openai[minor]: release 0.3 (#29100)

## Goal

Solve the following problems with `langchain-openai`:

- Structured output with `o1` [breaks out of the
box](https://langchain.slack.com/archives/C050X0VTN56/p1735232400232099).
- `with_structured_output` by default does not use OpenAI’s [structured
output
feature](https://platform.openai.com/docs/guides/structured-outputs).
- We override API defaults for temperature and other parameters.

## Breaking changes:

- Default method for structured output is changing to OpenAI’s dedicated
[structured output
feature](https://platform.openai.com/docs/guides/structured-outputs).
For schemas specified via TypedDict or JSON schema, strict schema
validation is disabled by default but can be enabled by specifying
`strict=True`.
- To recover previous default, pass `method="function_calling"` into
`with_structured_output`.
- Models that don’t support `method="json_schema"` (e.g., `gpt-4` and
`gpt-3.5-turbo`, currently the default model for ChatOpenAI) will raise
an error unless `method` is explicitly specified.
- To recover previous default, pass `method="function_calling"` into
`with_structured_output`.
- Schemas specified via Pydantic `BaseModel` that have fields with
non-null defaults or metadata (like min/max constraints) will raise an
error.
- To recover previous default, pass `method="function_calling"` into
`with_structured_output`.
- `strict` now defaults to False for `method="json_schema"` when schemas
are specified via TypedDict or JSON schema.
- To recover previous behavior, use `with_structured_output(schema,
strict=True)`
- Schemas specified via Pydantic V1 will raise a warning (and use
`method="function_calling"`) unless `method` is explicitly specified.
- To remove the warning, pass `method="function_calling"` into
`with_structured_output`.
- Streaming with default structured output method / Pydantic schema no
longer generates intermediate streamed chunks.
- To recover previous behavior, pass `method="function_calling"` into
`with_structured_output`.
- We no longer override default temperature (was 0.7 in LangChain, now
will follow OpenAI, currently 1.0).
- To recover previous behavior, initialize `ChatOpenAI` or
`AzureChatOpenAI` with `temperature=0.7`.
- Note: conceptually there is a difference between forcing a tool call
and forcing a response format. Tool calls may have more concise
arguments vs. generating content adhering to a schema. Prompts may need
to be adjusted to recover desired behavior.

---------

Co-authored-by: Jacob Lee <jacoblee93@gmail.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>

libs/partners/xai/langchain_xai/chat_models.py

@@ -320,9 +320,9 @@ class ChatXAI(BaseChatOpenAI):  # type: ignore[override]
     @model_validator(mode="after")
     def validate_environment(self) -> Self:
         """Validate that api key and python package exists in environment."""
-        if self.n < 1:
+        if self.n is not None and self.n < 1:
             raise ValueError("n must be at least 1.")
-        if self.n > 1 and self.streaming:
+        if self.n is not None and self.n > 1 and self.streaming:
             raise ValueError("n must be 1 when streaming.")
 
         client_params: dict = {
@@ -331,10 +331,11 @@ class ChatXAI(BaseChatOpenAI):  # type: ignore[override]
             ),
             "base_url": self.xai_api_base,
             "timeout": self.request_timeout,
-            "max_retries": self.max_retries,
             "default_headers": self.default_headers,
             "default_query": self.default_query,
         }
+        if self.max_retries is not None:
+            client_params["max_retries"] = self.max_retries
 
         if client_params["api_key"] is None:
             raise ValueError(