chore: drop UP045 (#33362)

Python 3.9 EOL

libs/partners/ollama/langchain_ollama/_utils.py

@@ -3,7 +3,6 @@
 from __future__ import annotations
 
 import base64
-from typing import Optional
 from urllib.parse import unquote, urlparse
 
 from httpx import ConnectError
@@ -49,8 +48,8 @@ def validate_model(client: Client, model_name: str) -> None:
 
 
 def parse_url_with_auth(
-    url: Optional[str],
-) -> tuple[Optional[str], Optional[dict[str, str]]]:
+    url: str | None,
+) -> tuple[str | None, dict[str, str] | None]:
     """Parse URL and extract `userinfo` credentials for headers.
 
     Handles URLs of the form: `https://user:password@host:port/path`
@@ -101,7 +100,7 @@ def parse_url_with_auth(
 
 def merge_auth_headers(
     client_kwargs: dict,
-    auth_headers: Optional[dict[str, str]],
+    auth_headers: dict[str, str] | None,
 ) -> None:
     """Merge authentication headers into client kwargs in-place.
 

libs/partners/ollama/langchain_ollama/chat_models.py

@@ -46,7 +46,7 @@ import json
 import logging
 from collections.abc import AsyncIterator, Callable, Iterator, Mapping, Sequence
 from operator import itemgetter
-from typing import Any, Literal, Optional, Union, cast
+from typing import Any, Literal, cast
 from uuid import uuid4
 
 from langchain_core.callbacks import CallbackManagerForLLMRun
@@ -96,13 +96,13 @@ log = logging.getLogger(__name__)
 
 
 def _get_usage_metadata_from_generation_info(
-    generation_info: Optional[Mapping[str, Any]],
-) -> Optional[UsageMetadata]:
+    generation_info: Mapping[str, Any] | None,
+) -> UsageMetadata | None:
     """Get usage metadata from Ollama generation info mapping."""
     if generation_info is None:
         return None
-    input_tokens: Optional[int] = generation_info.get("prompt_eval_count")
-    output_tokens: Optional[int] = generation_info.get("eval_count")
+    input_tokens: int | None = generation_info.get("prompt_eval_count")
+    output_tokens: int | None = generation_info.get("eval_count")
     if input_tokens is not None and output_tokens is not None:
         return UsageMetadata(
             input_tokens=input_tokens,
@@ -166,7 +166,7 @@ def _parse_json_string(
 
 def _parse_arguments_from_tool_call(
     raw_tool_call: dict[str, Any],
-) -> Optional[dict[str, Any]]:
+) -> dict[str, Any] | None:
     """Parse arguments by trying to parse any shallowly nested string-encoded JSON.
 
     Band-aid fix for issue in Ollama with inconsistent tool call argument structure.
@@ -259,7 +259,7 @@ class ChatOllama(BaseChatModel):
 
     ???+ note "Setup"
 
-        Install ``langchain-ollama`` and download any models you want to use from ollama.
+        Install `langchain-ollama` and download any models you want to use from ollama.
 
         .. code-block:: bash
 
@@ -523,7 +523,7 @@ class ChatOllama(BaseChatModel):
     model: str
     """Model name to use."""
 
-    reasoning: Optional[Union[bool, str]] = None
+    reasoning: bool | str | None = None
     """Controls the reasoning/thinking mode for `supported models <https://ollama.com/search?c=thinking>`__.
 
     - `True`: Enables reasoning mode. The model's reasoning process will be
@@ -536,7 +536,7 @@ class ChatOllama(BaseChatModel):
       however, if the model's default behavior *is* to perform reasoning, think tags
       ()``<think>`` and ``</think>``) will be present within the main response content
       unless you set ``reasoning`` to `True`.
-    - `str`: e.g. ``'low'``, ``'medium'``, ``'high'``. Enables reasoning with a custom
+    - `str`: e.g. `'low'`, ``'medium'``, `'high'`. Enables reasoning with a custom
       intensity level. Currently, this is only supported ``gpt-oss``. See the
       `Ollama docs <https://github.com/ollama/ollama-python/blob/da79e987f0ac0a4986bf396f043b36ef840370bc/ollama/_types.py#L210>`__
       for more information.
@@ -548,13 +548,13 @@ class ChatOllama(BaseChatModel):
     !!! version-added "Added in version 0.3.4"
     """
 
-    mirostat: Optional[int] = None
+    mirostat: int | None = None
     """Enable Mirostat sampling for controlling perplexity.
 
