core: Removing unnecessary pydantic core schema rebuilds (#30848)

We only need to rebuild model schemas if type annotation information
isn't available during declaration - that shouldn't be the case for
these types corrected here.

Need to do more thorough testing to make sure these structures have
complete schemas, but hopefully this boosts startup / import time.

libs/core/langchain_core/messages/ai.py

@@ -276,9 +276,6 @@ class AIMessage(BaseMessage):
         return (base.strip() + "\n" + "\n".join(lines)).strip()
 
 
-AIMessage.model_rebuild()
-
-
 class AIMessageChunk(AIMessage, BaseMessageChunk):
     """Message chunk from an AI."""
 

libs/core/langchain_core/messages/chat.py

@@ -22,9 +22,6 @@ class ChatMessage(BaseMessage):
     """The type of the message (used during serialization). Defaults to "chat"."""
 
 
-ChatMessage.model_rebuild()
-
-
 class ChatMessageChunk(ChatMessage, BaseMessageChunk):
     """Chat Message chunk."""
 

libs/core/langchain_core/messages/function.py

@@ -30,9 +30,6 @@ class FunctionMessage(BaseMessage):
     """The type of the message (used for serialization). Defaults to "function"."""
 
 
-FunctionMessage.model_rebuild()
-
-
 class FunctionMessageChunk(FunctionMessage, BaseMessageChunk):
     """Function Message chunk."""
 

libs/core/langchain_core/messages/human.py

@@ -52,9 +52,6 @@ class HumanMessage(BaseMessage):
         super().__init__(content=content, **kwargs)
 
 
-HumanMessage.model_rebuild()
-
-
 class HumanMessageChunk(HumanMessage, BaseMessageChunk):
     """Human Message chunk."""
 

libs/core/langchain_core/messages/modifier.py

@@ -26,6 +26,3 @@ class RemoveMessage(BaseMessage):
             raise ValueError(msg)
 
         super().__init__("", id=id, **kwargs)
-
-
-RemoveMessage.model_rebuild()

libs/core/langchain_core/messages/system.py

@@ -46,9 +46,6 @@ class SystemMessage(BaseMessage):
         super().__init__(content=content, **kwargs)
 
 
-SystemMessage.model_rebuild()
-
-
 class SystemMessageChunk(SystemMessage, BaseMessageChunk):
     """System Message chunk."""
 

libs/core/langchain_core/messages/tool.py

@@ -146,9 +146,6 @@ class ToolMessage(BaseMessage, ToolOutputMixin):
         super().__init__(content=content, **kwargs)
 
 
-ToolMessage.model_rebuild()
-
-
 class ToolMessageChunk(ToolMessage, BaseMessageChunk):
     """Tool Message chunk."""
 

libs/core/langchain_core/output_parsers/list.py

@@ -133,9 +133,6 @@ class ListOutputParser(BaseTransformOutputParser[list[str]]):
             yield [part]
 
 
-ListOutputParser.model_rebuild()
-
-
 class CommaSeparatedListOutputParser(ListOutputParser):
     """Parse the output of an LLM call to a comma-separated list."""
 

libs/core/langchain_core/output_parsers/pydantic.py

@@ -114,9 +114,6 @@ class PydanticOutputParser(JsonOutputParser, Generic[TBaseModel]):
         return self.pydantic_object
 
 
-PydanticOutputParser.model_rebuild()
-
-
 _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"]}}

libs/core/langchain_core/output_parsers/string.py

@@ -31,6 +31,3 @@ class StrOutputParser(BaseTransformOutputParser[str]):
     def parse(self, text: str) -> str:
         """Returns the input text with no changes."""
         return text
-
-
-StrOutputParser.model_rebuild()

libs/core/langchain_core/prompts/pipeline.py

@@ -132,6 +132,3 @@ class PipelinePromptTemplate(BasePromptTemplate):
     @property
     def _prompt_type(self) -> str:
         raise ValueError
-
-
-PipelinePromptTemplate.model_rebuild()

libs/core/langchain_core/runnables/base.py

@@ -5650,9 +5650,6 @@ class RunnableBindingBase(RunnableSerializable[Input, Output]):
             yield item
 
