the index is absent or stale. SQLite, files, +bundles, and manifests remain canonical storage; the index is never a source +of truth. + ## Portability JSONL and JSONL.GZ are supported portable record formats. Snapshot v2 adds a diff --git a/pyproject.toml b/pyproject.toml index 12c70c9..83ba9dd 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -38,6 +38,9 @@ dev = [ docs = [ "mkdocs-material>=9,<10", ] +vector = [ + "chromadb>=1.0,<2", +] [project.scripts] hotmem = "hotmem.cli:main" diff --git a/src/hotmem/cli.py b/src/hotmem/cli.py index 67d6658..bf82053 100644 --- a/src/hotmem/cli.py +++ b/src/hotmem/cli.py @@ -38,7 +38,15 @@ def main(): @click.option("--mount", default=None, type=click.Path(), help="Mount directory path.") @click.option("--db", "db_path", default=None, type=click.Path(), help="Explicit database path.") @click.option("--host", default="127.0.0.1", help="Host to bind to.") -def serve(port: int, mount: str | None, db_path: str | None, host: str): +@click.option( + "--vector-index", + "vector_backend", + default="none", + type=click.Choice(["none", "chroma"]), + help="Optional derived vector index backend (default: none). The index is " + "disposable and rebuildable; SQLite remains canonical storage.", +) +def serve(port: int, mount: str | None, db_path: str | None, host: str, vector_backend: str): """Start the HotMem sidecar server.""" import uvicorn @@ -59,7 +67,12 @@ def serve(port: int, mount: str | None, db_path: str | None, host: str): detail={"path": db_path}, ) - app = create_app(db_path=db_path, swap_path=swap_path, port=port) + app = create_app( + db_path=db_path, + swap_path=swap_path, + port=port, + vector_backend=vector_backend, + ) _trace.info( "serve", diff --git a/src/hotmem/db.py b/src/hotmem/db.py index 99170ae..78eabb7 100644 --- a/src/hotmem/db.py +++ b/src/hotmem/db.py @@ -785,11 +785,11 @@ def search_with_cosine( archived_clause = "" if include_archived else " AND promotion_state != 'ARCHIVED'" rows = self._conn.execute( f"""SELECT id, identifier, fact_text, fact_summary, importance, - metadata_json, source, created_at, - cosine_sim(embedding, ?) AS cosine_score + metadata_json, source, created_at, + cosine_sim(embedding, ?) AS cosine_score FROM memories WHERE {_ttl_live()}{archived_clause} - ORDER BY cosine_score DESC""", + ORDER BY cosine_score DESC, id ASC""", (query_embedding,), ).fetchall() return [dict(r) for r in rows] @@ -822,6 +822,72 @@ def count(self) -> int: row = self._conn.execute("SELECT COUNT(*) FROM memories").fetchone() return row[0] + def fingerprint(self) -> tuple[int, int, int]: + """Return a cheap store fingerprint: (COUNT, MAX(rowid), MAX(event seq)). + + Used by the optional derived vector index (#49) to detect staleness + against its rebuild marker. The rowid component catches INSERT OR + REPLACE rewrites that a plain count comparison would miss; the event + seq component catches server-mediated mutations whose count/rowid + happen to be unchanged (rowid reuse). ``index.rebuilt`` events are + excluded — the rebuild endpoint appends its own event AFTER + snapshotting the fingerprint, and that event must not invalidate the + marker it just wrote. Pure SQL — no file I/O. + """ + row = self._conn.execute( + """SELECT (SELECT COUNT(*) FROM memories), + COALESCE((SELECT MAX(rowid) FROM memories), 0), + COALESCE( + (SELECT MAX(seq) FROM events WHERE event_type != 'index.rebuilt'), + 0)""" + ).fetchone() + return (int(row[0]), int(row[1]), int(row[2])) + + def has_unindexed_text_rows(self) -> bool: + """True when any row has searchable text but no embedding. + + Such rows (legacy imports with empty embeddings) rank via importance + in the full-scan path but cannot appear in vector-index candidates. + The accelerated search path (#49) checks this and uses the exact + full scan when such rows exist, preserving ranking parity. + """ + row = self._conn.execute( + """SELECT EXISTS(SELECT 1 FROM memories + WHERE (embedding IS NULL OR length(embedding) = 0) + AND (COALESCE(fact_text, '') != '' OR COALESCE(fact_summary, '') != ''))""" + ).fetchone() + return bool(row[0]) + + def search_by_ids( + self, + query_embedding: bytes, + memory_ids: list[str], + *, + include_archived: bool = False, + ) -> list[dict[str, Any]]: + """Return the given memories with cosine scores — same predicates as search. + + Applies the identical TTL-live and archived filters as + ``search_with_cosine``, so ids that expired, were archived, or were + deleted since indexing are filtered out here. Used by the accelerated + search path (#49) to re-score vector-index candidates in SQLite. + """ + if not memory_ids: + return [] + archived_clause = "" if include_archived else " AND promotion_state != 'ARCHIVED'" + placeholders = ", ".join("?" for _ in memory_ids) + rows = self._conn.execute( + f"""SELECT id, identifier, fact_text, fact_summary, importance, + metadata_json, source, created_at, + cosine_sim(embedding, ?) AS cosine_score + FROM memories + WHERE id IN ({placeholders}) + AND {_ttl_live()}{archived_clause} + ORDER BY cosine_score DESC, id ASC""", + (query_embedding, *memory_ids), + ).fetchall() + return [dict(r) for r in rows] + def all_rows(self, *, include_embedding: bool = False) -> list[dict[str, Any]]: """Return all memory rows as dicts (for snapshot export).""" v2_cols = ( diff --git a/src/hotmem/events.py b/src/hotmem/events.py index 18d8d8e..b45a968 100644 --- a/src/hotmem/events.py +++ b/src/hotmem/events.py @@ -62,6 +62,7 @@ class EventType: BUNDLE_DISCOVERED = "bundle.discovered" HYGIENE_CHECKED = "hygiene.checked" HYGIENE_WARNING = "hygiene.warning" + INDEX_REBUILT = "index.rebuilt" def _utc_now_iso() -> str: diff --git a/src/hotmem/search.py b/src/hotmem/search.py index f0f0b07..f2b0444 100644 --- a/src/hotmem/search.py +++ b/src/hotmem/search.py @@ -9,8 +9,14 @@ they are skipped (no searchable text). The /v1/search response shape is unchanged: each result carries role/content/memory_id/identifier/score. + An optional derived vector index (#49) may supply cosine CANDIDATES; the + same hybrid scorer always recomputes final ranking from SQLite rows, so + results are identical with or without acceleration. When the index is + absent or stale the deterministic full-scan path is used — the index is + never canonical. + Interface: - search_memories(db, query, top_k, max_chars?) -> list[MessageObject] + search_memories(db, query, top_k, max_chars?, include_archived?, vector_index?) Deps: hotmem.db, hotmem.embed, hotmem.trace Extension: add reranking, decay weighting, or MMR diversity here. @@ -18,12 +24,15 @@ from __future__ import annotations -from typing import Any +from typing import TYPE_CHECKING, Any from hotmem.db import MemoryDB from hotmem.embed import embed_text, pack_embedding from hotmem.trace import Timer, get_tracer +if TYPE_CHECKING: + from hotmem.vector_index import VectorIndex + _trace = get_tracer("search") # Scoring weights @@ -54,6 +63,53 @@ def _search_text(row: dict[str, Any]) -> str: return row.get("fact_summary") or "" +def _fetch_candidates( + db: MemoryDB, + query: str, + query_vec: list[float], + query_blob: bytes, + include_archived: bool, + vector_index: VectorIndex | None, +) -> list[dict[str, Any]]: + """Return candidate rows with cosine scores for hybrid ranking. + + Default (no index / stale index / empty result): the deterministic + full-table scan via ``db.search_with_cosine`` — identical to the + pre-#49 behavior. + + Accelerated (fresh index): the index supplies oversampled cosine + candidate ids; those ids are re-fetched and re-scored in SQLite with the + same TTL-live/archived predicates, unioned with FTS match ids so text-only + matches are never lost. Ranking is recomputed downstream either way, so + both paths produce identical results. + """ + if ( + vector_index is not None + and not vector_index.is_stale(db) + # Rows with searchable text but no embedding rank via importance in + # the full scan but can never be vector candidates — use the exact + # scan while any exist so ranking parity is preserved. + and not db.has_unindexed_text_rows() + ): + try: + hits = vector_index.search(query_vec, top_k=vector_index.oversample()) + except Exception: # index is disposable; never let it fail search + _trace.warn("candidates", "vector index search failed; falling back to scan") + hits = [] + if hits: + candidate_ids = [h["id"] for h in hits] + fts_rows = db.fts_search(query, include_archived=include_archived) + candidate_ids += [r["id"] for r in fts_rows] + # Dedupe, preserving order (index ranking first, FTS additions after). + seen: set[str] = set() + unique_ids = [i for i in candidate_ids if not (i in seen or seen.add(i))] + rows = db.search_by_ids(query_blob, unique_ids, include_archived=include_archived) + # Rows re-fetched by id already carry canonical cosine scores from + # the SQLite UDF — the index's own scores are advisory only. + return rows + return db.search_with_cosine(query_blob, include_archived=include_archived) + + def search_memories( db: MemoryDB, query: str, @@ -61,12 +117,18 @@ def search_memories( max_chars: int | None = None, *, include_archived: bool = False, + vector_index: VectorIndex | None = None, ) -> list[dict[str, Any]]: """Search memories and return