diff --git a/chromadb/api/models/AsyncCollection.py b/chromadb/api/models/AsyncCollection.py
index 61a00bdc6b6..350fa27af51 100644
--- a/chromadb/api/models/AsyncCollection.py
+++ b/chromadb/api/models/AsyncCollection.py
@@ -4,13 +4,14 @@
     Union,
     cast,
 )
-import numpy as np
+from numpy.typing import NDArray
 
 from chromadb.api.types import (
     URI,
     CollectionMetadata,
     Embedding,
     Embeddings,
+    EmbeddingDType,
     Include,
     Metadata,
     Document,
@@ -37,7 +38,7 @@ async def add(
         embeddings: Optional[
             Union[
                 OneOrMany[Embedding],
-                OneOrMany[np.ndarray],
+                OneOrMany[NDArray[EmbeddingDType]],
             ]
         ] = None,
         metadatas: Optional[OneOrMany[Metadata]] = None,
@@ -99,7 +100,7 @@ async def get(
         limit: Optional[int] = None,
         offset: Optional[int] = None,
         where_document: Optional[WhereDocument] = None,
-        include: Include = ["metadatas", "documents"],
+        include: Include = ["metadatas", "documents"],  # type: ignore[list-item]
     ) -> GetResult:
         """Get embeddings and their associate data from the data store. If no ids or where filter is provided returns
         all embeddings up to limit starting at offset.
@@ -152,7 +153,7 @@ async def query(
         query_embeddings: Optional[
             Union[
                 OneOrMany[Embedding],
-                OneOrMany[np.ndarray],
+                OneOrMany[NDArray[EmbeddingDType]],
             ]
         ] = None,
         query_texts: Optional[OneOrMany[Document]] = None,
@@ -161,7 +162,7 @@ async def query(
         n_results: int = 10,
         where: Optional[Where] = None,
         where_document: Optional[WhereDocument] = None,
-        include: Include = ["metadatas", "documents", "distances"],
+        include: Include = ["metadatas", "documents", "distances"],  # type: ignore[list-item]
     ) -> QueryResult:
         """Get the n_results nearest neighbor embeddings for provided query_embeddings or query_texts.
 
@@ -240,7 +241,7 @@ async def update(
         embeddings: Optional[
             Union[
                 OneOrMany[Embedding],
-                OneOrMany[np.ndarray],
+                OneOrMany[NDArray[EmbeddingDType]],
             ]
         ] = None,
         metadatas: Optional[OneOrMany[Metadata]] = None,
@@ -284,7 +285,7 @@ async def upsert(
         embeddings: Optional[
             Union[
                 OneOrMany[Embedding],
-                OneOrMany[np.ndarray],
+                OneOrMany[NDArray[EmbeddingDType]],
             ]
         ] = None,
         metadatas: Optional[OneOrMany[Metadata]] = None,
diff --git a/chromadb/api/models/Collection.py b/chromadb/api/models/Collection.py
index 336f2633d97..dc1aeb0dfef 100644
--- a/chromadb/api/models/Collection.py
+++ b/chromadb/api/models/Collection.py
@@ -1,5 +1,6 @@
 from typing import TYPE_CHECKING, Optional, Union, cast
 import numpy as np
+from numpy.typing import NDArray
 
 from chromadb.api.models.CollectionCommon import CollectionCommon
 from chromadb.api.types import (
@@ -7,6 +8,7 @@
     CollectionMetadata,
     Embedding,
     Embeddings,
+    EmbeddingDType,
     Include,
     Metadata,
     Document,
@@ -41,10 +43,10 @@ def count(self) -> int:
     def add(
         self,
         ids: OneOrMany[ID],
-        embeddings: Optional[  # type: ignore[type-arg]
+        embeddings: Optional[
             Union[
                 OneOrMany[Embedding],
-                OneOrMany[np.ndarray],
+                OneOrMany[NDArray[EmbeddingDType]],
             ]
         ] = None,
         metadatas: Optional[OneOrMany[Metadata]] = None,
@@ -97,7 +99,7 @@ def get(
         limit: Optional[int] = None,
         offset: Optional[int] = None,
         where_document: Optional[WhereDocument] = None,
-        include: Include = ["metadatas", "documents"],
+        include: Include = ["metadatas", "documents"],  # type: ignore[list-item]
     ) -> GetResult:
         """Get embeddings and their associate data from the data store. If no ids or where filter is provided returns
         all embeddings up to limit starting at offset.
@@ -159,7 +161,7 @@ def query(
         n_results: int = 10,
         where: Optional[Where] = None,
         where_document: Optional[WhereDocument] = None,
-        include: Include = ["metadatas", "documents", "distances"],
+        include: Include = ["metadatas", "documents", "distances"],  # type: ignore[list-item]
     ) -> QueryResult:
         """Get the n_results nearest neighbor embeddings for provided query_embeddings or query_texts.
 
diff --git a/chromadb/api/models/CollectionCommon.py b/chromadb/api/models/CollectionCommon.py
index a5395920fc8..bc16e4d07f5 100644
--- a/chromadb/api/models/CollectionCommon.py
+++ b/chromadb/api/models/CollectionCommon.py
@@ -10,6 +10,7 @@
     cast,
 )
 import numpy as np
+from numpy.typing import NDArray
 from uuid import UUID
 
 import chromadb.utils.embedding_functions as ef
@@ -19,6 +20,7 @@
     DataLoader,
     Embedding,
     Embeddings,
+    EmbeddingDType,
     Embeddable,
     RecordSet,
     GetResult,
@@ -152,10 +154,10 @@ def get_model(self) -> CollectionModel:
     def _unpack_embedding_set(
         self,
         ids: OneOrMany[ID],
-        embeddings: Optional[  # type: ignore[type-arg]
+        embeddings: Optional[
             Union[
                 OneOrMany[Embedding],
-                OneOrMany[np.ndarray],
+                OneOrMany[NDArray[EmbeddingDType]],
             ]
         ],
         metadatas: Optional[OneOrMany[Metadata]],
@@ -340,7 +342,7 @@ def _validate_and_prepare_query_request(
         valid_query_embeddings = (
             validate_embeddings(
                 self._normalize_embeddings(
-                    maybe_cast_one_to_many_embedding(query_embeddings)  # type: ignore[type-arg]
+                    maybe_cast_one_to_many_embedding(query_embeddings)  # type: ignore[arg-type]
                 )
             )
             if query_embeddings is not None
@@ -429,7 +431,7 @@ def _process_add_request(
         embeddings: Optional[
             Union[
                 OneOrMany[Embedding],
-                OneOrMany[np.ndarray],
+                OneOrMany[NDArray[EmbeddingDType]],
             ]
         ],
         metadatas: Optional[OneOrMany[Metadata]],
diff --git a/chromadb/api/types.py b/chromadb/api/types.py
index 34252543ffb..3d5a6a7225b 100644
--- a/chromadb/api/types.py
+++ b/chromadb/api/types.py
@@ -249,12 +249,7 @@ def __call__(self: EmbeddingFunction[D], input: D) -> Embeddings:
 
             converted = maybe_cast_one_to_many_embedding(result)
 
-            if converted is None:
-                raise ValueError(
-                    "Expected embeddings not to be None"
-                )
-
-            return validate_embeddings(converted)
+            return validate_embeddings(converted)  # type: ignore[arg-type]
 
         setattr(cls, "__call__", __call__)