* to_df() is now async, added `to_df_blocking` to convenience
* add remote lancedb client to public lancedb
* make lancedb connection class understand url scheme
`lancedb+<connection_type>://<host>:<port>`.
Adds:
* Make `mkdocstrings` aware we are using numpy-style docstrings
* Fixes broken link on `index.md` to Python API docs (and added link to
node ones)
* Added examples to various classes.
* Added doctest to verify examples work.
pypi does not allow packages to be uploaded that has a direct reference
for now we'll just ask the user to install tantivy separately
---------
Co-authored-by: Chang She <chang@lancedb.com>
This is v1 of integrating full text search index into LanceDB.
# API
The query API is roughly the same as before, except if the input is text
instead of a vector we assume that its fts search.
## Example
If `table` is a LanceDB LanceTable, then:
Build index: `table.create_fts_index("text")`
Query: `df = table.search("puppy").limit(10).select(["text"]).to_df()`
# Implementation
Here we use the tantivy-py package to build the index. We then use the
row id's as the full-text-search index's doc id then we just do a Take
operation to fetch the rows.
# Limitations
1. don't support incremental row appends yet. New data won't show up in
search
2. local filesystem only
3. requires building tantivy explicitly
---------
Co-authored-by: Chang She <chang@lancedb.com>