ranked, LLM-ready message objects. Archived memories are excluded by default; pass ``include_archived=True`` for audit/full profiles. + When ``vector_index`` is provided and not stale, it supplies cosine + candidates (oversampled) which are re-scored in SQLite with the identical + hybrid formula — the response shape and ranking are byte-identical to the + fallback. Otherwise the deterministic full-scan path runs unchanged. + Returns: List of dicts with keys: role, content, memory_id, identifier, score """ @@ -75,8 +137,9 @@ def search_memories( query_vec = embed_text(query) query_blob = pack_embedding(query_vec) - # Get all candidates with cosine scores from DB - candidates = db.search_with_cosine(query_blob, include_archived=include_archived) + candidates = _fetch_candidates( + db, query, query_vec, query_blob, include_archived, vector_index + ) fts_scores = _normalize_bm25(db.fts_search(query, include_archived=include_archived)) # Apply hybrid scoring diff --git a/src/hotmem/server.py b/src/hotmem/server.py index 0c47706..90af51e 100644 --- a/src/hotmem/server.py +++ b/src/hotmem/server.py @@ -51,6 +51,14 @@ from hotmem.storage import UnsupportedSchemeError from hotmem.swap import compute_content_hash from hotmem.trace import Timer, get_tracer, new_trace_id +from hotmem.vector_index import ( + VALID_BACKENDS, + NullVectorIndex, + VectorIndex, + VectorIndexConfig, + get_vector_index, + rebuild_vector_index, +) _trace = get_tracer("server") @@ -213,6 +221,16 @@ async def lifespan(app: FastAPI): _state["db"] = db _state["start_time"] = time.time() + # Optional derived vector index (#49): disposable acceleration only — + # constructed after the DB, closed before it. Never canonical. + if _state.get("vector_index_injected") is None: + _state["vector_index"] = get_vector_index( + VectorIndexConfig(backend=_state.get("vector_backend", "none")), + base_dir=_state.get("base_dir"), + ) + else: + _state["vector_index"] = _state["vector_index_injected"] + # Auto-hydrate if swap file exists if swap_path and Path(swap_path).exists(): result = snapshot_hydrate(db, swap_path) @@ -234,6 +252,7 @@ async def lifespan(app: FastAPI): detail={"db_path": str(db_path), "port": _state.get("port", 8711)}, ) yield + _state["vector_index"].close() db.close() @@ -245,15 +264,32 @@ def create_app( swap_path: str | Path | None = None, port: int = 8711, base_dir: str | Path | None = None, + vector_backend: str = "none", + vector_index: VectorIndex | None = None, ) -> FastAPI: """Create and configure the FastAPI application. ``base_dir`` resolves relative file_ref URIs. Defaults to the parent directory of ``db_path`` (i.e. the mount dir). + + ``vector_backend`` selects the optional derived vector index (#49): + "none" (default — zero vector dependencies) or "chroma" (requires the + optional ``hotmem[vector]`` extra; degrades to none with a warning when + chromadb is not installed). The index is disposable and rebuildable — + SQLite/files/bundles remain canonical storage. + + ``vector_index`` injects a prebuilt index instance (test seam); it takes + precedence over ``vector_backend``. """ + if vector_backend not in VALID_BACKENDS: + raise ValueError( + f"unknown vector_backend {vector_backend!r}; expected one of {VALID_BACKENDS}" + ) _state["db_path"] = str(db_path) _state["swap_path"] = str(swap_path) if swap_path else None _state["port"] = port + _state["vector_backend"] = vector_backend + _state["vector_index_injected"] = vector_index if base_dir is None: base_dir = str(Path(db_path).resolve().parent) _state["base_dir"] = str(base_dir) @@ -390,9 +426,14 @@ async def add_memory(req: AddRequest): @app.post("/v1/search") async def search(req: SearchRequest): db: MemoryDB = _state["db"] + vector_index: VectorIndex = _state["vector_index"] with Timer() as t: messages = search_memories( - db, query=req.query, top_k=req.top_k, max_chars=req.max_chars + db, + query=req.query, + top_k=req.top_k, + max_chars=req.max_chars, + vector_index=vector_index, ) return { "memories": messages, @@ -915,4 +956,91 @@ async def promotion_by_state( "trace_ms": round(t.ms, 2), } + # ── Vector index endpoints (#49 — optional, derived, disposable) ──── + + @app.post("/v1/vector-index/rebuild") + async def rebuild_index(): + """Full rebuild of the derived vector index from canonical storage. + + Reads only SQLite rows (metadata + embeddings) — never touches a + backing file. Returns 400 ``vector_index_disabled`` when no backend + is configured (the default). This is an admin operation, never on + the search hot path; stale indexes fall back to the SQLite scan. + """ + import asyncio + + db: MemoryDB = _state["db"] + vector_index: VectorIndex = _state["vector_index"] + if isinstance(vector_index, NullVectorIndex): + if vector_index.requested_backend == "none": + error = { + "error": "vector_index_disabled", + "message": ( + "no vector index backend is configured; start with " + "--vector-index chroma to enable the derived index" + ), + } + else: + error = { + "error": "vector_dependency_missing", + "requested_backend": vector_index.requested_backend, + "message": ( + f"backend {vector_index.requested_backend!r} was requested but its " + "package is not installed; install with: " + "uv pip install 'hotmem[vector]'" + ), + } + return JSONResponse(status_code=400, content=error) + result = await asyncio.to_thread( + rebuild_vector_index, + db, + vector_index, + embedding_model=EMBEDDING_MODEL, + embedding_dim=EMBEDDING_DIM, + ) + append_event( + db, + event_type=EventType.INDEX_REBUILT, + payload={ + "backend": vector_index.status(db)["backend"], + "indexed_count": result["indexed_count"], + "db_count": result["db_count"], + "skipped_no_embedding": result["skipped_no_embedding"], + }, + ) + return result + + @app.get("/v1/vector-index/status") + async def vector_index_status(): + """Observability for the derived index: backend, counts, staleness. + + ``stale: true`` means search is currently served by the deterministic + SQLite fallback (the index is never required for correctness). + """ + db: MemoryDB = _state["db"] + vector_index: VectorIndex = _state["vector_index"] + with Timer() as t: + status = vector_index.status(db) + status["trace_ms"] = round(t.ms, 2) + return status + + @app.delete("/v1/vector-index") + async def clear_index(): + """Clear the derived index (entries + rebuild marker). + + The index is disposable: clearing it never loses memory — canonical + storage is untouched and search falls back to the SQLite scan until + the next rebuild. + """ + db: MemoryDB = _state["db"] + vector_index: VectorIndex = _state["vector_index"] + with Timer() as t: + vector_index.clear() + cleared_count = db.count() # canonical store is the survivor + return { + "cleared": True, + "db_count": cleared_count, + "trace_ms": round(t.ms, 2), + } + return app diff --git a/src/hotmem/vector_index.py b/src/hotmem/vector_index.py new file mode 100644 index 0000000..ca42790 --- /dev/null +++ b/src/hotmem/vector_index.py @@ -0,0 +1,507 @@ +"""HotMem vector index — optional, derived, disposable retrieval acceleration. + +Purpose: + Provide an optional derived vector index in front of the canonical + cosine+FTS search path. SQLite/files/bundles/manifests remain canonical: + the index is disposable, rebuildable, and NEVER a source of truth. + Losing or deleting the index never loses memory — search transparently + falls back to the deterministic SQLite scan. + + The index only supplies CANDIDATE ids; ranking is always recomputed by + the canonical hybrid scorer (cosine + FTS + importance) so the response + shape and ranking contract are identical with or without acceleration. + +Interface: + VectorIndexConfig(backend="none", oversample=1000) + VectorIndex (Protocol): upsert/search/delete/is_stale/status/close/clear + NullVectorIndex — no-op backend (default; forces fallback) + ChromaVectorIndex — optional Chroma-backed index (lazy import) + get_vector_index(config, base_dir) -> VectorIndex + rebuild_vector_index(db, index) -> dict + db_fingerprint(db) -> tuple[int, int, int] + +Deps: hotmem.db, hotmem.trace (chromadb is optional — [vector] extra) +Extension: add new backends by implementing the VectorIndex Protocol. +""" + +from __future__ import annotations + +import json +import shutil +from dataclasses import dataclass +from pathlib import Path +from typing import Any, Protocol, runtime_checkable + +from hotmem.trace import Timer, get_tracer + +_trace = get_tracer("vector_index") + +# Directory name for the derived index inside the mount/base dir. +INDEX_DIR_NAME = "hotmem-vector-index" +# Rebuild marker file name inside the index directory. +REBUILD_MARKER_NAME = "rebuild_marker.json" +# Default candidate oversampling for the accelerated path. +DEFAULT_OVERSAMPLE = 1000 +# Batch size for upserts during rebuild. +UPSERT_BATCH = 500 + +VALID_BACKENDS = ("none", "chroma") + + +@dataclass(frozen=True) +class VectorIndexConfig: + """Configuration for the optional derived vector index.""" + + backend: str = "none" + oversample: int = DEFAULT_OVERSAMPLE + + def __post_init__(self) -> None: + if self.backend not in VALID_BACKENDS: + raise ValueError( + f"unknown vector index backend {self.backend!r}; expected one of {VALID_BACKENDS}" + ) + if