diff --git a/.github/workflows/lint.yml b/.github/workflows/lint.yml
index 74a1477b..dff2153a 100644
--- a/.github/workflows/lint.yml
+++ b/.github/workflows/lint.yml
@@ -25,7 +25,9 @@ jobs:
         # so linting on fewer versions makes CI faster.
         python-version:
           - "3.9"
+          - "3.10"
           - "3.11"
+          - "3.12"
 
     steps:
     - uses: actions/checkout@v2
diff --git a/.github/workflows/run_tests.yml b/.github/workflows/run_tests.yml
index e155c1ce..eed80b64 100644
--- a/.github/workflows/run_tests.yml
+++ b/.github/workflows/run_tests.yml
@@ -18,7 +18,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: [3.9, '3.10', 3.11]
+        python-version: [3.9, '3.10', 3.11, 3.12]
         connection: ['hiredis', 'plain']
         redis-stack-version: ['6.2.6-v9', 'latest', 'edge']
 
@@ -75,12 +75,12 @@ jobs:
         AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }}
         AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
       run: |
-        poetry run test-cov
+        poetry run test-verbose
 
     - name: Run tests
       if: matrix.connection != 'plain' || matrix.redis-stack-version != 'latest'
       run: |
-        SKIP_VECTORIZERS=True SKIP_RERANKERS=True poetry run test-cov
+        SKIP_VECTORIZERS=True SKIP_RERANKERS=True poetry run test-verbose
 
     - name: Run notebooks
       if: matrix.connection == 'plain' && matrix.redis-stack-version == 'latest'
diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md
index b0c4cd03..7b35b96b 100644
--- a/CONTRIBUTING.md
+++ b/CONTRIBUTING.md
@@ -78,17 +78,17 @@ To run Testcontainers-based tests you need a local Docker installation such as:
 
 Tests w/ vectorizers:
 ```bash
-poetry run test-cov
+poetry run test-verbose
 ```
 
 Tests w/out vectorizers:
 ```bash
-SKIP_VECTORIZERS=true poetry run test-cov
+SKIP_VECTORIZERS=true poetry run test-verbose
 ```
 
 Tests w/out rerankers:
 ```bash
-SKIP_RERANKERS=true poetry run test-cov
+SKIP_RERANKERS=true poetry run test-verbose
 ```
 
 ### Documentation
diff --git a/Makefile b/Makefile
index ae0069b1..1451a2f5 100644
--- a/Makefile
+++ b/Makefile
@@ -19,10 +19,10 @@ check-types:
 lint: format check-types
 	
 test:
-	SKIP_RERANKERS=true SKIP_VECTORIZERS=true poetry run test-cov
+	SKIP_RERANKERS=true SKIP_VECTORIZERS=true poetry run test-verbose
 	
 test-all:
-	poetry run test-cov
+	poetry run test-verbose
 
 check: lint test
 
diff --git a/conftest.py b/conftest.py
index 7c4a98d9..befe56cd 100644
--- a/conftest.py
+++ b/conftest.py
@@ -1,34 +1,55 @@
 import os
 import pytest
-import asyncio
 
 from redisvl.redis.connection import RedisConnectionFactory
 from testcontainers.compose import DockerCompose
 
 
+@pytest.fixture(autouse=True)
+def set_tokenizers_parallelism():
+    """Disable tokenizers parallelism in tests to avoid deadlocks"""
+    os.environ["TOKENIZERS_PARALLELISM"] = "false"
+
 
 @pytest.fixture(scope="session", autouse=True)
-def redis_container():
-    # Set the default Redis version if not already set
+def redis_container(request):
+    """
+    Create a unique Compose project for each xdist worker by setting
+    COMPOSE_PROJECT_NAME. That prevents collisions on container/volume names.
+    """
+    # In xdist, the config has "workerid" in workerinput
+    worker_id = request.config.workerinput.get("workerid", "master")
+
+    # Set the Compose project name so containers do not clash across workers
+    os.environ["COMPOSE_PROJECT_NAME"] = f"redis_test_{worker_id}"
     os.environ.setdefault("REDIS_VERSION", "edge")
 
-    compose = DockerCompose("tests", compose_file_name="docker-compose.yml", pull=True)
+    compose = DockerCompose(
+        context="tests",
+        compose_file_name="docker-compose.yml",
+        pull=True,
+    )
     compose.start()
 
-    redis_host, redis_port = compose.get_service_host_and_port("redis", 6379)
-    redis_url = f"redis://{redis_host}:{redis_port}"
-    os.environ["REDIS_URL"] = redis_url
-
     yield compose
 
     compose.stop()
 
+
 @pytest.fixture(scope="session")
-def redis_url():
-    return os.getenv("REDIS_URL", "redis://localhost:6379")
+def redis_url(redis_container):
+    """
+    Use the `DockerCompose` fixture to get host/port of the 'redis' service
+    on container port 6379 (mapped to an ephemeral port on the host).
+    """
+    host, port = redis_container.get_service_host_and_port("redis", 6379)
+    return f"redis://{host}:{port}"
 
 @pytest.fixture
 async def async_client(redis_url):
+    """
+    An async Redis client that uses the dynamic `redis_url`.
+    """
     client = await RedisConnectionFactory.get_async_redis_connection(redis_url)
     yield client
     try:
@@ -38,8 +59,11 @@ async def async_client(redis_url):
             raise
 
 @pytest.fixture
-def client():
-    conn = RedisConnectionFactory.get_redis_connection(os.environ["REDIS_URL"])
+def client(redis_url):
+    """
+    A sync Redis client that uses the dynamic `redis_url`.
+    """
+    conn = RedisConnectionFactory.get_redis_connection(redis_url)
     yield conn
     conn.close()
 
diff --git a/poetry.lock b/poetry.lock
index 1a3167fb..f7d432a6 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -339,13 +339,13 @@ files = [
 
 [[package]]
 name = "attrs"
-version = "24.3.0"
+version = "25.1.0"
 description = "Classes Without Boilerplate"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "attrs-24.3.0-py3-none-any.whl", hash = "sha256:ac96cd038792094f438ad1f6ff80837353805ac950cd2aa0e0625ef19850c308"},
-    {file = "attrs-24.3.0.tar.gz", hash = "sha256:8f5c07333d543103541ba7be0e2ce16eeee8130cb0b3f9238ab904ce1e85baff"},
+    {file = "attrs-25.1.0-py3-none-any.whl", hash = "sha256:c75a69e28a550a7e93789579c22aa26b0f5b83b75dc4e08fe092980051e1090a"},
+    {file = "attrs-25.1.0.tar.gz", hash = "sha256:1c97078a80c814273a76b2a298a932eb681c87415c11dee0a6921de7f1b02c3e"},
 ]
 
 [package.extras]
@@ -358,31 +358,32 @@ tests-mypy = ["mypy (>=1.11.1)", "pytest-mypy-plugins"]
 
 [[package]]
 name = "babel"
-version = "2.16.0"
+version = "2.17.0"
 description = "Internationalization utilities"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "babel-2.16.0-py3-none-any.whl", hash = "sha256:368b5b98b37c06b7daf6696391c3240c938b37767d4584413e8438c5c435fa8b"},
-    {file = "babel-2.16.0.tar.gz", hash = "sha256:d1f3554ca26605fe173f3de0c65f750f5a42f924499bf134de6423582298e316"},
+    {file = "babel-2.17.0-py3-none-any.whl", hash = "sha256:4d0b53093fdfb4b21c92b5213dba5a1b23885afa8383709427046b21c366e5f2"},
+    {file = "babel-2.17.0.tar.gz", hash = "sha256:0c54cffb19f690cdcc52a3b50bcbf71e07a808d1c80d549f2459b9d2cf0afb9d"},
 ]
 
 [package.extras]
-dev = ["freezegun (>=1.0,<2.0)", "pytest (>=6.0)", "pytest-cov"]
+dev = ["backports.zoneinfo", "freezegun (>=1.0,<2.0)", "jinja2 (>=3.0)", "pytest (>=6.0)", "pytest-cov", "pytz", "setuptools", "tzdata"]
 
 [[package]]
 name = "beautifulsoup4"
-version = "4.12.3"
+version = "4.13.3"
 description = "Screen-scraping library"
 optional = false
-python-versions = ">=3.6.0"
+python-versions = ">=3.7.0"
 files = [
-    {file = "beautifulsoup4-4.12.3-py3-none-any.whl", hash = "sha256:b80878c9f40111313e55da8ba20bdba06d8fa3969fc68304167741bbf9e082ed"},
-    {file = "beautifulsoup4-4.12.3.tar.gz", hash = "sha256:74e3d1928edc070d21748185c46e3fb33490f22f52a3addee9aee0f4f7781051"},
+    {file = "beautifulsoup4-4.13.3-py3-none-any.whl", hash = "sha256:99045d7d3f08f91f0d656bc9b7efbae189426cd913d830294a15eefa0ea4df16"},
+    {file = "beautifulsoup4-4.13.3.tar.gz", hash = "sha256:1bd32405dacc920b42b83ba01644747ed77456a65760e285fbc47633ceddaf8b"},
 ]
 