-    (Default: `0`, `0` = disabled, ``1`` = Mirostat, ``2`` = Mirostat 2.0)
+    (Default: `0`, `0` = disabled, `1` = Mirostat, `2` = Mirostat 2.0)
     """
 
-    mirostat_eta: Optional[float] = None
+    mirostat_eta: float | None = None
     """Influences how quickly the algorithm responds to feedback from generated text.
 
     A lower learning rate will result in slower adjustments, while a higher learning
@@ -563,7 +563,7 @@ class ChatOllama(BaseChatModel):
     (Default: ``0.1``)
     """
 
-    mirostat_tau: Optional[float] = None
+    mirostat_tau: float | None = None
     """Controls the balance between coherence and diversity of the output.
 
     A lower value will result in more focused and coherent text.
@@ -571,19 +571,19 @@ class ChatOllama(BaseChatModel):
     (Default: ``5.0``)
     """
 
-    num_ctx: Optional[int] = None
+    num_ctx: int | None = None
     """Sets the size of the context window used to generate the next token.
 
     (Default: ``2048``)
     """
 
-    num_gpu: Optional[int] = None
+    num_gpu: int | None = None
     """The number of GPUs to use.
 
-    On macOS it defaults to ``1`` to enable metal support, `0` to disable.
+    On macOS it defaults to `1` to enable metal support, `0` to disable.
     """
 
-    num_thread: Optional[int] = None
+    num_thread: int | None = None
     """Sets the number of threads to use during computation.
 
     By default, Ollama will detect this for optimal performance. It is recommended to
@@ -591,26 +591,26 @@ class ChatOllama(BaseChatModel):
     the logical number of cores).
     """
 
-    num_predict: Optional[int] = None
+    num_predict: int | None = None
     """Maximum number of tokens to predict when generating text.
 
     (Default: ``128``, ``-1`` = infinite generation, ``-2`` = fill context)
     """
 
-    repeat_last_n: Optional[int] = None
+    repeat_last_n: int | None = None
     """Sets how far back for the model to look back to prevent repetition.
 
     (Default: ``64``, `0` = disabled, ``-1`` = ``num_ctx``)
     """
 
-    repeat_penalty: Optional[float] = None
+    repeat_penalty: float | None = None
     """Sets how strongly to penalize repetitions.
 
     A higher value (e.g., ``1.5``) will penalize repetitions more strongly, while a
     lower value (e.g., ``0.9``) will be more lenient. (Default: ``1.1``)
     """
 
-    temperature: Optional[float] = None
+    temperature: float | None = None
     """The temperature of the model.
 
     Increasing the temperature will make the model answer more creatively.
@@ -618,17 +618,17 @@ class ChatOllama(BaseChatModel):
     (Default: ``0.8``)
     """
 
-    seed: Optional[int] = None
+    seed: int | None = None
     """Sets the random number seed to use for generation.
 
     Setting this to a specific number will make the model generate the same text for the
     same prompt.
     """
 
-    stop: Optional[list[str]] = None
+    stop: list[str] | None = None
     """Sets the stop tokens to use."""
 
-    tfs_z: Optional[float] = None
+    tfs_z: float | None = None
     """Tail free sampling.
 
     Used to reduce the impact of less probable tokens from the output.
@@ -636,10 +636,10 @@ class ChatOllama(BaseChatModel):
     A higher value (e.g., ``2.0``) will reduce the impact more, while a value of ``1.0``
     disables this setting.
 
-    (Default: ``1``)
+    (Default: `1`)
     """
 
-    top_k: Optional[int] = None
+    top_k: int | None = None
     """Reduces the probability of generating nonsense.
 
     A higher value (e.g. ``100``) will give more diverse answers, while a lower value
@@ -648,7 +648,7 @@ class ChatOllama(BaseChatModel):
     (Default: ``40``)
     """
 
-    top_p: Optional[float] = None
+    top_p: float | None = None
     """Works together with top-k.
 
     A higher value (e.g., ``0.95``) will lead to more diverse text, while a lower value
@@ -657,13 +657,13 @@ class ChatOllama(BaseChatModel):
     (Default: ``0.9``)
     """
 
-    format: Optional[Union[Literal["", "json"], JsonSchemaValue]] = None
+    format: Literal["", "json"] | JsonSchemaValue | None = None
     """Specify the format of the output (options: ``'json'``, JSON schema)."""
 