self.oversample < 1: + raise ValueError("oversample must be >= 1") + + +def db_fingerprint(db: Any) -> tuple[int, ...]: + """Cheap canonical-store fingerprint: (COUNT, MAX(rowid), MAX(event seq)). + + Detects inserts, deletes, INSERT OR REPLACE rewrites, and server-mediated + mutations whose count/rowid happen to be unchanged (rowid reuse). Pure + SQL — no file I/O. + """ + return db.fingerprint() + + +@runtime_checkable +class VectorIndex(Protocol): + """Protocol for derived vector index backends. + + Implementations hold NO canonical data: every method must be safe to + no-op or fail — search then falls back to the SQLite cosine scan. + """ + + def upsert(self, records: list[dict[str, Any]]) -> None: + """Upsert records: {id, embedding (list[float]), metadata (dict)}.""" + ... + + def search(self, query_embedding: list[float], top_k: int) -> list[dict[str, Any]]: + """Return ranked hits: [{id, cosine_score}] best-first.""" + ... + + def delete(self, memory_ids: list[str]) -> None: + """Remove entries for the given memory ids.""" + ... + + def count(self) -> int: + """Return the number of indexed entries.""" + ... + + def oversample(self) -> int: + """Candidate batch size for the accelerated search path. + + When the store has at most this many rows the accelerated path is + exact (every row is a candidate); larger stores are approximate by + design — the canonical fallback remains the correctness floor. + """ + ... + + def is_stale(self, db: Any) -> bool: + """True when the index does not match the canonical store fingerprint.""" + ... + + def apply_rebuild_marker(self, marker: dict[str, Any]) -> None: + """Record the rebuild marker (store fingerprint at rebuild time).""" + ... + + def status(self, db: Any) -> dict[str, Any]: + """Observability snapshot: backend, counts, staleness, rebuild marker.""" + ... + + def clear(self) -> None: + """Remove all indexed entries and the rebuild marker (index stays usable).""" + ... + + def close(self) -> None: + """Release backend resources.""" + ... + + +class _MarkerMixin: + """Shared rebuild-marker persistence for filesystem-backed index backends.""" + + marker_path: Path + + def apply_rebuild_marker(self, marker: dict[str, Any]) -> None: + self._write_marker(marker) + + def _read_marker(self) -> dict[str, Any] | None: + try: + return json.loads(self.marker_path.read_text()) + except (OSError, json.JSONDecodeError): + return None + + def _write_marker(self, marker: dict[str, Any]) -> None: + self.marker_path.parent.mkdir(parents=True, exist_ok=True) + self.marker_path.write_text(json.dumps(marker, indent=2, sort_keys=True) + "\n") + + def _delete_marker(self) -> None: + with _suppress_oserror(): + self.marker_path.unlink() + + def _stale_vs_marker(self, db: Any) -> bool: + marker = self._read_marker() + if marker is None: + return True + try: + return db_fingerprint(db) != ( + marker.get("db_count"), + marker.get("max_rowid"), + marker.get("max_event_seq"), + ) + except (TypeError, AttributeError): + return True + + +class NullVectorIndex(_MarkerMixin): + """No-op index: search returns [], forcing deterministic SQLite fallback. + + Used when no backend is configured (the default — HotMem runs with zero + vector dependencies) or when an optional backend is requested but its + package is not installed. + """ + + def __init__( + self, + requested_backend: str = "none", + base_dir: str | Path | None = None, + oversample: int = DEFAULT_OVERSAMPLE, + ) -> None: + self.requested_backend = requested_backend + self.base_dir = base_dir + self._oversample = oversample + if base_dir is not None: + self.marker_path = Path(base_dir) / INDEX_DIR_NAME / REBUILD_MARKER_NAME + else: # markerless null index (direct library use only) + self.marker_path = Path("/dev/null/hotmem-null-index") / REBUILD_MARKER_NAME + + def upsert(self, records: list[dict[str, Any]]) -> None: + return None + + def search(self, query_embedding: list[float], top_k: int) -> list[dict[str, Any]]: + return [] + + def delete(self, memory_ids: list[str]) -> None: + return None + + def count(self) -> int: + return 0 + + def oversample(self) -> int: + return self._oversample + + def is_stale(self, db: Any) -> bool: + return True + + def status(self, db: Any) -> dict[str, Any]: + return { + "backend": "none", + "requested_backend": self.requested_backend, + "dependency_available": self.requested_backend == "none", + "indexed_count": 0, + "db_count": db.count(), + "stale": True, + "rebuilt_at": None, + "path": str(self.marker_path.parent) if self.base_dir is not None else None, + } + + def clear(self) -> None: + self._delete_marker() + + def close(self) -> None: + return None + + +class ChromaVectorIndex(_MarkerMixin): + """Chroma-backed derived index (optional [vector] extra). + + Persists under ``/hotmem-vector-index/``. Embeddings are reused + from canonical SQLite rows (same dims/model) — never recomputed. The + collection carries only id + embedding + light metadata; deleting the + directory loses nothing that cannot be rebuilt from SQLite. + """ + + def __init__(self, base_dir: str | Path, oversample: int = DEFAULT_OVERSAMPLE) -> None: + try: + import chromadb + except ImportError as err: + raise ImportError( + "ChromaVectorIndex requires chromadb. " + "Install it with: uv pip install 'hotmem[vector]'" + ) from err + + self.base_dir = Path(base_dir) + self.index_path = self.base_dir / INDEX_DIR_NAME + self.marker_path = self.index_path / REBUILD_MARKER_NAME + self._oversample = oversample + self._client = chromadb.PersistentClient(path=str(self.index_path)) + self._collection = self._client.get_or_create_collection( + name="hotmem_memories", + metadata={"hnsw:space": "cosine"}, + ) + _trace.info("init", "chroma vector index opened", detail={"path": str(self.index_path)}) + + def upsert(self, records: list[dict[str, Any]]) -> None: + if not records: + return + for start in range(0, len(records), UPSERT_BATCH): + batch = records[start : start + UPSERT_BATCH] + self._collection.upsert( + ids=[r["id"] for r in batch], + embeddings=[r["embedding"] for r in batch], + metadatas=[self._sanitize(r.get("metadata") or {}) for r in batch], + ) + + def search(self, query_embedding: list[float], top_k: int) -> list[dict[str, Any]]: + if top_k < 1 or self._collection.count() == 0: + return [] + result = self._collection.query( + query_embeddings=[query_embedding], + n_results=min(top_k, self._collection.count()), + include=["distances"], + ) + ids = (result.get("ids") or [[]])[0] + distances = (result.get("distances") or [[]])[0] + hits = [] + for mid, dist in zip(ids, distances, strict=False): + cosine = 1.0 - float(dist) if dist is not None else 0.0 + hits.append({"id": mid, "cosine_score": max(0.0, min(1.0, cosine))}) + return hits + + def delete(self, memory_ids: list[str]) -> None: + if not memory_ids: + return + with _suppress_exception(Exception): + self._collection.delete(ids=list(memory_ids)) + + def count(self) -> int: + return int(self._collection.count()) + + def oversample(self) -> int: + return self._oversample + + def is_stale(self, db: Any) -> bool: + return self._stale_vs_marker(db) + + def status(self, db: Any) -> dict[str, Any]: + marker = self._read_marker() or {} + fingerprint = db_fingerprint(db) + stale = self._stale_vs_marker(db) + return { + "backend": "chroma", + "requested_backend": "chroma", + "dependency_available": True, + "indexed_count": self.count(), + "db_count": fingerprint[0], + "stale": stale, + "rebuilt_at": marker.get("rebuilt_at"), + "path": str(self.index_path), + } + + def clear(self) -> None: + with _suppress_exception(Exception): + self._client.delete_collection("hotmem_memories") + self._collection = self._client.get_or_create_collection( + name="hotmem_memories", + metadata={"hnsw:space": "cosine"}, + ) + self._delete_marker() + _trace.info("clear", "vector index cleared") + + def close(self) -> None: + return None + + @staticmethod + def _sanitize(metadata: dict[str, Any]) -> dict[str, Any]: + """Keep metadata flat, non-null, and primitive-typed for Chroma.""" + clean = {} + for key in ("identifier", "memory_type", "promotion_state"): + value = metadata.get(key) + if value is not None: + clean[key] = str(value) + return clean or {"identifier": ""} + + +class _suppress_oserror: + """Context manager that swallows OSError (marker best-effort cleanup).""" + + def __enter__(self) -> _suppress_oserror: + return self + + def __exit__(self, exc_type, exc, tb) -> bool: + return exc_type is not None and issubclass(exc_type, OSError) + + +class _suppress_exception: + """Context manager that swallows a given exception type.""" + + def __init__(self, exc_type: type[BaseException]) -> None: + self.exc_type = exc_type + + def __enter__(self) -> _suppress_exception: + return self + + def __exit__(self, exc_type, exc, tb) -> bool: + return exc_type is not None and issubclass(exc_type, self.exc_type) + + +def chroma_available() -> bool: + """True when the optional chromadb package is importable.""" + try: + import chromadb # noqa: F401 + except ImportError: + return False + return True + + +def get_vector_index( + config: VectorIndexConfig | None, + base_dir: str | Path | None = None, +) -> VectorIndex: + """Factory: build a