chore: import upstream snapshot with attribution

examples/validators/annotator.py

@@ -0,0 +1,39 @@
+from typing import Annotated
+from pydantic import BaseModel, ValidationError
+from pydantic.functional_validators import AfterValidator
+
+
+def name_must_contain_space(v: str) -> str:
+    if " " not in v:
+        raise ValueError("name must be a first and last name separated by a space")
+    return v.lower()
+
+
+class UserDetail(BaseModel):
+    age: int
+    name: Annotated[str, AfterValidator(name_must_contain_space)]
+
+
+# Example 1) Valid input, notice that the name is lowercased
+person: UserDetail = UserDetail(age=29, name="Jason Liu")
+print(person.model_dump_json(indent=2))
+"""
+{
+    "age": 29,
+    "name": "jason liu"
+}
+"""
+
+# Example 2) Invalid input, we'll get a validation error
+# In the future this validation error will be raised by the API and
+# used by the LLM to generate a better response
+try:
+    person: UserDetail = UserDetail(age=29, name="Jason")
+except ValidationError as e:
+    print(e)
+    """
+    1 validation error for UserDetail
+    name
+        Value error, name must be a first and last name separated by a space [type=value_error, input_value='Jason', input_type=str]
+        For further information visit https://errors.pydantic.dev/2.3/v/value_error
+    """