core[patch], community[patch], openai[patch]: consolidate openai tool… (#16485)

… converters

One way to convert anything to an OAI function:
convert_to_openai_function
One way to convert anything to an OAI tool: convert_to_openai_tool
Corresponding bind functions on OAI models: bind_functions, bind_tools

libs/core/tests/unit_tests/utils/test_function_calling.py

@@ -0,0 +1,74 @@
+from typing import Any, Callable, Literal, Type
+
+import pytest
+
+from langchain_core.pydantic_v1 import BaseModel, Field
+from langchain_core.tools import BaseTool
+from langchain_core.utils.function_calling import convert_to_openai_function
+
+
+@pytest.fixture()
+def pydantic() -> Type[BaseModel]:
+    class dummy_function(BaseModel):
+        """dummy function"""
+
+        arg1: int = Field(..., description="foo")
+        arg2: Literal["bar", "baz"] = Field(..., description="one of 'bar', 'baz'")
+
+    return dummy_function
+
+
+@pytest.fixture()
+def function() -> Callable:
+    def dummy_function(arg1: int, arg2: Literal["bar", "baz"]) -> None:
+        """dummy function
+
+        Args:
+            arg1: foo
+            arg2: one of 'bar', 'baz'
+        """
+        pass
+
+    return dummy_function
+
+
+@pytest.fixture()
+def tool() -> BaseTool:
+    class Schema(BaseModel):
+        arg1: int = Field(..., description="foo")
+        arg2: Literal["bar", "baz"] = Field(..., description="one of 'bar', 'baz'")
+
+    class DummyFunction(BaseTool):
+        args_schema: Type[BaseModel] = Schema
+        name: str = "dummy_function"
+        description: str = "dummy function"
+
+        def _run(self, *args: Any, **kwargs: Any) -> Any:
+            pass
+
+    return DummyFunction()
+
+
+def test_convert_to_openai_function(
+    pydantic: Type[BaseModel], function: Callable, tool: BaseTool
+) -> None:
+    expected = {
+        "name": "dummy_function",
+        "description": "dummy function",
+        "parameters": {
+            "type": "object",
+            "properties": {
+                "arg1": {"description": "foo", "type": "integer"},
+                "arg2": {
+                    "description": "one of 'bar', 'baz'",
+                    "enum": ["bar", "baz"],
+                    "type": "string",
+                },
+            },
+            "required": ["arg1", "arg2"],
+        },
+    }
+
+    for fn in (pydantic, function, tool, expected):
+        actual = convert_to_openai_function(fn)  # type: ignore
+        assert actual == expected