The IVF probe count was the one vector search parameter with no
setting, and it is what bounds recall on a large indexed corpus:
partitions grow with the corpus, so a fixed probe count covers less of
it, and vector_refine_factor can only re-score what the probes
returned. Defaults to 20, matching lance, so search is unchanged.
Also corrects the create-index docs, which predate the measurement:
optimize() covers new chunks, so a rebuild is about retraining
centroids rather than reaching unindexed rows.
Retrieval scores are each database's own rank arithmetic; the databases
in a selection share an embedder, so similarity in that one space is the
signal comparable across databases by construction. Measured product to
product against score ordering: +8.3 to +16.6pp recall@5 across five
cells on two corpora, flat in collection count and corpus shape where
score ordering dips with both, closing roughly 60% of the gap to a
reranker; order-sensitivity residual 0.00pp in every cell. Exact ties
collapse from 51-81% of candidates to under 1%. Full-text-only searches
keep retrieval-score order, having no query vector. The vector column
already travels with every search result, so the similarity costs no
additional transfer; per-chunk embeddings are materialized only for the
federated path that reads them.
Deleting or replacing every indexed row while unindexed rows remain
returns lance to the zero-coverage scan path. ensure_indexes rebuilds
a declared FTS index that covers none of a populated table's rows,
and delete_by_document_id runs index maintenance like the other chunk
writes. A legacy database in that state is repaired by its first write.
An FTS index built over an empty table indexes nothing and lance never
catches it up on add. ensure_indexes skips FTS while the table is
empty; create, replace_for_document and embed-only rebuild ensure
indexes after writing, so the index always covers at least its first
rows. The first write into a fresh table writes one extra chunks table
version for the index build; a failed build fails the write.
lance serves unsorted results with matching rows dropped when a
declared FTS index has indexed nothing, or when a populated table has
no FTS index at all. doctor fails on both: vacuum remediation for an
existing index, rebuild --embed-only for a missing one, since optimize
never creates an index. The chunk repository warns once per repository
on the first FTS or hybrid search against either state; a failing
coverage check is logged and never fails the search. Removes
_ensure_fts_index, which had no callers.
Comments and docstrings across the branch narrated rejected
alternatives, consequences and history; each now states the current
contract. Renames test_a_legacy_uri_client_keeps_its_error to
test_an_unnamed_database_keeps_its_error. Documents the Sandbox
connection paths, the citation header's database segment, both
AmbiguousDatabaseError conditions on create_app, and run_inspector's
scope parameter. Doc paragraphs added by the branch in python.md,
storage.md and cli.md are one physical line each.
Each database owns an embedder, so embedding per database cost a round
trip each. One database still embeds inside the repository, which returns
early for a filter that matches nothing.
The CLI reports this error, and importing it from the settings repository
pulled lancedb onto the CLI's import path. Deferring the import into cli()
bought nothing, since cli() runs on every invocation: it cost about 1.9
seconds on a cold start, `--help` included.
It now sits beside the other store exceptions, in a module that imports
nothing, and every importer points there.
Sixty-three comments said what the next statement already said: # Connect to
LanceDB above connect_lancedb, # Path object above isinstance(source, Path),
# Get page numbers from provenance above the prov loop, # Clear and populate
results above list_view.clear(). They cost a read and carry nothing.
The line is whether a comment restates one statement or labels a phase. Phase
labels stay: the migrations keep # Create staging table with new schema and
# Copy from staging to final table in batches, each heading ten lines of a
long procedure. So do comments carrying a fact the code cannot: the
merge_insert update-only note on document_meta, why the poller builds sources
eagerly, why create_document_from_source returns a list for directories, that
indexes need training data, the field-group markers in the config models, and
the file:// URL-encoding note in create_document_from_source.
capabilities/ is untouched. Its docstrings sit next to prompt surface, and
changing them needs an eval to back it.
