Restructure the storage page into search and provenance, duplicate ids,
ranking, Python operations and CLI commands, and state each in reference
voice. `Several Databases` becomes `Multiple Databases`, with the anchor
carried through every referrer, and the instruction files follow the same
name. Example databases are `papers`, `wiki` and `notes`.
`AmbiguousCitationError` is raised for a cited chunk id held by more than one
selected database, not for any shared id.
Three groups, not two: `search`, `ask`, `analyze` and `chat` cover the set,
`settings`, `init-config` and `download-models` open no database, and every
other command works on one — or on a configured set of one, which is
unambiguous and keeps its name. A database named in `lancedb.databases` keeps
that name whether or not it is the only one covered; only `lancedb.uri` places
one without naming it.
Document ids repeat between copies of a database, where the sandbox refuses a
duplicate but the chat filter's `id IN (...)` matches the document in every
copy. `build_document_id_filter` claimed ids never widen a selection.
Document the facade: `covers_multiple`, `source_names`, `source`,
`reader_for`, `clients_for`, the lifetime of a borrowed client, and
`sources=None` against `sources=[]`.
Drop the vision callout from the README, which the features list already
covers.
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.
The README feature list and the overview stopped at the analysis capability.
Both examples and the app backend composed agents without the capabilities the
documentation recommends alongside an evidence capability.
custom_agent.py ran each input as an independent agent run, so it needed a state
dict and a carried history before compaction could mean anything there: without
state the evidence record is empty, and earlier evidence would reduce to
receipts retaining nothing.
