core[patch]: convert_to_openai_tool Anthropic support (#27591)

libs/core/langchain_core/messages/utils.py

@@ -883,8 +883,6 @@ def convert_to_openai_messages(
 ) -> Union[dict, list[dict]]:
     """Convert LangChain messages into OpenAI message dicts.
 
-    .. versionadded:: 0.3.11
-
     Args:
         messages: Message-like object or iterable of objects whose contents are
             in OpenAI, Anthropic, Bedrock Converse, or VertexAI formats.
@@ -937,6 +935,8 @@ def convert_to_openai_messages(
             #   {'role': 'assistant', 'content': 'thats nice'}
             # ]
 
+    .. versionadded:: 0.3.11
+
     """  # noqa: E501
     if text_format not in ("string", "block"):
         err = f"Unrecognized {text_format=}, expected one of 'string' or 'block'."

libs/core/langchain_core/utils/function_calling.py

@@ -336,30 +336,32 @@ def convert_to_openai_function(
     strict: Optional[bool] = None,
 ) -> dict[str, Any]:
     """Convert a raw function/class to an OpenAI function.
-
-    .. versionchanged:: 0.2.29
-
-        ``strict`` arg added.
-
     Args:
         function:
             A dictionary, Pydantic BaseModel class, TypedDict class, a LangChain
             Tool object, or a Python function. If a dictionary is passed in, it is
-            assumed to already be a valid OpenAI function or a JSON schema with
+            assumed to already be a valid OpenAI function, a JSON schema with
-            top-level 'title' and 'description' keys specified.
+            top-level 'title' and 'description' keys specified, or an Anthropic format
+            tool.
         strict:
             If True, model output is guaranteed to exactly match the JSON Schema
             provided in the function definition. If None, ``strict`` argument will not
             be included in function definition.
 
-            .. versionadded:: 0.2.29
-
     Returns:
         A dict version of the passed in function which is compatible with the OpenAI
         function-calling API.
 
     Raises:
         ValueError: If function is not in a supported format.
+
+    .. versionchanged:: 0.2.29
+
+        ``strict`` arg added.
+
+    .. versionchanged:: 0.3.13
+
+        Support for Anthropic format tools added.
     """
     from langchain_core.tools import BaseTool
 
@@ -378,6 +380,15 @@ def convert_to_openai_function(
             "description": function.pop("description"),
             "parameters": function,
         }
+    # an Anthropic format tool
+    elif isinstance(function, dict) and all(
+        k in function for k in ("name", "description", "input_schema")
+    ):
+        oai_function = {
+            "name": function["name"],
+            "description": function["description"],
+            "parameters": function["input_schema"],
+        }
     elif isinstance(function, type) and is_basemodel_subclass(function):
         oai_function = cast(dict, convert_pydantic_to_openai_function(function))
     elif is_typeddict(function):
@@ -414,34 +425,35 @@ def convert_to_openai_tool(
     *,
     strict: Optional[bool] = None,
 ) -> dict[str, Any]:
-    """Convert a raw function/class to an OpenAI tool.
+    """Convert a tool-like object to an OpenAI tool schema.
-
-    .. versionchanged:: 0.2.29
-
-        ``strict`` arg added.
 
     Args:
         tool:
             Either a dictionary, a pydantic.BaseModel class, Python function, or
             BaseTool. If a dictionary is passed in, it is assumed to already be a valid
-            OpenAI tool, OpenAI function, or a JSON schema with top-level 'title' and
+            OpenAI tool, OpenAI function, a JSON schema with top-level 'title' and
-            'description' keys specified.
+            'description' keys specified, or an Anthropic format tool.
         strict:
             If True, model output is guaranteed to exactly match the JSON Schema
             provided in the function definition. If None, ``strict`` argument will not
             be included in tool definition.
 
-            .. versionadded:: 0.2.29
-
     Returns:
         A dict version of the passed in tool which is compatible with the
         OpenAI tool-calling API.
+
+    .. versionchanged:: 0.2.29
+
+        ``strict`` arg added.
+
+    .. versionchanged:: 0.3.13
+
+        Support for Anthropic format tools added.
     """
     if isinstance(tool, dict) and tool.get("type") == "function" and "function" in tool:
         return tool
     oai_function = convert_to_openai_function(tool, strict=strict)
-    oai_tool: dict[str, Any] = {"type": "function", "function": oai_function}
+    return {"type": "function", "function": oai_function}
-    return oai_tool
 
 
 def tool_example_to_messages(

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

@@ -210,6 +210,26 @@ def json_schema() -> dict:
     }
 
 
+@pytest.fixture()
+def anthropic_tool() -> dict:
+    return {
+        "name": "dummy_function",
+        "description": "dummy function",
+        "input_schema": {
+            "type": "object",
+            "properties": {
+                "arg1": {"description": "foo", "type": "integer"},
+                "arg2": {
+                    "description": "one of 'bar', 'baz'",
+                    "enum": ["bar", "baz"],
+                    "type": "string",
+                },
+            },
+            "required": ["arg1", "arg2"],
+        },
+    }
+
+
 class Dummy:
     def dummy_function(self, arg1: int, arg2: Literal["bar", "baz"]) -> None:
         """dummy function
@@ -237,6 +257,7 @@ def test_convert_to_openai_function(
     dummy_structured_tool: StructuredTool,
     dummy_tool: BaseTool,
     json_schema: dict,
+    anthropic_tool: dict,
     annotated_function: Callable,
     dummy_pydantic: type[BaseModel],
     runnable: Runnable,
@@ -268,6 +289,7 @@ def test_convert_to_openai_function(
         dummy_structured_tool,
         dummy_tool,
         json_schema,
+        anthropic_tool,
         expected,
         Dummy.dummy_function,
         DummyWithClassMethod.dummy_function,