-    keep_alive: Optional[Union[int, str]] = None
+    keep_alive: int | str | None = None
     """How long the model will stay loaded into memory."""
 
-    base_url: Optional[str] = None
+    base_url: str | None = None
     """Base url the model is hosted under.
 
     If none, defaults to the Ollama client default.
@@ -685,7 +685,7 @@ class ChatOllama(BaseChatModel):
 
     """
 
-    client_kwargs: Optional[dict] = {}
+    client_kwargs: dict | None = {}
     """Additional kwargs to pass to the httpx clients. Pass headers in here.
 
     These arguments are passed to both synchronous and async clients.
@@ -694,7 +694,7 @@ class ChatOllama(BaseChatModel):
     to synchronous and asynchronous clients.
     """
 
-    async_client_kwargs: Optional[dict] = {}
+    async_client_kwargs: dict | None = {}
     """Additional kwargs to merge with `client_kwargs` before passing to httpx client.
 
     These are clients unique to the async client; for shared args use `client_kwargs`.
@@ -702,7 +702,7 @@ class ChatOllama(BaseChatModel):
     For a full list of the params, see the `httpx documentation <https://www.python-httpx.org/api/#asyncclient>`__.
     """
 
-    sync_client_kwargs: Optional[dict] = {}
+    sync_client_kwargs: dict | None = {}
     """Additional kwargs to merge with `client_kwargs` before passing to httpx client.
 
     These are clients unique to the sync client; for shared args use `client_kwargs`.
@@ -719,7 +719,7 @@ class ChatOllama(BaseChatModel):
     def _chat_params(
         self,
         messages: list[BaseMessage],
-        stop: Optional[list[str]] = None,
+        stop: list[str] | None = None,
         **kwargs: Any,
     ) -> dict[str, Any]:
         """Assemble the parameters for a chat completion request.
@@ -834,8 +834,8 @@ class ChatOllama(BaseChatModel):
         ollama_messages: list = []
         for message in messages:
             role: str
-            tool_call_id: Optional[str] = None
-            tool_calls: Optional[list[dict[str, Any]]] = None
+            tool_call_id: str | None = None
+            tool_calls: list[dict[str, Any]] | None = None
             if isinstance(message, HumanMessage):
                 role = "user"
             elif isinstance(message, AIMessage):
@@ -925,9 +925,9 @@ class ChatOllama(BaseChatModel):
     async def _acreate_chat_stream(
         self,
         messages: list[BaseMessage],
-        stop: Optional[list[str]] = None,
+        stop: list[str] | None = None,
         **kwargs: Any,
-    ) -> AsyncIterator[Union[Mapping[str, Any], str]]:
+    ) -> AsyncIterator[Mapping[str, Any] | str]:
         chat_params = self._chat_params(messages, stop, **kwargs)
 
         if chat_params["stream"]:
@@ -939,9 +939,9 @@ class ChatOllama(BaseChatModel):
     def _create_chat_stream(
         self,
         messages: list[BaseMessage],
-        stop: Optional[list[str]] = None,
+        stop: list[str] | None = None,
         **kwargs: Any,
-    ) -> Iterator[Union[Mapping[str, Any], str]]:
+    ) -> Iterator[Mapping[str, Any] | str]:
         chat_params = self._chat_params(messages, stop, **kwargs)
 
         if chat_params["stream"]:
@@ -953,8 +953,8 @@ class ChatOllama(BaseChatModel):
     def _chat_stream_with_aggregation(
         self,
         messages: list[BaseMessage],
-        stop: Optional[list[str]] = None,
-        run_manager: Optional[CallbackManagerForLLMRun] = None,
+        stop: list[str] | None = None,
+        run_manager: CallbackManagerForLLMRun | None = None,
         verbose: bool = False,  # noqa: FBT002
         **kwargs: Any,
     ) -> ChatGenerationChunk:
@@ -979,8 +979,8 @@ class ChatOllama(BaseChatModel):
     async def _achat_stream_with_aggregation(
         self,
         messages: list[BaseMessage],
-        stop: Optional[list[str]] = None,
-        run_manager: Optional[AsyncCallbackManagerForLLMRun] = None,
+        stop: list[str] | None = None,
+        run_manager: AsyncCallbackManagerForLLMRun | None = None,
         verbose: bool = False,  # noqa: FBT002
         **kwargs: Any,
     ) -> ChatGenerationChunk:
@@ -1003,7 +1003,7 @@ class ChatOllama(BaseChatModel):
         return final_chunk
 