 [package.dependencies]
 soupsieve = ">1.2"
+typing-extensions = ">=4.0.0"
 
 [package.extras]
 cchardet = ["cchardet"]
@@ -393,33 +394,33 @@ lxml = ["lxml"]
 
 [[package]]
 name = "black"
-version = "24.10.0"
+version = "25.1.0"
 description = "The uncompromising code formatter."
 optional = false
 python-versions = ">=3.9"
 files = [
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-    {file = "black-24.10.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:1c536fcf674217e87b8cc3657b81809d3c085d7bf3ef262ead700da345bfa6ea"},
-    {file = "black-24.10.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:649fff99a20bd06c6f727d2a27f401331dc0cc861fb69cde910fe95b01b5928f"},
-    {file = "black-24.10.0-cp310-cp310-win_amd64.whl", hash = "sha256:fe4d6476887de70546212c99ac9bd803d90b42fc4767f058a0baa895013fbb3e"},
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+    {file = "black-25.1.0.tar.gz", hash = "sha256:33496d5cd1222ad73391352b4ae8da15253c5de89b93a80b3e2c8d9a19ec2666"},
 ]
 
 [package.dependencies]
@@ -457,32 +458,32 @@ css = ["tinycss2 (>=1.1.0,<1.5)"]
 
 [[package]]
 name = "boto3"
-version = "1.35.97"
+version = "1.36.13"
 description = "The AWS SDK for Python"
 optional = true
 python-versions = ">=3.8"
 files = [
-    {file = "boto3-1.35.97-py3-none-any.whl", hash = "sha256:8e49416216a6e3a62c2a0c44fba4dd2852c85472e7b702516605b1363867d220"},
-    {file = "boto3-1.35.97.tar.gz", hash = "sha256:7d398f66a11e67777c189d1f58c0a75d9d60f98d0ee51b8817e828930bf19e4e"},
+    {file = "boto3-1.36.13-py3-none-any.whl", hash = "sha256:20d97739cea1b0f549e9096c453ac727a350da28bd0451098714260b655a85ea"},
+    {file = "boto3-1.36.13.tar.gz", hash = "sha256:c8031aa1c4a7c331081b2d86c49a362654b86e0b89d0a41fa166a68b226f4aba"},
 ]
 
 [package.dependencies]
-botocore = ">=1.35.97,<1.36.0"
+botocore = ">=1.36.13,<1.37.0"
 jmespath = ">=0.7.1,<2.0.0"
-s3transfer = ">=0.10.0,<0.11.0"
+s3transfer = ">=0.11.0,<0.12.0"
 
 [package.extras]
 crt = ["botocore[crt] (>=1.21.0,<2.0a0)"]
 
 [[package]]
 name = "botocore"
-version = "1.35.97"
+version = "1.36.13"
 description = "Low-level, data-driven core of boto 3."
 optional = true
 python-versions = ">=3.8"
 files = [
-    {file = "botocore-1.35.97-py3-none-any.whl", hash = "sha256:fed4f156b1a9b8ece53738f702ba5851b8c6216b4952de326547f349cc494f14"},
-    {file = "botocore-1.35.97.tar.gz", hash = "sha256:88f2fab29192ffe2f2115d5bafbbd823ff4b6eb2774296e03ec8b5b0fe074f61"},
+    {file = "botocore-1.36.13-py3-none-any.whl", hash = "sha256:d644a814440bf8d55f4e29b1c0e6f021e2573b7784e0c91f55f4d9d689e08005"},
+    {file = "botocore-1.36.13.tar.gz", hash = "sha256:50a3ff292f8dfdde21074b5c916afe847b01e074ab16d9c9fe71b34960c77134"},
 ]
 
 [package.dependencies]
@@ -494,28 +495,28 @@ urllib3 = [
 ]
 
 [package.extras]
-crt = ["awscrt (==0.22.0)"]
+crt = ["awscrt (==0.23.8)"]
 
 [[package]]
 name = "cachetools"
-version = "5.5.0"
+version = "5.5.1"
 description = "Extensible memoizing collections and decorators"
 optional = true
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-version = "2024.12.14"
+version = "2025.1.31"
 description = "Python package for providing Mozilla's CA Bundle."
 optional = false
 python-versions = ">=3.6"
 files = [
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 [[package]]
@@ -714,20 +715,19 @@ colorama = {version = "*", markers = "platform_system == \"Windows\""}
 
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 name = "cohere"
-version = "5.13.6"
+version = "5.13.11"
 description = ""
 optional = true
 python-versions = "<4.0,>=3.9"
 files = [
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 pydantic = ">=1.9.2"
 pydantic-core = ">=2.18.2,<3.0.0"
 requests = ">=2.0.0,<3.0.0"
@@ -780,83 +780,6 @@ traitlets = ">=4"
 [package.extras]
 test = ["pytest"]
 
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-
-[package.extras]
-toml = ["tomli"]
-
 [[package]]
 name = "cryptography"
 version = "43.0.3"
@@ -908,37 +831,37 @@ test-randomorder = ["pytest-randomly"]
 
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 [[package]]
@@ -1071,15 +994,29 @@ files = [
 [package.extras]
 test = ["pytest (>=6)"]
 
+[[package]]
+name = "execnet"
+version = "2.1.1"
+description = "execnet: rapid multi-Python deployment"
+optional = false
+python-versions = ">=3.8"
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+[package.extras]
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+
 [[package]]
 name = "executing"
-version = "2.1.0"
+version = "2.2.0"
 description = "Get the currently executing AST node of a frame, and other information"
 optional = false
 python-versions = ">=3.8"
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 ]
 
 [package.extras]
@@ -1147,18 +1084,18 @@ devel = ["colorama", "json-spec", "jsonschema", "pylint", "pytest", "pytest-benc
 
 [[package]]
 name = "filelock"
-version = "3.16.1"
+version = "3.17.0"
 description = "A platform independent file lock."
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-python-versions = ">=3.8"
+python-versions = ">=3.9"
 files = [
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 ]
 
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 typing = ["typing-extensions (>=4.12.2)"]
 
 [[package]]
@@ -1275,13 +1212,13 @@ files = [
 
 [[package]]
 name = "fsspec"
-version = "2024.12.0"
+version = "2025.2.0"
 description = "File-system specification"
 optional = true
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.extras]
@@ -1308,19 +1245,19 @@ sftp = ["paramiko"]
 smb = ["smbprotocol"]
 ssh = ["paramiko"]
 test = ["aiohttp (!=4.0.0a0,!=4.0.0a1)", "numpy", "pytest", "pytest-asyncio (!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "requests"]
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+test-downstream = ["aiobotocore (>=2.5.4,<3.0.0)", "dask[dataframe,test]", "moto[server] (>4,<5)", "pytest-timeout", "xarray"]
 test-full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "cloudpickle", "dask", "distributed", "dropbox", "dropboxdrivefs", "fastparquet", "fusepy", "gcsfs", "jinja2", "kerchunk", "libarchive-c", "lz4", "notebook", "numpy", "ocifs", "pandas", "panel", "paramiko", "pyarrow", "pyarrow (>=1)", "pyftpdlib", "pygit2", "pytest", "pytest-asyncio (!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "python-snappy", "requests", "smbprotocol", "tqdm", "urllib3", "zarr", "zstandard"]
 tqdm = ["tqdm"]
 
 [[package]]
 name = "google-api-core"
-version = "2.24.0"
+version = "2.24.1"
 description = "Google API client core library"
 optional = true
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.dependencies]
@@ -1346,13 +1283,13 @@ grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0.dev0)"]
 
 [[package]]
 name = "google-auth"
-version = "2.37.0"
+version = "2.38.0"
 description = "Google Authentication Library"
 optional = true
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.dependencies]
@@ -1370,13 +1307,13 @@ requests = ["requests (>=2.20.0,<3.0.0.dev0)"]
 
 [[package]]
 name = "google-cloud-aiplatform"
-version = "1.76.0"
+version = "1.79.0"
 description = "Vertex AI API client library"
 optional = true
 python-versions = ">=3.8"
 files = [
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+    {file = "google_cloud_aiplatform-1.79.0-py2.py3-none-any.whl", hash = "sha256:e52d518c386ce2b4ce57f1b73b46c57531d9a6ccd70c21a37b349f428bfc1c3f"},
+    {file = "google_cloud_aiplatform-1.79.0.tar.gz", hash = "sha256:362bfd16716dcfb6c131736f25246790002b29c99a246fcf4c08a7c71bd2301f"},
 ]
 
