Bump version: 0.4.1 → 0.4.2

issue separate requests under the hood and concatenate results

.bumpversion.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.4.1
+current_version = 0.4.2
 commit = True
 message = Bump version: {current_version} → {new_version}
 tag = True

Cargo.toml

@@ -5,10 +5,10 @@ exclude = ["python"]
 resolver = "2"
 
 [workspace.dependencies]
-lance = { "version" = "=0.9.1", "features" = ["dynamodb"] }
-lance-index = { "version" = "=0.9.1" }
-lance-linalg = { "version" = "=0.9.1" }
-lance-testing = { "version" = "=0.9.1" }
+lance = { "version" = "=0.9.2", "features" = ["dynamodb"] }
+lance-index = { "version" = "=0.9.2" }
+lance-linalg = { "version" = "=0.9.2" }
+lance-testing = { "version" = "=0.9.2" }
 # Note that this one does not include pyarrow
 arrow = { version = "49.0.0", optional = false }
 arrow-array = "49.0"

docs/src/python/pydantic.md

@@ -7,7 +7,7 @@ LanceDB integrates with Pydantic for schema inference, data ingestion, and query
 
 LanceDB supports to create Apache Arrow Schema from a
 [Pydantic BaseModel](https://docs.pydantic.dev/latest/api/main/#pydantic.main.BaseModel)
-via [pydantic_to_schema()](python.md##lancedb.pydantic.pydantic_to_schema) method.
+via [pydantic_to_schema()](python.md#lancedb.pydantic.pydantic_to_schema) method.
 
 ::: lancedb.pydantic.pydantic_to_schema
 

node/package.json

@@ -1,6 +1,6 @@
 {
   "name": "vectordb",
-  "version": "0.4.1",
+  "version": "0.4.2",
   "description": " Serverless, low-latency vector database for AI applications",
   "main": "dist/index.js",
   "types": "dist/index.d.ts",
@@ -81,10 +81,10 @@
     }
   },
   "optionalDependencies": {
-    "@lancedb/vectordb-darwin-arm64": "0.4.1",
-    "@lancedb/vectordb-darwin-x64": "0.4.1",
-    "@lancedb/vectordb-linux-arm64-gnu": "0.4.1",
-    "@lancedb/vectordb-linux-x64-gnu": "0.4.1",
-    "@lancedb/vectordb-win32-x64-msvc": "0.4.1"
+    "@lancedb/vectordb-darwin-arm64": "0.4.2",
+    "@lancedb/vectordb-darwin-x64": "0.4.2",
+    "@lancedb/vectordb-linux-arm64-gnu": "0.4.2",
+    "@lancedb/vectordb-linux-x64-gnu": "0.4.2",
+    "@lancedb/vectordb-win32-x64-msvc": "0.4.2"
   }
 }

python/.bumpversion.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.4.2
+current_version = 0.4.3
 commit = True
 message = [python] Bump version: {current_version} → {new_version}
 tag = True

python/lancedb/query.py

@@ -70,7 +70,7 @@ class Query(pydantic.BaseModel):
     vector_column: str = VECTOR_COLUMN_NAME
 
     # vector to search for
-    vector: List[float]
+    vector: Union[List[float], List[List[float]]]
 
     # sql filter to refine the query with
     filter: Optional[str] = None
@@ -421,6 +421,8 @@ class LanceVectorQueryBuilder(LanceQueryBuilder):
         vector and the returned vectors.
         """
         vector = self._query if isinstance(self._query, list) else self._query.tolist()
+        if isinstance(vector[0], np.ndarray):
+            vector = [v.tolist() for v in vector]
         query = Query(
             vector=vector,
             filter=self._where,

python/lancedb/remote/table.py

@@ -11,6 +11,7 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 
+import asyncio
 import uuid
 from functools import cached_property
 from typing import Dict, Optional, Union
@@ -227,8 +228,24 @@ class RemoteTable(Table):
         return LanceVectorQueryBuilder(self, query, vector_column_name)
 
     def _execute_query(self, query: Query) -> pa.Table:
-        result = self._conn._client.query(self._name, query)
-        return self._conn._loop.run_until_complete(result).to_arrow()
+        if (
+            query.vector is not None
+            and len(query.vector) > 0
+            and not isinstance(query.vector[0], float)
+        ):
+            futures = []
+            for v in query.vector:
+                v = list(v)
+                q = query.copy()
+                q.vector = v
+                futures.append(self._conn._client.query(self._name, q))
+            result = self._conn._loop.run_until_complete(asyncio.gather(*futures))
+            return pa.concat_tables(
+                [add_index(r.to_arrow(), i) for i, r in enumerate(result)]
+            )
+        else:
+            result = self._conn._client.query(self._name, query)
+            return self._conn._loop.run_until_complete(result).to_arrow()
 
     def delete(self, predicate: str):
         """Delete rows from the table.
@@ -342,3 +359,11 @@ class RemoteTable(Table):
         self._conn._loop.run_until_complete(
             self._conn._client.post(f"/v1/table/{self._name}/update/", data=payload)
         )
+
+
+def add_index(tbl: pa.Table, i: int) -> pa.Table:
+    return tbl.add_column(
+        0,
+        pa.field("query_index", pa.uint32()),
+        pa.array([i] * len(tbl), pa.uint32()),
+    )

python/pyproject.toml

@@ -1,9 +1,9 @@
 [project]
 name = "lancedb"
-version = "0.4.2"
+version = "0.4.3"
 dependencies = [
     "deprecation",
-    "pylance==0.9.1",
+    "pylance==0.9.2",
     "ratelimiter~=1.0",
     "retry>=0.9.2",
     "tqdm>=4.27.0",

rust/ffi/node/Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "vectordb-node"
-version = "0.4.1"
+version = "0.4.2"
 description = "Serverless, low-latency vector database for AI applications"
 license = "Apache-2.0"
 edition = "2018"

rust/vectordb/Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "vectordb"
-version = "0.4.1"
+version = "0.4.2"
 edition = "2021"
 description = "LanceDB: A serverless, low-latency vector database for AI applications"
 license = "Apache-2.0"