     def _get_ls_params(
-        self, stop: Optional[list[str]] = None, **kwargs: Any
+        self, stop: list[str] | None = None, **kwargs: Any
     ) -> LangSmithParams:
         """Get standard params for tracing."""
         params = self._get_invocation_params(stop=stop, **kwargs)
@@ -1020,8 +1020,8 @@ class ChatOllama(BaseChatModel):
     def _generate(
         self,
         messages: list[BaseMessage],
-        stop: Optional[list[str]] = None,
-        run_manager: Optional[CallbackManagerForLLMRun] = None,
+        stop: list[str] | None = None,
+        run_manager: CallbackManagerForLLMRun | None = None,
         **kwargs: Any,
     ) -> ChatResult:
         final_chunk = self._chat_stream_with_aggregation(
@@ -1044,7 +1044,7 @@ class ChatOllama(BaseChatModel):
     def _iterate_over_stream(
         self,
         messages: list[BaseMessage],
-        stop: Optional[list[str]] = None,
+        stop: list[str] | None = None,
         **kwargs: Any,
     ) -> Iterator[ChatGenerationChunk]:
         reasoning = kwargs.get("reasoning", self.reasoning)
@@ -1106,8 +1106,8 @@ class ChatOllama(BaseChatModel):
     def _stream(
         self,
         messages: list[BaseMessage],
-        stop: Optional[list[str]] = None,
-        run_manager: Optional[CallbackManagerForLLMRun] = None,
+        stop: list[str] | None = None,
+        run_manager: CallbackManagerForLLMRun | None = None,
         **kwargs: Any,
     ) -> Iterator[ChatGenerationChunk]:
         for chunk in self._iterate_over_stream(messages, stop, **kwargs):
@@ -1121,7 +1121,7 @@ class ChatOllama(BaseChatModel):
     async def _aiterate_over_stream(
         self,
         messages: list[BaseMessage],
-        stop: Optional[list[str]] = None,
+        stop: list[str] | None = None,
         **kwargs: Any,
     ) -> AsyncIterator[ChatGenerationChunk]:
         reasoning = kwargs.get("reasoning", self.reasoning)
@@ -1183,8 +1183,8 @@ class ChatOllama(BaseChatModel):
     async def _astream(
         self,
         messages: list[BaseMessage],
-        stop: Optional[list[str]] = None,
-        run_manager: Optional[AsyncCallbackManagerForLLMRun] = None,
+        stop: list[str] | None = None,
+        run_manager: AsyncCallbackManagerForLLMRun | None = None,
         **kwargs: Any,
     ) -> AsyncIterator[ChatGenerationChunk]:
         async for chunk in self._aiterate_over_stream(messages, stop, **kwargs):
@@ -1198,8 +1198,8 @@ class ChatOllama(BaseChatModel):
     async def _agenerate(
         self,
         messages: list[BaseMessage],
-        stop: Optional[list[str]] = None,
-        run_manager: Optional[AsyncCallbackManagerForLLMRun] = None,
+        stop: list[str] | None = None,
+        run_manager: AsyncCallbackManagerForLLMRun | None = None,
         **kwargs: Any,
     ) -> ChatResult:
         final_chunk = await self._achat_stream_with_aggregation(
@@ -1226,9 +1226,9 @@ class ChatOllama(BaseChatModel):
 
     def bind_tools(
         self,
-        tools: Sequence[Union[dict[str, Any], type, Callable, BaseTool]],
+        tools: Sequence[dict[str, Any] | type | Callable | BaseTool],
         *,
-        tool_choice: Optional[Union[dict, str, Literal["auto", "any"], bool]] = None,  # noqa: PYI051, ARG002
+        tool_choice: dict | str | Literal["auto", "any"] | bool | None = None,  # noqa: PYI051, ARG002
         **kwargs: Any,
     ) -> Runnable[LanguageModelInput, AIMessage]:
         """Bind tool-like objects to this chat model.
@@ -1249,12 +1249,12 @@ class ChatOllama(BaseChatModel):
 
     def with_structured_output(
         self,
-        schema: Union[dict, type],
+        schema: dict | type,
         *,
         method: Literal["function_calling", "json_mode", "json_schema"] = "json_schema",
         include_raw: bool = False,
         **kwargs: Any,
-    ) -> Runnable[LanguageModelInput, Union[dict, BaseModel]]:
+    ) -> Runnable[LanguageModelInput, dict | BaseModel]:
         r"""Model wrapper that returns outputs formatted to match the given schema.
 
