core[minor], openai[minor], langchain[patch]: BaseLanguageModel.with_…

…structured_output langchain-ai#17302)

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

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

---------

Co-authored-by: Erick Friis <[email protected]>

libs/core/langchain_core/language_models/base.py

@@ -5,24 +5,27 @@
 from typing import (
     TYPE_CHECKING,
     Any,
+    Dict,
     List,
     Optional,
     Sequence,
     Set,
+    Type,
     TypeVar,
     Union,
 )
 
 from typing_extensions import TypeAlias
 
-from langchain_core._api import deprecated
+from langchain_core._api import beta, deprecated
 from langchain_core.messages import (
     AnyMessage,
     BaseMessage,
     MessageLikeRepresentation,
     get_buffer_string,
 )
 from langchain_core.prompt_values import PromptValue
+from langchain_core.pydantic_v1 import BaseModel
 from langchain_core.runnables import Runnable, RunnableSerializable
 from langchain_core.utils import get_pydantic_field_names
 
@@ -155,6 +158,13 @@ async def agenerate_prompt(
                 prompt and additional model provider-specific output.
         """
 
+    @beta()
+    def with_structured_output(
+        self, schema: Union[Dict, Type[BaseModel]], **kwargs: Any
+    ) -> Runnable[LanguageModelInput, Union[Dict, BaseModel]]:
+        """Implement this if there is a way of steering the model to generate responses that match a given schema."""  # noqa: E501
+        raise NotImplementedError()
+
     @deprecated("0.1.7", alternative="invoke", removal="0.2.0")
     @abstractmethod
     def predict(

libs/core/langchain_core/output_parsers/__init__.py

@@ -24,6 +24,7 @@
     MarkdownListOutputParser,
     NumberedListOutputParser,
 )
+from langchain_core.output_parsers.pydantic import PydanticOutputParser
 from langchain_core.output_parsers.string import StrOutputParser
 from langchain_core.output_parsers.transform import (
     BaseCumulativeTransformOutputParser,
@@ -45,4 +46,5 @@
     "SimpleJsonOutputParser",
     "XMLOutputParser",
     "JsonOutputParser",
+    "PydanticOutputParser",
 ]

libs/core/langchain_core/output_parsers/base.py

@@ -15,15 +15,17 @@
 
 from typing_extensions import get_args
 
+from langchain_core.language_models import LanguageModelOutput
 from langchain_core.messages import AnyMessage, BaseMessage
 from langchain_core.outputs import ChatGeneration, Generation
-from langchain_core.runnables import RunnableConfig, RunnableSerializable
+from langchain_core.runnables import Runnable, RunnableConfig, RunnableSerializable
 from langchain_core.runnables.config import run_in_executor
 
 if TYPE_CHECKING:
     from langchain_core.prompt_values import PromptValue
 
 T = TypeVar("T")
+OutputParserLike = Runnable[LanguageModelOutput, T]
 
 
 class BaseLLMOutputParser(Generic[T], ABC):
@@ -57,7 +59,7 @@ async def aparse_result(
 
 
 class BaseGenerationOutputParser(
-    BaseLLMOutputParser, RunnableSerializable[Union[str, BaseMessage], T]
+    BaseLLMOutputParser, RunnableSerializable[LanguageModelOutput, T]
 ):
     """Base class to parse the output of an LLM call."""
 
@@ -116,7 +118,7 @@ async def ainvoke(
 
 
 class BaseOutputParser(
-    BaseLLMOutputParser, RunnableSerializable[Union[str, BaseMessage], T]
+    BaseLLMOutputParser, RunnableSerializable[LanguageModelOutput, T]
 ):
     """Base class to parse the output of an LLM call.
 

libs/core/langchain_core/output_parsers/pydantic.py

@@ -0,0 +1,62 @@
+import json
+from typing import Any, List, Type
+
+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
+
+
+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
+
+
+_PYDANTIC_FORMAT_INSTRUCTIONS = """The output should be formatted as a JSON instance that conforms to the JSON schema below.
+
+As an example, for the schema {{"properties": {{"foo": {{"title": "Foo", "description": "a list of strings", "type": "array", "items": {{"type": "string"}}}}}}, "required": ["foo"]}}
+the object {{"foo": ["bar", "baz"]}} is a well-formatted instance of the schema. The object {{"properties": {{"foo": ["bar", "baz"]}}}} is not well-formatted.
+
+Here is the output schema:
+```
+{schema}
+```"""  # noqa: E501

libs/core/tests/unit_tests/output_parsers/test_imports.py

@@ -14,6 +14,7 @@
     "SimpleJsonOutputParser",
     "XMLOutputParser",
     "JsonOutputParser",
+    "PydanticOutputParser",
 ]
 
 

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"]