VectorIndex from config, degrading to Null safely. + + ``backend="none"`` (or ``config=None``) → NullVectorIndex — no vector + dependency is ever imported. ``backend="chroma"`` → ChromaVectorIndex; + when chromadb is not installed the factory warns and returns a Null + index tagged with the requested backend (observable via status()). + """ + if config is None: + config = VectorIndexConfig() + if config.backend == "none": + return NullVectorIndex( + requested_backend="none", base_dir=base_dir, oversample=config.oversample + ) + if config.backend == "chroma": + if not chroma_available(): + _trace.warn( + "factory", + "chromadb is not installed; falling back to NullVectorIndex " + "(search will use the SQLite cosine scan)", + detail={"requested_backend": "chroma"}, + ) + return NullVectorIndex( + requested_backend="chroma", base_dir=base_dir, oversample=config.oversample + ) + if base_dir is None: + raise ValueError("base_dir is required for the chroma vector index backend") + return ChromaVectorIndex(base_dir=base_dir, oversample=config.oversample) + raise ValueError(f"unknown vector index backend {config.backend!r}") + + +def rebuild_vector_index( + db: Any, + index: VectorIndex, + *, + embedding_model: str = "", + embedding_dim: int = 0, +) -> dict[str, Any]: + """Full rebuild of the derived index from canonical SQLite storage. + + Reads memory rows (including embeddings) via ``db.all_rows`` — a pure SQL + read that NEVER touches the storage adapter or any backing file. Rows + without an embedding (file-backed memories without a summary) are skipped; + they are excluded from cosine search by design and remain fully retrievable + via get/hydrate and (for those with text) FTS. + + The rebuild marker records the store fingerprint at rebuild time so + staleness is a cheap comparison, not a per-row checksum. + """ + import datetime as _dt + + with Timer() as t: + if isinstance(index, NullVectorIndex): + # No-op backend: nothing to index and no marker to write. + fingerprint = db_fingerprint(db) + return { + "indexed_count": 0, + "db_count": fingerprint[0], + "skipped_no_embedding": fingerprint[0], + "rebuilt_at": _dt.datetime.now(_dt.UTC).strftime("%Y-%m-%dT%H:%M:%SZ"), + "trace_ms": round(t.ms, 2), + } + + index.clear() + rows = db.all_rows(include_embedding=True) + records = [] + indexed = 0 + for row in rows: + blob = row.get("embedding") + if not blob: + continue + embedding = _unpack_blob(blob) + if not embedding: + continue + records.append( + { + "id": row["id"], + "embedding": embedding, + "metadata": { + "identifier": row.get("identifier") or "", + "memory_type": row.get("memory_type") or "", + "promotion_state": row.get("promotion_state") or "", + }, + } + ) + indexed += 1 + if len(records) >= UPSERT_BATCH: + index.upsert(records) + records = [] + if records: + index.upsert(records) + + fingerprint = db_fingerprint(db) + marker = { + "db_count": fingerprint[0], + "max_rowid": fingerprint[1], + "max_event_seq": fingerprint[2], + "indexed_count": indexed, + "embedding_model": embedding_model, + "embedding_dim": embedding_dim, + "rebuilt_at": _dt.datetime.now(_dt.UTC).strftime("%Y-%m-%dT%H:%M:%SZ"), + } + index.apply_rebuild_marker(marker) + + result = { + "indexed_count": indexed, + "db_count": fingerprint[0], + "skipped_no_embedding": fingerprint[0] - indexed, + "rebuilt_at": marker["rebuilt_at"], + "trace_ms": round(t.ms, 2), + } + _trace.info("rebuild", "vector index rebuilt from canonical storage", detail=result) + return result + + +def _unpack_blob(blob: bytes) -> list[float]: + import struct + + count = len(blob) // 4 + if count == 0: + return [] + return list(struct.unpack(f"{count}f", blob)) + + +def remove_index_directory(base_dir: str | Path) -> bool: + """Delete the entire derived index directory (files only, never SQLite). + + Returns True when something was removed. The index is disposable: removal + never loses memory — canonical storage is untouched and search falls back + to the SQLite scan until the next rebuild. + """ + index_dir = Path(base_dir) / INDEX_DIR_NAME + if index_dir.exists(): + shutil.rmtree(index_dir) + _trace.info("remove", "vector index directory removed", detail={"path": str(index_dir)}) + return True + return False diff --git a/tests/golden/test_golden_additive.py b/tests/golden/test_golden_additive.py index cdc1f13..2dbb03f 100644 --- a/tests/golden/test_golden_additive.py +++ b/tests/golden/test_golden_additive.py @@ -118,3 +118,50 @@ def test_v2_provenance_columns_are_optional_and_defaulted(client, tmp_path): assert first["byte_length"] is None assert first["tier"] == "hot" assert first["schema_version"] == 1 + + +def test_search_identical_with_and_without_vector_acceleration(tmp_path): + """#49: enabling the derived vector index must not change search results. + + The same store is searched through the default app (null index — + deterministic SQLite scan) and through an accelerated app whose index was + rebuilt from canonical storage. Ids, ordering, scores, and the response + shape must be exactly equal: the index accelerates candidate retrieval, + it is not an alternate ranking contract. + """ + from test_vector_index import FakeVectorIndex + + facts = [ + "duplicate invoice risk for vendor x", + "payment terms are net 30 days", + "invoice validation requires a PO number", + ] + query = {"query": "invoice", "top_k": 3} + + # Baseline: default app, no vector backend (the pre-#49 behavior). + baseline_app = create_app(db_path=tmp_path / "plain.sqlite") + with TestClient(baseline_app) as c: + for i, fact in enumerate(facts): + c.post("/v1/add", json={"identifier": "v", "fact": fact, "importance": 0.5 + i / 10}) + baseline = c.post("/v1/search", json=query).json() + + # Accelerated: same seed, rebuilt derived index. + index = FakeVectorIndex() + accelerated_app = create_app( + db_path=tmp_path / "accel.sqlite", vector_backend="chroma", vector_index=index + ) + with TestClient(accelerated_app) as c: + for i, fact in enumerate(facts): + c.post("/v1/add", json={"identifier": "v", "fact": fact, "importance": 0.5 + i / 10}) + rebuilt = c.post("/v1/vector-index/rebuild").json() + assert rebuilt["indexed_count"] == len(facts) + assert c.get("/v1/vector-index/status").json()["stale"] is False + accelerated = c.post("/v1/search", json=query).json() + + # Shape is the locked golden search shape; ranking is exactly equal. + # (memory_ids are per-store UUIDs, so compare scores/content/order.) + assert mask(accelerated) == mask(baseline) + assert [(m["score"], m["content"]) for m in accelerated["memories"]] == [ + (m["score"], m["content"]) for m in baseline["memories"] + ] + assert accelerated["count"] == baseline["count"] == len(facts) diff --git a/tests/test_vector_index.py b/tests/test_vector_index.py new file mode 100644 index 0000000..1446362 --- /dev/null +++ b/tests/test_vector_index.py @@ -0,0 +1,657 @@ +"""Tests for #49 — optional derived vector index. + +Covers the required cases from the issue: + 1. HotMem runs with no vector backend installed (NullVectorIndex default). + 2. Index rebuildable from canonical storage (rebuild parity). + 3. Search fallback when index absent (directory deleted). + 4. Search fallback when index stale. + 5. Index loss does not lose memory (SQLite remains canonical). + 6. Default behavior unchanged (no config → identical results). + 7. Large referenced files are NOT eagerly read for indexing. + 8. Deterministic fallback-search behavior. + 9. ChromaVectorIndex path (import-guarded; skipped when chromadb absent). +""" + +from __future__ import annotations + +import math +from pathlib import Path +from typing import Any + +import pytest +from fastapi.testclient import TestClient + +from hotmem.db import MemoryDB +from hotmem.embed import embed_text, pack_embedding +from hotmem.memory import FileRef, add_file_backed +from hotmem.search import search_memories +from hotmem.vector_index import ( + ChromaVectorIndex, + NullVectorIndex, + VectorIndexConfig, + db_fingerprint, + get_vector_index, + rebuild_vector_index, + remove_index_directory, +) + +# ── Test double: faithful in-memory index ──────────────────────────────────── + + +class FakeVectorIndex: + """In-memory VectorIndex implementing the protocol exactly. + + Uses exact cosine over all stored vectors (no approximation) and the + same fingerprint/marker staleness contract as the real backends. + """ + + def __init__(self) -> None: + self.vectors: dict[str, list[float]] = {} + self.metadata: dict[str, dict[str, Any]] = {} + self.marker: tuple[int, ...] | None = None + self.upsert_calls = 0 + + def upsert(self, records: list[dict[str, Any]]) -> None: + self.upsert_calls += 1 + for r in records: + self.vectors[r["id"]] = list(r["embedding"]) + self.metadata[r["id"]] = dict(r.get("metadata") or {}) + + def apply_rebuild_marker(self, marker: dict[str, Any]) -> None: + self.marker = (marker["db_count"], marker["max_rowid"], marker["max_event_seq"]) + self.rebuilt_at = marker.get("rebuilt_at") + + def search(self, query_embedding: list[float], top_k: int) -> list[dict[str, Any]]: + scored = [] + for mid, vec in self.vectors.items(): + dot = sum(a * b for a, b in zip(query_embedding, vec, strict=True)) + na = math.sqrt(sum(a * a for a in