         Args:

libs/partners/ollama/langchain_ollama/embeddings.py

@@ -2,7 +2,7 @@
 
 from __future__ import annotations
 
-from typing import Any, Optional
+from typing import Any
 
 from langchain_core.embeddings import Embeddings
 from ollama import AsyncClient, Client
@@ -128,7 +128,7 @@ class OllamaEmbeddings(BaseModel, Embeddings):
 
     """
 
-    base_url: Optional[str] = None
+    base_url: str | None = None
     """Base url the model is hosted under.
 
     If none, defaults to the Ollama client default.
@@ -150,7 +150,7 @@ class OllamaEmbeddings(BaseModel, Embeddings):
 
     """
 
-    client_kwargs: Optional[dict] = {}
+    client_kwargs: dict | None = {}
     """Additional kwargs to pass to the httpx clients. Pass headers in here.
 
     These arguments are passed to both synchronous and async clients.
@@ -159,7 +159,7 @@ class OllamaEmbeddings(BaseModel, Embeddings):
     to synchronous and asynchronous clients.
     """
 
-    async_client_kwargs: Optional[dict] = {}
+    async_client_kwargs: dict | None = {}
     """Additional kwargs to merge with `client_kwargs` before passing to httpx client.
 
     These are clients unique to the async client; for shared args use `client_kwargs`.
@@ -167,7 +167,7 @@ class OllamaEmbeddings(BaseModel, Embeddings):
     For a full list of the params, see the `httpx documentation <https://www.python-httpx.org/api/#asyncclient>`__.
     """
 
-    sync_client_kwargs: Optional[dict] = {}
+    sync_client_kwargs: dict | None = {}
     """Additional kwargs to merge with `client_kwargs` before passing to httpx client.
 
     These are clients unique to the sync client; for shared args use `client_kwargs`.
@@ -175,73 +175,73 @@ class OllamaEmbeddings(BaseModel, Embeddings):
     For a full list of the params, see the `httpx documentation <https://www.python-httpx.org/api/#client>`__.
     """
 
-    _client: Optional[Client] = PrivateAttr(default=None)
+    _client: Client | None = PrivateAttr(default=None)
     """The client to use for making requests."""
 
-    _async_client: Optional[AsyncClient] = PrivateAttr(default=None)
+    _async_client: AsyncClient | None = PrivateAttr(default=None)
     """The async client to use for making requests."""
 
-    mirostat: Optional[int] = None
+    mirostat: int | None = None
     """Enable Mirostat sampling for controlling perplexity.
-    (default: `0`, `0` = disabled, ``1`` = Mirostat, ``2`` = Mirostat 2.0)"""
+    (default: `0`, `0` = disabled, `1` = Mirostat, `2` = Mirostat 2.0)"""
 
-    mirostat_eta: Optional[float] = None
+    mirostat_eta: float | None = None
     """Influences how quickly the algorithm responds to feedback
     from the generated text. A lower learning rate will result in
     slower adjustments, while a higher learning rate will make
     the algorithm more responsive. (Default: ``0.1``)"""
 
-    mirostat_tau: Optional[float] = None
+    mirostat_tau: float | None = None
     """Controls the balance between coherence and diversity
     of the output. A lower value will result in more focused and
     coherent text. (Default: ``5.0``)"""
 
-    num_ctx: Optional[int] = None
+    num_ctx: int | None = None
     """Sets the size of the context window used to generate the
     next token. (Default: ``2048``)	"""
 
-    num_gpu: Optional[int] = None
-    """The number of GPUs to use. On macOS it defaults to ``1`` to
+    num_gpu: int | None = None
+    """The number of GPUs to use. On macOS it defaults to `1` to
     enable metal support, `0` to disable."""
 
-    keep_alive: Optional[int] = None
+    keep_alive: int | None = None
     """Controls how long the model will stay loaded into memory
     following the request (default: ``5m``)
     """
 
-    num_thread: Optional[int] = None
+    num_thread: int | None = None
     """Sets the number of threads to use during computation.
     By default, Ollama will detect this for optimal performance.
     It is recommended to set this value to the number of physical
     CPU cores your system has (as opposed to the logical number of cores)."""
 
