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[python] Use pydantic for embedding function persistence (#467)

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1. Support persistent embedding function so users can just search using
query string
2. Add fixed size list conversion for multiple vector columns
3. Add support for empty query (just apply select/where/limit).
4. Refactor and simplify some of the data prep code

---------

Co-authored-by: Chang She <chang@lancedb.com>
Co-authored-by: Weston Pace <weston.pace@gmail.com>
This commit is contained in:
Chang She
2023-09-05 21:30:45 -07:00
committed by GitHub
parent 52fa7f5577
commit 9a9a73a65d
13 changed files with 815 additions and 192 deletions
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14
python/lancedb/remote/table.py
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@@ -20,7 +20,7 @@ from lance import json_to_schema
from lancedb.common import DATA, VEC, VECTOR_COLUMN_NAME
from ..query import LanceQueryBuilder
from ..query import LanceVectorQueryBuilder
from ..table import Query, Table, _sanitize_data
from .arrow import to_ipc_binary
from .client import ARROW_STREAM_CONTENT_TYPE
@@ -73,7 +73,11 @@ class RemoteTable(Table):
fill_value: float = 0.0,
) -> int:
data = _sanitize_data(
data, self.schema, on_bad_vectors=on_bad_vectors, fill_value=fill_value
data,
self.schema,
metadata=None,
on_bad_vectors=on_bad_vectors,
fill_value=fill_value,
)
payload = to_ipc_binary(data)
@@ -89,9 +93,9 @@ class RemoteTable(Table):
)
def search(
self, query: Union[VEC, str], vector_column: str = VECTOR_COLUMN_NAME
) -> LanceQueryBuilder:
return LanceQueryBuilder(self, query, vector_column)
self, query: Union[VEC, str], vector_column_name: str = VECTOR_COLUMN_NAME
) -> LanceVectorQueryBuilder:
return LanceVectorQueryBuilder(self, query, vector_column_name)
def _execute_query(self, query: Query) -> pa.Table:
result = self._conn._client.query(self._name, query)