diff --git a/py/autoevals/llm.py b/py/autoevals/llm.py
index 7759f09..03252b0 100644
--- a/py/autoevals/llm.py
+++ b/py/autoevals/llm.py
@@ -49,7 +49,6 @@
 import re
 from collections import defaultdict
 from dataclasses import dataclass
-from typing import Dict, List, Optional
 
 import chevron
 import yaml
@@ -126,9 +125,9 @@ def build_classification_tools(useCoT, choice_strings):
 class OpenAIScorer(ScorerWithPartial):
     def __init__(
         self,
-        api_key: Optional[str] = None,
-        base_url: Optional[str] = None,
-        client: Optional[Client] = None,
+        api_key: str | None = None,
+        base_url: str | None = None,
+        client: Client | None = None,
     ) -> None:
         self.extra_args = {}
         if api_key:
@@ -142,10 +141,10 @@ def __init__(
 class OpenAILLMScorer(OpenAIScorer):
     def __init__(
         self,
-        temperature: Optional[float] = None,
-        api_key: Optional[str] = None,
-        base_url: Optional[str] = None,
-        client: Optional[Client] = None,
+        temperature: float | None = None,
+        api_key: str | None = None,
+        base_url: str | None = None,
+        client: Client | None = None,
     ) -> None:
         super().__init__(
             api_key=api_key,
@@ -159,7 +158,7 @@ class OpenAILLMClassifier(OpenAILLMScorer):
     def __init__(
         self,
         name: str,
-        messages: List,
+        messages: list,
         model,
         choice_scores,
         classification_tools,
@@ -169,7 +168,7 @@ def __init__(
         engine=None,
         api_key=None,
         base_url=None,
-        client: Optional[Client] = None,
+        client: Client | None = None,
     ):
         super().__init__(
             client=client,
@@ -264,11 +263,11 @@ def _run_eval_sync(self, output, expected, **kwargs):
 @dataclass
 class ModelGradedSpec:
     prompt: str
-    choice_scores: Dict[str, float]
-    model: Optional[str] = None
-    engine: Optional[str] = None
-    use_cot: Optional[bool] = None
-    temperature: Optional[float] = None
+    choice_scores: dict[str, float]
+    model: str | None = None
+    engine: str | None = None
+    use_cot: bool | None = None
+    temperature: float | None = None
 
 
 class LLMClassifier(OpenAILLMClassifier):
@@ -316,7 +315,7 @@ class LLMClassifier(OpenAILLMClassifier):
         **extra_render_args: Additional template variables
     """
 
-    _SPEC_FILE_CONTENTS: Dict[str, str] = defaultdict(str)
+    _SPEC_FILE_CONTENTS: dict[str, str] = defaultdict(str)
 
     def __init__(
         self,
@@ -330,7 +329,7 @@ def __init__(
         engine=None,
         api_key=None,
         base_url=None,
-        client: Optional[Client] = None,
+        client: Client | None = None,
         **extra_render_args,
     ):
         choice_strings = list(choice_scores.keys())
@@ -359,11 +358,11 @@ def __init__(
         )
 
     @classmethod
-    def from_spec(cls, name: str, spec: ModelGradedSpec, client: Optional[Client] = None, **kwargs):
+    def from_spec(cls, name: str, spec: ModelGradedSpec, client: Client | None = None, **kwargs):
         return cls(name, spec.prompt, spec.choice_scores, client=client, **kwargs)
 
     @classmethod
-    def from_spec_file(cls, name: str, path: str, client: Optional[Client] = None, **kwargs):
+    def from_spec_file(cls, name: str, path: str, client: Client | None = None, **kwargs):
         if cls._SPEC_FILE_CONTENTS[name] == "":
             with open(path) as f:
                 cls._SPEC_FILE_CONTENTS[name] = f.read()
@@ -381,7 +380,7 @@ def __new__(
         temperature=None,
         api_key=None,
         base_url=None,
-        client: Optional[Client] = None,
+        client: Client | None = None,
     ):
         kwargs = {}
         if model is not None:
diff --git a/py/autoevals/moderation.py b/py/autoevals/moderation.py
index 76090ba..08ea9fe 100644
--- a/py/autoevals/moderation.py
+++ b/py/autoevals/moderation.py
@@ -1,5 +1,3 @@
-from typing import Optional
-
 from autoevals.llm import OpenAIScorer
 
 from .oai import Client, arun_cached_request, run_cached_request
@@ -50,7 +48,7 @@ def __init__(
         threshold=None,
         api_key=None,
         base_url=None,
-        client: Optional[Client] = None,
+        client: Client | None = None,
     ):
         """Initialize a Moderation scorer.
 
