Document.source names the configured database, as SearchResult and
Citation already do. A listing spanning databases is unreadable
without it, and `--database NAME list` could not name the one it
opened.
Reciprocal rank fusion compares ranks, so every database contributes its
own best matches whether or not they answer the question, and results from
databases holding nothing relevant displace better ones. Measured on one
corpus split three ways over 3,045 queries: retrieval MAP 0.6044 without a
reranker against 0.9798 for the same corpus in a single database, and
0.9918 against 0.9914 with one.
Chat answers with the same capabilities `ask` does, so it federates as
naturally as `ask` and `analyze` — but it went through the one-database
guard and refused a configured set outright, which left no way to chat
across several databases.
The guard was the visible half. `run_chat` also defaulted `db_path` to the
single default path whenever it was None, so lifting the refusal alone
would still have opened one database. It now leaves the path unresolved
when `lancedb.databases` names the set, and the client resolves it.
Listing and counting documents fan out over the set, which is what the
document filter reads, and visual grounding resolves the database holding
the cited chunk through the citation's source: chunks, pages and bounding
boxes all come from that one database. A limit on a listing means that
many documents in total, not that many per database.
The info modal reports every database it covers, each under its
configured name and without its location, since names are the only
identity that leaves the configuration. `database_lines` is what one
database reports about itself, shared by both paths, and it reports a
failure as a line so one unreachable database does not cost the report on
the others.
`inspect` stays a one-database command. It browses one database's
documents and chunks, so a set has nothing to show it.
lancedb.databases, the sources argument and the --database selector had no
documentation. Adds a Several Databases section to the storage
configuration page covering the name-to-location map, its mutual
exclusion with uri, the shared embedding configuration the set requires,
and which commands cover the set against which work on one. Adds a
Searching Several Databases section to the Python API page, --database to
the CLI's global options, the key to the sample configuration, and one
README feature line.
overview.md repeated the landing page: the same install-and-ask block and
five of six identical links. It was positioning prose, where the docs had no
page describing how the system works.
Rewrite it as Architecture, following the data through: source adapter,
converter, chunker, embedder, transaction; then storage and its versioning;
then retrieval, with the 10x rerank fetch and section-bounded expansion; then
the two capabilities; then laptop versus ingester. Retitled in the nav and on
the landing page, filename kept so existing links resolve.
Extras were listed in three places and none was complete.
docs/installation.md now carries a table of all fifteen slim extras, what each
provides, and which the full package already includes.
haiku_rag_slim/README.md names them and links there. The claim that other
providers need their own pydantic-ai extra was wrong: haiku.rag-slim defines
anthropic, google, groq, mistral, bedrock and vertexai itself.
configuration/storage.md opens with the four operational constraints, which
were either buried in an S3 section or undocumented: one writer per URI,
reader lag by read_consistency_interval_seconds, migrate after a
schema-changing upgrade, and the fixed embedding dimension with what
ConfigMismatchError means and which rebuild mode resolves it.
The one-writer rule is stated as a haiku.rag constraint, which is what it is:
the multi-table lock, version snapshot and rollback are process-local, so a
second writer can commit inside another's transaction and be reverted by its
rollback. storage.md and ingester.md both claimed it was a LanceDB property
that corrupts manifests. The S3 deployment section now links to the
constraint instead of restating it.
Get started reads index, Quickstart, Installation, Architecture. The landing
page's list was missing Installation.
Every `Store` built its own connection with its own caches and discarded them on
close, so the index a vector query loads was refetched by the next connection.
On object storage that first fetch dominates: measured on a ~500k-chunk 2560-dim
corpus over a ~200ms link, the first query cost ~41s and the second ~3s, and a
new connection reusing the session cost ~7s instead of ~47s.
`connect_lancedb` now passes a process-wide session, keyed on the configured
cache sizes so a caller asking for different sizes gets its own.
Also sets `read_consistency_interval`, defaulting to 30s. It was None, meaning a
connection never re-checked for other processes' writes. Per-call connections hid
that; a shared session makes connections long-lived enough for a reader to go
stale against the ingester.
All three settings reject negatives at the config boundary. A negative cache size
raises OverflowError and a negative interval panics inside Lance, so neither is
catchable further in. Zero stays valid for both: no cache, and check on every
read.
The routing tests now assert the kwargs they care about rather than the full call
signature, since every connection carries the two new kwargs.
Context expansion is now automatic and structure-aware. For structured
documents, expands within the section containing the match. For sections
that exceed the budget or are too small, expands item-by-item outward
skipping noise labels. Unstructured documents use budget-based outward
expansion. Results sorted by relevance score.
