new: deprecate upload records, update tests, prohibit migration of co…

qdrant_client/async_client_base.py

@@ -277,6 +277,11 @@ def upload_records(
     ) -> None:
         raise NotImplementedError()
 
+    async def upload_points(
+        self, collection_name: str, points: Iterable[types.PointStruct], **kwargs: Any
+    ) -> None:
+        raise NotImplementedError()
+
     def upload_collection(
         self,
         collection_name: str,

qdrant_client/async_qdrant_client.py

@@ -9,6 +9,7 @@
 #
 # ******  WARNING: THIS FILE IS AUTOGENERATED  ******
 
+import warnings
 from typing import Any, Dict, Iterable, List, Mapping, Optional, Sequence, Tuple, Union
 
 from qdrant_client import grpc as grpc
@@ -1741,6 +1742,11 @@ def upload_records(
                 This parameter overwrites shard keys written in the records.
 
         """
+        warnings.warn(
+            "`upload_records` is deprecated, use `upload_points` instead",
+            DeprecationWarning,
+            stacklevel=2,
+        )
         assert len(kwargs) == 0, f"Unknown arguments: {list(kwargs.keys())}"
         return self._client.upload_records(
             collection_name=collection_name,
@@ -1751,7 +1757,53 @@ def upload_records(
             max_retries=max_retries,
             wait=wait,
             shard_key_selector=shard_key_selector,
-            **kwargs,
+        )
+
+    async def upload_points(
+        self,
+        collection_name: str,
+        points: Iterable[types.PointStruct],
+        batch_size: int = 64,
+        parallel: int = 1,
+        method: Optional[str] = None,
+        max_retries: int = 3,
+        wait: bool = False,
+        shard_key_selector: Optional[types.ShardKeySelector] = None,
+        **kwargs: Any,
+    ) -> None:
+        """Upload points to the collection
+
+        Similar to `upload_collection` method, but operates with points, rather than vector and payload individually.
+
+        Args:
+            collection_name:  Name of the collection to upload to
+            points: Iterator over points to upload
+            batch_size: How many vectors upload per-request, Default: 64
+            parallel: Number of parallel processes of upload
+            method: Start method for parallel processes, Default: forkserver
+            max_retries: maximum number of retries in case of a failure
+                during the upload of a batch
+            wait:
+                Await for the results to be applied on the server side.
+                If `true`, each update request will explicitly wait for the confirmation of completion. Might be slower.
+                If `false`, each update request will return immediately after the confirmation of receiving.
+                Default: `false`
+            shard_key_selector: Defines the shard groups that should be used to write updates into.
+                If multiple shard_keys are provided, the update will be written to each of them.
+                Only works for collections with `custom` sharding method.
+                This parameter overwrites shard keys written in the records.
+
+        """
+        assert len(kwargs) == 0, f"Unknown arguments: {list(kwargs.keys())}"
+        return await self._client.upload_points(
+            collection_name=collection_name,
+            points=points,
+            batch_size=batch_size,
+            parallel=parallel,
+            method=method,
+            max_retries=max_retries,
+            wait=wait,
+            shard_key_selector=shard_key_selector,
         )
 
     def upload_collection(
@@ -1806,7 +1858,6 @@ def upload_collection(
             max_retries=max_retries,
             wait=wait,
             shard_key_selector=shard_key_selector,
-            **kwargs,
         )
 
     async def create_payload_index(

qdrant_client/async_qdrant_fastembed.py

@@ -13,8 +13,6 @@
 from itertools import tee
 from typing import Any, Dict, Iterable, List, Optional, Tuple, Union
 
-from pydantic import BaseModel
-
 from qdrant_client.async_client_base import AsyncQdrantBase
 from qdrant_client.conversions import common_types as types
 from qdrant_client.fastembed_common import QueryResponse
@@ -172,13 +170,13 @@ def _scored_points_to_query_responses(
             )
         return response
 