diff --git a/py/autoevals/oai.py b/py/autoevals/oai.py
index ff8b4f2..c439a09 100644
--- a/py/autoevals/oai.py
+++ b/py/autoevals/oai.py
@@ -4,9 +4,10 @@
 import textwrap
 import time
 import warnings
+from collections.abc import Callable
 from contextvars import ContextVar
 from dataclasses import dataclass
-from typing import Any, Callable, Dict, Optional, Protocol, Tuple, Type, TypeVar, Union, cast, runtime_checkable
+from typing import Any, Optional, Protocol, TypeVar, Union, cast, runtime_checkable
 
 PROXY_URL = "https://api.braintrust.dev/v1/proxy"
 
@@ -50,10 +51,10 @@ def moderations(self) -> Moderations: ...
         def api_key(self) -> str: ...
 
         @property
-        def organization(self) -> Optional[str]: ...
+        def organization(self) -> str | None: ...
 
         @property
-        def base_url(self) -> Union[str, Any, None]: ...
+        def base_url(self) -> str | Any | None: ...
 
     class AsyncOpenAI(OpenAI): ...
 
@@ -75,18 +76,18 @@ class Moderation(Protocol):
         acreate: Callable[..., Any]
         create: Callable[..., Any]
 
-    api_key: Optional[str]
-    api_base: Optional[str]
-    base_url: Optional[str]
+    api_key: str | None
+    api_base: str | None
+    base_url: str | None
 
     class error(Protocol):
         class RateLimitError(Exception): ...
 
 
-_openai_module: Optional[Union[OpenAIV1Module, OpenAIV0Module]] = None
+_openai_module: OpenAIV1Module | OpenAIV0Module | None = None
 
 
-def get_openai_module() -> Union[OpenAIV1Module, OpenAIV0Module]:
+def get_openai_module() -> OpenAIV1Module | OpenAIV0Module:
     global _openai_module
 
     if _openai_module is not None:
@@ -150,11 +151,11 @@ def complete(self, **kwargs):
         ```
     """
 
-    openai: Union[OpenAIV0Module, OpenAIV1Module.OpenAI]
+    openai: OpenAIV0Module | OpenAIV1Module.OpenAI
     complete: Callable[..., Any] = None  # type: ignore # Set in __post_init__
     embed: Callable[..., Any] = None  # type: ignore # Set in __post_init__
     moderation: Callable[..., Any] = None  # type: ignore # Set in __post_init__
-    RateLimitError: Type[Exception] = None  # type: ignore # Set in __post_init__
+    RateLimitError: type[Exception] = None  # type: ignore # Set in __post_init__
     is_async: bool = False
     _is_wrapped: bool = False
 
@@ -199,11 +200,11 @@ def is_wrapped(self) -> bool:
 
 T = TypeVar("T")
 
-_named_wrapper: Optional[Type[Any]] = None
-_wrap_openai: Optional[Callable[[Any], Any]] = None
+_named_wrapper: type[Any] | None = None
+_wrap_openai: Callable[[Any], Any] | None = None
 
 
-def get_openai_wrappers() -> Tuple[Type[Any], Callable[[Any], Any]]:
+def get_openai_wrappers() -> tuple[type[Any], Callable[[Any], Any]]:
     global _named_wrapper, _wrap_openai
 
     if _named_wrapper is not None and _wrap_openai is not None:
@@ -213,7 +214,7 @@ def get_openai_wrappers() -> Tuple[Type[Any], Callable[[Any], Any]]:
         from braintrust.oai import NamedWrapper as BraintrustNamedWrapper  # type: ignore
         from braintrust.oai import wrap_openai  # type: ignore
 
-        _named_wrapper = cast(Type[Any], BraintrustNamedWrapper)
+        _named_wrapper = cast(type[Any], BraintrustNamedWrapper)
     except ImportError:
 
         class NamedWrapper:
@@ -237,7 +238,7 @@ def resolve_client(client: Client, is_async: bool = False) -> LLMClient:
     return LLMClient(openai=client, is_async=is_async)
 
 
-def init(client: Optional[Client] = None, is_async: bool = False):
+def init(client: Client | None = None, is_async: bool = False):
     """Initialize Autoevals with an optional custom LLM client.
 