 
-RunnableBindingBase.model_rebuild()
-
-
 class RunnableBinding(RunnableBindingBase[Input, Output]):
     """Wrap a Runnable with additional functionality.
 

libs/core/langchain_core/runnables/configurable.py

@@ -8,7 +8,6 @@ from abc import abstractmethod
 from collections.abc import (
     AsyncIterator,
     Iterator,
-    Mapping,  # noqa: F401 Needed by pydantic
     Sequence,
 )
 from functools import wraps
@@ -464,9 +463,6 @@ class RunnableConfigurableFields(DynamicRunnable[Input, Output]):
         return (self.default, config)
 
 
-RunnableConfigurableFields.model_rebuild()
-
-
 # Before Python 3.11 native StrEnum is not available
 class StrEnum(str, enum.Enum):
     """String enum."""

libs/core/langchain_core/runnables/utils.py

@@ -6,6 +6,7 @@ import ast
 import asyncio
 import inspect
 import textwrap
+from collections.abc import Mapping, Sequence
 from contextvars import Context
 from functools import lru_cache
 from inspect import signature
@@ -33,8 +34,6 @@ if TYPE_CHECKING:
         Awaitable,
         Coroutine,
         Iterable,
-        Mapping,
-        Sequence,
     )
 
     from langchain_core.runnables.schema import StreamEvent

libs/core/langchain_core/tools/simple.py

@@ -176,6 +176,3 @@ class Tool(BaseTool):
             args_schema=args_schema,
             **kwargs,
         )
-
-
-Tool.model_rebuild()

libs/core/tests/unit_tests/language_models/chat_models/test_rate_limiting.py

@@ -227,9 +227,6 @@ class SerializableModel(GenericFakeChatModel):
         return True
 
 
-SerializableModel.model_rebuild()
-
-
 def test_serialization_with_rate_limiter() -> None:
     """Test model serialization with rate limiter."""
     from langchain_core.load import dumps

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

@@ -45,8 +45,6 @@ def test_base_generation_parser() -> None:
             assert isinstance(content, str)
             return content.swapcase()
 
-    StrInvertCase.model_rebuild()
-
     model = GenericFakeChatModel(messages=iter([AIMessage(content="hEllo")]))
     chain = model | StrInvertCase()
     assert chain.invoke("") == "HeLLO"

libs/core/tests/unit_tests/prompts/test_structured.py

@@ -35,9 +35,6 @@ class FakeStructuredChatModel(FakeListChatModel):
         return "fake-messages-list-chat-model"
 
 
-FakeStructuredChatModel.model_rebuild()
-
-
 def test_structured_prompt_pydantic() -> None:
     class OutputSchema(BaseModel):
         name: str

libs/core/tests/unit_tests/runnables/test_runnable_events_v1.py

@@ -1188,9 +1188,6 @@ class HardCodedRetriever(BaseRetriever):
         return self.documents
 
 
-HardCodedRetriever.model_rebuild()
-
-
 async def test_event_stream_with_retriever() -> None:
     """Test the event stream with a retriever."""
     retriever = HardCodedRetriever(

libs/core/tests/unit_tests/test_pydantic_imports.py

@@ -0,0 +1,20 @@
+import importlib
+from pathlib import Path
+
+from pydantic import BaseModel
+
+
+def test_all_models_built() -> None:
+    for path in Path("../core/langchain_core/").glob("*"):
+        module_name = path.stem
+        if not module_name.startswith(".") and path.suffix != ".typed":
+            module = importlib.import_module("langchain_core." + module_name)
+            all_ = getattr(module, "__all__", [])
+            for attr_name in all_:
+                attr = getattr(module, attr_name)
+                try:
+                    if issubclass(attr, BaseModel):
+                        assert attr.__pydantic_complete__ is True
+                except TypeError:
+                    # This is expected for non-class attributes
+                    pass

libs/core/tests/unit_tests/test_tools.py

@@ -1091,9 +1091,6 @@ class FooBase(BaseTool):
         return assert_bar(bar, bar_config)
 
 
-FooBase.model_rebuild()
-
-
 class AFooBase(FooBase):
     async def _arun(self, bar: Any, bar_config: RunnableConfig, **kwargs: Any) -> Any:
         return assert_bar(bar, bar_config)