add support for numpy2.0

chromadb/api/types.py

@@ -103,7 +103,7 @@ def maybe_cast_one_to_many_document(target: OneOrMany[Document]) -> Documents:
 
 
 # Images
-ImageDType = Union[np.uint, np.int_, np.float_]  # type: ignore[name-defined]
+ImageDType = Union[np.uint, np.int_, np.float64]
 Image = NDArray[ImageDType]
 Images = List[Image]
 

chromadb/test/ef/test_multimodal_ef.py

@@ -17,7 +17,7 @@
 # then hashes them to a fixed dimension.
 class hashing_multimodal_ef(EmbeddingFunction[Embeddable]):
     def __init__(self) -> None:
-        self._hef = hashing_embedding_function(dim=10, dtype=np.float_)
+        self._hef = hashing_embedding_function(dim=10, dtype=np.float64)
 
     def __call__(self, input: Embeddable) -> Embeddings:
         to_texts = [str(i) for i in input]
@@ -82,7 +82,7 @@ def test_multimodal(
 
     # get() should return all the documents and images
     # ids corresponding to images should not have documents
-    get_result = multimodal_collection.get(include=["documents"])
+    get_result = multimodal_collection.get(include=["documents"])  # type: ignore[list-item]
     assert len(get_result["ids"]) == len(document_ids) + len(image_ids)
     for i, id in enumerate(get_result["ids"]):
         assert id in document_ids or id in image_ids
@@ -124,14 +124,14 @@ def test_multimodal(
 
     # Query with images
     query_result = multimodal_collection.query(
-        query_images=[query_image], n_results=n_query_results, include=["documents"]
+        query_images=[query_image], n_results=n_query_results, include=["documents"]  # type: ignore[list-item]
     )
 
     assert query_result["ids"][0] == nearest_image_neighbor_ids
 
     # Query with documents
     query_result = multimodal_collection.query(
-        query_texts=[query_document], n_results=n_query_results, include=["documents"]
+        query_texts=[query_document], n_results=n_query_results, include=["documents"]  # type: ignore[list-item]
     )
 
     assert query_result["ids"][0] == nearest_document_neighbor_ids
@@ -152,6 +152,6 @@ def test_multimodal_update_with_image(
 
     multimodal_collection.update(ids=id, images=image)
 
-    get_result = multimodal_collection.get(ids=id, include=["documents"])
+    get_result = multimodal_collection.get(ids=id, include=["documents"])  # type: ignore[list-item]
     assert get_result["documents"] is not None
     assert get_result["documents"][0] is None

pyproject.toml

@@ -20,10 +20,10 @@ dependencies = [
   'chroma-hnswlib==0.7.6',
   'fastapi >= 0.95.2',
   'uvicorn[standard] >= 0.18.3',
-  'numpy >= 1.22.5',
+  'numpy >= 2.0.0',
   'posthog >= 2.4.0',
   'typing_extensions >= 4.5.0',
-  'onnxruntime >= 1.14.1',
+  'onnxruntime >= 1.19.0',
   'opentelemetry-api>=1.2.0',
   'opentelemetry-exporter-otlp-proto-grpc>=1.2.0',
   'opentelemetry-instrumentation-fastapi>=0.41b0',

requirements.txt

@@ -7,8 +7,8 @@ httpx>=0.27.0
 importlib-resources
 kubernetes>=28.1.0
 mmh3>=4.0.1
-numpy>=1.22.5, <2.0.0
-onnxruntime>=1.14.1
+numpy>=2.0.0
+onnxruntime>=1.19.0
 opentelemetry-api>=1.2.0
 opentelemetry-exporter-otlp-proto-grpc>=1.24.0
 opentelemetry-instrumentation-fastapi>=0.41b0