query_embedding)) + nb = math.sqrt(sum(b * b for b in vec)) + cosine = dot / (na * nb) if na and nb else 0.0 + scored.append({"id": mid, "cosine_score": cosine}) + scored.sort(key=lambda h: (-h["cosine_score"], h["id"])) + return scored[:top_k] + + def delete(self, memory_ids: list[str]) -> None: + for mid in memory_ids: + self.vectors.pop(mid, None) + self.metadata.pop(mid, None) + + def count(self) -> int: + return len(self.vectors) + + def oversample(self) -> int: + return 1000 + + def is_stale(self, db: MemoryDB) -> bool: + return self.marker != db_fingerprint(db) + + def status(self, db: MemoryDB) -> dict[str, Any]: + return { + "backend": "fake", + "requested_backend": "fake", + "dependency_available": True, + "indexed_count": self.count(), + "db_count": db.count(), + "stale": self.is_stale(db), + "rebuilt_at": None, + "path": None, + } + + def clear(self) -> None: + self.vectors.clear() + self.metadata.clear() + self.marker = None + + def close(self) -> None: + return None + + +# ── Seed helpers ───────────────────────────────────────────────────────────── + + +def _add_fact( + db: MemoryDB, + id: str, + text: str, + importance: float = 0.5, + **kwargs: Any, +) -> None: + vec = embed_text(text) + db.insert( + id=id, + identifier="test", + fact_text=text, + embedding=pack_embedding(vec), + importance=importance, + **kwargs, + ) + + +def _add_file_backed( + db: MemoryDB, + id: str, + uri: str, + *, + summary: str | None = None, +) -> str: + Path(uri).parent.mkdir(parents=True, exist_ok=True) + Path(uri).write_bytes(b"0123456789") # ensure the backing file exists (stat check) + ref = FileRef(source_uri=uri, byte_offset=0, byte_length=10, source_format="bin") + memory_id, _ = add_file_backed( + db, + identifier="test", + file_ref=ref, + base_dir=None, + summary=summary, + ) + return memory_id + + +def _seed_store(db: MemoryDB) -> None: + """Mixed seeds: inline facts, file-backed w/ + w/o summary, archived, TTL-dead.""" + base = Path(db.db_path).parent + _add_fact(db, "f1", "invoice validation rules for vendor x", importance=0.9) + _add_fact(db, "f2", "payment terms are net 30 days", importance=0.1) + _add_fact(db, "f3", "duplicate invoice risk mitigation", importance=0.5) + _add_fact(db, "arch", "archived invoice policy", promotion_state="ARCHIVED") + _add_fact( + db, + "expired", + "expired invoice memory", + ttl_seconds=1, + created_at="2000-01-01T00:00:00Z", + ) + _add_file_backed(db, "fs1", str(base / "seed-1.bin"), summary="Q3 revenue summary data") + _add_file_backed(db, "fs2", str(base / "seed-2.bin"), summary=None) + + +def _messages(results: list[dict[str, Any]]) -> list[tuple[str, float]]: + return [(r["memory_id"], r["score"]) for r in results] + + +# ── 1. Default: no backend, no vector dependency ───────────────────────────── + + +def test_default_backend_is_null_no_chroma_import(tmp_path: Path): + index = get_vector_index(None, base_dir=tmp_path) + assert isinstance(index, NullVectorIndex) + assert index.requested_backend == "none" + # Subprocess: prove the default path never imports chromadb even when it + # IS installed (isolation from this session's already-imported modules). + import subprocess + import sys + + code = ( + "import sys; " + "from hotmem.vector_index import get_vector_index, VectorIndexConfig; " + f"idx = get_vector_index(VectorIndexConfig(backend='none'), base_dir={str(tmp_path)!r}); " + "assert idx.search([0.0], top_k=1) == []; " + "assert 'chromadb' not in sys.modules, 'default backend must not import chromadb'; " + "print('ok')" + ) + result = subprocess.run( + [sys.executable, "-c", code], capture_output=True, text=True, timeout=60 + ) + assert result.returncode == 0, result.stderr + assert result.stdout.strip() == "ok" + + +def test_null_index_search_returns_empty_and_is_stale(tmp_db: MemoryDB, tmp_path: Path): + _add_fact(tmp_db, "1", "hello world") + index = get_vector_index(None, base_dir=tmp_path) + assert index.search(embed_text("hello"), top_k=5) == [] + assert index.is_stale(tmp_db) is True + assert index.count() == 0 + + +def test_config_rejects_unknown_backend(): + with pytest.raises(ValueError, match="unknown vector index backend"): + VectorIndexConfig(backend="qdrant") + + +def test_search_with_null_index_equals_plain_search(tmp_db: MemoryDB, tmp_path: Path): + _seed_store(tmp_db) + index = get_vector_index(None, base_dir=tmp_path) + plain = search_memories(tmp_db, "invoice", top_k=5) + with_null = search_memories(tmp_db, "invoice", top_k=5, vector_index=index) + assert _messages(plain) == _messages(with_null) + + +# ── 2. Rebuild parity ──────────────────────────────────────────────────────── + + +def test_rebuild_indexes_rows_with_embeddings_only(tmp_db: MemoryDB): + _seed_store(tmp_db) + index = FakeVectorIndex() + result = rebuild_vector_index(tmp_db, index) + + # f1..f3 + arch + expired (expired still has an embedding; TTL applies at + # query time) + fs1 (summary embedding). fs2 has no summary -> no embedding. + assert result["indexed_count"] == 6 + assert result["db_count"] == 7 + assert result["skipped_no_embedding"] == 1 + assert index.count() == 6 + assert index.is_stale(tmp_db) is False + + +def test_rebuild_parity_accelerated_equals_fallback(tmp_db: MemoryDB): + _seed_store(tmp_db) + index = FakeVectorIndex() + rebuild_vector_index(tmp_db, index) + + for query in ("invoice", "payment terms", "duplicate invoice risk", "Q3 revenue", "zzz"): + fallback = search_memories(tmp_db, query, top_k=5) + accelerated = search_memories(tmp_db, query, top_k=5, vector_index=index) + assert _messages(fallback) == _messages(accelerated), f"parity broke for {query!r}" + + +def test_rebuild_parity_includes_archived_when_requested(tmp_db: MemoryDB): + _seed_store(tmp_db) + index = FakeVectorIndex() + rebuild_vector_index(tmp_db, index) + + fallback = search_memories(tmp_db, "invoice policy", top_k=5, include_archived=True) + accelerated = search_memories( + tmp_db, "invoice policy", top_k=5, include_archived=True, vector_index=index + ) + assert _messages(fallback) == _messages(accelerated) + assert "arch" in [m[0] for m in _messages(accelerated)] + + +def test_rebuild_on_null_index_is_noop(tmp_db: MemoryDB, tmp_path: Path): + _add_fact(tmp_db, "1", "hello") + index = get_vector_index(None, base_dir=tmp_path) + result = rebuild_vector_index(tmp_db, index) + assert result["indexed_count"] == 0 + assert result["db_count"] == 1 + + +# ── 3. Stale index -> fallback ─────────────────────────────────────────────── + + +def test_stale_index_falls_back_and_still_finds_new_memory(tmp_db: MemoryDB): + _seed_store(tmp_db) + index = FakeVectorIndex() + rebuild_vector_index(tmp_db, index) + + # Mutate canonical storage without updating the index. + _add_fact(tmp_db, "new", "fresh invoice fact after rebuild") + + assert index.is_stale(tmp_db) is True + results = search_memories(tmp_db, "fresh invoice", top_k=3, vector_index=index) + assert results[0]["memory_id"] == "new" + + +def test_fingerprint_changes_on_mutation(tmp_db: MemoryDB): + _add_fact(tmp_db, "1", "one") + before = db_fingerprint(tmp_db) + _add_fact(tmp_db, "2", "two") + assert db_fingerprint(tmp_db) != before + + +def test_index_search_failure_falls_back(tmp_db: MemoryDB): + _add_fact(tmp_db, "1", "invoice validation") + + class ExplodingIndex(FakeVectorIndex): + def search(self, query_embedding, top_k): # type: ignore[no-untyped-def] + raise RuntimeError("index backend exploded") + + index = ExplodingIndex() + index.marker = db_fingerprint(tmp_db) # fresh, so the search path is taken + index.upsert([{"id": "1", "embedding": embed_text("invoice validation"), "metadata": {}}]) + assert index.is_stale(tmp_db) is False + results = search_memories(tmp_db, "invoice", top_k=3, vector_index=index) + assert results[0]["memory_id"] == "1" + + +# ── 4/5. Index loss never loses memory ─────────────────────────────────────── + + +def test_missing_index_directory_search_still_works(tmp_db: MemoryDB, tmp_path: Path): + _seed_store(tmp_db) + config = VectorIndexConfig(backend="chroma") + # When chromadb is absent the factory degrades to Null; when present the + # index directory does not exist yet. Either way search must work — + # the index is optional and never required for correctness. + index = get_vector_index(config, base_dir=tmp_path) + assert index.is_stale(tmp_db) is True # nothing rebuilt yet + results = search_memories(tmp_db, "invoice", top_k=5, vector_index=index) + assert results, "search must work when the index is absent" + + +def test_index_loss_does_not_lose_memory(tmp_db: MemoryDB, tmp_path: Path): + _seed_store(tmp_db) + index = FakeVectorIndex() + rebuild_vector_index(tmp_db, index) + assert index.count() == 6 + + index.clear() # simulate total index loss + assert index.count() == 0 + assert tmp_db.count() == 7 # canonical storage untouched + + results = search_memories(tmp_db, "invoice validation", top_k=5, vector_index=index) + assert results, "search falls back to the SQLite scan" + + rebuild_vector_index(tmp_db, index) # rebuild restores acceleration + assert index.count() == 6 + + +def test_remove_index_directory_never_touches_sqlite(tmp_db: MemoryDB, tmp_path: Path): + db_path = tmp_path / "hotmem.sqlite" + db = MemoryDB(db_path) + try: + _add_fact(db, "1", "invoice