-    def _records_iterator(
+    def _points_iterator(
         self,
         ids: Optional[Iterable[models.ExtendedPointId]],
         metadata: Optional[Iterable[Dict[str, Any]]],
         encoded_docs: Iterable[Tuple[str, List[float]]],
         ids_accumulator: list,
-    ) -> Iterable[models.Record]:
+    ) -> Iterable[models.PointStruct]:
         if ids is None:
             ids = iter(lambda: uuid.uuid4().hex, None)
         if metadata is None:
@@ -187,7 +185,7 @@ def _records_iterator(
         for idx, meta, (doc, vector) in zip(ids, metadata, encoded_docs):
             ids_accumulator.append(idx)
             payload = {"document": doc, **meta}
-            yield models.Record(id=idx, payload=payload, vector={vector_name: vector})
+            yield models.PointStruct(id=idx, payload=payload, vector={vector_name: vector})
 
     def get_fastembed_vector_params(
         self,
@@ -289,12 +287,12 @@ async def add(
             distance == vector_params.distance
         ), f"Distance mismatch: {distance} != {vector_params.distance}"
         inserted_ids: list = []
-        records = self._records_iterator(
+        points = self._points_iterator(
             ids=ids, metadata=metadata, encoded_docs=encoded_docs, ids_accumulator=inserted_ids
         )
-        self.upload_records(
+        await self.upload_points(
             collection_name=collection_name,
-            records=records,
+            points=points,
             wait=True,
             parallel=parallel or 1,
             batch_size=batch_size,

qdrant_client/async_qdrant_remote.py

@@ -2054,6 +2054,31 @@ def upload_records(
             wait=wait,
         )
 
+    async def upload_points(
+        self,
+        collection_name: str,
+        points: Iterable[types.PointStruct],
+        batch_size: int = 64,
+        parallel: int = 1,
+        method: Optional[str] = None,
+        max_retries: int = 3,
+        wait: bool = False,
+        shard_key_selector: Optional[types.ShardKeySelector] = None,
+        **kwargs: Any,
+    ) -> None:
+        batches_iterator = self._updater_class.iterate_records_batches(
+            records=points, batch_size=batch_size
+        )
+        self._upload_collection(
+            batches_iterator=batches_iterator,
+            collection_name=collection_name,
+            max_retries=max_retries,
+            parallel=parallel,
+            method=method,
+            wait=wait,
+            shard_key_selector=shard_key_selector,
+        )
+
     def upload_collection(
         self,
         collection_name: str,

qdrant_client/client_base.py

@@ -296,6 +296,14 @@ def upload_records(
     ) -> None:
         raise NotImplementedError()
 
+    def upload_points(
+        self,
+        collection_name: str,
+        points: Iterable[types.PointStruct],
+        **kwargs: Any,
+    ) -> None:
+        raise NotImplementedError()
+
     def upload_collection(
         self,
         collection_name: str,

qdrant_client/conversions/common_types.py

@@ -8,7 +8,7 @@
 else:
     from typing_extensions import TypeAlias
 
-from typing import List, Tuple, Union, get_args
+from typing import List, Union, get_args
 
 from qdrant_client import grpc as grpc
 from qdrant_client.http import models as rest
@@ -53,6 +53,7 @@ def get_args_subscribed(tp: type):  # type: ignore
 PayloadSchemaType = Union[
     rest.PayloadSchemaType, rest.PayloadSchemaParams, int, grpc.PayloadIndexParams
 ]  # type(grpc.PayloadSchemaType) == int
+PointStruct: TypeAlias = rest.PointStruct
 Points = Union[rest.Batch, List[Union[rest.PointStruct, grpc.PointStruct]]]
 PointsSelector = Union[
     List[PointId], rest.Filter, grpc.Filter, rest.PointsSelector, grpc.PointsSelector

qdrant_client/local/async_qdrant_local.py

@@ -15,7 +15,19 @@
 import os
 import shutil
 from io import TextIOWrapper
-from typing import Any, Dict, Iterable, List, Mapping, Optional, Sequence, Tuple, Union
+from typing import (
+    Any,
+    Dict,
+    Generator,
+    Iterable,
+    List,
+    Mapping,
+    Optional,
+    Sequence,
+    Tuple,
+    Union,
+)
+from uuid import uuid4
 
 import numpy as np
 import portalocker
@@ -643,16 +655,26 @@ async def recreate_collection(
             collection_name, vectors_config, init_from, sparse_vectors_config
         )
 