-    repeat_last_n: Optional[int] = None
+    repeat_last_n: int | None = None
     """Sets how far back for the model to look back to prevent
     repetition. (Default: ``64``, `0` = disabled, ``-1`` = ``num_ctx``)"""
 
-    repeat_penalty: Optional[float] = None
+    repeat_penalty: float | None = None
     """Sets how strongly to penalize repetitions. A higher value (e.g., ``1.5``)
     will penalize repetitions more strongly, while a lower value (e.g., ``0.9``)
     will be more lenient. (Default: ``1.1``)"""
 
-    temperature: Optional[float] = None
+    temperature: float | None = None
     """The temperature of the model. Increasing the temperature will
     make the model answer more creatively. (Default: ``0.8``)"""
 
-    stop: Optional[list[str]] = None
+    stop: list[str] | None = None
     """Sets the stop tokens to use."""
 
-    tfs_z: Optional[float] = None
+    tfs_z: float | None = None
     """Tail free sampling is used to reduce the impact of less probable
     tokens from the output. A higher value (e.g., ``2.0``) will reduce the
-    impact more, while a value of ``1.0`` disables this setting. (default: ``1``)"""
+    impact more, while a value of ``1.0`` disables this setting. (default: `1`)"""
 
-    top_k: Optional[int] = None
+    top_k: int | None = None
     """Reduces the probability of generating nonsense. A higher value (e.g. ``100``)
     will give more diverse answers, while a lower value (e.g. ``10``)
     will be more conservative. (Default: ``40``)"""
 
-    top_p: Optional[float] = None
+    top_p: float | None = None
     """Works together with top-k. A higher value (e.g., ``0.95``) will lead
     to more diverse text, while a lower value (e.g., ``0.5``) will
     generate more focused and conservative text. (Default: ``0.9``)"""

libs/partners/ollama/langchain_ollama/llms.py

@@ -3,7 +3,7 @@
 from __future__ import annotations
 
 from collections.abc import AsyncIterator, Iterator, Mapping
-from typing import Any, Literal, Optional, Union
+from typing import Any, Literal
 
 from langchain_core.callbacks import (
     AsyncCallbackManagerForLLMRun,
@@ -22,7 +22,7 @@ class OllamaLLM(BaseLLM):
     """Ollama large language models.
 
     Setup:
-        Install ``langchain-ollama`` and install/run the Ollama server locally:
+        Install `langchain-ollama` and install/run the Ollama server locally:
 
         .. code-block:: bash
 
@@ -112,7 +112,7 @@ class OllamaLLM(BaseLLM):
     model: str
     """Model name to use."""
 
-    reasoning: Optional[bool] = None
+    reasoning: bool | None = None
     """Controls the reasoning/thinking mode for
     `supported models <https://ollama.com/search?c=thinking>`__.
 
@@ -132,71 +132,71 @@ class OllamaLLM(BaseLLM):
     !!! version-added "Added in version 0.3.4"
     """
 
-    mirostat: Optional[int] = None
+    mirostat: int | None = None
     """Enable Mirostat sampling for controlling perplexity.
-    (default: `0`, `0` = disabled, ``1`` = Mirostat, ``2`` = Mirostat 2.0)"""
+    (default: `0`, `0` = disabled, `1` = Mirostat, `2` = Mirostat 2.0)"""
 
-    mirostat_eta: Optional[float] = None
+    mirostat_eta: float | None = None
     """Influences how quickly the algorithm responds to feedback
     from the generated text. A lower learning rate will result in
     slower adjustments, while a higher learning rate will make
     the algorithm more responsive. (Default: ``0.1``)"""
 
-    mirostat_tau: Optional[float] = None
+    mirostat_tau: float | None = None
     """Controls the balance between coherence and diversity
     of the output. A lower value will result in more focused and
     coherent text. (Default: ``5.0``)"""
 
-    num_ctx: Optional[int] = None
+    num_ctx: int | None = None
     """Sets the size of the context window used to generate the
     next token. (Default: ``2048``)"""
 
-    num_gpu: Optional[int] = None
-    """The number of GPUs to use. On macOS it defaults to ``1`` to
+    num_gpu: int | None = None
+    """The number of GPUs to use. On macOS it defaults to `1` to
     enable metal support, `0` to disable."""
 
-    num_thread: Optional[int] = None
+    num_thread: int | None = None
     """Sets the number of threads to use during computation.
     By default, Ollama will detect this for optimal performance.
     It is recommended to set this value to the number of physical
     CPU cores your system has (as opposed to the logical number of cores)."""
 