rule") + index_dir = tmp_path / "hotmem-vector-index" + index_dir.mkdir() + (index_dir / "rebuild_marker.json").write_text("{}") + assert remove_index_directory(tmp_path) is True + assert not index_dir.exists() + assert db_path.exists() + assert db.count() == 1 + assert remove_index_directory(tmp_path) is False # idempotent + finally: + db.close() + + +# ── 6. Deterministic fallback ──────────────────────────────────────────────── + + +def test_fallback_search_is_deterministic(tmp_db: MemoryDB): + _seed_store(tmp_db) + first = search_memories(tmp_db, "invoice", top_k=5) + second = search_memories(tmp_db, "invoice", top_k=5) + assert _messages(first) == _messages(second) + + +def test_stale_index_results_equal_fallback_results(tmp_db: MemoryDB): + _seed_store(tmp_db) + index = FakeVectorIndex() + rebuild_vector_index(tmp_db, index) + _add_fact(tmp_db, "late", "late arriving invoice fact") + stale = search_memories(tmp_db, "invoice fact", top_k=5, vector_index=index) + fallback = search_memories(tmp_db, "invoice fact", top_k=5) + assert _messages(stale) == _messages(fallback) + + +# ── 7. No eager file reads during indexing ────────────────────────────────── + + +def test_rebuild_performs_no_file_reads( + tmp_db: MemoryDB, tmp_path: Path, monkeypatch: pytest.MonkeyPatch +): + from spy import SpyAdapter + + import hotmem.storage as storage_module + + big_file = tmp_path / "big.parquet" + big_file.write_bytes(b"\x00" * (2 * 1024 * 1024)) # 2 MB "large" backing file + file_memory_id = _add_file_backed(tmp_db, "big", str(big_file), summary="large parquet summary") + _add_fact(tmp_db, "f1", "inline invoice fact") + + spy = SpyAdapter(storage_module.LocalFilesystemAdapter()) + monkeypatch.setitem(storage_module.ADAPTERS, "", spy) + monkeypatch.setitem(storage_module.ADAPTERS, "file", spy) + + index = FakeVectorIndex() + result = rebuild_vector_index(tmp_db, index) + + assert result["indexed_count"] == 2 + assert spy.total_file_reads == 0 # no read/read_range/checksum ever + # The file-backed memory is indexed from its summary embedding only — + # the 2 MB backing file was never opened. + assert file_memory_id in index.vectors + + +# ── HTTP surface ───────────────────────────────────────────────────────────── + + +class _VectorApp: + """App fixture with an injected fake index (no chromadb needed).""" + + def __init__(self, tmp_path: Path, vector_index: Any) -> TestClient: + from hotmem.server import create_app + + mount = tmp_path / "mount" + mount.mkdir(exist_ok=True) + app = create_app( + db_path=mount / "hotmem.sqlite", + base_dir=mount, + vector_backend="chroma", + vector_index=vector_index, + ) + self.client = TestClient(app) + self.mount = mount + + +def test_status_endpoint_reports_staleness(tmp_path: Path): + holder = _VectorApp(tmp_path, FakeVectorIndex()) + with holder.client as c: + resp = c.get("/v1/vector-index/status") + assert resp.status_code == 200 + body = resp.json() + assert body["backend"] == "fake" + assert body["stale"] is True # never rebuilt + assert body["db_count"] == 0 + + c.post("/v1/add", json={"identifier": "test", "fact": "invoice validation"}) + resp = c.get("/v1/vector-index/status") + assert resp.json()["db_count"] == 1 + + +def test_rebuild_endpoint_and_event(tmp_path: Path): + index = FakeVectorIndex() + holder = _VectorApp(tmp_path, index) + with holder.client as c: + c.post("/v1/add", json={"identifier": "test", "fact": "invoice validation"}) + # Backing file must exist for the file-backed add path. + (holder.mount / "data.bin").write_bytes(b"\x01\x02\x03\x04") + resp = c.post( + "/v1/add", + json={ + "identifier": "test", + "file_uri": "data.bin", + "byte_offset": 0, + "byte_length": 4, + "source_format": "bin", + }, + ) + assert resp.status_code == 200 + resp = c.post("/v1/vector-index/rebuild") + assert resp.status_code == 200 + body = resp.json() + # 1 inline fact + 1 file-backed WITHOUT summary (skipped: no embedding). + assert body["indexed_count"] == 1 + assert body["db_count"] == 2 + assert body["skipped_no_embedding"] == 1 + + # Staleness observable through the status endpoint. + status = c.get("/v1/vector-index/status").json() + assert status["stale"] is False + + # Rebuild event appended to the append-only event log. + events = c.get("/v1/events", params={"event_type": "index.rebuilt"}).json() + assert events["count"] == 1 + assert events["events"][0]["payload"]["indexed_count"] == 1 + + +def test_search_response_shape_unchanged_with_acceleration(tmp_path: Path): + index = FakeVectorIndex() + holder = _VectorApp(tmp_path, index) + with holder.client as c: + c.post("/v1/add", json={"identifier": "test", "fact": "invoice validation rules"}) + c.post("/v1/vector-index/rebuild") + accelerated = c.post("/v1/search", json={"query": "invoice", "top_k": 5}).json() + assert set(accelerated.keys()) == {"memories", "count", "trace_ms"} + msg_keys = { + "role", + "content", + "memory_id", + "identifier", + "score", + "created_at", + } + assert all(set(m.keys()) == msg_keys for m in accelerated["memories"]) + + +def test_clear_endpoint(tmp_path: Path): + index = FakeVectorIndex() + holder = _VectorApp(tmp_path, index) + with holder.client as c: + c.post("/v1/add", json={"identifier": "test", "fact": "invoice validation"}) + c.post("/v1/vector-index/rebuild") + assert index.count() == 1 + + resp = c.delete("/v1/vector-index") + assert resp.status_code == 200 + assert resp.json()["cleared"] is True + assert resp.json()["db_count"] == 1 # memories survive + assert index.count() == 0 + assert c.get("/v1/vector-index/status").json()["stale"] is True + + # Search still works after clearing. + search = c.post("/v1/search", json={"query": "invoice"}).json() + assert search["count"] == 1 + + +def test_rebuild_rejected_without_backend(tmp_path: Path): + from hotmem.server import create_app + + mount = tmp_path / "mount" + mount.mkdir() + app = create_app(db_path=mount / "hotmem.sqlite", base_dir=mount) + with TestClient(app) as c: + resp = c.post("/v1/vector-index/rebuild") + assert resp.status_code == 400 + assert resp.json()["error"] == "vector_index_disabled" + + status = c.get("/v1/vector-index/status").json() + assert status == { + "backend": "none", + "requested_backend": "none", + "dependency_available": True, + "indexed_count": 0, + "db_count": 0, + "stale": True, + "rebuilt_at": None, + "path": str(mount / "hotmem-vector-index"), + "trace_ms": status["trace_ms"], + } + + +def test_rebuild_rejected_when_dependency_missing(tmp_path: Path, monkeypatch: pytest.MonkeyPatch): + import hotmem.vector_index as vi + + monkeypatch.setattr(vi, "chroma_available", lambda: False) + from hotmem.server import create_app + + mount = tmp_path / "mount" + mount.mkdir() + app = create_app(db_path=mount / "hotmem.sqlite", base_dir=mount, vector_backend="chroma") + with TestClient(app) as c: + resp = c.post("/v1/vector-index/rebuild") + assert resp.status_code == 400 + body = resp.json() + assert body["error"] == "vector_dependency_missing" + assert body["requested_backend"] == "chroma" + + +def test_create_app_rejects_unknown_backend(tmp_path: Path): + from hotmem.server import create_app + + with pytest.raises(ValueError, match="unknown vector_backend"): + create_app(db_path=tmp_path / "x.sqlite", vector_backend="qdrant") + + +# ── 9. ChromaVectorIndex (skipped when chromadb is not installed) ──────────── + +try: + import chromadb # noqa: F401 + + _CHROMA = True +except ImportError: + _CHROMA = False + +requires_chroma = pytest.mark.skipif(not _CHROMA, reason="chromadb not installed") + + +@requires_chroma +def test_chroma_rebuild_and_search_parity(tmp_path: Path): + db_path = tmp_path / "hotmem.sqlite" + db = MemoryDB(db_path) + try: + _seed_store(db) + index = ChromaVectorIndex(base_dir=tmp_path) + result = rebuild_vector_index(db, index) + + assert result["indexed_count"] == 6 + assert index.count() == 6 + assert index.is_stale(db) is False + + marker = tmp_path / "hotmem-vector-index" / "rebuild_marker.json" + assert marker.exists() + + for query in ("invoice", "payment terms", "Q3 revenue"): + fallback = search_memories(db, query, top_k=5) + accelerated = search_memories(db, query, top_k=5, vector_index=index) + assert _messages(fallback) == _messages(accelerated), query + finally: + db.close() + + +@requires_chroma +def test_chroma_stale_after_insert(tmp_path: Path): + db_path = tmp_path / "hotmem.sqlite" + db = MemoryDB(db_path) + try: + _add_fact(db, "1", "invoice validation") + index = ChromaVectorIndex(base_dir=tmp_path) + rebuild_vector_index(db, index) + assert index.is_stale(db) is False + + _add_fact(db, "2", "another fact") + assert index.is_stale(db) is True + + results = search_memories(db, "another fact", top_k=2, vector_index=index) + assert results[0]["memory_id"] == "2" # fallback found it + finally: + db.close() + + +@requires_chroma +def test_chroma_clear_and_delete(tmp_path: Path): + db_path = tmp_path / "hotmem.sqlite" + db = MemoryDB(db_path) + try: + _add_fact(db, "1", "invoice validation") + index = ChromaVectorIndex(base_dir=tmp_path) + rebuild_vector_index(db, index) + assert index.count() == 1 + + index.clear() + assert index.count() == 0 + assert index.is_stale(db) is True + + rebuild_vector_index(db, index) + assert index.count() == 1 + index.delete(["1"]) + assert index.count() == 0 + finally: + db.close() + + +@requires_chroma +def test_chroma_persistence_across_instances(tmp_path: Path): + db_path = tmp_path / "hotmem.sqlite" + db = MemoryDB(db_path) + try: + _add_fact(db, "1", "invoice validation") + first = ChromaVectorIndex(base_dir=tmp_path) + rebuild_vector_index(db, first) + first.close() + + second = ChromaVectorIndex(base_dir=tmp_path) + assert second.count() == 1 + assert second.is_stale(db) is False # marker survived persistence + finally: + db.close() diff --git a/uv.lock b/uv.lock index 7e504bd..f3dbcc9 100644 --- a/uv.lock +++ b/uv.lock @@ -1,6 +1,152 @@ version = 1 revision = 3 requires-python = ">=3.11" +resolution-markers = [ + "python_full_version >= '3.14'", + "python_full_version == '3.13.