docs(openai): add comprehensive documentation and examples for extra_body + others (#32149)

This PR addresses the common issue where users struggle to pass custom
parameters to OpenAI-compatible APIs like LM Studio, vLLM, and others.
The problem occurs when users try to use `model_kwargs` for custom
parameters, which causes API errors.

## Problem

Users attempting to pass custom parameters (like LM Studio's `ttl`
parameter) were getting errors:

```python
# ❌ This approach fails
llm = ChatOpenAI(
    base_url="http://localhost:1234/v1",
    model="mlx-community/QwQ-32B-4bit",
    model_kwargs={"ttl": 5}  # Causes TypeError: unexpected keyword argument 'ttl'
)
```

## Solution

The `extra_body` parameter is the correct way to pass custom parameters
to OpenAI-compatible APIs:

```python
# ✅ This approach works correctly
llm = ChatOpenAI(
    base_url="http://localhost:1234/v1",
    model="mlx-community/QwQ-32B-4bit",
    extra_body={"ttl": 5}  # Custom parameters go in extra_body
)
```

## Changes Made

1. **Enhanced Documentation**: Updated the `extra_body` parameter
docstring with comprehensive examples for LM Studio, vLLM, and other
providers

2. **Added Documentation Section**: Created a new "OpenAI-compatible
APIs" section in the main class docstring with practical examples

3. **Unit Tests**: Added tests to verify `extra_body` functionality
works correctly:
- `test_extra_body_parameter()`: Verifies custom parameters are included
in request payload
- `test_extra_body_with_model_kwargs()`: Ensures `extra_body` and
`model_kwargs` work together

4. **Clear Guidance**: Documented when to use `extra_body` vs
`model_kwargs`

## Examples Added

**LM Studio with TTL (auto-eviction):**
```python
ChatOpenAI(
    base_url="http://localhost:1234/v1",
    api_key="lm-studio",
    model="mlx-community/QwQ-32B-4bit",
    extra_body={"ttl": 300}  # Auto-evict after 5 minutes
)
```

**vLLM with custom sampling:**
```python
ChatOpenAI(
    base_url="http://localhost:8000/v1",
    api_key="EMPTY",
    model="meta-llama/Llama-2-7b-chat-hf",
    extra_body={
        "use_beam_search": True,
        "best_of": 4
    }
)
```

## Why This Works

- `model_kwargs` parameters are passed directly to the OpenAI client's
`create()` method, causing errors for non-standard parameters
- `extra_body` parameters are included in the HTTP request body, which
is exactly what OpenAI-compatible APIs expect for custom parameters

Fixes #32115.

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Co-authored-by: Mason Daugherty <github@mdrxy.com>
Co-authored-by: Mason Daugherty <mason@langchain.dev>

libs/standard-tests/README.md

@@ -13,13 +13,13 @@ Not pinning your version will ensure you always have the latest tests, but it ma
 also break your CI if we introduce tests that your integration doesn't pass.
 
 Pip:
-    
+
     ```bash
     pip install -U langchain-tests
     ```
 
 Poetry:
-    
+
     ```bash
     poetry add langchain-tests
     ```
@@ -32,44 +32,44 @@ To add standard tests to an integration package's e.g. ChatModel, you need to cr
 2. An integration test class that inherits from ChatModelIntegrationTests
 
 `tests/unit_tests/test_standard.py`:
-    
-```python
-"""Standard LangChain interface tests"""
 
-from typing import Type
+    ```python
+    """Standard LangChain interface tests"""
 
-import pytest
-from langchain_core.language_models import BaseChatModel
-from langchain_tests.unit_tests import ChatModelUnitTests
+    from typing import Type
 
-from langchain_parrot_chain import ChatParrotChain
+    import pytest
+    from langchain_core.language_models import BaseChatModel
+    from langchain_tests.unit_tests import ChatModelUnitTests
+
+    from langchain_parrot_chain import ChatParrotChain
 
 
-class TestParrotChainStandard(ChatModelUnitTests):
-    @pytest.fixture
-    def chat_model_class(self) -> Type[BaseChatModel]:
-        return ChatParrotChain
-```
+    class TestParrotChainStandard(ChatModelUnitTests):
+        @pytest.fixture
+        def chat_model_class(self) -> Type[BaseChatModel]:
+            return ChatParrotChain
+    ```
 
 `tests/integration_tests/test_standard.py`:
-    
-```python
-"""Standard LangChain interface tests"""
 
-from typing import Type
+    ```python
+    """Standard LangChain interface tests"""
 
-import pytest
-from langchain_core.language_models import BaseChatModel
-from langchain_tests.integration_tests import ChatModelIntegrationTests
+    from typing import Type
 
-from langchain_parrot_chain import ChatParrotChain
+    import pytest
+    from langchain_core.language_models import BaseChatModel
+    from langchain_tests.integration_tests import ChatModelIntegrationTests
+
+    from langchain_parrot_chain import ChatParrotChain
 
 
-class TestParrotChainStandard(ChatModelIntegrationTests):
-    @pytest.fixture
-    def chat_model_class(self) -> Type[BaseChatModel]:
-        return ChatParrotChain
-```
+    class TestParrotChainStandard(ChatModelIntegrationTests):
+        @pytest.fixture
+        def chat_model_class(self) -> Type[BaseChatModel]:
+            return ChatParrotChain
+    ```
 
 ## Reference