 [package.dependencies]
@@ -1398,10 +1335,10 @@ autologging = ["mlflow (>=1.27.0,<=2.16.0)"]
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 datasets = ["pyarrow (>=10.0.1)", "pyarrow (>=14.0.0)", "pyarrow (>=3.0.0,<8.0dev)"]
 endpoint = ["requests (>=2.28.1)"]
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+
+[package.extras]
+protobuf = ["grpcio-tools (>=1.70.0)"]
 
 [[package]]
 name = "grpcio-status"
-version = "1.69.0"
+version = "1.70.0"
 description = "Status proto mapping for gRPC"
 optional = true
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
 googleapis-common-protos = ">=1.5.5"
-grpcio = ">=1.69.0"
+grpcio = ">=1.70.0"
 protobuf = ">=5.26.1,<6.0dev"
 
 [[package]]
@@ -1800,13 +1737,13 @@ trio = ["trio (>=0.22.0,<1.0)"]
 
 [[package]]
 name = "httpx"
-version = "0.27.2"
+version = "0.28.1"
 description = "The next generation HTTP client."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "httpx-0.27.2-py3-none-any.whl", hash = "sha256:7bb2708e112d8fdd7829cd4243970f0c223274051cb35ee80c03301ee29a3df0"},
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 ]
 
 [package.dependencies]
@@ -1814,7 +1751,6 @@ anyio = "*"
 certifi = "*"
 httpcore = "==1.*"
 idna = "*"
-sniffio = "*"
 
 [package.extras]
 brotli = ["brotli", "brotlicffi"]
@@ -1836,13 +1772,13 @@ files = [
 
 [[package]]
 name = "huggingface-hub"
-version = "0.27.1"
+version = "0.28.1"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = true
 python-versions = ">=3.8.0"
 files = [
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 ]
 
 [package.dependencies]
@@ -1855,13 +1791,13 @@ tqdm = ">=4.42.1"
 typing-extensions = ">=3.7.4.3"
 
 [package.extras]
-all = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "fastapi", "gradio (>=4.0.0)", "jedi", "libcst (==1.4.0)", "mypy (==1.5.1)", "numpy", "pytest (>=8.1.1,<8.2.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "ruff (>=0.5.0)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
+all = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "fastapi", "gradio (>=4.0.0)", "jedi", "libcst (==1.4.0)", "mypy (==1.5.1)", "numpy", "pytest (>=8.1.1,<8.2.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 cli = ["InquirerPy (==0.3.4)"]
-dev = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "fastapi", "gradio (>=4.0.0)", "jedi", "libcst (==1.4.0)", "mypy (==1.5.1)", "numpy", "pytest (>=8.1.1,<8.2.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "ruff (>=0.5.0)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
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 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
 hf-transfer = ["hf-transfer (>=0.1.4)"]
 inference = ["aiohttp"]
-quality = ["libcst (==1.4.0)", "mypy (==1.5.1)", "ruff (>=0.5.0)"]
+quality = ["libcst (==1.4.0)", "mypy (==1.5.1)", "ruff (>=0.9.0)"]
 tensorflow = ["graphviz", "pydot", "tensorflow"]
 tensorflow-testing = ["keras (<3.0)", "tensorflow"]
 testing = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "fastapi", "gradio (>=4.0.0)", "jedi", "numpy", "pytest (>=8.1.1,<8.2.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "soundfile", "urllib3 (<2.0)"]
@@ -1909,13 +1845,13 @@ files = [
 
 [[package]]
 name = "importlib-metadata"
-version = "8.5.0"
+version = "8.6.1"
 description = "Read metadata from Python packages"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 files = [
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+    {file = "importlib_metadata-8.6.1-py3-none-any.whl", hash = "sha256:02a89390c1e15fdfdc0d7c6b25cb3e62650d0494005c97d6f148bf5b9787525e"},
+    {file = "importlib_metadata-8.6.1.tar.gz", hash = "sha256:310b41d755445d74569f993ccfc22838295d9fe005425094fad953d7f15c8580"},
 ]
 
 [package.dependencies]
@@ -1927,7 +1863,7 @@ cover = ["pytest-cov"]
 doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
 enabler = ["pytest-enabler (>=2.2)"]
 perf = ["ipython"]
-test = ["flufl.flake8", "importlib-resources (>=1.3)", "jaraco.test (>=5.4)", "packaging", "pyfakefs", "pytest (>=6,!=8.1.*)", "pytest-perf (>=0.9.2)"]
+test = ["flufl.flake8", "importlib_resources (>=1.3)", "jaraco.test (>=5.4)", "packaging", "pyfakefs", "pytest (>=6,!=8.1.*)", "pytest-perf (>=0.9.2)"]
 type = ["pytest-mypy"]
 
 [[package]]
@@ -2397,17 +2333,18 @@ test = ["ipykernel", "pre-commit", "pytest (<8)", "pytest-cov", "pytest-timeout"
 
 [[package]]
 name = "jupyter-events"
-version = "0.11.0"
+version = "0.12.0"
 description = "Jupyter Event System library"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "jupyter_events-0.11.0-py3-none-any.whl", hash = "sha256:36399b41ce1ca45fe8b8271067d6a140ffa54cec4028e95491c93b78a855cacf"},
-    {file = "jupyter_events-0.11.0.tar.gz", hash = "sha256:c0bc56a37aac29c1fbc3bcfbddb8c8c49533f9cf11f1c4e6adadba936574ab90"},
+    {file = "jupyter_events-0.12.0-py3-none-any.whl", hash = "sha256:6464b2fa5ad10451c3d35fabc75eab39556ae1e2853ad0c0cc31b656731a97fb"},
+    {file = "jupyter_events-0.12.0.tar.gz", hash = "sha256:fc3fce98865f6784c9cd0a56a20644fc6098f21c8c33834a8d9fe383c17e554b"},
 ]
 
 [package.dependencies]
 jsonschema = {version = ">=4.18.0", extras = ["format-nongpl"]}
+packaging = "*"
 python-json-logger = ">=2.0.4"
 pyyaml = ">=5.3"
 referencing = "*"
@@ -2492,13 +2429,13 @@ test = ["jupyter-server (>=2.0.0)", "pytest (>=7.0)", "pytest-jupyter[server] (>
 
 [[package]]
 name = "jupyterlab"
-version = "4.3.4"
+version = "4.3.5"
 description = "JupyterLab computational environment"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "jupyterlab-4.3.4-py3-none-any.whl", hash = "sha256:b754c2601c5be6adf87cb5a1d8495d653ffb945f021939f77776acaa94dae952"},
-    {file = "jupyterlab-4.3.4.tar.gz", hash = "sha256:f0bb9b09a04766e3423cccc2fc23169aa2ffedcdf8713e9e0fb33cac0b6859d0"},
+    {file = "jupyterlab-4.3.5-py3-none-any.whl", hash = "sha256:571bbdee20e4c5321ab5195bc41cf92a75a5cff886be5e57ce78dfa37a5e9fdb"},
+    {file = "jupyterlab-4.3.5.tar.gz", hash = "sha256:c779bf72ced007d7d29d5bcef128e7fdda96ea69299e19b04a43635a7d641f9d"},
 ]
 
 [package.dependencies]
@@ -2724,35 +2661,35 @@ files = [
 
 [[package]]
 name = "mistralai"
-version = "1.2.6"
+version = "1.5.0"
 description = "Python Client SDK for the Mistral AI API."
 optional = true
-python-versions = "<4.0,>=3.8"
+python-versions = ">=3.8"
 files = [
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+    {file = "mistralai-1.5.0-py3-none-any.whl", hash = "sha256:9372537719f87bd6f9feef4747d0bf1f4fbe971f8c02945ca4b4bf3c94571c97"},
+    {file = "mistralai-1.5.0.tar.gz", hash = "sha256:fd94bc93bc25aad9c6dd8005b1a0bc4ba1250c6b3fbf855a49936989cc6e5c0d"},
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 [package.dependencies]
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-httpx = ">=0.27.0,<0.28.0"
-jsonpath-python = ">=1.0.6,<2.0.0"
-pydantic = ">=2.9.0,<3.0.0"
-python-dateutil = ">=2.8.2,<3.0.0"
-typing-inspect = ">=0.9.0,<0.10.0"
+eval-type-backport = ">=0.2.0"
+httpx = ">=0.27.0"
+jsonpath-python = ">=1.0.6"
+pydantic = ">=2.9.0"
+python-dateutil = ">=2.8.2"
+typing-inspect = ">=0.9.0"
 
