port remote connection client into lancedb (#194)

* 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>`.
This commit is contained in:
Rob Meng
2023-06-15 18:57:52 -04:00
committed by GitHub
parent 78de8f5782
commit cbb56e25ab
12 changed files with 412 additions and 8 deletions

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# Copyright 2023 LanceDB Developers
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import abc
from typing import List, Optional
import attr
import pandas as pd
import pyarrow as pa
from pydantic import BaseModel
__all__ = ["LanceDBClient", "VectorQuery", "VectorQueryResult"]
class VectorQuery(BaseModel):
# vector to search for
vector: List[float]
# sql filter to refine the query with
filter: Optional[str] = None
# top k results to return
k: int
# # metrics
_metric: str = "L2"
# which columns to return in the results
columns: Optional[List[str]] = None
# optional query parameters for tuning the results,
# e.g. `{"nprobes": "10", "refine_factor": "10"}`
nprobes: int = 10
refine_factor: Optional[int] = None
@attr.define
class VectorQueryResult:
# for now the response is directly seralized into a pandas dataframe
tbl: pa.Table
def to_arrow(self) -> pa.Table:
return self.tbl
class LanceDBClient(abc.ABC):
@abc.abstractmethod
def query(self, table_name: str, query: VectorQuery) -> VectorQueryResult:
"""Query the LanceDB server for the given table and query."""
pass

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# Copyright 2023 LanceDB Developers
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import functools
import aiohttp
import attr
import pyarrow as pa
import urllib.parse
from lancedb.remote import VectorQuery, VectorQueryResult
from lancedb.remote.errors import LanceDBClientError
def _check_not_closed(f):
@functools.wraps(f)
def wrapped(self, *args, **kwargs):
if self.closed:
raise ValueError("Connection is closed")
return f(self, *args, **kwargs)
return wrapped
@attr.define(slots=False)
class RestfulLanceDBClient:
url: str
closed: bool = attr.field(default=False, init=False)
@functools.cached_property
def session(self) -> aiohttp.ClientSession:
parsed = urllib.parse.urlparse(self.url)
scheme = parsed.scheme
if not scheme.startswith("lancedb"):
raise ValueError(
f"Invalid scheme: {scheme}, must be like lancedb+<flavor>://"
)
flavor = scheme.split("+")[1]
url = f"{flavor}://{parsed.hostname}:{parsed.port}"
return aiohttp.ClientSession(url)
async def close(self):
await self.session.close()
self.closed = True
@_check_not_closed
async def query(self, table_name: str, query: VectorQuery) -> VectorQueryResult:
async with self.session.post(
f"/table/{table_name}/", json=query.dict(exclude_none=True)
) as resp:
resp: aiohttp.ClientResponse = resp
if 400 <= resp.status < 500:
raise LanceDBClientError(
f"Bad Request: {resp.status}, error: {await resp.text()}"
)
if 500 <= resp.status < 600:
raise LanceDBClientError(
f"Internal Server Error: {resp.status}, error: {await resp.text()}"
)
if resp.status != 200:
raise LanceDBClientError(
f"Unknown Error: {resp.status}, error: {await resp.text()}"
)
resp_body = await resp.read()
with pa.ipc.open_file(pa.BufferReader(resp_body)) as reader:
tbl = reader.read_all()
return VectorQueryResult(tbl)

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# Copyright 2023 LanceDB Developers
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
class LanceDBClientError(RuntimeError):
pass