+    async def upload_points(
+        self, collection_name: str, points: Iterable[types.PointStruct], **kwargs: Any
+    ) -> None:
+        self._upload_points(collection_name, points)
+
     def upload_records(
         self, collection_name: str, records: Iterable[types.Record], **kwargs: Any
+    ) -> None:
+        self._upload_points(collection_name, records)
+
+    def _upload_points(
+        self, collection_name: str, points: Iterable[Union[types.PointStruct, types.Record]]
     ) -> None:
         collection = self._get_collection(collection_name)
         collection.upsert(
             [
                 rest_models.PointStruct(
-                    id=record.id, vector=record.vector or {}, payload=record.payload or {}
+                    id=point.id, vector=point.vector or {}, payload=point.payload or {}
                 )
-                for record in records
+                for point in points
             ]
         )
 
@@ -666,6 +688,10 @@ def upload_collection(
         ids: Optional[Iterable[types.PointId]] = None,
         **kwargs: Any,
     ) -> None:
+        def uuid_generator() -> Generator[str, None, None]:
+            while True:
+                yield str(uuid4())
+
         collection = self._get_collection(collection_name)
         if isinstance(vectors, dict) and any(
             (isinstance(v, np.ndarray) for v in vectors.values())
@@ -686,7 +712,7 @@ def upload_collection(
                     payload=payload or {},
                 )
                 for (point_id, vector, payload) in zip(
-                    ids or itertools.count(), iter(vectors), payload or itertools.cycle([{}])
+                    ids or uuid_generator(), iter(vectors), payload or itertools.cycle([{}])
                 )
             ]
         )

qdrant_client/local/qdrant_local.py

@@ -4,7 +4,19 @@
 import os
 import shutil
 from io import TextIOWrapper
-from typing import Any, Dict, Iterable, List, Mapping, Optional, Sequence, Tuple, Union
+from typing import (
+    Any,
+    Dict,
+    Generator,
+    Iterable,
+    List,
+    Mapping,
+    Optional,
+    Sequence,
+    Tuple,
+    Union,
+)
+from uuid import uuid4
 
 import numpy as np
 import portalocker
@@ -643,7 +655,10 @@ def create_collection(
         if src_collection and from_collection_name:
             batch_size = 100
             records, next_offset = self.scroll(from_collection_name, limit=2, with_vectors=True)
-            self.upload_records(collection_name, records)
+            self.upload_records(
+                collection_name, records
+            )  # it is not crucial to replace upload_records here
+            # since it is an internal usage, and we don't have custom shard keys in qdrant local
             while next_offset is not None:
                 records, next_offset = self.scroll(
                     from_collection_name, offset=next_offset, limit=batch_size, with_vectors=True
@@ -666,20 +681,31 @@ def recreate_collection(
             collection_name, vectors_config, init_from, sparse_vectors_config
         )
 
+    def upload_points(
+        self, collection_name: str, points: Iterable[types.PointStruct], **kwargs: Any
+    ) -> None:
+        self._upload_points(collection_name, points)
+
     def upload_records(
         self, collection_name: str, records: Iterable[types.Record], **kwargs: Any
     ) -> None:
         # upload_records in local mode behaves like upload_records with wait=True in server mode
+        self._upload_points(collection_name, records)
 
+    def _upload_points(
+        self,
+        collection_name: str,
+        points: Iterable[Union[types.PointStruct, types.Record]],
+    ) -> None:
         collection = self._get_collection(collection_name)
         collection.upsert(
             [
                 rest_models.PointStruct(
-                    id=record.id,
-                    vector=record.vector or {},
-                    payload=record.payload or {},
+                    id=point.id,
+                    vector=point.vector or {},
+                    payload=point.payload or {},
                 )
-                for record in records
+                for point in points
             ]
         )
 
@@ -694,6 +720,9 @@ def upload_collection(
         **kwargs: Any,
     ) -> None:
         # upload_collection in local mode behaves like upload_collection with wait=True in server mode
+        def uuid_generator() -> Generator[str, None, None]:
+            while True:
+                yield str(uuid4())
 
         collection = self._get_collection(collection_name)
         if isinstance(vectors, dict) and any(isinstance(v, np.ndarray) for v in vectors.values()):
@@ -716,7 +745,7 @@ def upload_collection(
                     payload=payload or {},
                 )
                 for (point_id, vector, payload) in zip(
-                    ids or itertools.count(),
+                    ids or uuid_generator(),
                     iter(vectors),
                     payload or itertools.cycle([{}]),
                 )