-    num_predict: Optional[int] = None
+    num_predict: int | None = None
     """Maximum number of tokens to predict when generating text.
     (Default: ``128``, ``-1`` = infinite generation, ``-2`` = fill context)"""
 
-    repeat_last_n: Optional[int] = None
+    repeat_last_n: int | None = None
     """Sets how far back for the model to look back to prevent
     repetition. (Default: ``64``, `0` = disabled, ``-1`` = ``num_ctx``)"""
 
-    repeat_penalty: Optional[float] = None
+    repeat_penalty: float | None = None
     """Sets how strongly to penalize repetitions. A higher value (e.g., ``1.5``)
     will penalize repetitions more strongly, while a lower value (e.g., ``0.9``)
     will be more lenient. (Default: ``1.1``)"""
 
-    temperature: Optional[float] = None
+    temperature: float | None = None
     """The temperature of the model. Increasing the temperature will
     make the model answer more creatively. (Default: ``0.8``)"""
 
-    seed: Optional[int] = None
+    seed: int | None = None
     """Sets the random number seed to use for generation. Setting this
     to a specific number will make the model generate the same text for
     the same prompt."""
 
-    stop: Optional[list[str]] = None
+    stop: list[str] | None = None
     """Sets the stop tokens to use."""
 
-    tfs_z: Optional[float] = None
+    tfs_z: float | None = None
     """Tail free sampling is used to reduce the impact of less probable
     tokens from the output. A higher value (e.g., ``2.0``) will reduce the
-    impact more, while a value of 1.0 disables this setting. (default: ``1``)"""
+    impact more, while a value of 1.0 disables this setting. (default: `1`)"""
 
-    top_k: Optional[int] = None
+    top_k: int | None = None
     """Reduces the probability of generating nonsense. A higher value (e.g. ``100``)
     will give more diverse answers, while a lower value (e.g. ``10``)
     will be more conservative. (Default: ``40``)"""
 
-    top_p: Optional[float] = None
+    top_p: float | None = None
     """Works together with top-k. A higher value (e.g., ``0.95``) will lead
     to more diverse text, while a lower value (e.g., ``0.5``) will
     generate more focused and conservative text. (Default: ``0.9``)"""
@@ -204,10 +204,10 @@ class OllamaLLM(BaseLLM):
     format: Literal["", "json"] = ""
     """Specify the format of the output (options: ``'json'``)"""
 
-    keep_alive: Optional[Union[int, str]] = None
+    keep_alive: int | str | None = None
     """How long the model will stay loaded into memory."""
 
-    base_url: Optional[str] = None
+    base_url: str | None = None
     """Base url the model is hosted under.
 
     If none, defaults to the Ollama client default.
@@ -229,7 +229,7 @@ class OllamaLLM(BaseLLM):
 
     """
 
-    client_kwargs: Optional[dict] = {}
+    client_kwargs: dict | None = {}
     """Additional kwargs to pass to the httpx clients. Pass headers in here.
 
     These arguments are passed to both synchronous and async clients.
@@ -238,7 +238,7 @@ class OllamaLLM(BaseLLM):
     to synchronous and asynchronous clients.
     """
 
-    async_client_kwargs: Optional[dict] = {}
+    async_client_kwargs: dict | None = {}
     """Additional kwargs to merge with `client_kwargs` before passing to httpx client.
 
     These are clients unique to the async client; for shared args use `client_kwargs`.
@@ -246,7 +246,7 @@ class OllamaLLM(BaseLLM):
     For a full list of the params, see the `httpx documentation <https://www.python-httpx.org/api/#asyncclient>`__.
     """
 
-    sync_client_kwargs: Optional[dict] = {}
+    sync_client_kwargs: dict | None = {}
     """Additional kwargs to merge with `client_kwargs` before passing to httpx client.
 
     These are clients unique to the sync client; for shared args use `client_kwargs`.
@@ -254,16 +254,16 @@ class OllamaLLM(BaseLLM):
     For a full list of the params, see the `httpx documentation <https://www.python-httpx.org/api/#client>`__.
     """
 
-    _client: Optional[Client] = PrivateAttr(default=None)
+    _client: Client | None = PrivateAttr(default=None)
     """The client to use for making requests."""
 