 [package.extras]
-gcp = ["google-auth (==2.27.0)", "requests (>=2.32.3,<3.0.0)"]
+gcp = ["google-auth (>=2.27.0)", "requests (>=2.32.3)"]
 
 [[package]]
 name = "mistune"
-version = "3.1.0"
+version = "3.1.1"
 description = "A sane and fast Markdown parser with useful plugins and renderers"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "mistune-3.1.0-py3-none-any.whl", hash = "sha256:b05198cf6d671b3deba6c87ec6cf0d4eb7b72c524636eddb6dbf13823b52cee1"},
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+    {file = "mistune-3.1.1-py3-none-any.whl", hash = "sha256:02106ac2aa4f66e769debbfa028509a275069dcffce0dfa578edd7b991ee700a"},
+    {file = "mistune-3.1.1.tar.gz", hash = "sha256:e0740d635f515119f7d1feb6f9b192ee60f0cc649f80a8f944f905706a21654c"},
 ]
 
 [package.dependencies]
@@ -3052,13 +2989,13 @@ test = ["flaky", "ipykernel (>=6.19.3)", "ipython", "ipywidgets", "nbconvert (>=
 
 [[package]]
 name = "nbconvert"
-version = "7.16.5"
+version = "7.16.6"
 description = "Converting Jupyter Notebooks (.ipynb files) to other formats.  Output formats include asciidoc, html, latex, markdown, pdf, py, rst, script.  nbconvert can be used both as a Python library (`import nbconvert`) or as a command line tool (invoked as `jupyter nbconvert ...`)."
 optional = false
 python-versions = ">=3.8"
 files = [
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-    {file = "nbconvert-7.16.5.tar.gz", hash = "sha256:c83467bb5777fdfaac5ebbb8e864f300b277f68692ecc04d6dab72f2d8442344"},
+    {file = "nbconvert-7.16.6-py3-none-any.whl", hash = "sha256:1375a7b67e0c2883678c48e506dc320febb57685e5ee67faa51b18a90f3a712b"},
+    {file = "nbconvert-7.16.6.tar.gz", hash = "sha256:576a7e37c6480da7b8465eefa66c17844243816ce1ccc372633c6b71c3c0f582"},
 ]
 
 [package.dependencies]
@@ -3371,6 +3308,18 @@ files = [
 [package.dependencies]
 nvidia-nvjitlink-cu12 = "*"
 
+[[package]]
+name = "nvidia-cusparselt-cu12"
+version = "0.6.2"
+description = "NVIDIA cuSPARSELt"
+optional = true
+python-versions = "*"
+files = [
+    {file = "nvidia_cusparselt_cu12-0.6.2-py3-none-manylinux2014_aarch64.whl", hash = "sha256:067a7f6d03ea0d4841c85f0c6f1991c5dda98211f6302cb83a4ab234ee95bef8"},
+    {file = "nvidia_cusparselt_cu12-0.6.2-py3-none-manylinux2014_x86_64.whl", hash = "sha256:df2c24502fd76ebafe7457dbc4716b2fec071aabaed4fb7691a201cde03704d9"},
+    {file = "nvidia_cusparselt_cu12-0.6.2-py3-none-win_amd64.whl", hash = "sha256:0057c91d230703924c0422feabe4ce768841f9b4b44d28586b6f6d2eb86fbe70"},
+]
+
 [[package]]
 name = "nvidia-nccl-cu12"
 version = "2.21.5"
@@ -3407,13 +3356,13 @@ files = [
 
 [[package]]
 name = "openai"
-version = "1.59.7"
+version = "1.61.1"
 description = "The official Python library for the openai API"
 optional = true
 python-versions = ">=3.8"
 files = [
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+    {file = "openai-1.61.1-py3-none-any.whl", hash = "sha256:72b0826240ce26026ac2cd17951691f046e5be82ad122d20a8e1b30ca18bd11e"},
+    {file = "openai-1.61.1.tar.gz", hash = "sha256:ce1851507218209961f89f3520e06726c0aa7d0512386f0f977e3ac3e4f2472e"},
 ]
 
 [package.dependencies]
@@ -3463,20 +3412,6 @@ files = [
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 ]
 
-[[package]]
-name = "parameterized"
-version = "0.9.0"
-description = "Parameterized testing with any Python test framework"
-optional = true
-python-versions = ">=3.7"
-files = [
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-]
-
-[package.extras]
-dev = ["jinja2"]
-
 [[package]]
 name = "parso"
 version = "0.8.4"
@@ -3652,13 +3587,13 @@ twisted = ["twisted"]
 
 [[package]]
 name = "prompt-toolkit"
-version = "3.0.48"
+version = "3.0.50"
 description = "Library for building powerful interactive command lines in Python"
 optional = false
-python-versions = ">=3.7.0"
+python-versions = ">=3.8.0"
 files = [
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 ]
 
 [package.dependencies]
@@ -3757,13 +3692,13 @@ files = [
 
 [[package]]
 name = "proto-plus"
-version = "1.25.0"
-description = "Beautiful, Pythonic protocol buffers."
+version = "1.26.0"
+description = "Beautiful, Pythonic protocol buffers"
 optional = true
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.dependencies]
@@ -3885,13 +3820,13 @@ files = [
 
 [[package]]
 name = "pydantic"
-version = "2.10.5"
+version = "2.10.6"
 description = "Data validation using Python type hints"
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "pydantic-2.10.6-py3-none-any.whl", hash = "sha256:427d664bf0b8a2b34ff5dd0f5a18df00591adcee7198fbd71981054cef37b584"},
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 ]
 
 [package.dependencies]
@@ -4142,22 +4077,25 @@ docs = ["sphinx (>=5.3)", "sphinx-rtd-theme (>=1.0)"]
 testing = ["coverage (>=6.2)", "hypothesis (>=5.7.1)"]
 
 [[package]]
-name = "pytest-cov"
-version = "5.0.0"
-description = "Pytest plugin for measuring coverage."
+name = "pytest-xdist"
+version = "3.6.1"
+description = "pytest xdist plugin for distributed testing, most importantly across multiple CPUs"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
-coverage = {version = ">=5.2.1", extras = ["toml"]}
-pytest = ">=4.6"
+execnet = ">=2.1"
+psutil = {version = ">=3.0", optional = true, markers = "extra == \"psutil\""}
+pytest = ">=7.0.0"
 
 [package.extras]
-testing = ["fields", "hunter", "process-tests", "pytest-xdist", "virtualenv"]
+psutil = ["psutil (>=3.0)"]
+setproctitle = ["setproctitle"]
+testing = ["filelock"]
 
 [[package]]
 name = "python-dateutil"
@@ -4233,17 +4171,18 @@ files = [
 
 [[package]]
 name = "pywinpty"
-version = "2.0.14"
+version = "2.0.15"
 description = "Pseudo terminal support for Windows from Python."
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 files = [
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 [[package]]
@@ -4310,120 +4249,120 @@ files = [
 
 [[package]]
 name = "pyzmq"
-version = "26.2.0"
+version = "26.2.1"
 description = "Python bindings for 0MQ"
 optional = false
 python-versions = ">=3.7"
 files = [
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 [package.dependencies]
@@ -4449,18 +4388,19 @@ ocsp = ["cryptography (>=36.0.1)", "pyopenssl (==23.2.1)", "requests (>=2.31.0)"
 
 [[package]]
 name = "referencing"
-version = "0.35.1"
+version = "0.36.2"
 description = "JSON Referencing + Python"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
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 [package.dependencies]
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 rpds-py = ">=0.7.0"
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 [[package]]
 name = "regex"
@@ -4739,20 +4679,20 @@ pyasn1 = ">=0.1.3"
 
 [[package]]
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 [package.extras]
-crt = ["botocore[crt] (>=1.33.2,<2.0a.0)"]
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 [[package]]
 name = "safetensors"
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 [[package]]
 name = "sentence-transformers"
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 ]
 
 [package.dependencies]
@@ -5425,13 +5365,13 @@ typing = ["mypy (>=1.6,<2.0)", "traitlets (>=5.11.1)"]
 
 [[package]]
 name = "testcontainers"
-version = "4.9.0"
+version = "4.9.1"
 description = "Python library for throwaway instances of anything that can run in a Docker container"
 optional = false
 python-versions = "<4.0,>=3.9"
 files = [
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 ]
 
 [package.dependencies]
@@ -5591,28 +5531,31 @@ files = [
 
 [[package]]
 name = "torch"
-version = "2.5.1"
+version = "2.6.0"
 description = "Tensors and Dynamic neural networks in Python with strong GPU acceleration"
 optional = true
-python-versions = ">=3.8.0"
+python-versions = ">=3.9.0"
 files = [
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 ]
 
