core[minor], openai[minor], langchain[patch]: BaseLanguageModel.with_structured_output #17302)

```python
class Foo(BaseModel):
  bar: str

structured_llm = ChatOpenAI().with_structured_output(Foo)
```

---------

Co-authored-by: Erick Friis <erick@langchain.dev>

libs/langchain/langchain/output_parsers/pydantic.py

@@ -1,53 +1,3 @@
-import json
-from typing import Any, List, Type
+from langchain_core.output_parsers import PydanticOutputParser
 
-from langchain_core.exceptions import OutputParserException
-from langchain_core.output_parsers import JsonOutputParser
-from langchain_core.outputs import Generation
-from langchain_core.pydantic_v1 import BaseModel, ValidationError
-
-from langchain.output_parsers.format_instructions import PYDANTIC_FORMAT_INSTRUCTIONS
-
-
-class PydanticOutputParser(JsonOutputParser):
-    """Parse an output using a pydantic model."""
-
-    pydantic_object: Type[BaseModel]
-    """The pydantic model to parse.
-    
-    Attention: To avoid potential compatibility issues, it's recommended to use
-        pydantic <2 or leverage the v1 namespace in pydantic >= 2.
-    """
-
-    def parse_result(self, result: List[Generation], *, partial: bool = False) -> Any:
-        json_object = super().parse_result(result)
-        try:
-            return self.pydantic_object.parse_obj(json_object)
-        except ValidationError as e:
-            name = self.pydantic_object.__name__
-            msg = f"Failed to parse {name} from completion {json_object}. Got: {e}"
-            raise OutputParserException(msg, llm_output=json_object)
-
-    def get_format_instructions(self) -> str:
-        # Copy schema to avoid altering original Pydantic schema.
-        schema = {k: v for k, v in self.pydantic_object.schema().items()}
-
-        # Remove extraneous fields.
-        reduced_schema = schema
-        if "title" in reduced_schema:
-            del reduced_schema["title"]
-        if "type" in reduced_schema:
-            del reduced_schema["type"]
-        # Ensure json in context is well-formed with double quotes.
-        schema_str = json.dumps(reduced_schema)
-
-        return PYDANTIC_FORMAT_INSTRUCTIONS.format(schema=schema_str)
-
-    @property
-    def _type(self) -> str:
-        return "pydantic"
-
-    @property
-    def OutputType(self) -> Type[BaseModel]:
-        """Return the pydantic model."""
-        return self.pydantic_object
+__all__ = ["PydanticOutputParser"]