docs: nits

libs/core/langchain_core/language_models/base.py

@@ -105,10 +105,10 @@ class BaseLanguageModel(
     cache: Union[BaseCache, bool, None] = Field(default=None, exclude=True)
     """Whether to cache the response.
 
-    * If true, will use the global cache.
+    * If ``true``, will use the global cache.
-    * If false, will not use a cache
+    * If ``false``, will not use a cache
-    * If None, will use the global cache if it's set, otherwise no cache.
+    * If ``None``, will use the global cache if it's set, otherwise no cache.
-    * If instance of BaseCache, will use the provided cache.
+    * If instance of ``BaseCache``, will use the provided cache.
 
     Caching is not currently supported for streaming methods of models.
     """
@@ -374,7 +374,7 @@ class BaseLanguageModel(
 
         Useful for checking if an input fits in a model's context window.
 
-        **Note**: the base implementation of get_num_tokens_from_messages ignores
+        .. NOTE:: The base implementation of ``get_num_tokens_from_messages()`` ignores
         tool schemas.
 
         Args:

libs/core/langchain_core/runnables/base.py

@@ -736,8 +736,8 @@ class Runnable(Generic[Input, Output], ABC):
         Args:
             input: The input to the Runnable.
             config: A config to use when invoking the Runnable.
-               The config supports standard keys like 'tags', 'metadata' for tracing
+               The config supports standard keys like ``tags``, ``metadata`` for tracing
-               purposes, 'max_concurrency' for controlling how much work to do
+               purposes, ``max_concurrency`` for controlling how much work to do
                in parallel, and other keys. Please refer to the RunnableConfig
                for more details.
 
@@ -751,10 +751,10 @@ class Runnable(Generic[Input, Output], ABC):
         config: Optional[RunnableConfig] = None,
         **kwargs: Any,
     ) -> Output:
-        """Default implementation of ainvoke, calls invoke from a thread.
+        """Default implementation of ``ainvoke()``, calls ``invoke()`` from a thread.
 
         The default implementation allows usage of async code even if
-        the Runnable did not implement a native async version of invoke.
+        the Runnable did not implement a native async version of ``invoke()``.
 
         Subclasses should override this method if they can run asynchronously.
         """
@@ -768,13 +768,14 @@ class Runnable(Generic[Input, Output], ABC):
         return_exceptions: bool = False,
         **kwargs: Optional[Any],
     ) -> list[Output]:
-        """Default implementation runs invoke in parallel using a thread pool executor.
+        """Default implementation runs ``invoke()`` in parallel using a thread pool
+        executor.
 
         The default implementation of batch works well for IO bound runnables.
 
         Subclasses should override this method if they can batch more efficiently;
         e.g., if the underlying Runnable uses an API which supports a batch mode.
-        """
+        """  # noqa: D205
         if not inputs:
             return []
 
@@ -824,7 +825,7 @@ class Runnable(Generic[Input, Output], ABC):
         return_exceptions: bool = False,
         **kwargs: Optional[Any],
     ) -> Iterator[tuple[int, Union[Output, Exception]]]:
-        """Run invoke in parallel on a list of inputs.
+        """Run ``invoke()`` in parallel on a list of inputs.
 
         Yields results as they complete.
         """
@@ -875,7 +876,8 @@ class Runnable(Generic[Input, Output], ABC):
         return_exceptions: bool = False,
         **kwargs: Optional[Any],
     ) -> list[Output]:
-        """Default implementation runs ainvoke in parallel using asyncio.gather.
+        """Default implementation runs ``ainvoke()`` in parallel using
+        ``asyncio.gather``.
 
         The default implementation of batch works well for IO bound runnables.
 
@@ -885,17 +887,17 @@ class Runnable(Generic[Input, Output], ABC):
         Args:
             inputs: A list of inputs to the Runnable.
             config: A config to use when invoking the Runnable.
-                The config supports standard keys like 'tags', 'metadata' for tracing
+                The config supports standard keys like ``tags``, ``metadata`` for
-                purposes, 'max_concurrency' for controlling how much work to do
+                tracing purposes, ``max_concurrency`` for controlling how much work to
-                in parallel, and other keys. Please refer to the RunnableConfig
+                do in parallel, and other keys. Please refer to the RunnableConfig
-                for more details. Defaults to None.
+                for more details. Defaults to ``None``.
             return_exceptions: Whether to return exceptions instead of raising them.
-                Defaults to False.
+                Defaults to ``False``.
             kwargs: Additional keyword arguments to pass to the Runnable.
 
         Returns:
             A list of outputs from the Runnable.
-        """
+        """  # noqa: D205
         if not inputs:
             return []
 
@@ -943,19 +945,19 @@ class Runnable(Generic[Input, Output], ABC):
         return_exceptions: bool = False,
         **kwargs: Optional[Any],
     ) -> AsyncIterator[tuple[int, Union[Output, Exception]]]:
-        """Run ainvoke in parallel on a list of inputs.
+        """Run ``ainvoke()`` in parallel on a list of inputs.
 
         Yields results as they complete.
 
