openai[minor]: implement langchain-openai package (#15503)

Todo

- [x] copy over integration tests
- [x] update docs with new instructions in #15513 
- [x] add linear ticket to bump core -> community, community->langchain,
and core->openai deps
- [ ] (optional): add `pip install langchain-openai` command to each
notebook using it
- [x] Update docstrings to not need `openai` install
- [x] Add serialization
- [x] deprecate old models

Contributor steps:

- [x] Add secret names to manual integrations workflow in
.github/workflows/_integration_test.yml
- [x] Add secrets to release workflow (for pre-release testing) in
.github/workflows/_release.yml

Maintainer steps (Contributors should not do these):

- [x] set up pypi and test pypi projects
- [x] add credential secrets to Github Actions
- [ ] add package to conda-forge


Functional changes to existing classes:

- now relies on openai client v1 (1.6.1) via concrete dep in
langchain-openai package

Codebase organization

- some function calling stuff moved to
`langchain_core.utils.function_calling` in order to be used in both
community and langchain-openai

libs/community/tests/integration_tests/llms/test_openai.py

@@ -22,37 +22,6 @@ def test_openai_call() -> None:
     assert isinstance(output, str)
 
 
-def test_openai_model_param() -> None:
-    llm = OpenAI(model="foo")
-    assert llm.model_name == "foo"
-    llm = OpenAI(model_name="foo")
-    assert llm.model_name == "foo"
-
-
-def test_openai_extra_kwargs() -> None:
-    """Test extra kwargs to openai."""
-    # Check that foo is saved in extra_kwargs.
-    llm = OpenAI(foo=3, max_tokens=10)
-    assert llm.max_tokens == 10
-    assert llm.model_kwargs == {"foo": 3}
-
-    # Test that if extra_kwargs are provided, they are added to it.
-    llm = OpenAI(foo=3, model_kwargs={"bar": 2})
-    assert llm.model_kwargs == {"foo": 3, "bar": 2}
-
-    # Test that if provided twice it errors
-    with pytest.raises(ValueError):
-        OpenAI(foo=3, model_kwargs={"foo": 2})
-
-    # Test that if explicit param is specified in kwargs it errors
-    with pytest.raises(ValueError):
-        OpenAI(model_kwargs={"temperature": 0.2})
-
-    # Test that "model" cannot be specified in kwargs
-    with pytest.raises(ValueError):
-        OpenAI(model_kwargs={"model": "gpt-3.5-turbo-instruct"})
-
-
 def test_openai_llm_output_contains_model_name() -> None:
     """Test llm_output contains model_name."""
     llm = OpenAI(max_tokens=10)