-    _async_client: Optional[AsyncClient] = PrivateAttr(default=None)
+    _async_client: AsyncClient | None = PrivateAttr(default=None)
     """The async client to use for making requests."""
 
     def _generate_params(
         self,
         prompt: str,
-        stop: Optional[list[str]] = None,
+        stop: list[str] | None = None,
         **kwargs: Any,
     ) -> dict[str, Any]:
         if self.stop is not None and stop is not None:
@@ -310,7 +310,7 @@ class OllamaLLM(BaseLLM):
         return "ollama-llm"
 
     def _get_ls_params(
-        self, stop: Optional[list[str]] = None, **kwargs: Any
+        self, stop: list[str] | None = None, **kwargs: Any
     ) -> LangSmithParams:
         """Get standard params for tracing."""
         params = super()._get_ls_params(stop=stop, **kwargs)
@@ -343,9 +343,9 @@ class OllamaLLM(BaseLLM):
     async def _acreate_generate_stream(
         self,
         prompt: str,
-        stop: Optional[list[str]] = None,
+        stop: list[str] | None = None,
         **kwargs: Any,
-    ) -> AsyncIterator[Union[Mapping[str, Any], str]]:
+    ) -> AsyncIterator[Mapping[str, Any] | str]:
         if self._async_client:
             async for part in await self._async_client.generate(
                 **self._generate_params(prompt, stop=stop, **kwargs)
@@ -355,9 +355,9 @@ class OllamaLLM(BaseLLM):
     def _create_generate_stream(
         self,
         prompt: str,
-        stop: Optional[list[str]] = None,
+        stop: list[str] | None = None,
         **kwargs: Any,
-    ) -> Iterator[Union[Mapping[str, Any], str]]:
+    ) -> Iterator[Mapping[str, Any] | str]:
         if self._client:
             yield from self._client.generate(
                 **self._generate_params(prompt, stop=stop, **kwargs)
@@ -366,8 +366,8 @@ class OllamaLLM(BaseLLM):
     async def _astream_with_aggregation(
         self,
         prompt: str,
-        stop: Optional[list[str]] = None,
-        run_manager: Optional[AsyncCallbackManagerForLLMRun] = None,
+        stop: list[str] | None = None,
+        run_manager: AsyncCallbackManagerForLLMRun | None = None,
         verbose: bool = False,  # noqa: FBT002
         **kwargs: Any,
     ) -> GenerationChunk:
@@ -408,8 +408,8 @@ class OllamaLLM(BaseLLM):
     def _stream_with_aggregation(
         self,
         prompt: str,
-        stop: Optional[list[str]] = None,
-        run_manager: Optional[CallbackManagerForLLMRun] = None,
+        stop: list[str] | None = None,
+        run_manager: CallbackManagerForLLMRun | None = None,
         verbose: bool = False,  # noqa: FBT002
         **kwargs: Any,
     ) -> GenerationChunk:
@@ -450,8 +450,8 @@ class OllamaLLM(BaseLLM):
     def _generate(
         self,
         prompts: list[str],
-        stop: Optional[list[str]] = None,
-        run_manager: Optional[CallbackManagerForLLMRun] = None,
+        stop: list[str] | None = None,
+        run_manager: CallbackManagerForLLMRun | None = None,
         **kwargs: Any,
     ) -> LLMResult:
         generations = []
@@ -469,8 +469,8 @@ class OllamaLLM(BaseLLM):
     async def _agenerate(
         self,
         prompts: list[str],
-        stop: Optional[list[str]] = None,
-        run_manager: Optional[AsyncCallbackManagerForLLMRun] = None,
+        stop: list[str] | None = None,
+        run_manager: AsyncCallbackManagerForLLMRun | None = None,
         **kwargs: Any,
     ) -> LLMResult:
         generations = []
@@ -488,8 +488,8 @@ class OllamaLLM(BaseLLM):
     def _stream(
         self,
         prompt: str,
-        stop: Optional[list[str]] = None,
-        run_manager: Optional[CallbackManagerForLLMRun] = None,
+        stop: list[str] | None = None,
+        run_manager: CallbackManagerForLLMRun | None = None,
         **kwargs: Any,
     ) -> Iterator[GenerationChunk]:
         reasoning = kwargs.get("reasoning", self.reasoning)
@@ -519,8 +519,8 @@ class OllamaLLM(BaseLLM):
     async def _astream(
         self,
         prompt: str,
-        stop: Optional[list[str]] = None,
-        run_manager: Optional[AsyncCallbackManagerForLLMRun] = None,
+        stop: list[str] | None = None,
+        run_manager: AsyncCallbackManagerForLLMRun | None = None,
         **kwargs: Any,
     ) -> AsyncIterator[GenerationChunk]:
         reasoning = kwargs.get("reasoning", self.reasoning)