         Args:
             inputs: A list of inputs to the Runnable.
             config: A config to use when invoking the Runnable.
-                The config supports standard keys like 'tags', 'metadata' for tracing
+                The config supports standard keys like ``tags``, ``metadata`` for
-                purposes, 'max_concurrency' for controlling how much work to do
+                tracing purposes, ``max_concurrency`` for controlling how much work to
-                in parallel, and other keys. Please refer to the RunnableConfig
+                do in parallel, and other keys. Please refer to the RunnableConfig
-                for more details. Defaults to None. Defaults to None.
+                for more details. Defaults to ``None``.
             return_exceptions: Whether to return exceptions instead of raising them.
-                Defaults to False.
+                Defaults to ``False``.
             kwargs: Additional keyword arguments to pass to the Runnable.
 
         Yields:
@@ -1019,13 +1021,13 @@ class Runnable(Generic[Input, Output], ABC):
         config: Optional[RunnableConfig] = None,
         **kwargs: Optional[Any],
     ) -> AsyncIterator[Output]:
-        """Default implementation of astream, which calls ainvoke.
+        """Default implementation of ``astream()``, which calls ``ainvoke()``.
 
         Subclasses should override this method if they support streaming output.
 
         Args:
             input: The input to the Runnable.
-            config: The config to use for the Runnable. Defaults to None.
+            config: The config to use for the Runnable. Defaults to ``None``.
             kwargs: Additional keyword arguments to pass to the Runnable.
 
         Yields:
@@ -1221,7 +1223,7 @@ class Runnable(Generic[Input, Output], ABC):
 
         In addition to the standard events, users can also dispatch custom events (see example below).
 
-        Custom events will be only be surfaced with in the `v2` version of the API!
+        .. NOTE:: Custom events will be only be surfaced with in the `v2` version of the API.
 
         A custom event has following format:
 
@@ -1235,7 +1237,7 @@ class Runnable(Generic[Input, Output], ABC):
 
         Here are declarations associated with the standard events shown above:
 
-        `format_docs`:
+        ``format_docs``:
 
         .. code-block:: python
 
@@ -1245,7 +1247,7 @@ class Runnable(Generic[Input, Output], ABC):
 
             format_docs = RunnableLambda(format_docs)
 
-        `some_tool`:
+        ``some_tool``:
 
         .. code-block:: python
 
@@ -1254,7 +1256,7 @@ class Runnable(Generic[Input, Output], ABC):
                 '''Some_tool.'''
                 return {"x": x, "y": y}
 
-        `prompt`:
+        ``prompt``:
 
         .. code-block:: python
 
@@ -1354,8 +1356,8 @@ class Runnable(Generic[Input, Output], ABC):
             exclude_types: Exclude events from runnables with matching types.
             exclude_tags: Exclude events from runnables with matching tags.
             kwargs: Additional keyword arguments to pass to the Runnable.
-                These will be passed to astream_log as this implementation
+                These will be passed to ``astream_log`` as this implementation
-                of astream_events is built on top of astream_log.
+                of astream_events is built on top of ``astream_log``.
 
         Yields:
             An async stream of StreamEvents.
@@ -2551,9 +2553,9 @@ class RunnableSerializable(Serializable, Runnable[Input, Output]):
             which: The ConfigurableField instance that will be used to select the
                 alternative.
             default_key: The default key to use if no alternative is selected.
-                Defaults to "default".
+                Defaults to ``'default'``.
             prefix_keys: Whether to prefix the keys with the ConfigurableField id.
-                Defaults to False.
+                Defaults to ``False``.
             **kwargs: A dictionary of keys to Runnable instances or callables that
                 return Runnable instances.
 

libs/core/langchain_core/runnables/configurable.py

@@ -544,7 +544,7 @@ class RunnableConfigurableAlternatives(DynamicRunnable[Input, Output]):
     """The alternatives to choose from."""
 
     default_key: str = "default"
-    """The enum value to use for the default option. Defaults to "default"."""
+    """The enum value to use for the default option. Defaults to ``'default'``."""
 
     prefix_keys: bool
     """Whether to prefix configurable fields of each alternative with a namespace

libs/core/langchain_core/tracers/context.py

@@ -62,13 +62,13 @@ def tracing_v2_enabled(
 
     Args:
         project_name (str, optional): The name of the project.
-            Defaults to "default".
+            Defaults to ``'default'``.
         example_id (str or UUID, optional): The ID of the example.
-            Defaults to None.
+            Defaults to ``None``.
         tags (list[str], optional): The tags to add to the run.
-            Defaults to None.
+            Defaults to ``None``.
         client (LangSmithClient, optional): The client of the langsmith.
-            Defaults to None.
+            Defaults to ``None``.
 