 [package.dependencies]
@@ -5629,17 +5572,18 @@ nvidia-cufft-cu12 = {version = "11.2.1.3", markers = "platform_system == \"Linux
 nvidia-curand-cu12 = {version = "10.3.5.147", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-cusolver-cu12 = {version = "11.6.1.9", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-cusparse-cu12 = {version = "12.3.1.170", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-cusparselt-cu12 = {version = "0.6.2", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-nccl-cu12 = {version = "2.21.5", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-nvjitlink-cu12 = {version = "12.4.127", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-nvtx-cu12 = {version = "12.4.127", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 setuptools = {version = "*", markers = "python_version >= \"3.12\""}
 sympy = {version = "1.13.1", markers = "python_version >= \"3.9\""}
-triton = {version = "3.1.0", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version < \"3.13\""}
-typing-extensions = ">=4.8.0"
+triton = {version = "3.2.0", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+typing-extensions = ">=4.10.0"
 
 [package.extras]
 opt-einsum = ["opt-einsum (>=3.3)"]
-optree = ["optree (>=0.12.0)"]
+optree = ["optree (>=0.13.0)"]
 
 [[package]]
 name = "tornado"
@@ -5699,13 +5643,13 @@ test = ["argcomplete (>=3.0.3)", "mypy (>=1.7.0)", "pre-commit", "pytest (>=7.0,
 
 [[package]]
 name = "transformers"
-version = "4.48.0"
+version = "4.48.2"
 description = "State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow"
 optional = true
 python-versions = ">=3.9.0"
 files = [
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+    {file = "transformers-4.48.2.tar.gz", hash = "sha256:dcfb73473e61f22fb3366fe2471ed2e42779ecdd49527a1bdf1937574855d516"},
 ]
 
 [package.dependencies]
@@ -5785,21 +5729,18 @@ nbconvert = "*"
 
 [[package]]
 name = "triton"
-version = "3.1.0"
+version = "3.2.0"
 description = "A language and compiler for custom Deep Learning operations"
 optional = true
 python-versions = "*"
 files = [
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 ]
 
-[package.dependencies]
-filelock = "*"
-
 [package.extras]
 build = ["cmake (>=3.20)", "lit"]
 tests = ["autopep8", "flake8", "isort", "llnl-hatchet", "numpy", "pytest", "scipy (>=1.7.1)"]
@@ -6088,83 +6029,90 @@ files = [
 
 [[package]]
 name = "wrapt"
-version = "1.17.1"
+version = "1.17.2"
 description = "Module for decorators, wrappers and monkey patching."
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "wrapt-1.17.2.tar.gz", hash = "sha256:41388e9d4d1522446fe79d3213196bd9e3b301a336965b9e27ca2788ebd122f3"},
 ]
 
 [[package]]
@@ -6294,4 +6242,4 @@ voyageai = ["voyageai"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9,<3.13"
-content-hash = "b20421e470da84100bb94c6c2e6f1bfe32ac5b94da78e47623ae6b8060ce00fc"
+content-hash = "90a9660f1dd328f2eff7339396a530c969e99e30ef643bb3956c8888aee3da1a"
diff --git a/pyproject.toml b/pyproject.toml
index 656fc2e8..5da4dd50 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -13,6 +13,7 @@ classifiers = [
   "Programming Language :: Python :: 3.9",
   "Programming Language :: Python :: 3.10",
   "Programming Language :: Python :: 3.11",
+  "Programming Language :: Python :: 3.12",
   "License :: OSI Approved :: MIT License",
 ]
 packages = [{ include = "redisvl", from = "." }]
@@ -35,6 +36,7 @@ cohere = { version = ">=4.44", optional = true }
 mistralai = { version = ">=1.0.0", optional = true }
 boto3 = { version = ">=1.34.0", optional = true }
 voyageai = { version = ">=0.2.2", optional = true }
+pytest-xdist = {extras = ["psutil"], version = "^3.6.1"}
 
 [tool.poetry.extras]
 openai = ["openai"]
@@ -50,7 +52,6 @@ black = ">=20.8b1"
 isort = ">=5.6.4"
 pylint = "3.1.0"
 pytest = "8.1.1"
-pytest-cov = "5.0.0"
 pytest-asyncio = "0.23.6"
 mypy = "1.9.0"
 types-redis = "*"
@@ -81,8 +82,6 @@ check-lint = "scripts:check_lint"
 check-mypy = "scripts:check_mypy"
 test = "scripts:test"
 test-verbose = "scripts:test_verbose"
-test-cov = "scripts:test_cov"
-cov = "scripts:cov"
 test-notebooks = "scripts:test_notebooks"
 build-docs = "scripts:build_docs"
 serve-docs = "scripts:serve_docs"
@@ -92,7 +91,7 @@ requires = ["poetry-core>=1.0.0"]
 build-backend = "poetry.core.masonry.api"
 
 [tool.black]
-target-version = ['py39', 'py310', 'py311']
+target-version = ['py39', 'py310', 'py311', 'py312']
 exclude = '''
 (
   | \.egg
diff --git a/redisvl/schema/fields.py b/redisvl/schema/fields.py
index 132e785f..c5e0eac4 100644
--- a/redisvl/schema/fields.py
+++ b/redisvl/schema/fields.py
@@ -235,6 +235,7 @@ def as_redis_field(self) -> RedisField:
 
 class FlatVectorField(BaseField):
     "Vector field with a FLAT index (brute force nearest neighbors search)"
+
     type: str = Field(default="vector", const=True)
     attrs: FlatVectorFieldAttributes
 
diff --git a/redisvl/utils/vectorize/text/custom.py b/redisvl/utils/vectorize/text/custom.py
index 6c8787d5..31172f02 100644
--- a/redisvl/utils/vectorize/text/custom.py
+++ b/redisvl/utils/vectorize/text/custom.py
@@ -1,18 +1,66 @@
-import os
-from typing import Any, Callable, Dict, List, Optional
+from typing import Any, Callable, List, Optional
 
 from pydantic.v1 import PrivateAttr
 
 from redisvl.utils.vectorize.base import BaseVectorizer
 
 
+def _check_vector(result: list, method_name: str) -> None:
+    """
+    Validates the structure of returned embeddings.
+
+    - For methods named "*_many", expects a list of lists of floats.
+    - For single methods, expects a list of floats.
+
+    Raises:
+        ValueError: If the embeddings do not match the expected structure.
+    """
+    if method_name.endswith("_many"):
+        # embed_many / aembed_many → list of lists
+        if not isinstance(result, list) or not result:
+            raise ValueError(f"{method_name} must return a non-empty list of lists.")
+        if not isinstance(result[0], list) or not result[0]:
+            raise ValueError(f"{method_name} must return a list of non-empty lists.")
+        if not isinstance(result[0][0], float):
+            raise ValueError(f"{method_name} must return a list of lists of floats.")
+    else:
+        # embed / aembed → a single list of floats
+        if not isinstance(result, list) or not result:
+            raise ValueError(f"{method_name} must return a non-empty list.")
+        if not isinstance(result[0], float):
+            raise ValueError(f"{method_name} must return a list of floats.")
+
+
+def validate_async(method):
+    """
+    Decorator that lazily validates the output of async methods (aembed, aembed_many).
+    On first call, it checks the returned embeddings with _check_vector, then sets a flag
+    so subsequent calls skip re-validation.
+    """
+
+    async def wrapper(self, *args, **kwargs):
+        result = await method(self, *args, **kwargs)
+        method_name = method.__name__
+        validated_attr = f"_{method_name}_validated"
+
+        try:
+            if not getattr(self, validated_attr):
+                _check_vector(result, method_name)
+                setattr(self, validated_attr, True)
+        except Exception as e:
+            raise ValueError(f"Invalid embedding method: {e}")
+
+        return result
+
+    return wrapper
+
+
 class CustomTextVectorizer(BaseVectorizer):
     """The CustomTextVectorizer class wraps user-defined embedding methods to create
     embeddings for text data.
 
     This vectorizer is designed to accept a provided callable text vectorizer and
     provides a class definition to allow for compatibility with RedisVL.
-
     The vectorizer may support both synchronous and asynchronous operations which
     allows for batch processing of texts, but at a minimum only syncronous embedding
     is required to satisfy the 'embed()' method.
@@ -33,10 +81,15 @@ class CustomTextVectorizer(BaseVectorizer):
 
     """
 
-    _embed_func: Callable = PrivateAttr()
-    _embed_many_func: Optional[Callable] = PrivateAttr()
-    _aembed_func: Optional[Callable] = PrivateAttr()
-    _aembed_many_func: Optional[Callable] = PrivateAttr()
+    # User-provided callables
+    _embed: Callable = PrivateAttr()
+    _embed_many: Optional[Callable] = PrivateAttr()
+    _aembed: Optional[Callable] = PrivateAttr()
+    _aembed_many: Optional[Callable] = PrivateAttr()
+
+    # Validation flags for async methods
+    _aembed_validated: bool = PrivateAttr(default=False)
+    _aembed_many_validated: bool = PrivateAttr(default=False)
 
     def __init__(
         self,
@@ -58,97 +111,49 @@ def __init__(
                 Defaults to 'float32'.
 