     This function sets up the global client context for Autoevals to use. If no client is provided,
@@ -259,10 +260,10 @@ def init(client: Optional[Client] = None, is_async: bool = False):
 
 
 def prepare_openai(
-    client: Optional[Client] = None,
+    client: Client | None = None,
     is_async: bool = False,
-    api_key: Optional[str] = None,
-    base_url: Optional[str] = None,
+    api_key: str | None = None,
+    base_url: str | None = None,
 ):
     """Prepares and configures an OpenAI client for use with AutoEval.
 
@@ -348,7 +349,7 @@ def prepare_openai(
     return LLMClient(openai=openai_obj, is_async=is_async)
 
 
-def post_process_response(resp: Any) -> Dict[str, Any]:
+def post_process_response(resp: Any) -> dict[str, Any]:
     # This normalizes against craziness in OpenAI v0 vs. v1
     if hasattr(resp, "to_dict"):
         # v0
@@ -358,18 +359,18 @@ def post_process_response(resp: Any) -> Dict[str, Any]:
         return resp.dict()
 
 
-def set_span_purpose(kwargs: Dict[str, Any]) -> None:
+def set_span_purpose(kwargs: dict[str, Any]) -> None:
     kwargs.setdefault("span_info", {}).setdefault("span_attributes", {})["purpose"] = "scorer"
 
 
 def run_cached_request(
     *,
-    client: Optional[LLMClient] = None,
+    client: LLMClient | None = None,
     request_type: str = "complete",
-    api_key: Optional[str] = None,
-    base_url: Optional[str] = None,
+    api_key: str | None = None,
+    base_url: str | None = None,
     **kwargs: Any,
-) -> Dict[str, Any]:
+) -> dict[str, Any]:
     wrapper = prepare_openai(client=client, is_async=False, api_key=api_key, base_url=base_url)
     if wrapper.is_wrapped:
         set_span_purpose(kwargs)
@@ -393,12 +394,12 @@ def run_cached_request(
 
 async def arun_cached_request(
     *,
-    client: Optional[LLMClient] = None,
+    client: LLMClient | None = None,
     request_type: str = "complete",
-    api_key: Optional[str] = None,
-    base_url: Optional[str] = None,
+    api_key: str | None = None,
+    base_url: str | None = None,
     **kwargs: Any,
-) -> Dict[str, Any]:
+) -> dict[str, Any]:
     wrapper = prepare_openai(client=client, is_async=True, api_key=api_key, base_url=base_url)
     if wrapper.is_wrapped:
         set_span_purpose(kwargs)
diff --git a/py/autoevals/ragas.py b/py/autoevals/ragas.py
index bc9f81b..2e432fe 100644
--- a/py/autoevals/ragas.py
+++ b/py/autoevals/ragas.py
@@ -58,7 +58,6 @@
 
 import asyncio
 import json
-from typing import Optional
 
 import chevron
 
@@ -133,12 +132,12 @@ def extract_entities_request(text, **extra_args):
     )
 
 
-async def aextract_entities(*, text, client: Optional[Client] = None, **extra_args):
+async def aextract_entities(*, text, client: Client | None = None, **extra_args):
     response = await arun_cached_request(client=client, **extract_entities_request(text=text, **extra_args))
     return json.loads(response["choices"][0]["message"]["tool_calls"][0]["function"]["arguments"])
 
 
-def extract_entities(*, text, client: Optional[Client] = None, **extra_args):
+def extract_entities(*, text, client: Client | None = None, **extra_args):
     response = run_cached_request(client=client, **extract_entities_request(text=text, **extra_args))
     return json.loads(response["choices"][0]["message"]["tool_calls"][0]["function"]["arguments"])
 