The cassette-recording docs were wrong three ways. They named
tests/test_qa.py::test_qa_anthropic, which no longer exists; they targeted
whole modules, so a rewrite would re-record cassettes for services the
recorder is not running; and they used COHERE_API_KEY where the SDK reads
CO_API_KEY. docs/development.md now names exact tests with -n0, and the keyed
example is test_cohere_reranker, which owns the one cassette recording
api.cohere.com.
engine.py held four unrelated things: what the tables are, how to open a
connection, how to read a database's state, and the Store that coordinates
writes. At 1240 lines the Store's own concerns — locks, migrations, vacuum,
tags — were hard to find among them.
Table records, Arrow schemas, index_specs, ensure_indexes, REQUIRED_TABLES
and query_to_pydantic move to store/schema.py, which imports nothing from
haiku.rag: it describes the tables and never opens or mutates one.
gather_database_info, get_database_stats, DatabaseInfo and its result models
move to store/info.py. Nothing in Store calls them — they are read paths for
the CLI, doctor, inspector and ingester API — so info depends on engine and
not the reverse.
engine.py keeps the Store, ConnectionMode, connect_lancedb, the tag helpers
and the restore-order and retention constants. No re-exports: importers
point at the new modules.
test_app_info_uses_connect_lancedb_for_remote patched
haiku.rag.store.engine.connect_lancedb; gather_database_info now binds that
name in info.py, so the patch targets where the call is looked up.
create_document_from_source resolves a fetcher per call and never closed
it, so every one-shot URL or WebDAV ingest leaked an httpx connection
pool. Close it, but only when we built it: resolve_adhoc_fetcher returns
a caller-supplied source when one matches the URI, and the ingester keeps
those open across jobs.
Directory ingestion also yielded symlinked files resolving outside the
directory it was given. rglob does not recurse into symlinked
directories, so a symlinked file was the only way out of the tree; skip
those, as FSSource.discover already does.
The chunk repository docstring named client._ensure_chunks_embedded,
which does not exist.
Collapsing the caption text into `get_pictures_grouped` served the enrichment
path, which uses it, but the multimodal reranker discards the second return value
while still paying to read the column. That is the widest fan-out in the codebase,
`limit * 10` candidates, and it previously projected self_ref and picture_data
alone.
`with_text` is opt-in and off by default, so the cheap projection is what a caller
gets unless it asks for more. The reranker test asserts the projection as well as
the query count, since a count alone would not notice the column coming back.
`resolve_refs`, `get_items_in_range`, `get_caption_picture_refs` and
`get_all_items_grouped` have no callers left: the grouped equivalents serve every
path that used them. `get_all_items_grouped` had none even before this branch.
Tests whose subject was a removed method go with it. Tests that only used one to
fetch a fixture now use the grouped call, so what they assert is unchanged.
`_attach_picture_data` fetched picture bytes once per document, over the
`limit * 10` candidates reranking asks for, so it was the per-document fetch with
the most candidates behind it. It now issues one query however many documents the
candidates span: one for ten documents, as for one.
Removes `get_text_for_refs`, whose only caller now gets the text back with the
bytes from `get_pictures_grouped`.
`test_client_search_include_images_false_skips_lookup` returned no search
results, so asserting the picture accessor went uncalled held whatever the code
did. It now returns a picture-carrying result, making "did not fetch" the
assertion rather than "had nothing to fetch".
`expand_with_items` fetched its own inputs per document: one query to resolve
refs to positions, one for the window of items around them. A result set spanning
N documents cost 2N queries, which was 10 of the 18 measured for a limit=5 search
on a remote object-store corpus.
`expand_context` now does both fetches once for every document it is expanding,
and `expand_with_items` takes the positions and items it needs. Two queries for
one document, and two for five.
Each document keeps its own inclusive window in `get_items_in_ranges`. Positions
repeat across documents, so a shared range would splice one document's items into
another's context.
`_populate_image_data` ran its stages once per result document, so a result set
spanning N documents cost 4N `document_items` queries. Measured on a remote
object-store corpus, a limit=5 search with expansion was 18 queries, 16 of them
against `document_items`.
The stages now run once each across every document, and flat in document count:
two queries for the dependent caption-to-picture mapping when results ranked on a
caption, one for the picture bytes. Two queries for a picture-ref result set,
three at most.