         Raises:
-            ValueError: if any of the provided functions accept or return incorrect types.
-            TypeError: if any of the provided functions are not Callable objects.
-            ValueError: If an invalid dtype is provided.
+            ValueError: if embedding validation fails.
         """
+        # Store user-provided callables
+        self._embed = embed
+        self._embed_many = embed_many
+        self._aembed = aembed
+        self._aembed_many = aembed_many
 
-        self._validate_embed(embed)
-        self._embed_func = embed
-        if embed_many:
-            self._validate_embed_many(embed_many)
-            self._embed_many_func = embed_many
-
-        if aembed:
-            self._validate_aembed(aembed)
-            self._aembed_func = aembed
-        if aembed_many:
-            self._validate_aembed_many(aembed_many)
-            self._aembed_many_func = aembed_many
+        # Manually validate sync methods to discover dimension
+        dims = self._validate_sync_callables()
 
-        super().__init__(model=self.type, dims=self._set_model_dims(), dtype=dtype)
+        # Initialize the base class now that we know the dimension
+        super().__init__(model=self.type, dims=dims, dtype=dtype)
 
-    def _validate_embed(self, func: Callable):
-        """calls the func with dummy input and validates that it returns a vector"""
-        try:
-            test_str = "this is a test sentence"
-            candidate_vector = func(test_str)
-            if type(candidate_vector) != list or type(candidate_vector[0]) != float:
-                raise ValueError(
-                    f"Candidate function for embed() does not have the correct return type. Please provide a function with with return type List[float]"
-                )
-        except TypeError:
-            raise TypeError(f"{func} is not a callable object")
-
-    def _validate_embed_many(self, func: Callable):
-        """calls the func with dummy input and validates that it returns a list of vectors"""
-        try:
-            test_strs = ["first test sentence", "second test sentence"]
-            candidate_vectors = func(test_strs)
-            if (
-                type(candidate_vectors) != list
-                or type(candidate_vectors[0]) != list
-                or type(candidate_vectors[0][0]) != float
-            ):
-                raise ValueError(
-                    f"Candidate function for embed_many does not have the correct return type. Please provide a function with with return type List[List[float]]"
-                )
-        except TypeError:
-            raise TypeError(f"{func} is not a callable object")
-
-    def _validate_aembed(self, func: Callable):
-        """calls the func with dummy input and validates that it returns a vector"""
-        import asyncio
+    @property
+    def type(self) -> str:
+        return "custom"
 
-        try:
-            test_str = "this is a test sentence"
-            loop = asyncio.get_event_loop()
-            candidate_vector = loop.run_until_complete(func(test_str))
-            if type(candidate_vector) != list or type(candidate_vector[0]) != float:
-                raise ValueError(
-                    f"Candidate function for aembed() does not have the correct return type. Please provide a function with with return type List[float]"
-                )
-        except TypeError:
-            raise TypeError(f"{func} is not a callable object")
-
-    def _validate_aembed_many(self, func: Callable):
-        """calls the func with dummy input and validates that it returns a list of vectors"""
-        import asyncio
+    def _validate_sync_callables(self) -> int:
+        """
+        Validate the sync embed function with a test call and discover the dimension.
+        Optionally validate embed_many if provided. Returns the discovered dimension.
 
+        Raises:
+            ValueError: If embed or embed_many produce malformed results or fail entirely.
+        """
+        # Check embed
         try:
-            test_strs = ["first test sentence", "second test sentence"]
-            loop = asyncio.get_event_loop()
-            candidate_vectors = loop.run_until_complete(func(test_strs))
-            if (
-                type(candidate_vectors) != list
-                or type(candidate_vectors[0]) != list
-                or type(candidate_vectors[0][0]) != float
-            ):
-                raise ValueError(
-                    f"Candidate function for aembed_many does not have the correct return type. Please provide a function with with return type List[List[float]]"
-                )
-        except TypeError:
-            raise TypeError(f"{func} is not a callable object")
-
-    def _set_model_dims(self) -> int:
-        try:
-            test_string = "dimension test"
-            embedding = self._embed_func(test_string)
-        except Exception as e:  # pylint: disable=broad-except
-            raise ValueError(
-                f"Error in checking model dimensions. Attempted to embed '{test_string}'. :{str(e)}"
-            )
-        return len(embedding)
+            test_single = self._embed("dimension test")
+            _check_vector(test_single, "embed")
+            dims = len(test_single)
+        except Exception as e:
+            raise ValueError(f"Invalid embedding method: {e}")
+
+        # Check embed_many
+        if self._embed_many:
+            try:
+                test_batch = self._embed_many(["dimension test (many)"])
+                _check_vector(test_batch, "embed_many")
+            except Exception as e:
+                raise ValueError(f"Invalid embedding method: {e}")
+
+        return dims
 
     def embed(
         self,
@@ -157,20 +162,19 @@ def embed(
         as_buffer: bool = False,
         **kwargs,
     ) -> List[float]:
-        """Embed a chunk of text using the provided function.
+        """
+        Generate an embedding for a single piece of text using your sync embed function.
 
         Args:
-            text (str): Chunk of text to embed.
-            preprocess (Optional[Callable], optional): Optional preprocessing callable to
-                perform before vectorization. Defaults to None.
-            as_buffer (bool, optional): Whether to convert the raw embedding
-                to a byte string. Defaults to False.
+            text (str): The text to embed.
+            preprocess (Optional[Callable]): An optional callable to preprocess the text.
+            as_buffer (bool): If True, return the embedding as a byte buffer.
 
         Returns:
-            List[float]: Embedding.
+            List[float]: The embedding of the input text.
 
         Raises:
-            TypeError: If the wrong input type is passed in for the text.
+            TypeError: If the input is not a string.
         """
         if not isinstance(text, str):
             raise TypeError("Must pass in a str value to embed.")
@@ -180,7 +184,11 @@ def embed(
 
         dtype = kwargs.pop("dtype", self.dtype)
 
-        result = self._embed_func(text, **kwargs)
+        try:
+            result = self._embed(text, **kwargs)
+        except Exception as e:
+            raise ValueError(f"Embedding text failed: {e}")
+
         return self._process_embedding(result, as_buffer, dtype)
 
     def embed_many(
@@ -191,42 +199,46 @@ def embed_many(
         as_buffer: bool = False,
         **kwargs,
     ) -> List[List[float]]:
-        """Embed many chunks of texts using the provided function.
+        """
+        Generate embeddings for multiple pieces of text in batches using your sync embed_many function.
 
         Args:
-            texts (List[str]): List of text chunks to embed.
-            preprocess (Optional[Callable], optional): Optional preprocessing
-                callable to perform before vectorization. Defaults to None.
-            batch_size (int, optional): Batch size of texts to use when creating
-                embeddings. Defaults to 10.
-            as_buffer (bool, optional): Whether to convert the raw embedding
-                to a byte string. Defaults to False.
+            texts (List[str]): A list of texts to embed.
+            preprocess (Optional[Callable]): Optional preprocessing for each text.
+            batch_size (int): Number of texts per batch.
+            as_buffer (bool): If True, convert each embedding to a byte buffer.
 
         Returns:
-            List[List[float]]: List of embeddings.
+            List[List[float]]: A list of embeddings, where each embedding is a list of floats.
 
         Raises:
-            TypeError: If the wrong input type is passed in for the text.
-            NotImplementedError: if embed_many was not passed to constructor.
+            TypeError: If the input is not a list of strings.
+            NotImplementedError: If no embed_many function was provided.
         """
         if not isinstance(texts, list):
             raise TypeError("Must pass in a list of str values to embed.")
-        if len(texts) > 0 and not isinstance(texts[0], str):
+        if texts and not isinstance(texts[0], str):
             raise TypeError("Must pass in a list of str values to embed.")
 