@@ -169,7 +168,7 @@ class ContextEntityRecall(OpenAILLMScorer):
         context: The context document(s) to search for entities in
     """
 
-    def __init__(self, pairwise_scorer=None, model=DEFAULT_RAGAS_MODEL, client: Optional[Client] = None, **kwargs):
+    def __init__(self, pairwise_scorer=None, model=DEFAULT_RAGAS_MODEL, client: Client | None = None, **kwargs):
         super().__init__(client=client, **kwargs)
 
         self.extraction_model = model
@@ -313,7 +312,7 @@ class ContextRelevancy(OpenAILLMScorer):
         context: The context document(s) to evaluate
     """
 
-    def __init__(self, pairwise_scorer=None, model=DEFAULT_RAGAS_MODEL, client: Optional[Client] = None, **kwargs):
+    def __init__(self, pairwise_scorer=None, model=DEFAULT_RAGAS_MODEL, client: Client | None = None, **kwargs):
         super().__init__(client=client, **kwargs)
 
         self.model = model
@@ -473,7 +472,7 @@ class ContextRecall(OpenAILLMScorer):
         context: The context document(s) to evaluate
     """
 
-    def __init__(self, pairwise_scorer=None, model=DEFAULT_RAGAS_MODEL, client: Optional[Client] = None, **kwargs):
+    def __init__(self, pairwise_scorer=None, model=DEFAULT_RAGAS_MODEL, client: Client | None = None, **kwargs):
         super().__init__(client=client, **kwargs)
 
         self.model = model
@@ -633,7 +632,7 @@ class ContextPrecision(OpenAILLMScorer):
         context: The context document(s) to evaluate
     """
 
-    def __init__(self, pairwise_scorer=None, model=DEFAULT_RAGAS_MODEL, client: Optional[Client] = None, **kwargs):
+    def __init__(self, pairwise_scorer=None, model=DEFAULT_RAGAS_MODEL, client: Client | None = None, **kwargs):
         super().__init__(client=client, **kwargs)
 
         self.model = model
@@ -839,28 +838,28 @@ def extract_faithfulness_request(context, statements, **extra_args):
     )
 
 
-async def aextract_statements(question, answer, client: Optional[Client] = None, **extra_args):
+async def aextract_statements(question, answer, client: Client | None = None, **extra_args):
     response = await arun_cached_request(
         client=client, **extract_statements_request(question=question, answer=answer, **extra_args)
     )
     return load_function_call(response)
 
 
-def extract_statements(question, answer, client: Optional[Client] = None, **extra_args):
+def extract_statements(question, answer, client: Client | None = None, **extra_args):
     response = run_cached_request(
         client=client, **extract_statements_request(question=question, answer=answer, **extra_args)
     )
     return load_function_call(response)
 
 
-async def aextract_faithfulness(context, statements, client: Optional[Client] = None, **extra_args):
+async def aextract_faithfulness(context, statements, client: Client | None = None, **extra_args):
     response = await arun_cached_request(
         client=client, **extract_faithfulness_request(context=context, statements=statements, **extra_args)
     )
     return load_function_call(response)
 
 
-def extract_faithfulness(context, statements, client: Optional[Client] = None, **extra_args):
+def extract_faithfulness(context, statements, client: Client | None = None, **extra_args):
     response = run_cached_request(
         client=client, **extract_faithfulness_request(context=context, statements=statements, **extra_args)
     )
@@ -895,7 +894,7 @@ class Faithfulness(OpenAILLMScorer):
         context: The context document(s) to evaluate against
     """
 