Picture text comes back with the bytes rather than from a second query, since it
is on the same rows.
Predicates are per document, `(document_id = 'a' AND self_ref IN (…)) OR (…)`,
rather than `self_ref IN (union)`. self_ref and position values repeat across
documents, so a union predicate would return other documents' rows: for
picture_data that fetches blobs nobody asked for, and it can hand one document
another document's picture.
Opening a database ran `list_tables` three times, opened the settings table
twice, and read and parsed the same settings row three times: once for the stored
vector dimension, once for the version behind the migration check, and once for
config validation. On object storage each of those is a round trip.
`_initialize` now reads both once and threads them down. `_init_tables` and
`_check_migrations` take what it read instead of fetching their own copy, and
`validate_config_compatibility` accepts the settings it should compare against,
still reading for itself when called directly.
Passing the pre-init read to validation is equivalent: nothing between the read
and the validation rewrites `embeddings`, which is all it compares.
The settings read no longer swallows every exception. It did before, when the
only consequence was falling back to the configured vector dimension; now the
same empty result feeds the migration check, where it would read as version
0.0.0 and declare every migration pending. Only decode failures are tolerated,
and a decoded non-object normalizes to {} rather than reaching callers that
expect a mapping.
`_init_tables` left `chunks.id`, `chunks.document_id` and `documents.id`
unindexed, so those lookups scanned the column. On object storage that is
network I/O per query, on paths that run per document: citation lookup,
delete-by-document, the re-ingest merge, and every dedup probe.
Declare the index set per table in `index_specs()` and apply it through
`ensure_indexes()`, which skips a column only when it is already indexed with
the declared type. Both halves of that are load-bearing. Skipping is required
because `create_index(replace=True)` rebuilds an identical index, writing a new
index and a new table version and orphaning the old files until the next vacuum.
Comparing the type is required because column coverage alone would let a
wrong-typed index stand, and a BTree on `label` silently loses the
low-cardinality equality lookup the Bitmap is there for.
Columns not declared for a table are left alone, so an externally created index
such as a vector index on `chunks` survives.
`_init_tables`, `recreate_embeddings_table`, `ChunkRepository.delete_all` and
`DocumentRepository.delete_all` now all route through it instead of repeating
their own subsets.
Also recreate `document_items` from `get_document_items_arrow_schema()` in
`DocumentRepository.delete_all`, which was using the LanceModel and so returned
`picture_data` as 32-bit `binary`.
Existing databases are unchanged; the migration follows separately.
Delete repository methods with no callers (SettingsRepository CRUD,
ChunkRepository.update/delete/get_chunks_in_range), the DataFrame branch of
_process_search_results whose only caller always passes a query, and guards
that cannot be reached from their call sites: the rebuild mode=None default,
the staging drop already performed by _resolve_rebuild_recovery, the empty
batch skip, two context fast paths, the doctor prefix guard, the poller
_task attribute that is never assigned, and a docling caption fallback for
a field name no item class defines.
set_haiku_version built a recreated settings row from the process-global
Config rather than the store's own, so a store opened with a custom config
stamped global settings into the database.
check_source_accessible called urlparse outside its try block, so a stored
URI with a malformed IPv6 host raised ValueError instead of reporting the
source as inaccessible, aborting the whole rebuild sweep.
Convert all LanceDB operations from sync calls wrapped in async
functions to the native async API (connect_async, AsyncConnection,
AsyncTable, AsyncQuery). Database I/O no longer blocks the event loop.
- Store and HaikuRAG use async context managers (async with). Store
initialization is deferred to __aenter__; direct construction
without async with is no longer supported.
- Index creation uses config objects (FTS, BTree, IvfPq) instead of
string-based index_type parameter.
- Upgrade callbacks are async.
- HaikuRAG tracks background vacuum tasks and awaits them in __aexit__
and before destructive rebuild operations to avoid races with
concurrent table mutations.
- temp_db_path fixture uses pytest's tmp_path for reliable async
cleanup.
