anthropic[patch]: make description optional on AnthropicTool (#30935)

PR Summary

This change adds a fallback in ChatAnthropic.with_structured_output() to
handle Pydantic models that don’t include a docstring. Without it,
calling:
```py
from pydantic import BaseModel
from langchain_anthropic import ChatAnthropic

class SampleModel(BaseModel):
    sample_field: str

llm = ChatAnthropic(
    model="claude-3-7-sonnet-latest"
).with_structured_output(SampleModel.model_json_schema())

llm.invoke("test")
```
will raise a
```
KeyError: 'description'
```
because Pydantic omits the description field when no docstring is
present.

This issue doesn’t occur when using ChatOpenAI or if you add a docstring
to the model:
```py
from pydantic import BaseModel
from langchain_openai import ChatOpenAI

class SampleModel(BaseModel):
    """Schema for sample_field output."""
    sample_field: str

llm = ChatOpenAI(
    model="gpt-4o-mini"
).with_structured_output(SampleModel.model_json_schema())

llm.invoke("test")
```

---------

Co-authored-by: Chester Curme <chester.curme@gmail.com>

libs/partners/anthropic/langchain_anthropic/chat_models.py

@@ -82,8 +82,8 @@ class AnthropicTool(TypedDict):
     """Anthropic tool definition."""
 
     name: str
-    description: str
     input_schema: dict[str, Any]
+    description: NotRequired[str]
     cache_control: NotRequired[dict[str, str]]
 
 
@@ -1675,9 +1675,10 @@ def convert_to_anthropic_tool(
         oai_formatted = convert_to_openai_tool(tool)["function"]
         anthropic_formatted = AnthropicTool(
             name=oai_formatted["name"],
-            description=oai_formatted["description"],
             input_schema=oai_formatted["parameters"],
         )
+        if "description" in oai_formatted:
+            anthropic_formatted["description"] = oai_formatted["description"]
     return anthropic_formatted
 
 

libs/partners/anthropic/tests/unit_tests/test_chat_models.py

@@ -931,3 +931,12 @@ def test_anthropic_bind_tools_tool_choice() -> None:
     assert cast(RunnableBinding, chat_model_with_tools).kwargs["tool_choice"] == {
         "type": "any"
     }
+
+
+def test_optional_description() -> None:
+    llm = ChatAnthropic(model="claude-3-5-haiku-latest")
+
+    class SampleModel(BaseModel):
+        sample_field: str
+
+    _ = llm.with_structured_output(SampleModel.model_json_schema())