     Yields:
         LangChainTracer: The LangChain tracer.

libs/partners/ollama/langchain_ollama/llms.py

@@ -35,27 +35,30 @@ class OllamaLLM(BaseLLM):
     """Model name to use."""
 
     mirostat: Optional[int] = None
-    """Enable Mirostat sampling for controlling perplexity.
+    """Enable Mirostat sampling for controlling perplexity. (Default: ``0``)
-    (default: 0, 0 = disabled, 1 = Mirostat, 2 = Mirostat 2.0)"""
+
+    - ``0`` = Disabled
+    - ``1`` = Mirostat
+    - ``2`` = Mirostat 2.0"""
 
     mirostat_eta: Optional[float] = 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)"""
+    the algorithm more responsive. (Default: ``0.1``)"""
 
     mirostat_tau: Optional[float] = 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)"""
+    coherent text. (Default: ``5.0``)"""
 
     num_ctx: Optional[int] = None
     """Sets the size of the context window used to generate the
-    next token. (Default: 2048)	"""
+    next token. (Default: ``2048``)"""
 
     num_gpu: Optional[int] = None
-    """The number of GPUs to use. On macOS it defaults to 1 to
+    """The number of GPUs to use. Defaults to ``1`` on macOS (to enable metal
-    enable metal support, 0 to disable."""
+    support). Set to ``0`` to disable."""
 
     num_thread: Optional[int] = None
     """Sets the number of threads to use during computation.
@@ -65,20 +68,26 @@ class OllamaLLM(BaseLLM):
 
     num_predict: Optional[int] = None
     """Maximum number of tokens to predict when generating text.
-    (Default: 128, -1 = infinite generation, -2 = fill context)"""
+    (Default: ``128``)
+
+    - ``-1`` = Infinite generation
+    - ``-2`` = Fill context"""
 
     repeat_last_n: Optional[int] = None
-    """Sets how far back for the model to look back to prevent
+    """Sets how far back for the model to look back to prevent repetition.
-    repetition. (Default: 64, 0 = disabled, -1 = num_ctx)"""
+    (Default: 64)
+
+    - ``0`` = Disabled
+    - ``-1`` = ``num_ctx``"""
 
     repeat_penalty: Optional[float] = None
-    """Sets how strongly to penalize repetitions. A higher value (e.g., 1.5)
+    """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 penalize repetitions more strongly, while a lower value (e.g., ``0.9``)
-    will be more lenient. (Default: 1.1)"""
+    will be more lenient. (Default: ``1.1``)"""
 
     temperature: Optional[float] = None
     """The temperature of the model. Increasing the temperature will
-    make the model answer more creatively. (Default: 0.8)"""
+    make the model answer more creatively. (Default: ``0.8``)"""
 
     seed: Optional[int] = None
     """Sets the random number seed to use for generation. Setting this
@@ -90,21 +99,21 @@ class OllamaLLM(BaseLLM):
 
     tfs_z: Optional[float] = 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
+    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
-    """Reduces the probability of generating nonsense. A higher value (e.g. 100)
+    """Reduces the probability of generating nonsense. A higher value (e.g.
-    will give more diverse answers, while a lower value (e.g. 10)
+    ``100``) will give more diverse answers, while a lower value (e.g. ``10``)
-    will be more conservative. (Default: 40)"""
+    will be more conservative. (Default: ``40``)"""
 
     top_p: Optional[float] = None
-    """Works together with top-k. A higher value (e.g., 0.95) will lead
+    """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
+    to more diverse text, while a lower value (e.g., ``0.5``) will
-    generate more focused and conservative text. (Default: 0.9)"""
+    generate more focused and conservative text. (Default: ``0.9``)"""
 
     format: Literal["", "json"] = ""
-    """Specify the format of the output (options: json)"""
+    """Specify the format of the output."""
 
     keep_alive: Optional[Union[int, str]] = None
     """How long the model will stay loaded into memory."""
@@ -115,21 +124,20 @@ class OllamaLLM(BaseLLM):
     client_kwargs: Optional[dict] = {}
     """Additional kwargs to pass to the httpx clients. 
     These arguments are passed to both synchronous and async clients.
-    Use sync_client_kwargs and async_client_kwargs to pass different arguments
+    Use ``sync_client_kwargs`` and ``async_client_kwargs`` to pass different
-    to synchronous and asynchronous clients.
+    arguments to synchronous and asynchronous clients.
     """
 
     async_client_kwargs: Optional[dict] = {}
-    """Additional kwargs to merge with client_kwargs before passing to the HTTPX 
+    """Additional kwargs to merge with ``client_kwargs`` before
-    AsyncClient.
+    passing to the httpx ``AsyncClient``.
-    
+    `Full list of params. <https://www.python-httpx.org/api/#asyncclient>`__
-    For a full list of the params, see the `HTTPX documentation <https://www.python-httpx.org/api/#asyncclient>`__.
     """
 
     sync_client_kwargs: Optional[dict] = {}
-    """Additional kwargs to merge with client_kwargs before passing to the HTTPX Client.
+    """Additional kwargs to merge with ``client_kwargs`` before
-    
+    passing to the httpx ``Client``.
-    For a full list of the params, see the `HTTPX documentation <https://www.python-httpx.org/api/#client>`__.
+    `Full list of params. <https://www.python-httpx.org/api/#client>`__
     """
 
     _client: Client = PrivateAttr(default=None)  # type: ignore