*'", + "python_full_version == '3.12.*'", + "python_full_version < '3.12'", +] + +[[package]] +name = "aiohappyeyeballs" +version = "2.7.1" +source = { registry = "https://pypi.org/simple" } +sdist = { url = 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upload-time = "2026-07-20T02:07:41.55Z" }, + { url = "https://files.pythonhosted.org/packages/61/02/962c1cbfc401a30c1d034dc67ff395f64b52302c6d62de556c1fca99acc0/yarl-1.24.5-py3-none-any.whl", hash = "sha256:a33700d13d9b7d84fd10947b09ff69fb9a792e519c8cb9764a3ca70baa6c23a7", size = 58612, upload-time = "2026-07-20T02:07:43.461Z" }, +] From adf411270c080b2b1122629ca4f49122ae9502e9 Mon Sep 17 00:00:00 2001 From: valiantone Date: Fri, 28 Aug 2026 12:52:48 +0200 Subject: [PATCH 2/6] fix: snapshot vector-index rebuild fingerprint before reading rows (#49) The rebuild marker now records the store fingerprint taken BEFORE the all_rows() read. A mutation landing mid-rebuild (concurrent insert) thus changes the live fingerprint and the marker reads stale, so search takes the deterministic fallback until the next rebuild. Snapshotting after the read could bless an index that silently misses rows inserted during the rebuild. Adds a regression test simulating the mid-rebuild insert. --- src/hotmem/vector_index.py | 13 ++++++++++--- tests/test_vector_index.py | 23 +++++++++++++++++++++++ 2 files changed, 33 insertions(+), 3 deletions(-) diff --git a/src/hotmem/vector_index.py b/src/hotmem/vector_index.py index ca42790..ed9ba9b 100644 --- a/src/hotmem/vector_index.py +++ b/src/hotmem/vector_index.py @@ -414,8 +414,10 @@ def rebuild_vector_index( they are excluded from cosine search by design and remain fully retrievable via get/hydrate and (for those with text) FTS. - The rebuild marker records the store fingerprint at rebuild time so - staleness is a cheap comparison, not a per-row checksum. + The rebuild marker records the store fingerprint snapshotted BEFORE the + row read, so any concurrent mutation makes the marker read stale and + search falls back deterministically — an index can be stale-fresh, never + silently incomplete. """ import datetime as _dt @@ -432,6 +434,12 @@ def rebuild_vector_index( } index.clear() + # Snapshot the fingerprint BEFORE reading rows. Any mutation landing + # after this point changes the live fingerprint, so the marker reads + # stale and search takes the deterministic fallback until the next + # rebuild — the safe direction. Snapshotting after the read would + # instead bless an index that may miss rows inserted mid-rebuild. + fingerprint = db_fingerprint(db) rows = db.all_rows(include_embedding=True) records = [] indexed = 0 @@ -460,7 +468,6 @@ def rebuild_vector_index( if records: index.upsert(records) - fingerprint = db_fingerprint(db) marker = { "db_count": fingerprint[0], "max_rowid": fingerprint[1], diff --git a/tests/test_vector_index.py b/tests/test_vector_index.py index 1446362..ccf21c8 100644 --- a/tests/test_vector_index.py +++ b/tests/test_vector_index.py @@ -267,6 +267,29 @@ def test_rebuild_on_null_index_is_noop(tmp_db: MemoryDB, tmp_path: Path): assert result["db_count"] == 1 +def test_concurrent_insert_during_rebuild_marks_index_stale( + tmp_db: MemoryDB, monkeypatch: pytest.MonkeyPatch +): + """A row inserted between the fingerprint snapshot and the row read must + leave the marker stale — never silently unindexed-and-fresh (#49 review). + + The fingerprint is snapshotted BEFORE the row read, so a mutation landing + mid-rebuild changes the live fingerprint and the index reads stale (the + deterministic fallback serves search until the next rebuild). + """ + original_all_rows = tmp_db.all_rows + + def all_rows_with_insert(*args: Any, **kwargs: Any): + _add_fact(tmp_db, "late-row", "inserted while the rebuild is running") + return original_all_rows(*args, **kwargs) + + monkeypatch.setattr(tmp_db, "all_rows", all_rows_with_insert) + index = FakeVectorIndex() + rebuild_vector_index(tmp_db, index) + + assert index.is_stale(tmp_db) is True + + # ── 3. Stale index -> fallback ─────────────────────────────────────────────── From 2050dfd8078f44d2bd99a0af3120e36231274794 Mon Sep 17 00:00:00 2001 From: valiantone Date: Fri, 28 Aug 2026 12:53:20 +0200 Subject: [PATCH 3/6] =?UTF-8?q?release:=20v0.2.4=20=E2=80=94=20optional=20?= =?UTF-8?q?derived=20vector=20index=20(#49)?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- CHANGELOG.md | 2 +- pyproject.toml | 2 +- src/hotmem/__init__.py | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 0c92bbb..5577738 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -4,7 +4,7 @@ All notable changes to HotMem will be documented in this file. Format follows [Keep a Changelog](https://keepachangelog.com/). -## [Unreleased] +## [0.2.4] - 2026-08-28 ### Added — Optional derived vector index (#49) - Pluggable vector index for search acceleration: `VectorIndex` protocol with diff --git a/pyproject.toml b/pyproject.toml index 83ba9dd..3010130 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [project] name = "hotmem" -version = "0.2.3" +version = "0.2.4" description = "A local-first memory sidecar for agent applications" readme = "README.md" requires-python = ">=3.11" diff --git a/src/hotmem/__init__.py b/src/hotmem/__init__.py index 4109b65..670f66e 100644 --- a/src/hotmem/__init__.py +++ b/src/hotmem/__init__.py @@ -1,3 +1,3 @@ """HotMem — A local-first memory sidecar for agent applications.""" -__version__ = "0.2.3" +__version__ = "0.2.4" From 56e3afc76eb42779d840dee9aff566db94063528 Mon Sep 17 00:00:00 2001 From: valiantone Date: Fri, 28 Aug 2026 13:19:18 +0200 Subject: [PATCH 4/6] chore: refresh uv.lock for v0.2.4 version bump --- uv.lock | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/uv.lock b/uv.lock index f3dbcc9..0097721 100644 --- a/uv.lock +++ b/uv.lock @@ -796,7 +796,7 @@ wheels = [ [[package]] name = "hotmem" -version = "0.2.3" +version = "0.2.4" source = { editable = "." } dependencies = [ { name = "click" }, From b72457503e49572cb4ffeafaa88706ee708cdbe6 Mon Sep 17 00:00:00 2001 From: valiantone Date: Fri, 28 Aug 2026 13:44:49 +0200 Subject: [PATCH 5/6] fix: correct JSONL _stream line offsets for chunk-spanning lines (#86) _stream computed line_start = offset + pos in (carry+chunk) coordinates, overstating file offsets by the carry length for every line after a chunk-spanning line. Affected unsupported_reason offsets and byte_ranges (feeding FileInspection -> API/MCP/CLI). Offsets now use base + pos with base = offset - len(carry), verified for exact parity against the spike's C scanner (bench/native_spike). Adds a chunk-boundary regression test; discovered by the native helper spike (#48, #84). --- CHANGELOG.md | 7 ++++++ src/hotmem/inspectors/jsonl_inspector.py | 3 ++- tests/test_inspectors.py | 28 ++++++++++++++++++++++++ 3 files changed, 37 insertions(+), 1 deletion(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 5577738..f1ba84f 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -32,6 +32,13 @@ Format follows [Keep a Changelog](https://keepachangelog.com/). `DELETE /v1/vector-index` (clear). `/v1/search` response shape unchanged. - `hotmem serve --vector-index {none,chroma}` CLI flag (default `none`). +### Fixed — JSONL inspector line offsets (#86) +- `JSONLInspector._stream` computed line offsets in (carry+chunk) coordinates, + overstating `unsupported_reason` offsets and `byte_ranges` by the carried + byte count whenever an earlier line spanned the 1 MiB read-chunk boundary. + Offsets are now exact file coordinates (regression test included; discovered + by the native helper spike, #48/#84). + ## [0.2.3] - 2026-08-07 ### Changed diff --git a/src/hotmem/inspectors/jsonl_inspector.py b/src/hotmem/inspectors/jsonl_inspector.py index 8658ffa..5fdbb6d 100644 --- a/src/hotmem/inspectors/jsonl_inspector.py +++ b/src/hotmem/inspectors/jsonl_inspector.py @@ -106,6 +106,7 @@ def _stream( data = carry + chunk chunk_end = offset + len(chunk) + base = offset - len(carry) # file offset of data[0] (carry precedes chunk) pos = 0 nl = data.find(b"\n", pos) while nl != -1: @@ -126,7 +127,7 @@ def _stream( ) line_index += 1 pos = nl + 1 - line_start = offset + pos + line_start = base + pos nl = data.find(b"\n", pos) carry = data[pos:] offset = chunk_end diff --git a/tests/test_inspectors.py b/tests/test_inspectors.py index 3bed0c0..59a89d5 100644 --- a/tests/test_inspectors.py +++ b/tests/test_inspectors.py @@ -121,6 +121,34 @@ def test_jsonl_malformed_line_reported_not_raised(tmp_path): assert "line 1" in insp.unsupported_reason +def test_jsonl_chunk_spanning_line_offsets_are_exact(tmp_path): + """#86: offsets of lines following a chunk-spanning line must be exact. + + ``_stream`` previously computed line_start in (carry+chunk) coordinates, + overstating file offsets by the carry length whenever an earlier line + spanned the 1 MiB read-chunk boundary. + """ + path = tmp_path / "span.jsonl" + line0 = json.dumps({"i": 0, "pad": "x" * (1 << 20)}).encode() + b"\n" # spans chunk 1 + bad = b'{"broken"\n' + lines = [line0, bad] + [json.dumps({"i": i}).encode() + b"\n" for i in (2, 3, 4)] + with open(path, "wb") as f: + f.write(b"".join(lines)) + + offsets = [] + pos = 0 + for ln in lines: + offsets.append(pos) + pos += len(ln) + + insp = inspect_file(str(path), count_rows=True, sample_size=5) + assert insp.row_count == 5 + assert insp.unsupported_reason is not None + assert insp.unsupported_reason.startswith(f"line 1 (offset {offsets[1]}): ") + expected = [(offsets[0], len(line0))] + [(offsets[i], len(lines[i])) for i in (2, 3, 4)] + assert insp.byte_ranges == expected + + def test_jsonl_handles_no_trailing_newline(tmp_path): path = tmp_path / "notrail.jsonl" path.write_text('{"a": 1}\n{"a": 2}') # no trailing newline From 7f48efaa2214af66b9aacf2e8bf835ddda422162 Mon Sep 17 00:00:00 2001 From: valiantone Date: Fri, 28 Aug 2026 13:44:49 +0200 Subject: [PATCH 6/6] =?UTF-8?q?chore(bench):=20spike=20review=20nits=20?= =?UTF-8?q?=E2=80=94=20corpus=20byte=20accounting,=20report=20rows,=20form?= =?UTF-8?q?atting=20(#91)?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - gen_corpus.py: malformed-line accounting used a hardcoded 38 instead of the actual 41 bytes (40 + newline); counter now derives from the line. The insertion threshold is unaffected (drift began after insertion), so the committed manifest stays valid for regenerated corpora. - run_bench.py: report rows column now takes the first arm with a measured row count instead of blindly the first arm; reformatted. --- bench/native_spike/gen_corpus.py | 5 +- bench/native_spike/run_bench.py | 80 ++++++++++++++++++++++---------- 2 files changed, 58 insertions(+), 27 deletions(-) diff --git a/bench/native_spike/gen_corpus.py b/bench/native_spike/gen_corpus.py index 0b66187..54f1151 100644 --- a/bench/native_spike/gen_corpus.py +++ b/bench/native_spike/gen_corpus.py @@ -166,9 +166,10 @@ def gen_jsonl_files(out: Path) -> list[dict]: if not bad_written and written >= target * 0.6: bad_line_offset = written bad_line_index = rows - f.write(b'{"id": "broken", "fact_text": "truncated') + bad_line = b'{"id": "broken", "fact_text": "truncated' + f.write(bad_line) f.write(b"\n") - written += 38 + written += len(bad_line) + 1 rows += 1 bad_written = True continue diff --git a/bench/native_spike/run_bench.py b/bench/native_spike/run_bench.py index 3236baf..e75733c 100644 --- a/bench/native_spike/run_bench.py +++ b/bench/native_spike/run_bench.py @@ -48,15 +48,29 @@ CACHE_MODES = ["warm", "cold"] -def spawn(bench: str, arm: str, *, path: str = "", offset: int = 0, length: int = 0, - runs: int, cache: str, env: dict | None = None, timeout: int = 1800) -> dict: +def spawn( + bench: str, + arm: str, + *, + path: str = "", + offset: int = 0, + length: int = 0, + runs: int, + cache: str, + env: dict | None = None, + timeout: int = 1800, +) -> dict: cmd = [ sys.executable, str(SPIKE_DIR / "bench_worker.py"), - "--bench", bench, - "--arm", arm, - "--runs", str(runs), - "--cache", cache, + "--bench", + bench, + "--arm", + arm, + "--runs", + str(runs), + "--cache", + cache, ] if path: cmd += ["--path", path, "--offset", str(offset), "--length", str(length)] @@ -88,6 +102,7 @@ def _ctx() -> dict: # b1 — range checksum # # --------------------------------------------------------------------- # + def run_b1(manifest: dict, runs: int, quick: bool) -> dict: cases = [] for e in manifest["checksum_files"]: @@ -123,6 +138,7 @@ def run_b1(manifest: dict, runs: int, quick: bool) -> dict: # b2 — JSONL scanning # # --------------------------------------------------------------------- # + def run_b2(manifest: dict, runs: int, quick: bool) -> dict: files = [e["name"] for e in manifest["jsonl_files"]] if quick: @@ -172,6 +188,7 @@ def run_b2(manifest: dict, runs: int, quick: bool) -> dict: # b3 — bundle parse profile # # --------------------------------------------------------------------- # + def run_b3(manifest: dict, runs: int, quick: bool) -> dict: trees = [t["name"] for t in manifest["bundle_trees"]] if quick: @@ -193,6 +210,7 @@ def run_b3(manifest: dict, runs: int, quick: bool) -> dict: # b4 — manifest verification # # --------------------------------------------------------------------- # + def run_b4(runs: int, quick: bool) -> dict: print(" [b4] manifest verification …", flush=True) cell = {"context": _ctx(), "arms": {}} @@ -214,6 +232,7 @@ def run_b4(runs: int, quick: bool) -> dict: # optional-boundary check (graceful degradation) # # --------------------------------------------------------------------- # + def run_boundary_check() -> dict: """Prove helpers degrade gracefully: run a c arm and a wasm arm with HOTMEM_SPIKE_DISABLE_NATIVE=1; both must report skipped=helper_unavailable @@ -222,13 +241,11 @@ def run_boundary_check() -> dict: env = {"HOTMEM_SPIKE_DISABLE_NATIVE": "1"} binf = benchlib.CORPUS_DIR / "bin_1mb.bin" jf = benchlib.CORPUS_DIR / "events_10mb.jsonl" - c1 = spawn("b1", "c_pread", path=str(binf), length=binf.stat().st_size, - runs=1, cache="warm", env=env) - c2 = spawn("b2", "wasm_scan", path=str(jf), runs=1, cache="warm", env=env) - ok = ( - c1.get("skipped") == "helper_unavailable" - and c2.get("skipped") == "helper_unavailable" + c1 = spawn( + "b1", "c_pread", path=str(binf), length=binf.stat().st_size, runs=1, cache="warm", env=env ) + c2 = spawn("b2", "wasm_scan", path=str(jf), runs=1, cache="warm", env=env) + ok = c1.get("skipped") == "helper_unavailable" and c2.get("skipped") == "helper_unavailable" return {"ok": ok, "c_pread_disabled": c1, "wasm_scan_disabled": c2} @@ -236,6 +253,7 @@ def run_boundary_check() -> dict: # report # # --------------------------------------------------------------------- # + def _fmt_ms(v) -> str: return "—" if v is None else f"{v:.1f}" @@ -262,18 +280,24 @@ def report(results: dict) -> str: lines: list[str] = [] host = results.get("host", {}) - lines.append(f"Host: {host.get('cpu', '?')} | sha_ni={host.get('sha_ni')} | " - f"kernel {host.get('kernel', '?')} | Python {host.get('python', '?')}") - lines.append(f"Profile: {results.get('profile')} | runs={results.get('config', {}).get('runs')}" - f" | corpus seed={results.get('corpus_seed')}") + lines.append( + f"Host: {host.get('cpu', '?')} | sha_ni={host.get('sha_ni')} | " + f"kernel {host.get('kernel', '?')} | Python {host.get('python', '?')}" + ) + lines.append( + f"Profile: {results.get('profile')} | runs={results.get('config', {}).get('runs')}" + f" | corpus seed={results.get('corpus_seed')}" + ) lines.append("") # ---- B1 ---- b1 = results.get("b1_range_checksum", {}) lines.append("## B1 — Range SHA-256 checksum (median ms, warm / cold; peak RSS MB in parens)") lines.append("") - header = ("| file (range) | py double-read | py single | py stream | c pread | c mmap " - "| py-single gains | c_mmap vs py_single |") + header = ( + "| file (range) | py double-read | py single | py stream | c pread | c mmap " + "| py-single gains | c_mmap vs py_single |" + ) lines.append(header) lines.append("|" + "---|" * 8) for case in b1.get("cases", []): @@ -312,7 +336,11 @@ def report(results: dict) -> str: for arm in B2_ARMS: vals.append(f"{_fmt_ms(_med(cell, arm, 'warm'))} / {_fmt_ms(_med(cell, arm, 'cold'))}") rows = next( - (_arm_cell(cell, a, "warm").get("output", {}).get("rows") for a in B2_ARMS), + ( + out + for a in B2_ARMS + if (out := _arm_cell(cell, a, "warm").get("output", {}).get("rows")) is not None + ), None, ) lines.append(f"| {cell['file']} | " + " | ".join(vals) + f" | {rows} |") @@ -354,8 +382,9 @@ def report(results: dict) -> str: # ---- boundary ---- bc = results.get("optional_boundary_check", {}) if bc: - lines.append("## Optional-boundary check (HOTMEM_SPIKE_DISABLE_NATIVE=1): " - f"**{bc.get('ok')}**") + lines.append( + f"## Optional-boundary check (HOTMEM_SPIKE_DISABLE_NATIVE=1): **{bc.get('ok')}**" + ) lines.append("") return "\n".join(lines) @@ -363,14 +392,15 @@ def report(results: dict) -> str: # --------------------------------------------------------------------- # + def main() -> int: ap = argparse.ArgumentParser(description=__doc__) ap.add_argument("--profile", choices=["reduced", "full"], default="reduced") - ap.add_argument("--quick", action="store_true", - help="smoke the harness: 1 run, small inputs") + ap.add_argument("--quick", action="store_true", help="smoke the harness: 1 run, small inputs") ap.add_argument("--out", default="results.json") - ap.add_argument("--report", action="store_true", - help="print markdown report from --out and exit") + ap.add_argument( + "--report", action="store_true", help="print markdown report from --out and exit" + ) args = ap.parse_args() out_path = SPIKE_DIR / args.out