-        if not self._embed_many_func:
-            raise NotImplementedError
+        if not self._embed_many:
+            raise NotImplementedError("No embed_many function was provided.")
 
         dtype = kwargs.pop("dtype", self.dtype)
+        embeddings: List[List[float]] = []
+
+        try:
+            for batch in self.batchify(texts, batch_size, preprocess):
+                results = self._embed_many(batch, **kwargs)
+                processed = [
+                    self._process_embedding(r, as_buffer, dtype) for r in results
+                ]
+                embeddings.extend(processed)
+        except Exception as e:
+            raise ValueError(f"Embedding text failed: {e}")
 
-        embeddings: List = []
-        for batch in self.batchify(texts, batch_size, preprocess):
-            results = self._embed_many_func(batch, **kwargs)
-            embeddings += [
-                self._process_embedding(r, as_buffer, dtype) for r in results
-            ]
         return embeddings
 
+    @validate_async
     async def aembed(
         self,
         text: str,
@@ -234,36 +246,40 @@ async def aembed(
         as_buffer: bool = False,
         **kwargs,
     ) -> List[float]:
-        """Asynchronously embed a chunk of text.
+        """
+        Asynchronously generate an embedding for a single piece of text.
 
         Args:
-            text (str): Chunk of text to embed.
-            preprocess (Optional[Callable], optional): Optional preprocessing callable to
-                perform before vectorization. Defaults to None.
-            as_buffer (bool, optional): Whether to convert the raw embedding
-                to a byte string. Defaults to False.
+            text (str): The text to embed.
+            preprocess (Optional[Callable]): An optional callable to preprocess the text.
+            as_buffer (bool): If True, return the embedding as a byte buffer.
 
         Returns:
-            List[float]: Embedding.
+            List[float]: The embedding of the input text.
 
         Raises:
-            TypeError: If the wrong input type is passed in for the text.
-            NotImplementedError: if aembed was not passed to constructor.
+            TypeError: If the input is not a string.
+            NotImplementedError: If no aembed function was provided.
         """
         if not isinstance(text, str):
             raise TypeError("Must pass in a str value to embed.")
 
-        if not self._aembed_func:
-            raise NotImplementedError
+        if not self._aembed:
+            raise NotImplementedError("No aembed function was provided.")
 
         if preprocess:
             text = preprocess(text)
 
         dtype = kwargs.pop("dtype", self.dtype)
 
-        result = await self._aembed_func(text, **kwargs)
+        try:
+            result = await self._aembed(text, **kwargs)
+        except Exception as e:
+            raise ValueError(f"Embedding text failed: {e}")
+
         return self._process_embedding(result, as_buffer, dtype)
 
+    @validate_async
     async def aembed_many(
         self,
         texts: List[str],
@@ -272,42 +288,41 @@ async def aembed_many(
         as_buffer: bool = False,
         **kwargs,
     ) -> List[List[float]]:
-        """Asynchronously embed many chunks of texts.
+        """
+        Asynchronously generate embeddings for multiple pieces of text in batches.
 
         Args:
-            texts (List[str]): List of text chunks to embed.
-            preprocess (Optional[Callable], optional): Optional preprocessing callable to
-                perform before vectorization. Defaults to None.
-            batch_size (int, optional): Batch size of texts to use when creating
-                embeddings. Defaults to 10.
-            as_buffer (bool, optional): Whether to convert the raw embedding
-                to a byte string. Defaults to False.
+            texts (List[str]): The texts to embed.
+            preprocess (Optional[Callable]): Optional preprocessing for each text.
+            batch_size (int): Number of texts per batch.
+            as_buffer (bool): If True, convert each embedding to a byte buffer.
 
         Returns:
-            List[List[float]]: List of embeddings.
+            List[List[float]]: A list of embeddings, where each embedding is a list of floats.
 
         Raises:
-            TypeError: If the wrong input type is passed in for the text.
-            NotImplementedError: If aembed_many was not passed to constructor.
+            TypeError: If the input is not a list of strings.
+            NotImplementedError: If no aembed_many function was provided.
         """
         if not isinstance(texts, list):
             raise TypeError("Must pass in a list of str values to embed.")
-        if len(texts) > 0 and not isinstance(texts[0], str):
+        if texts and not isinstance(texts[0], str):
             raise TypeError("Must pass in a list of str values to embed.")
 
-        if not self._aembed_many_func:
-            raise NotImplementedError
+        if not self._aembed_many:
+            raise NotImplementedError("No aembed_many function was provided.")
 
         dtype = kwargs.pop("dtype", self.dtype)
+        embeddings: List[List[float]] = []
 
-        embeddings: List = []
-        for batch in self.batchify(texts, batch_size, preprocess):
-            results = await self._aembed_many_func(batch, **kwargs)
-            embeddings += [
-                self._process_embedding(r, as_buffer, dtype) for r in results
-            ]
-        return embeddings
+        try:
+            for batch in self.batchify(texts, batch_size, preprocess):
+                results = await self._aembed_many(batch, **kwargs)
+                processed = [
+                    self._process_embedding(r, as_buffer, dtype) for r in results
+                ]
+                embeddings.extend(processed)
+        except Exception as e:
+            raise ValueError(f"Embedding text failed: {e}")
 
-    @property
-    def type(self) -> str:
-        return "custom"
+        return embeddings
diff --git a/scripts.py b/scripts.py
index 66c5e030..0bfbac01 100644
--- a/scripts.py
+++ b/scripts.py
@@ -29,35 +29,15 @@ def check_mypy():
 
 
 def test():
-    subprocess.run(["python", "-m", "pytest", "--log-level=CRITICAL"], check=True)
+    subprocess.run(["python", "-m", "pytest", "-n", "auto", "--log-level=CRITICAL"], check=True)
 
 
 def test_verbose():
     subprocess.run(
-        ["python", "-m", "pytest", "-vv", "-s", "--log-level=CRITICAL"], check=True
+        ["python", "-m", "pytest", "-n", "auto", "-vv", "-s", "--log-level=CRITICAL"], check=True
     )
 
 
-def test_cov():
-    subprocess.run(
-        [
-            "python",
-            "-m",
-            "pytest",
-            "-vv",
-            "--cov=./redisvl",
-            "--cov-report=xml",
-            "--log-level=CRITICAL",
-        ],
-        check=True,
-    )
-
-
-def cov():
-    subprocess.run(["coverage", "html"], check=True)
-    print("If data was present, coverage report is in ./htmlcov/index.html")
-
-
 def test_notebooks():
     subprocess.run(["cd", "docs/", "&&", "poetry run treon", "-v"], check=True)
 
diff --git a/tests/integration/test_connection.py b/tests/integration/test_connection.py
index 80556cdb..aa1f4e2a 100644
--- a/tests/integration/test_connection.py
+++ b/tests/integration/test_connection.py
@@ -20,10 +20,6 @@
 EXPECTED_LIB_NAME = f"redis-py(redisvl_v{__version__})"
 
 
-def test_get_address_from_env(redis_url):
-    assert get_address_from_env() == redis_url
-
-
 def test_unpack_redis_modules():
     module_list = [
         {
diff --git a/tests/integration/test_llmcache.py b/tests/integration/test_llmcache.py
index 0ae0b320..6c045b2b 100644
--- a/tests/integration/test_llmcache.py
+++ b/tests/integration/test_llmcache.py
@@ -1,8 +1,8 @@
 import asyncio
 import os
+import warnings
 from collections import namedtuple
 from time import sleep, time
-import warnings
 
 import pytest
 from pydantic.v1 import ValidationError
@@ -894,33 +894,43 @@ def test_bad_dtype_connecting_to_existing_cache(redis_url):
         )
 
 
-def test_vectorizer_dtype_mismatch():
+def test_vectorizer_dtype_mismatch(redis_url):
     with pytest.raises(ValueError):
         SemanticCache(
             name="test_dtype_mismatch",
             dtype="float32",
             vectorizer=HFTextVectorizer(dtype="float16"),
+            redis_url=redis_url,
             overwrite=True,
         )
 
 
-def test_invalid_vectorizer():
+def test_invalid_vectorizer(redis_url):
     with pytest.raises(TypeError):
         SemanticCache(
             name="test_invalid_vectorizer",
             vectorizer="invalid_vectorizer",  # type: ignore
+            redis_url=redis_url,
             overwrite=True,
         )
 
 
-def test_passes_through_dtype_to_default_vectorizer():
+def test_passes_through_dtype_to_default_vectorizer(redis_url):
     # The default is float32, so we should see float64 if we pass it in.
     cache = SemanticCache(
-        name="test_pass_through_dtype", dtype="float64", overwrite=True
+        name="test_pass_through_dtype",
+        dtype="float64",
+        redis_url=redis_url,
+        overwrite=True,
     )
     assert cache._vectorizer.dtype == "float64"
 
 
-def test_deprecated_dtype_argument():
+def test_deprecated_dtype_argument(redis_url):
     with pytest.warns(DeprecationWarning):
-        SemanticCache(name="test_deprecated_dtype", dtype="float32", overwrite=True)
+        SemanticCache(
+            name="test_deprecated_dtype",
+            dtype="float32",
+            redis_url=redis_url,
+            overwrite=True,
+        )
diff --git a/tests/integration/test_search_results.py b/tests/integration/test_search_results.py
index 90e4ffbe..83efad53 100644
--- a/tests/integration/test_search_results.py
+++ b/tests/integration/test_search_results.py
@@ -16,7 +16,7 @@ def filter_query():
 
