chore(core): delete function_calling.py utils marked for removal (#33376)

libs/core/langchain_core/utils/function_calling.py

@@ -27,7 +27,7 @@ from pydantic.v1 import create_model as create_model_v1
 from typing_extensions import TypedDict, is_typeddict
 
 import langchain_core
-from langchain_core._api import beta, deprecated
+from langchain_core._api import beta
 from langchain_core.messages import AIMessage, BaseMessage, HumanMessage, ToolMessage
 from langchain_core.utils.json_schema import dereference_refs
 from langchain_core.utils.pydantic import is_basemodel_subclass
@@ -168,42 +168,6 @@ def _convert_pydantic_to_openai_function(
     )
 
 
-convert_pydantic_to_openai_function = deprecated(
-    "0.1.16",
-    alternative="langchain_core.utils.function_calling.convert_to_openai_function()",
-    removal="1.0",
-)(_convert_pydantic_to_openai_function)
-
-
-@deprecated(
-    "0.1.16",
-    alternative="langchain_core.utils.function_calling.convert_to_openai_tool()",
-    removal="1.0",
-)
-def convert_pydantic_to_openai_tool(
-    model: type[BaseModel],
-    *,
-    name: str | None = None,
-    description: str | None = None,
-) -> ToolDescription:
-    """Converts a Pydantic model to a function description for the OpenAI API.
-
-    Args:
-        model: The Pydantic model to convert.
-        name: The name of the function. If not provided, the title of the schema will be
-            used.
-        description: The description of the function. If not provided, the description
-            of the schema will be used.
-
-    Returns:
-        The tool description.
-    """
-    function = _convert_pydantic_to_openai_function(
-        model, name=name, description=description
-    )
-    return {"type": "function", "function": function}
-
-
 def _get_python_function_name(function: Callable) -> str:
     """Get the name of a Python function."""
     return function.__name__
@@ -240,13 +204,6 @@ def _convert_python_function_to_openai_function(
     )
 
 
-convert_python_function_to_openai_function = deprecated(
-    "0.1.16",
-    alternative="langchain_core.utils.function_calling.convert_to_openai_function()",
-    removal="1.0",
-)(_convert_python_function_to_openai_function)
-
-
 def _convert_typed_dict_to_openai_function(typed_dict: type) -> FunctionDescription:
     visited: dict = {}
 
@@ -368,31 +325,6 @@ def _format_tool_to_openai_function(tool: BaseTool) -> FunctionDescription:
     }
 
 
-format_tool_to_openai_function = deprecated(
-    "0.1.16",
-    alternative="langchain_core.utils.function_calling.convert_to_openai_function()",
-    removal="1.0",
-)(_format_tool_to_openai_function)
-
-
-@deprecated(
-    "0.1.16",
-    alternative="langchain_core.utils.function_calling.convert_to_openai_tool()",
-    removal="1.0",
-)
-def format_tool_to_openai_tool(tool: BaseTool) -> ToolDescription:
-    """Format tool into the OpenAI function API.
-
-    Args:
-        tool: The tool to format.
-
-    Returns:
-        The tool description.
-    """
-    function = _format_tool_to_openai_function(tool)
-    return {"type": "function", "function": function}
-
-
 def convert_to_openai_function(
     function: dict[str, Any] | type | Callable | BaseTool,
     *,

libs/langchain/langchain_classic/chains/openai_tools/extraction.py

@@ -3,7 +3,9 @@ from langchain_core.language_models import BaseLanguageModel
 from langchain_core.output_parsers.openai_tools import PydanticToolsParser
 from langchain_core.prompts import ChatPromptTemplate
 from langchain_core.runnables import Runnable
-from langchain_core.utils.function_calling import convert_pydantic_to_openai_function
+from langchain_core.utils.function_calling import (
+    convert_to_openai_function as convert_pydantic_to_openai_function,
+)
 from pydantic import BaseModel
 
 _EXTRACTION_TEMPLATE = """Extract and save the relevant entities mentioned \

libs/langchain/langchain_classic/tools/convert_to_openai.py

@@ -1,4 +1,6 @@
-from langchain_core.utils.function_calling import format_tool_to_openai_function
+from langchain_core.utils.function_calling import (
+    convert_to_openai_function as format_tool_to_openai_function,
+)
 
 # For backwards compatibility
 __all__ = ["format_tool_to_openai_function"]

libs/langchain/langchain_classic/tools/render.py

@@ -11,8 +11,10 @@ from langchain_core.tools import (
     render_text_description_and_args,
 )
 from langchain_core.utils.function_calling import (
-    format_tool_to_openai_function,
-    format_tool_to_openai_tool,
+    convert_to_openai_function as format_tool_to_openai_function,
+)
+from langchain_core.utils.function_calling import (
+    convert_to_openai_tool as format_tool_to_openai_tool,
 )
 
 __all__ = [

libs/langchain/langchain_classic/utils/openai_functions.py

@@ -1,8 +1,9 @@
+from langchain_core.utils.function_calling import FunctionDescription, ToolDescription
 from langchain_core.utils.function_calling import (
-    FunctionDescription,
-    ToolDescription,
-    convert_pydantic_to_openai_function,
-    convert_pydantic_to_openai_tool,
+    convert_to_openai_function as convert_pydantic_to_openai_function,
+)
+from langchain_core.utils.function_calling import (
+    convert_to_openai_tool as convert_pydantic_to_openai_tool,
 )
 
 __all__ = [

libs/langchain/tests/unit_tests/utils/test_openai_functions.py

@@ -1,4 +1,4 @@
-from langchain_core.utils.function_calling import convert_pydantic_to_openai_function
+from langchain_core.utils.function_calling import convert_to_openai_function
 from pydantic import BaseModel, Field
 
 
@@ -9,7 +9,7 @@ def test_convert_pydantic_to_openai_function() -> None:
         key: str = Field(..., description="API key")
         days: int = Field(default=0, description="Number of days to forecast")
 
-    actual = convert_pydantic_to_openai_function(Data)
+    actual = convert_to_openai_function(Data)
     expected = {
         "name": "Data",
         "description": "The data to return.",
@@ -41,7 +41,7 @@ def test_convert_pydantic_to_openai_function_nested() -> None:
 
         data: Data
 
-    actual = convert_pydantic_to_openai_function(Model)
+    actual = convert_to_openai_function(Model)
     expected = {
         "name": "Model",
         "description": "The model to return.",