-    def __init__(self, model=DEFAULT_RAGAS_MODEL, client: Optional[Client] = None, **kwargs):
+    def __init__(self, model=DEFAULT_RAGAS_MODEL, client: Client | None = None, **kwargs):
         super().__init__(client=client, **kwargs)
 
         self.model = model
@@ -1061,7 +1060,7 @@ def __init__(
         strictness=3,
         temperature=0.5,
         embedding_model=DEFAULT_RAGAS_EMBEDDING_MODEL,
-        client: Optional[Client] = None,
+        client: Client | None = None,
         **kwargs,
     ):
         super().__init__(temperature=temperature, client=client, **kwargs)
@@ -1162,7 +1161,7 @@ def __init__(
         self,
         pairwise_scorer=None,
         model=DEFAULT_RAGAS_EMBEDDING_MODEL,
-        client: Optional[Client] = None,
+        client: Client | None = None,
         **kwargs,
     ):
         super().__init__(client=client, **kwargs)
@@ -1306,7 +1305,7 @@ def __init__(
         factuality_weight=0.75,
         answer_similarity_weight=0.25,
         answer_similarity=None,
-        client: Optional[Client] = None,
+        client: Client | None = None,
         **kwargs,
     ):
         super().__init__(client=client, **kwargs)
@@ -1387,9 +1386,9 @@ def load_function_call(response):
     return json.loads(response["choices"][0]["message"]["tool_calls"][0]["function"]["arguments"])
 
 
-async def aload_function_call_request(client: Optional[Client] = None, **kwargs):
+async def aload_function_call_request(client: Client | None = None, **kwargs):
     return load_function_call(await arun_cached_request(client=client, **kwargs))
 
 
-def load_function_call_request(client: Optional[Client] = None, **kwargs):
+def load_function_call_request(client: Client | None = None, **kwargs):
     return load_function_call(run_cached_request(client=client, **kwargs))
diff --git a/py/autoevals/score.py b/py/autoevals/score.py
index 067a47a..6025e9f 100644
--- a/py/autoevals/score.py
+++ b/py/autoevals/score.py
@@ -1,7 +1,7 @@
 import dataclasses
 import sys
 from abc import ABC, abstractmethod
-from typing import Any, Dict, Optional
+from typing import Any
 
 from .serializable_data_class import SerializableDataClass
 
@@ -13,14 +13,14 @@ class Score(SerializableDataClass):
     name: str
     """The name of the score. This should be a unique name for the scorer."""
 
-    score: Optional[float] = None
+    score: float | None = None
     """The score for the evaluation. This should be a float between 0 and 1. If the score is None, the evaluation is considered to be skipped."""
 
-    metadata: Dict[str, Any] = dataclasses.field(default_factory=dict)
+    metadata: dict[str, Any] = dataclasses.field(default_factory=dict)
     """Metadata for the score. This can be used to store additional information about the score."""
 
     # DEPRECATION_NOTICE: this field is deprecated, as errors are propagated up to the caller.
-    error: Optional[Exception] = None
+    error: Exception | None = None
     """Deprecated: The error field is deprecated, as errors are now propagated to the caller. The field will be removed in a future version of the library."""
 
     def as_dict(self):
diff --git a/py/autoevals/serializable_data_class.py b/py/autoevals/serializable_data_class.py
index 2fe62f6..8f9eeef 100644
--- a/py/autoevals/serializable_data_class.py
+++ b/py/autoevals/serializable_data_class.py
@@ -1,6 +1,6 @@
 import dataclasses
 import json
-from typing import Dict, Union, get_origin
+from typing import Union, get_origin
 
 
 class SerializableDataClass:
@@ -16,15 +16,15 @@ def __getitem__(self, item: str):
         return getattr(self, item)
 
     @classmethod
-    def from_dict(cls, d: Dict):
+    def from_dict(cls, d: dict):
         """Deserialize the object from a dictionary. This method
         is shallow and will not call from_dict() on nested objects."""
-        fields = set(f.name for f in dataclasses.fields(cls))
+        fields = {f.name for f in dataclasses.fields(cls)}
         filtered = {k: v for k, v in d.items() if k in fields}
         return cls(**filtered)
 