 
 @pytest.fixture
-def index(sample_data):
+def index(sample_data, redis_url):
     fields_spec = [
         {"name": "credit_score", "type": "tag"},
         {"name": "user", "type": "tag"},
@@ -47,7 +47,7 @@ def index(sample_data):
     index = SearchIndex.from_dict(json_schema)
 
     # connect to local redis instance
-    index.connect(os.environ["REDIS_URL"])
+    index.connect(redis_url=redis_url)
 
     # create the index (no data yet)
     index.create(overwrite=True)
diff --git a/tests/integration/test_semantic_router.py b/tests/integration/test_semantic_router.py
index db22e9af..04489aec 100644
--- a/tests/integration/test_semantic_router.py
+++ b/tests/integration/test_semantic_router.py
@@ -315,42 +315,46 @@ def test_bad_dtype_connecting_to_exiting_router(redis_url, routes):
         )
 
 
-def test_vectorizer_dtype_mismatch(routes):
+def test_vectorizer_dtype_mismatch(routes, redis_url):
     with pytest.raises(ValueError):
         SemanticRouter(
             name="test_dtype_mismatch",
             routes=routes,
             dtype="float32",
             vectorizer=HFTextVectorizer(dtype="float16"),
+            redis_url=redis_url,
             overwrite=True,
         )
 
 
-def test_invalid_vectorizer(routes):
+def test_invalid_vectorizer(routes, redis_url):
     with pytest.raises(TypeError):
         SemanticRouter(
             name="test_invalid_vectorizer",
             vectorizer="invalid_vectorizer",  # type: ignore
+            redis_url=redis_url,
             overwrite=True,
         )
 
 
-def test_passes_through_dtype_to_default_vectorizer(routes):
+def test_passes_through_dtype_to_default_vectorizer(routes, redis_url):
     # The default is float32, so we should see float64 if we pass it in.
     router = SemanticRouter(
         name="test_pass_through_dtype",
         routes=routes,
         dtype="float64",
+        redis_url=redis_url,
         overwrite=True,
     )
     assert router.vectorizer.dtype == "float64"
 
 
-def test_deprecated_dtype_argument(routes):
+def test_deprecated_dtype_argument(routes, redis_url):
     with pytest.warns(DeprecationWarning):
         SemanticRouter(
             name="test_deprecated_dtype",
             routes=routes,
             dtype="float32",
+            redis_url=redis_url,
             overwrite=True,
         )
diff --git a/tests/integration/test_session_manager.py b/tests/integration/test_session_manager.py
index 5d2ed36e..05188db5 100644
--- a/tests/integration/test_session_manager.py
+++ b/tests/integration/test_session_manager.py
@@ -589,33 +589,40 @@ def test_bad_dtype_connecting_to_exiting_session(redis_url):
         )
 
 
-def test_vectorizer_dtype_mismatch():
+def test_vectorizer_dtype_mismatch(redis_url):
     with pytest.raises(ValueError):
         SemanticSessionManager(
             name="test_dtype_mismatch",
             dtype="float32",
             vectorizer=HFTextVectorizer(dtype="float16"),
+            redis_url=redis_url,
             overwrite=True,
         )
 
 
-def test_invalid_vectorizer():
+def test_invalid_vectorizer(redis_url):
     with pytest.raises(TypeError):
         SemanticSessionManager(
             name="test_invalid_vectorizer",
             vectorizer="invalid_vectorizer",  # type: ignore
+            redis_url=redis_url,
             overwrite=True,
         )
 
 
-def test_passes_through_dtype_to_default_vectorizer():
+def test_passes_through_dtype_to_default_vectorizer(redis_url):
     # The default is float32, so we should see float64 if we pass it in.
     cache = SemanticSessionManager(
-        name="test_pass_through_dtype", dtype="float64", overwrite=True
+        name="test_pass_through_dtype",
+        dtype="float64",
+        redis_url=redis_url,
+        overwrite=True,
     )
     assert cache._vectorizer.dtype == "float64"
 
 
-def test_deprecated_dtype_argument():
+def test_deprecated_dtype_argument(redis_url):
     with pytest.warns(DeprecationWarning):
-        SemanticSessionManager(name="float64 session", dtype="float64", overwrite=True)
+        SemanticSessionManager(
+            name="float64 session", dtype="float64", redis_url=redis_url, overwrite=True
+        )
diff --git a/tests/integration/test_vectorizers.py b/tests/integration/test_vectorizers.py
index a0d954b5..52a32eca 100644
--- a/tests/integration/test_vectorizers.py
+++ b/tests/integration/test_vectorizers.py
@@ -89,7 +89,7 @@ def embed(text: str):
 
 @pytest.fixture
 def custom_embed_class():
-    class embedder:
+    class MyEmbedder:
         def embed(self, text: str):
             return [1.1, 2.2, 3.3, 4.4]
 
@@ -105,7 +105,7 @@ def embed_many_with_args(self, texts, param=True):
             else:
                 return [[6.0, 5.0, 4.0], [3.0, 2.0, 1.0]]
 
-    return embedder
+    return MyEmbedder
 
 
 def test_vectorizer_embed(vectorizer):
@@ -179,26 +179,26 @@ def test_custom_vectorizer_embed(custom_embed_class, custom_embed_func):
     embedding = custom_wrapper.embed("This is a test sentence.", max_len=2)
     assert embedding == [1.1, 2.2]
 
-    with pytest.raises(TypeError):
-        bad_wrapper = CustomTextVectorizer(embed="hello")
+    with pytest.raises(ValueError):
+        invalid_vectorizer = CustomTextVectorizer(embed="hello")
 
-    with pytest.raises(TypeError):
-        bad_wrapper = CustomTextVectorizer(embed=42)
+    with pytest.raises(ValueError):
+        invalid_vectorizer = CustomTextVectorizer(embed=42)
 
-    with pytest.raises(TypeError):
-        bad_wrapper = CustomTextVectorizer(embed={"foo": "bar"})
+    with pytest.raises(ValueError):
+        invalid_vectorizer = CustomTextVectorizer(embed={"foo": "bar"})
 
     def bad_arg_type(value: int):
         return [value]
 
     with pytest.raises(ValueError):
-        bad_wrapper = CustomTextVectorizer(embed=bad_arg_type)
+        invalid_vectorizer = CustomTextVectorizer(embed=bad_arg_type)
 
     def bad_return_type(text: str) -> str:
         return text
 
     with pytest.raises(ValueError):
-        bad_wrapper = CustomTextVectorizer(embed=bad_return_type)
+        invalid_vectorizer = CustomTextVectorizer(embed=bad_return_type)
 
 
 def test_custom_vectorizer_embed_many(custom_embed_class, custom_embed_func):
@@ -222,26 +222,30 @@ def test_custom_vectorizer_embed_many(custom_embed_class, custom_embed_func):
     embeddings = custom_wrapper.embed_many(["test one.", "test two"], param=False)
     assert embeddings == [[6.0, 5.0, 4.0], [3.0, 2.0, 1.0]]
 
-    with pytest.raises(TypeError):
-        bad_wrapper = CustomTextVectorizer(custom_embed_func, embed_many="hello")
+    with pytest.raises(ValueError):
+        invalid_vectorizer = CustomTextVectorizer(custom_embed_func, embed_many="hello")
 
-    with pytest.raises(TypeError):
-        bad_wrapper = CustomTextVectorizer(custom_embed_func, embed_many=42)
+    with pytest.raises(ValueError):
+        invalid_vectorizer = CustomTextVectorizer(custom_embed_func, embed_many=42)
 
-    with pytest.raises(TypeError):
-        bad_wrapper = CustomTextVectorizer(custom_embed_func, embed_many={"foo": "bar"})
+    with pytest.raises(ValueError):
+        invalid_vectorizer = CustomTextVectorizer(
+            custom_embed_func, embed_many={"foo": "bar"}
+        )
 
     def bad_arg_type(value: int):
         return [value]
 
     with pytest.raises(ValueError):
-        bad_wrapper = CustomTextVectorizer(custom_embed_func, embed_many=bad_arg_type)
+        invalid_vectorizer = CustomTextVectorizer(
+            custom_embed_func, embed_many=bad_arg_type
+        )
 
     def bad_return_type(text: str) -> str:
         return text
 
     with pytest.raises(ValueError):
-        bad_wrapper = CustomTextVectorizer(
+        invalid_vectorizer = CustomTextVectorizer(
             custom_embed_func, embed_many=bad_return_type
         )