lancedb

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Files

Will Jones abd75e0ead feat: search multiple query vectors as one query (#1811 )

Allows users to pass multiple query vector as part of a single query
plan. This just runs the queries in parallel without any further
optimization. It's mostly a convenience.

Previously, I think this was only handled by the sync Python remote API.
This makes it common across all SDKs.

Closes https://github.com/lancedb/lancedb/issues/1803

```python
>>> import lancedb
>>> import asyncio
>>> 
>>> async def main():
...     db = await lancedb.connect_async("./demo")
...     table = await db.create_table("demo", [{"id": 1, "vector": [1, 2, 3]}, {"id": 2, "vector": [4, 5, 6]}], mode="overwrite")
...     return await table.query().nearest_to([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [4.0, 5.0, 6.0]]).limit(1).to_pandas()
... 
>>> asyncio.run(main())
   query_index  id           vector  _distance
0            2   2  [4.0, 5.0, 6.0]        0.0
1            1   2  [4.0, 5.0, 6.0]        0.0
2            0   1  [1.0, 2.0, 3.0]        0.0
```

2024-11-13 16:05:16 -08:00

connection.rs

feat(node): enable logging and show full errors (#1775 )

2024-10-29 15:13:34 -07:00

error.rs

feat(node): enable logging and show full errors (#1775 )

2024-10-29 15:13:34 -07:00

index.rs

feat: expose hnsw indices (#1595 )

2024-09-10 11:08:13 -07:00

iterator.rs

feat(nodejs): catch unwinds in node bindings (#1414 )