     @classmethod
-    def from_dict_deep(cls, d: Dict):
+    def from_dict_deep(cls, d: dict):
         """Deserialize the object from a dictionary. This method
         is deep and will call from_dict_deep() on nested objects."""
         fields = {f.name: f for f in dataclasses.fields(cls)}
diff --git a/py/autoevals/string.py b/py/autoevals/string.py
index 0dcba9a..a6dc39c 100644
--- a/py/autoevals/string.py
+++ b/py/autoevals/string.py
@@ -18,7 +18,6 @@
 """
 
 import threading
-from typing import Optional
 
 from polyleven import levenshtein as distance
 
@@ -120,7 +119,7 @@ def __init__(
         expected_min=0.7,
         api_key=None,
         base_url=None,
-        client: Optional[LLMClient] = None,
+        client: LLMClient | None = None,
     ):
         self.prefix = prefix
         self.expected_min = expected_min
diff --git a/py/autoevals/test_embeddings.py b/py/autoevals/test_embeddings.py
index 04ce76b..6df632a 100644
--- a/py/autoevals/test_embeddings.py
+++ b/py/autoevals/test_embeddings.py
@@ -1,7 +1,6 @@
 import asyncio
 
 from autoevals import EmbeddingSimilarity
-from autoevals.value import normalize_value
 
 SYNONYMS = [
     ("water", ["water", "H2O", "agua"]),
diff --git a/py/autoevals/test_oai.py b/py/autoevals/test_oai.py
index d1140f6..8f31479 100644
--- a/py/autoevals/test_oai.py
+++ b/py/autoevals/test_oai.py
@@ -1,5 +1,5 @@
 import sys
-from typing import Any, Union, cast
+from typing import Any, cast
 
 import openai
 import pytest
@@ -25,7 +25,7 @@
 )
 
 
-def unwrap_named_wrapper(obj: Union[NamedWrapper, OpenAIV1Module.OpenAI, OpenAIV0Module]) -> Any:
+def unwrap_named_wrapper(obj: NamedWrapper | OpenAIV1Module.OpenAI | OpenAIV0Module) -> Any:
     return getattr(obj, "_NamedWrapper__wrapped")
 
 
diff --git a/py/autoevals/test_ragas.py b/py/autoevals/test_ragas.py
index 0f0326d..a224a4d 100644
--- a/py/autoevals/test_ragas.py
+++ b/py/autoevals/test_ragas.py
@@ -1,8 +1,6 @@
 import asyncio
-from typing import cast
 
 import pytest
-from pytest import approx
 
 from autoevals.ragas import *
 
diff --git a/py/autoevals/test_serializable_data_class.py b/py/autoevals/test_serializable_data_class.py
index 0cade6a..e31e207 100644
--- a/py/autoevals/test_serializable_data_class.py
+++ b/py/autoevals/test_serializable_data_class.py
@@ -1,14 +1,13 @@
 import unittest
 from dataclasses import dataclass
-from typing import List, Optional
 
 from .serializable_data_class import SerializableDataClass
 
 
 @dataclass
 class PromptData(SerializableDataClass):
-    prompt: Optional[str] = None
-    options: Optional[dict] = None
+    prompt: str | None = None
+    options: dict | None = None
 
 
 @dataclass
@@ -18,9 +17,9 @@ class PromptSchema(SerializableDataClass):
     _xact_id: str
     name: str
     slug: str
-    description: Optional[str]
+    description: str | None
     prompt_data: PromptData
-    tags: Optional[List[str]]
+    tags: list[str] | None
 
 
 class TestSerializableDataClass(unittest.TestCase):
diff --git a/py/autoevals/test_values.py b/py/autoevals/test_values.py
index f808b2f..25bd6f2 100644
--- a/py/autoevals/test_values.py
+++ b/py/autoevals/test_values.py
@@ -1,4 +1,3 @@
-import pytest
 from pytest import approx
 
 from autoevals.list import ListContains
diff --git a/py/autoevals/version.py b/py/autoevals/version.py
index 5e70889..1cf6267 100644
--- a/py/autoevals/version.py
+++ b/py/autoevals/version.py
@@ -1 +1 @@
-VERSION = "0.0.130"
+VERSION = "0.1.0"
diff --git a/setup.py b/setup.py
index cc18d12..d8b7080 100644
--- a/setup.py
+++ b/setup.py
@@ -48,6 +48,7 @@
     },
     classifiers=[
         "Programming Language :: Python :: 3",
+        "Programming Language :: Python :: 3.10",
         "Operating System :: OS Independent",
     ],
     package_dir={"": "py"},